WPS4654 Policy ReseaRch WoRking PaPeR 4654 Governance Matters VII: Aggregate and Individual Governance Indicators 1996-2007 Daniel Kaufmann Aart Kraay Massimo Mastruzzi The World Bank Development Research Group Macroeconomics and Growth Team & World Bank Institute Global Governance Program June 2008 Policy ReseaRch WoRking PaPeR 4654 Abstract This paper reports on the latest update of the Worldwide reflect the inherent difficulties in measuring governance Governance Indicators (WGI) research project, using any kind of data. The authors also briefly describe covering 212 countries and territories and measuring the evolution of the WGI since its inception, and show six dimensions of governance between 1996 and 2007: that the margins of error on the aggregate governance Voice and Accountability, Political Stability and Absence indicators have declined over the years, even though of Violence/Terrorism, Government Effectiveness, they still remain non-trivial. The authors find that Regulatory Quality, Rule of Law, and Control of even after taking margins of error into account, the Corruption. The latest aggregate indicators are based WGI permit meaningful cross-country comparisons on hundreds of specific and disaggregated individual as well as monitoring progress over time. In less than variables measuring various dimensions of governance, a decade, a substantial number of countries exhibit taken from 35 data sources provided by 32 different statistically significant improvements in at least one organizations. The data reflect the views on governance dimension of governance, while other countries exhibit of public sector, private sector and NGO experts, as deterioration in some dimensions. These aggregate well as thousands of citizen and firm survey respondents indicators, spanning more than a decade, together with worldwide. The authors also explicitly report the margins the disaggregated individual indicators, are available at of error accompanying each country estimate. These www.govindicators.org. This paper--a product of the Growth and the Macroeconomics Team, Development Research Group, in collaboration with the Global Governance Program of the World Bank Institute--is part of a larger effort in the department to study the causes and consequences of good governance. Policy Research Working Papers are also posted on the Web at http://econ. worldbank.org. The authors may be contacted at akraay@worldbank.org, dkaufmann@worldbank.org, and mmastruzzi@ worldbank.org. The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent. Produced by the Research Support Team Governance Matters VII: Aggregate and Individual Governance Indicators 1996-2007 Daniel Kaufmann Aart Kraay Massimo Mastruzzi The World Bank ________________________________________ 1818 H Street NW, Washington, DC 20433, USA, dkaufmann@worldbank.org, akraay@worldbank.org, mmastruzzi@worldbank.org. The views expressed here are the authors' and do not necessarily reflect those of the World Bank, its Executive Directors, or the countries they represent. The Worldwide Governance Indicators are not used by the World Bank for resource allocation. We would like to thank B. Parks, S. Rose, M. Camerer, M. Carballo, C. Cilley, N. Meisel, J. Ould-Auodia, R. Fullenbaum, Z. Nyiri, L. Fessou, M. Seligson, F. Marzo, C. Walker, P. Wongwan, G. Grein, P. Priestley, S. Sarkis, J. Langston, L. Abruzzese, S. Hatipoglu, D. Cingranelli, D. Richards, J. Zveglich, M. Lagos, R. Coutinho, S. Mannan, F. Paua, J. Blancke, Z. Tabernacki, J. Auger, L. Mootz, and D. Cieslikowsky for providing data and comments, and answering our numerous questions. 1. Introduction This paper presents the latest update of the Worldwide Governance Indicators (WGI) research project.1 The indicators measure six dimensions of governance: Voice and Accountability, Political Stability and Absence of Violence/Terrorism, Government Effectiveness, Regulatory Quality, Rule of Law, and Control of Corruption. They cover 212 countries and territories for 1996, 1998, 2000, and annually for 2002-2007.2 The indicators are based on several hundred individual variables measuring perceptions of governance, drawn from 35 separate data sources constructed by 32 different organizations from around the world. We assign these individual measures to categories capturing these six dimensions of governance, and use an unobserved components model to construct six aggregate governance indicators in each period. As in the past, we complement our estimates of governance for each country with margins of error that indicate the unavoidable uncertainty associated with measuring governance across countries. These margins of error have declined over time with the addition of new data sources to our aggregate indicators, and are substantially smaller than for any of the individual sources. We continue to encourage users of the governance indicators to take these margins of error into account when making comparisons of governance across countries, and within countries over time. In particular, a useful rule of thumb is that when confidence intervals for governance based on our reported margins of error overlap in comparisons of two countries, or a single country over time, this suggests that the data do not reveal statistically (or for that matter practically) significant differences in governance. The margins of error we report are not unique to the WGI, nor are they unique to perceptions-based measures of governance on which we rely. Measurement error is pervasive among all indicators of governance and institutional quality, including individual indicators as well as `objective' or fact-based ones -- if these are available at 1 This paper is the seventh in a series of estimates of governance across countries. Documentation of previous rounds can be found in Kaufmann, Kraay, and Zoido-Lobatón (1999a,b,2002), and Kaufmann, Kraay, and Mastruzzi (2004, 2005, 2006a, 2006b and 2007b). 2 A few of the entities covered by our indicators are not fully independent states (e.g. Puerto Rico, Hong Kong, West Bank/Gaza, Martinique, French Guyana and others). A handful of very small independent principalities (e.g. Monaco, San Marino, Lichtenstein and Andorra) are also included. For stylistic convenience all 212 entities are often referred to in this paper as "countries". 1 all. Unfortunately, typically little if any effort is devoted to estimating, let alone reporting, the substantial margins of error in any other governance and/or investment climate indicators ­ objective or subjective, aggregate or individual. A key advantage of the WGI is that we are explicit about the accompanying margins of error, whereas in most other cases they are often left implicit or ignored altogether.3 Despite these margins of error, the WGI are sufficiently informative that many cross-country comparisons result in statistically (and likely also practically) significant differences in estimated governance. In comparing governance levels across countries, for example, we document that over 65 percent of all cross-country pair-wise comparisons using the WGI for 2007 result in statistically significant differences at the 90 percent significance level, and nearly 74 percent of comparisons are significant at the less stringent 75 percent significance level. In assessing trends over time, we find that 31 percent of countries experience significant changes over the decade 1998-2007 in at least one of the six indicators (roughly evenly divided between significant improvements and deteriorations). This highlights the fact that governance can and does change even over relatively short periods such as a decade. This should both provide encouragement to reformers seeking to improve governance, as well as warn against complacency in other cases as sharp deteriorations in governance are possible. The aggregate indicators that we report constitute a useful way of organizing and summarizing the very large and disparate amount of information on governance embodied in all of our underlying data sources. The specific aggregation procedure we use also allows us to calculate explicit margins of error to capture the inherent uncertainties in measuring governance. At the same time, we recognize that for some purposes the information in the many individual underlying data sources can be of interest to users. For example, several of these provide highly specific and disaggregated information about particular dimensions of governance that could be of interest for monitoring particular reforms. For this reason, we report country scores on the individual indicators underlying our aggregate governance indicators, on the WGI website at www.govindicators.org. These disaggregated underlying indicators are 3The only other governance-related indicators that we are aware of that now report margins of error are the Transparency International Corruption Perceptions Index and the Global Integrity Index. 2 presented for the entire time period covered by the aggregate indicators, from 1996 to 2007. As a new feature this year, this data is available both interactively on a country- by-country basis as it has been in the past, as well as in downloadable spreadsheets reporting the data from all countries for each data source. As in past years, the WGI are based on subjective or perceptions-based data on governance reflecting the views of a diverse range of informed stakeholders including tens of thousands of household and firm survey respondents, as well as thousands of experts working for the private sector, NGOs, and public sector agencies. We rely on the reports of these stakeholders, which reflect their judgments and perceptions, for three main reasons. First and most basic, perceptions matter because agents base their actions on their perceptions, impression, and views. If citizens believe that the courts are inefficient or the police are corrupt, they are unlikely to avail themselves of their services. Similarly, enterprises base their investment decisions - and citizens their voting decisions - on their perceived view of the investment climate and the government's performance. Second, in many areas of governance, there are few alternatives to relying on perceptions data. This is most particularly so for the case of corruption, which almost by definition leaves no 'paper trail' that can be captured by purely objective measures. Third, we note that even when objective or fact-based data are available, often such data may capture a de jure notion of laws 'on the books' that differs substantially from the de facto reality that exists 'on the ground'. In fact, in Kaufmann, Kraay and Mastruzzi (2005) we document sharp divergences between de jure and de facto measures of business entry regulation and find that corruption explains a good deal of the extent to which the former are subverted in practice. And finally, we note, as discussed in more detail in Kaufmann and Kraay (2008), that virtually all measures of governance and the investment climate rely on judgment in some measure, so that the distinction between 'subjective' and 'objective' data is somewhat of a false dichotomy. Rather, a more useful distinction is between efforts to measure formal rules as distinct from their implementation in practice, recognizing that changes in formal rules (often associated with so-called 'actionable' indicators) need not lead to desired changes in outcomes. 3 The WGI project has evolved in several directions over the past decade. A key feature of the WGI is its effort to develop more precise or informative measures of broad concepts of governance by drawing on a diverse set of underlying indicators. One important dimension of this evolution is a basic one -- a steady expansion in the number of underlying data sources on which the WGI are based. In our very first effort (Kaufmann, Kraay and Zoido-Lobatón (1999a,b)) the WGI were based on just 13 data sources covering only 173 countries. Since then we have added sources each year as they have become available, and made backwards revisions to the earlier data as well to incorporate these sources, until the current round of the WGI which now covers 212 countries and is based on 35 separate data sources. As the number of data sources has expanded, the aggregate WGI have become more informative about the broad notions of governance they seek to capture. In particular, the average standard error associated with the governance estimates has declined by more than 1/3 since the first round of the indicators in 1996. Another important innovation three years ago was that we began to make the individual indicators underlying the aggregate WGI publicly available through the WGI website, including data from a large number of commercial sources. This makes the WGI project one of the largest cross-country datasets on governance available. The WGI have also evolved in terms of the accompanying analytic work on relevant data issues. In our first effort (Kaufmann, Kraay and Zoido-Lobatón (1999a,b)) we extensively discussed alternative approaches to constructing aggregate indicators, and over the years we have addressed further aggregation issues. For example, in Kaufmann, Kraay and Mastruzzi (2006a, 2007a) we analyzed extensively the possibility that expert assessments might make correlated perceptions errors in their assessments of governance and that this would distort the weighting of sources in the aggregate WGI. We showed that there was in fact very little evidence for such correlated perceptions errors, and moreover that the WGI were very robust to simple alternative weighting schemes, including just straight unweighted averaging of the underlying data sources. We have also investigated the empirical relevance of other potential problems with expert assessments, for example, the hypotheses that expert assessments are 4 tainted by ideological biases, or are biased towards the views of the business elite, or are biased by the recent economic performance of the countries in question (i.e. so- called 'halo effects'). In each case we proposed specific empirical tests and showed that such biases were for the most part not present, or at most were quantitatively unimportant.4 Another area where we have refined the WGI over time is in the interpretation of changes over time in the aggregate indicators. In Kaufmann, Kraay and Mastruzzi (2005) we developed a dynamic version of the unobserved components model on which the WGI are based and used it to develop formal statistical tests of the significance of changes in governance based on changes in the aggregate indicators. It turned out that a very simple rule of thumb using data from the static version of the WGI was a good approximation to this more complex and formal method of assessing significant changes: if 90 percent confidence intervals in the two periods being compared do not overlap, the observed change in the aggregate WGI is unlikely to signal a statistically -- or practically -- significant change in governance. We have also continuously monitored changes in world averages of governance on our individual data sources, finding no evidence of significant trends in one direction or the other, as a way of validating our choice of units for the aggregate indicators in which world averages are set to be the same over time.5 We contrast this careful attention to the significance of changes in governance indicators with the practice followed by the vast majority of governance and investment climate related datasets, that report no margins of error whatsoever and hence can provide no guidance to users as to circumstances under which observed changes in the data are likely to signal meaningful changes in unobserved governance. More generally, recognizing the importance of margins of error and the imprecision of country rankings, we do not follow the popular practice of producing precisely ranked "top ten" or "bottom ten" lists of countries according to their performance on the WGI, recognizing that such seemingly precise 'horse races' are of dubious relevance and reliability. 4See Kaufmann, Kraay and Mastruzzi (2004) for a discussion of ideological biases, Kaufmann, Kraay and Mastruzzi (2005) for a discussion of halo effects, and Kaufmann, Kraay and Mastruzzi (2007b) for a discussion of business elite biases. 5As discussed in Appendix D, we also adjust for (small) compositional effects driven by (small) increases in the number of countries covered by the governance indicators since 1996. 5 As a consequence of their increased visibility and use by policymakers and scholars worldwide, the WGI have also attracted considerably scrutiny by others. This natural and healthy process of scholarly debate over data and methodology has resulted in several written critiques of the WGI, to which we have provided detailed responses and rebuttals. Interested readers can refer to Kaufmann, Kraay and Mastruzzi (2007a) for a detailed response to several critiques of the WGI that have been raised by other authors, as well as the exchange over the WGI in the April 2007 issue of the Journal of Politics. Finally, we reiterate, as we have with each previous round of the WGI, that the composite indicators we construct are useful as a first tool for broad cross-country comparisons and for evaluating broad trends over time. In contrast, the aggregate WGI are often too blunt a tool to be useful in formulating specific governance reforms in particular country contexts. Such reforms, and evaluation of their progress, need to be informed by much more detailed and country-specific diagnostic data that can identify the relevant constraints on governance in particular country circumstances. We therefore view the WGI as complementary to a large number of other efforts to construct more detailed measures of governance, often just for a single country. We begin by describing the data used to construct this round of the governance indicators in Section 2. In this current update, we have added two data sources to the WGI. The first is the Institutional Profiles Database, an expert assessment of governance and institutional quality in 85 countries produced by the Treasury and Economic Policy Directorate General of the French Ministry of the Economy, Industry and Employment and the French bilateral aid agency Agence Française de Développement. The second consists of the AmericasBarometer household surveys conducted by the Latin America Public Opinion Project at Vanderbilt University. Details on both new sources are provided below. We have also made numerous minor revisions to the past data from several of our underlying sources in order to make them more fully comparable over time. These revisions have resulted in minor changes to our previous estimates for 1996-2006, and so the entire new dataset described here supersedes previous releases. In Section 3 we briefly describe cross-country differences and changes over time in governance as measured by our aggregate indicators. Section 4 concludes. 6 2. Methodology and Data Sources for 2007 In this section we briefly describe the latest update of the WGI. Our methodology for constructing aggregate governance indicators has not changed from past years, and a detailed description can be found in Kaufmann, Kraay, and Mastruzzi (2004), as well as in a technical Appendix D to this paper. We define governance broadly as the traditions and institutions by which authority in a country is exercised. This includes the process by which governments are selected, monitored and replaced; the capacity of the government to effectively formulate and implement sound policies; and the respect of citizens and the state for the institutions that govern economic and social interactions among them. The six dimensions of governance corresponding to this definition that we measure are: 1. Voice and Accountability (VA) ­ measuring perceptions of the extent to which a country's citizens are able to participate in selecting their government, as well as freedom of expression, freedom of association, and a free media. 2. Political Stability and Absence of Violence (PV) ­ measuring perceptions of the likelihood that the government will be destabilized or overthrown by unconstitutional or violent means, including politically-motivated violence and terrorism. 3. Government Effectiveness (GE) ­ measuring perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government's commitment to such policies. 4. Regulatory Quality (RQ) ­ measuring perceptions of the ability of the government to formulate and implement sound policies and regulations that permit and promote private sector development. 5. Rule of Law (RL) ­ measuring perceptions of the extent to which agents have confidence in and abide by the rules of society, and in particular the quality of contract enforcement, property rights, the police, and the courts, as well as the likelihood of crime and violence. 7 6. Control of Corruption (CC) ­ measuring perceptions of the extent to which public power is exercised for private gain, including both petty and grand forms of corruption, as well as "capture" of the state by elites and private interests. In brief, our methodology consists of identifying many individual sources of data on governance perceptions that we can assign to these six broad categories. We then use a statistical methodology known as an unobserved components model to construct aggregate indicators from these individual measures. These aggregate indicators are weighted averages of the underlying data, with weights reflecting the precision of the individual data sources. Crucially our methodology also generates margins of error for the estimates of governance for each country, which need to be taken into account when making comparisons of governance across countries and over time. 2.1 Underlying Data Sources We rely on a large number of individual data sources that provide us with information on perceptions of governance of a wide range of stakeholders. These data sources consist of surveys of firms and individuals, as well as the assessments of commercial risk rating agencies, non-governmental organizations, and a number of multilateral aid agencies and other public sector organizations. A full list of these sources is presented in Table 1. For the 2007 round of the WGI, we rely on a total of 340 individual variables measuring different dimensions of governance. These are taken from 35 different sources, produced by 32 different organizations. Appendices A and B provide a detailed description of each data source, and document how we have assigned individual questions from these data sources to our six aggregate indicators. Almost all of our data sources are available annually, and we use the data only from the most recent year available from each source in our aggregate indicators. In a few cases, as noted in Appendix A, we use data lagged one or two years if current data are not available. In some cases we use several individual variables from a single data source in our aggregate indicators. When we do so, we first compute a simple average of these variables from a single source, and then treat the average of these individual questions as a single observation from that data source. 8 The WGI data sources reflect the perceptions of a very diverse group of respondents. Several are surveys of individuals or domestic firms with first-hand knowledge of the governance situation in the country. These include the World Economic Forum's Global Competitiveness Report, the Institute for Management Development's World Competitiveness Yearbook, the World Bank / EBRD's business environment surveys, the Gallup World Poll, Latinobarometro, Afrobarometro, and the AmericasBarometer. We refer to these as "Surveys" in Table 1. We also capture the perceptions of country analysts at the major multilateral development agencies (the European Bank for Reconstruction and Development, the African Development Bank, the Asian Development Bank, and the World Bank), reflecting these individuals' in-depth experience working on the countries they assess. Together with some expert assessments provided by the United States Department of State and the French Ministry of Finance, Industry and Employment, we classify these as "Public Sector Data Providers" in Table 1. We also have a number of data sources provided by various nongovernmental organizations such as Reporters Without Borders, Freedom House, and the Bertelsmann Foundation. Finally, an important category of data sources for us are commercial business information providers, such as the Economist Intelligence Unit, Global Insight, and Political Risk Services. These last two types of data providers typically base their assessments on a global network of correspondents with extensive experience in the countries they are rating. The data sources in Table 1 are evenly divided among these four categories. Of the 35 data sources, eight are from commercial business information providers and the remaining categories have nine data sources each. However, an important distinction is that the commercial business information providers typically report data for much larger country samples than our other types of sources. An extreme example is the Global Insight Business Conditions and Risk Indicators, which provides information on 203 countries in each of our six aggregate indicators. Primarily for reasons of cost, household and firm surveys typically have much smaller country coverage. Our largest surveys, the Global Competitiveness Report survey and the Gallup World Poll each cover around 130 countries in 2007, and several regional surveys cover necessarily smaller sets of countries. Some of the expert assessments provided by NGOs and public sector organizations have quite substantial country coverage, but others, particularly regionally-focused ones again have much smaller country coverage. 9 Table 2 summarizes the distribution of country-level data points for each of the six indicators in 2007. The 2007 WGI are based on a total of 11,852 country level data points (after averaging multiple questions from individual sources), of which 43 percent come from commercial business information providers. The remaining data points are fairly evenly distributed between the remaining three types of data providers. This year, we continue the practice we started in 2006 of reporting the underlying data from virtually all of the individual data sources that go into our aggregate indicators. The sources we have made available on our website are noted in Table 1. A number of our data sources, such as Freedom House and Reporters Without Borders have always been publicly available through the publications and/or websites of their respective organizations. Several of our other sources provided by commercial risk rating agencies and commercial survey organizations have only been available for a fee. In the interests of greater transparency, these organizations have kindly agreed to allow us to report their proprietary data in the form in which it enters our governance indicators. As mentioned above and as documented in detail in Appendix A and B, we in some cases use a simple average of multiple questions from the same source as an ingredient in our governance indicators. We do this when we find more than one question from a single data source that is relevant to one of the dimensions of governance that we measure. On the interactive part of our website we report either the individual question, or the average of individual questions, from each source that enters into our governance indicators. All the individual variables have been rescaled to run from zero to one, with higher values indicating better outcomes. These individual indicators can be used to make comparisons of countries over time, as all of our underlying sources use reasonably comparable methodologies from one year to the next. They also can be used to compare different countries' scores on each of the individual indicators, recognizing however that these types of comparisons too are subject to margins of error. We caution users however not to compare directly the scores from different sources for a single country, as they are not comparable. To take a specific example, it does not make sense to compare a question rated on a 1-10 scale from a data source covering only developing countries with a similar question rated on a similar scale, but covering developed countries, as the distribution of true governance is likely different in the two groups. For example, the same score of 7 out of 10 10 on the two sources might correspond to quite different levels of governance quality. As discussed in detail in Kaufmann, Kraay, and Mastruzzi (2004) and also in Appendix D, our aggregation procedure provides a way of placing such different sources in common units that allows for meaningful aggregation across sources. The only data sources we have not been able to obtain permission to publicize fully are the World Bank's Country Policy and Institutional Assessment, and the corresponding internal assessments produced by the African Development Bank and the Asian Development Bank. We do note however that starting in 2002 the World Bank began publishing limited information on its CPIA assessments on its external website. For the years 2002-2004 the overall CPIA ratings are reported by quintile for countries eligible to borrow from the International Development Association (IDA), the concessional lending window of the World Bank. Starting in 2005, the individual country scores for the IDA allocation factor, a rating that reflects the CPIA as well as other considerations, is now publicly available. The African Development Bank's CPIA ratings are also publicly available by quintile only since 2004, and are fully public since 2005, and the Asian Development Bank's scores have been fully public for its concessional borrowers since 2005. Finally, as a new feature this year, we are also providing downloadable spreadsheets reporting further details of the available underlying source data for each indicator. These can be found on the Resources page of www.govindicators.org. 2.2 Revisions to Underlying Data Sources In this round of the governance indicators we have added two new data sources. The Institutional Profiles database is a relatively recent effort by the Treasury and Economic Policy Directorate General of the French Ministry of the Economy, Industry, and Employment and the French bilateral aid agency Agence Française de Développement. This data source covers 85 countries in 2006, with an earlier round covering 51 countries in 2001, and the latest version is documented in Meisel and Ould- Aoudia (2007). We have not used this source previously because of the long lag between the first and second rounds -- in the WGI we use only data sources that are updated every three years or more frequently. However, the Institutional Profiles 11 database is scheduled to be updated again in 2009, and so this year we use data from the 2006 database for 2006 and 2007. This dataset is an expert assessment, and the respondents are staff in the country offices of these two agencies in 85 developed and developing countries. Their views on various dimensions of governance and institutional quality are collected through an extensive questionnaire with 365 separate questions. These are combined into a number of sub-indices and indices by the authors of the dataset. Appendix Table A21 reports the variables we take from this source, which appear in all six of the aggregate WGI. The second data source is the AmericasBarometer survey project of the Latin America Public Opinion Project at Vanderbilt University.6 This source conducted household surveys in a set of 20 countries in Latin America in 2006. In Governance Matters IV, we used data from the first round of the surveys, covering 7 countries in 2004. We did not include this data source in 2005 because at the time they had not secured funding for subsequent updates of the surveys. Since then they have secured funding for the next several years, and have conducted surveys in 2006 and are fielding surveys for 2008. As detailed in Appendix Table A31 we use various questions from this survey in Voice and Accountability, Rule of Law, and Control of Corruption. As in past years, we have also made some minor revisions to the underlying data from our existing sources in previous years. In most cases this consisted of ensuring that when we average multiple questions from a single source, we choose questions that are available for as many years as possible so that the composition of these averages changes as little as possible over time. Also, one of our data sources, the Bertelsmann Transformation Index has this year begun to release detailed subcomponents of its broader indices that we have used in the past. For example, they now separately report assessments of corruption, which we now use as a separate source in the Control of Corruption Indicator, while previously this variable was merged with other dimensions of the rule of law. Readers interested in the details of these changes in individual indicators can compare Appendix A of this paper with Appendix A of Kaufmann, Kraay, and Mastruzzi (2007b) describing the 1996-2006 dataset. 6See also Seligson (2008) for further details on AmericasBarometer. 12 These minor revisions to the historical data result in only trivial changes in the six aggregate WGI over the period 1996-2006 when compared with last year's data. In all but one case over the past 10 years, the correlation between the original and the revised indicators is 0.999 or higher. The only minor exception is Regulatory Quality in 1998 where the correlation is still extremely high at 0.97. 2.3 Aggregation Methodology We combine the many individual data sources into six aggregate governance indicators, corresponding to the six dimensions of governance described above. The premise underlying this statistical approach should not be too controversial ­ each of the individual data sources we have provides an imperfect signal of some deep underlying notion of governance that is difficult to observe directly. This means that as users of the individual sources, we face a signal-extraction problem ­ how do we isolate an informative signal about governance from each individual data source, and how do we optimally combine the many data sources to get the best possible signal of governance in a country based on all the available data? The statistical procedure we use to perform this aggregation, known as the unobserved components model, is described in detail in our past work (see for example Kaufmann, Kraay and Mastruzzi (2004), as well as Appendix D). The main advantage of this approach is that the aggregate indicators are more informative about unobserved governance than any individual data source. Moreover, the methodology allows us to be explicit about the precision ­ or imprecision ­ of our estimates of governance in each country. This imprecision is not merely a consequence of our reliance on subjective or perceptions data on governance ­ rather imprecision is an issue that should be squarely addressed in all efforts to measure the quality of governance, recognizing the inherent complexity and imprecision associated with such a task. The aggregation procedure we use in effect first rescales the individual indicators from each underlying source in order to make them comparable across data sources. It then constructs a weighted average of each of these rescaled data sources to arrive at an aggregate indicator of governance. The weights assigned to each data source are in turn based on the estimates of the precision of each source that are produced by the unobserved components model. In brief, the identifying assumption in the unobserved 13 components model is that any observed correlation between two measures of corruption, for example, is due to their common, but unobserved, signal of corruption. From this assumption it follows that data sources that are more correlated with each other provide more reliable information about corruption, and so receive greater weight. In past work, we have discussed in detail the merits of this approach--see particularly Kaufmann, Kraay and Mastruzzi (2006a, Section 3). We have also documented that, since the underlying data sources on average are quite correlated with each other, the choice of weights used to construct the aggregate indicator does not substantially affect the estimates of governance that we report (Kaufmann, Kraay and Mastruzzi 2006a, 2007a).7 Here we briefly report some summary information on the weights for the 2007 indicators. Table 3 reports the weights assigned to each data source in each of the six governance indicators in 2007. 8 This table reports the weights that would be used in the case of a hypothetical country appearing in all of the available underlying data sources for each indicator. Because of gaps in the country coverage of all of our data sources, no single country appears in all data sources. Nevertheless, the information reported in Table 3 is informative about the relative weights of the underlying indicators. The weights used to construct the aggregate governance indicators for any particular country are approximately equal to the relative weights reported in Table 3 for the subset of indicators in which that country appears.9 7 It is also worth noting that a far more consequential weighting decision is whether to include a data source or not. In the WGI we have for the most part opted to include as many data sources as possible, then allowing the data and aggregation procedure to select the weights. For example, household-survey based data sources receive zero weight in the Transparency International Corruption Perceptions Index (TI-CPI) because the constructors of that measure have chosen to exclude all such data sources. Incidentally, while the WGI does include the disaggregate sources used by TI-CPI (and a number of other sources as well, which TI-CPI excludes) for the control of corruption aggregate component, the WGI does not include the TI-CPI itself, because it is also an aggregate poll of polls (in a similar vein to the recently launched Ibrahim Index of African Governance, which compiles individual sources). 8 A full version of this table reporting the weights for all years in Excel format is available for downloading on the Resources tab of www.govindicators.org 9 The precise expression for the weights used for each country can be found in Kaufmann, Kraay and Mastruzzi (2004, Equation (2)) and in the technical Appendix D to this paper. Information on the estimated variance of the error term of each source required to construct these weights can also be downloaded together with the weights reported in Table 3 for all periods at www.govindicators.org. 14 One noteworthy feature in Table 3 is that there are some systematic differences in the weights assigned to different types of sources. These are summarized in the bottom panel of the table. For each of the four types of data sources, we first report the share of each type in the total number of sources for each indicator. For example, for Control of Corruption, we rely on a total of 25 data sources, of which 7, or 28 percent, are from commercial business information providers. We also report the share of the total weights accounted for by each type of indicator. Taking the same example of Control of Corruption, these seven data sources together receive a slightly higher share of the total weight in the indicator, at 35 percent. The last column reports a simple average of these two figures across all six indicators. These show that data from commercial business information providers and data from non-governmental organizations receive weights that are somewhat higher than their proportion in the total number of data sources. NGO-based sources for example get 21 percent of the total weight in the aggregate indicators but account for 16 percent of the data sources. In contrast, survey-based indicators account for 13 percent of the weight on average, but account for 27 percent of sources; and indicators provided by public-sector organizations get almost exactly the same weight on average as their prevalence among the number of sources would suggest (25 versus 26 percent). We can combine this information with the information on country coverage of data sources reported in Table 2. In particular, in the bottom panel of Table 2 we report the distribution of country-level data points, weighting each point by the weight it receives in the corresponding aggregate indicator for each country. In light of the higher weights assigned to data from commercial business information providers, we find that the weighted average share of country-level data points for this type of source rises from 43 percent (unweighted) to 59 percent (weighted). Correspondingly, the weighted share of household surveys declines somewhat from 17 percent to 8 percent, and for public sector providers from 22 percent to 13 percent. We conclude this discussion of weighting by noting that while the weighting scheme we use has the attraction in principle of reducing the variance of the overall governance estimates, in practice this effect is relatively small, with the standard errors of the governance estimates declining by about 10 percent relative to an unweighted 15 benchmark.10 Moreover, if we compare our precision-weighted estimates of governance with an alternative set of aggregate indicators based on simple averages of the underlying indicators, we find that the two estimates of governance are very similar, with correlations of 0.99 on average across all our indicators and periods. This reflects the fact that all of our underlying data sources do, in most cases, provide fairly similar cross- country ratings of governance. We have also experimented with alternative weighting schemes that equally weight each type of governance indicator (of the four types identified in Table 1). Again we find that the correlations are very high with our benchmark indicators (see Kaufmann, Kraay, and Mastruzzi (2007a), Critique 8, for details). 3. Estimates of Governance 1996-2007 In Appendix C we report the aggregate governance indicators, for all countries, for each of the six indicators, for all periods. The aggregate indicators, as well as almost all of the underlying indicators, are available at www.govindicators.org. The units in which governance is measured follow a normal distribution with a mean of zero and a standard deviation of one in each period. This implies that virtually all scores lie between -2.5 and 2.5, with higher scores corresponding to better outcomes.11 This also implies that our aggregate estimates convey no information about trends in global averages of governance, but they are of course informative about changes in individual countries' relative positions over time. Moreover, as we discuss below, we find little evidence from our individual data sources of any systematic trends in world averages of governance. As a result, relative and absolute changes in countries' governance scores are likely to coincide quite closely. Table 4 summarizes some of the key features of our governance indicators. In the top panel we show the number of countries included in each of the six indicators and 10Related to this, the main reason why standard errors vary across countries is because some countries appear in more data sources than others, and not because countries vary in the average precision of the data sources in which they appear. 11These boundaries correspond to the 0.005 and 0.995 percentiles of the standard normal distribution. For a handful of cases, individual country ratings can exceed these boundaries when scores from individual data sources are particularly high or low. Note also that small adjustments to this distribution of scores are made for earlier years to correct for compositional effects driven by expansion of the sample of countries covered. See Appendix D for details. 16 seven periods of WGI measurement since 1996. Depending on the governance component, for 2007 the indicators cover between 207 and 212 countries. Over time, there has been a steady increase in the number of sources included in each of our indicators. This increase in the number of data sources is reflected in an increase in the median number of sources available per country, which, depending on the governance component, ranges from three to six in 1996, and from eight to 13 in 2007. Thanks to the increase in sources, the proportion of countries in our sample for which our governance estimates are based on only one source has also declined considerably, from an average of 15 percent of countries in 1996 to an average of only seven percent in 2007. An important consequence of this expanding data availability is that the standard errors of the governance indicators have declined substantially, as shown in the final panel of Table 4.12 In 1996 the average (for all countries and indicators) of the standard error was 0.33. In 2007 the standard error ranges from 0.18 to 0.23 for five of our six indicators, while for Political Stability it is slightly higher at 0.26 (vs. 0.37 in 1996), reflecting the somewhat smaller number of data sources available for this indicator. These substantial declines in standard errors (on average lowering them by over one- third) illustrate the benefits in terms of precision of constructing composite indicators based on an expanding number of data sources incorporating as much information as possible. Of course, since our aggregate indicators combine information from all of these sources, they have greater precision than any individual underlying data source. Looking across all nine time periods, the median standard error of the individual data sources for the governance indicators was substantially higher at 0.6, with an interquartile range from 0.46 to 0.90.13 In other words, on average the current set of aggregate WGI indicators exhibit standard errors which are less than one-half those of an individual indicator. This highlights the benefit of averaging data from many different 12As described in detail in Kaufmann, Kraay and Mastruzzi (2004), the output of our aggregation procedure is a distribution of possible values of governance for a country, conditional on the observed data for that country. The mean of this conditional distribution is our estimate of governance, and we refer to the standard deviation of this conditional distribution as the "standard error" of the governance estimate. 13In an earlier paper (Kaufmann, Kraay and Mastruzzi (2004)) we showed how to obtain margins of errors for other `objective' measures of governance and found that they were as large, or larger than those of the individual subjective measures on which we rely for the WGI (and thus obviously (thanks to the aggregation) we also found that the WGI had much lower margins of error than any `objective' measure. This underscores the fact that all efforts to measure governance involve margins of error, often non-trivial. 17 sources when seeking to measure broad concepts of governance as we do. Moreover, the likelihood of encountering an extreme outlier in a country's aggregate governance score is commensurately lower than in any individual source. 3.1 Cross-Country Comparisons of Governance Using the WGI We use Figure 1 and Figure 2 to emphasize the importance of taking these margins of error into account when making comparisons of governance across countries and over time. In the two panels of Figure 1, we order countries in ascending order according to their point estimates of governance in 2007 on the horizontal axis, and on the vertical axis we plot the estimate of governance and the associated 90% confidence intervals. These intervals indicate the range in which it is 90 percent likely that the true governance score falls.14 We do this for two of the six governance indicators, Political Stability and Absence of Violence/Terrorism, and Control of Corruption. The size of these confidence intervals varies across countries, as different countries appear in different numbers of sources with different levels of precision. The resulting confidence intervals are substantial relative to the units in which governance is measured. From Figure 1 it should also be evident that many of the small differences in estimates of governance across countries are not likely to be statistically significant at reasonable confidence levels, since the associated 90 percent confidence intervals are likely to overlap. For many applications, instead of merely observing the point estimates, it is therefore more useful to focus on the range of possible governance values for each country (as summarized in the 90% confidence intervals shown in Figure 1), recognizing that these likely ranges often overlap for countries that are being compared with each other.15 14A x% confidence interval for governance can be obtained as the point estimate of governance plus or minus the standard error times the (100-x)/2th percentile of the standard normal distribution. For example, the 90% confidence intervals we report throughout the paper are the point estimate plus or minus 1.64 times the standard error. 15Of course, asking whether 90% confidence intervals overlap or not corresponds to a hypothesis test at a significance level that is more stringent than 10%. The assumptions underlying our statistical model imply that the standard error of the difference between two country scores is the square root of the sum of the squared standard errors of the two sources, which is always smaller than the sum of the two standard errors themselves. It is more convenient -- and more conservative -- for users to simply inspect confidence intervals and see whether they overlap. 18 This is not to say however that the aggregate indicators cannot be used to make cross-country comparisons. To the contrary, there are a great many pair-wise country comparisons that do point to statistically significant, and likely also practically meaningful, differences across countries. Our 2007 Control of Corruption indicator for example covers 208 countries, so that it is possible to make a total of 21,528 pair-wise comparisons of corruption across countries using this measure. For 65 percent of these comparisons, 90% confidence intervals do not overlap, signaling quite highly statistically significant differences across countries. And if we lower our confidence level to 75 percent, which may be quite adequate for many applications, we find that 74 percent of all pair-wise comparisons are statistically significant. In sum, the likelihood that a comparison between any given pair of countries does exhibit a reasonably significant difference in governance performance is close to three-quarters. The benefit of improved precision of aggregate indicators with increased data availability over time can also be clearly seen from this calculation. Consider our 1996 Control of Corruption indicator, which was based on a median of only four data sources per country, as opposed to a median of 11 sources in 2007, implying substantially higher margins of error in 1996. Of the 11,781 possible pair-wise comparisons in 1996, only 46 percent are significant at the 90% confidence level, and only 59 percent at the 75 percent confidence interval (versus 65 percent and 74 percent respectively, in 2007). We also emphasize that the WGI are unusual in that we generate and report these margins of error, which allow an explicit assessment of the significance of observed cross-country and over time differences in estimates of governance. Although rarely explicitly disclosed -- or even acknowledged-- all other measures of governance are subject to margins of error as well, which in our past work we have shown to be at least as large as those we calculate for our individual and aggregate indicators.16 This underscores the need for caution in making cross-country comparisons with any type of governance indicator. 16See Kaufmann, Kraay, and Mastruzzi (2004). 19 3.2 Changes over Time in Governance Using the WGI We now turn to the changes over time in our estimates of governance in individual countries. Figure 2 illustrates these changes for two selected governance indicators over the decade 1998-2007, Voice and Accountability and Rule of Law. In both panels, we plot the 1998 score on the horizontal axis, and the 2007 score on the vertical axis. We also plot the 45-degree line, so that countries above this line correspond to improvements in governance, while countries below the line correspond to deteriorations in governance. The first feature of this graph is that most countries are clustered quite close to the 45-degree line, indicating that changes in our estimates of governance in most countries are relatively small over the ten-year period covered by the graph. A similar pattern emerges for the other four dimensions of governance (not shown in Figure 2), and, not surprisingly, the correlation between current and lagged estimates of governance is even higher when we consider shorter time periods than the decade shown here. Nevertheless, a substantial number of countries do show significant changes in governance. Over this period, we find that for each of our six indicators, on average 9 percent of countries experience changes that are significant at the 90 percent confidence level. Looking across all six indicators, 31 percent of countries experience a significant change in at least one of the six dimensions of governance over this period, roughly equally divided between improvements and deteriorations. We also note that the 90 percent confidence level is quite high, and for some purposes a lower confidence level, say 75 percent, would be appropriate for identifying changes in governance that are likely to be practically important. Not surprisingly this lower confidence level identifies substantially more cases of significant changes: 20 percent of countries experience a significant change on each indicator on average, and 59 percent of countries experience a significant change on at least one dimension of governance. In Figure 2 we have labeled those countries for which the change in estimated governance over the 1998-2007 period is sufficiently large that the 90% confidence intervals for governance in the two periods do not overlap.17 Examples of such 17 While this is not a formal test of the statistical significance of changes over time in governance, it is a very simple and transparent rule of thumb for identifying changes in governance that are 20 substantial changes in governance estimates between 1998 and 2007 include significant improvements in Voice and Accountability in countries such as Ghana, Indonesia, Nigeria, and Peru, but also declines in that component in countries such as Belarus, Zimbabwe and Cote d'Ivoire. In Rule of Law we see improvements in countries such as Georgia, Liberia, Rwanda, and Estonia, contrasting with declines in countries such as Cote D'Ivoire, Eritrea, and Zimbabwe. Other examples of improvements in estimates of governance not shown in Figure 2 include Rwanda, Algeria and Angola in Political Stability and Absence of Violence/Terrorism, Afghanistan, Serbia and Ethiopia in Government Effectiveness, Georgia and the Democratic Republic of Congo in Regulatory Quality, and Liberia and Serbia in Control of Corruption. In Table 5 we provide more detail on all of the statistically significant (at the 90 percent level) changes in our six governance indicators over the period 1998-2007. The first three columns report the level of governance in the two periods, and the change. The next three columns report on how the underlying data sources move for each case. In the column labeled "Agree" we report the number of sources available in both periods which move in the same direction as the aggregate indicator. The columns labeled "No Change" and "Disagree" report the number of sources on which that country's score does not change or moves in the opposite direction to the aggregate indicator. For each country we also summarize the extent to which changes in the individual sources agree with the direction of change in the aggregate indicator by calculating the "Agreement Ratio", or "Agree" / ("Agree" + "Disagree"). The agreement ratio is quite high for countries with large changes in governance. Averaging across all countries and indicators, we find an average agreement ratio of 0.91 for the period 1998-2007, as reported in Table 5. This provides confidence that for countries with statistically significant changes in our aggregate governance estimates, these changes are reflected in a strong majority of the individual underlying data sources. The last three columns of Table 5 further address directly the issue of adding sources over time. Averaging over all the significant changes, we find that for a typical change, between five and six new data sources were added between 1998 and 2007. likely to be significant. In Kaufmann, Kraay, and Mastruzzi (2005, 2006) we have shown in more detail how to assess the statistical significance of changes in governance, and that this simple rule of thumb turns out to be a fairly good approximation. 21 One might reasonably wonder about the extent to which changes in the aggregate indicators are driven by the addition of sources whose ratings differed from those for 2007 provided by sources also available in 1998. It turns out however that this effect is small in most cases. To see this, in the second-last column, we have calculated the change that we would have seen in the aggregate indicators had we used only those same data sources available in both 1998 and 2007 for the indicated country. We refer to this as the "balanced" (sources) change. The final column reports the ratio of this balanced change to the actual change reported in the third column of Table 5. If this ratio is less than one, the actual change exceeds (in absolute value) the balanced change, indicating that the addition of sources magnified the change relative to what would have been observed using only the balanced set of sources. And if this ratio is greater than one, the addition of new sources offsets the change observed among the balanced sources. It turns out that these compositional effects are not large. For 68 of the 85 significant changes reported in Table 5, the ratio of the balanced change to the actual change is between 0.75 and 1.25, i.e. the balanced change is within 25 percent of the actual change. Another way to see the relative unimportance of compositional effects is to calculate the share of the variance of the actual significant changes that is accounted for by the variance in the balanced changes. When we do this, we find that 97 percent of the variation in the observed changes is due to changes in underlying sources, and only three percent is due to the addition of sources.18 Finally, it is worth noting that the agreement ratios for significant changes in governance are substantially higher than the agreement ratios for all changes in governance. This can be seen in Table 6 which computes the same agreement ratio, but for all countries over the period 1998-2007. The agreement ratio averages 69 percent, compared with 91 percent for large changes, suggesting that for the more typical smaller changes in our governance estimates, there is relatively more disagreement across individual sources about the direction of the change than there is for large changes. Nevertheless, even for these smaller changes, typically the majority 18This is calculated as (VAR(Balanced Changes) + COV(Balanced Changes, Actual Changes))/ VAR(Actual Changes). This is also the slope of a regression of the balanced changes on the actual changes. 22 of underlying individual sources agree about the direction of the change. These examples underscore the importance of carefully examining the factors underlying changes in the aggregate governance indicators in particular countries. In order to facilitate this, on the WGI website users can retrieve the data from the individual indicators underlying our aggregate indicators and use this to examine trends in the underlying data as well as changes over time in the composition of data sources on which the estimates are based. 3.3 Trends in Global Averages of Governance We conclude by reviewing the available evidence on trends in global averages of governance over the expanded time period that we now cover. As we have already noted, the WGI are not informative about trends in global averages because we assume that world averages of governance are zero in each period, as a convenient choice of units. While the aggregate indicators are of course informative about the relative performance of individual (or groups of) countries over time, in order to assess trends in global averages of governance we need to return to our underlying individual data sources. In Table 7 we summarize trends in world averages in a number of our individual data sources. Most of the sources in this table are polls of experts, with data extending over the whole period 1996-2007 covered by the aggregate WGI. Other than expert polls, only one of them, GCS, is a survey with sufficiently standard format to enable comparisons over a reasonable period of time, in this case from 2002 to 2007. The first column reports the number of countries covered by the source in each of the periods shown, and the next three columns present the average across all countries of each of the sources in each of the indicated years. The underlying data have been rescaled to run from zero to one, and for each source and governance component, we report the score on the same question or average of questions that we use in the aggregate indicator. The next two columns report the standard deviation across countries for each source. The final column reports the change in the global average of each indicator over the longest period for which it is available, together with a t-statistic associated with a test of the null hypothesis that the world average score has not changed. 23 The picture that emerges from Table 7 is sobering, as there appears not to be strong evidence of a significant trend of improvements in governance worldwide over the 12 years of data covered in the table. Over this period, the average change in the global averages of these indicators is very small at only 0.02, on a scale from zero to one. While two-thirds of changes are positive (27 out of 41), only one-third of the changes in either direction are significantly different from zero at the 90 percent confidence level. Of these five register declines and nine improvements. This quite mixed picture suggests that there is substantial disagreement among sources about even the direction of changes in global averages of governance. As a result, we cautiously conclude that we do not have as yet any convincing evidence of significant improvements in governance worldwide. We also note that this evidence is consistent with our choice of units for the aggregate governance indicators, which are scaled to have a mean of zero in each period, and as a result relative and absolute changes in country scores on the WGI are likely to be quite similar. 4. Conclusions In this paper we have reported on the latest update of the Worldwide Governance Indicators for 2007. The WGI are available biannually since 1996, and annually for the six-year period 2002-2007. We have also continued our practice of reporting the individual indicators underlying the aggregate WGI. It is our hope that this more timely annual reporting, as well as providing access to individual indicators, are making the aggregate indicators more useful to users in academic and policymaking circles. We nevertheless emphasize to all users the limitations of these measures of governance, which are shared by virtually all efforts to measure governance across countries and over time. The aggregate indicators we construct are useful for broad cross-country and over time comparisons of governance, but all such comparisons should take appropriate account of the margins of error associated with the governance estimates. These margins of error are not unique to our perceptions-based measures but are present -- if not explicitly acknowledged -- in any effort to measure governance. They naturally reflect the inherent difficulty in measuring something as complicated and multifaceted as governance. However, we have shown the feasibility of using the 24 aggregate indicators to make comparisons of governance across countries and over time, subject to appropriate consideration of margins of error. In this paper we also gave a brief account of the evolution of the WGI over the past decade or so, including how the margins of error have declined over time, mostly due to the increasing availability of individual sources. Thus, while margins of error remain non-trivial, it is worth noting that for the current 2007 data we see that 65 percent of all cross-country comparisons result in highly-significant differences (at 90 percent confidence levels), and that about one- third of countries have experienced substantial changes in at least one dimension of governance between 1998 and 2007. We also caution users that the aggregate indicators can in some circumstances be a rather blunt tool for policy advice at the country level. We expect that the provision of the underlying data will help users in identifying -- and acting upon -- more specific aspects of governance that may be problematic in a given country. And we also encourage using these aggregate and individual indicators in conjunction with a wealth of possible more detailed and nuanced sources of country-level data and diagnostics on governance in formulating policy advice. 25 References Kaufmann, Daniel, Aart Kraay and Pablo Zoido-Lobatón (1999a). "Aggregating Governance Indicators." World Bank Policy Research Working Paper No. 2195, Washington, D.C. ------ (1999b). "Governance Matters." World Bank Policy Research Working Paper No. 2196, Washington, D.C. ------ (2002). "Governance Matters II ­ Updated Indicators for 2000/01." World Bank Policy Research Working Paper No. 2772, Washington, D.C. Kaufmann, Daniel, Aart Kraay and Massimo Mastruzzi (2004). "Governance Matters III: Governance Indicators for 1996, 1998, 2000, and 2002". World Bank Economic Review. 18:253-287. Kaufmann, Daniel, Aart Kraay and Massimo Mastruzzi (2005). "Governance Matters IV: Governance Indicators for 1996-2004. World Bank Policy Research Working Paper No. 3630. Washington, D.C. Kaufmann, Daniel, Aart Kraay and Massimo Mastruzzi (2006a). "Measuring Governance Using Perceptions Data", in Susan Rose-Ackerman, ed. Handbook of Economic Corruption. Edward Elgar. Kaufmann, Daniel, Aart Kraay and Massimo Mastruzzi (2006b). "Governance Matters V: Aggregate and Individual Governance Indicators for 1996-2005". World Bank Policy Research Working Paper No. 4012. Washington, D.C. Kaufmann, Daniel, Aart Kraay and Massimo Mastruzzi (2007a). "The Worldwide Governance Indicators Project: Answering the Critics". World Bank Policy Research Working Paper No. 4149. Washington, D.C. Kaufmann, Daniel, Aart Kraay and Massimo Mastruzzi (2007b). "Growth and Governance: A Reply/Rejoinder". Journal of Politics. 69(2):555-562. Kaufmann, Daniel, Aart Kraay and Massimo Mastruzzi (2007c). "Governance Matters VI: Aggregate and Individual Governance Indicators for 1996-2005". World Bank Policy Research Working Paper No. 4280. Washington, D.C. Kaufmann, Daniel and Aart Kraay (2008). "Governance Indicators: Where Are We and Where Should We Be Going?" World Bank Research Observer. Spring 2008. Meisel, Nicolas and Jacques Ould Aoudia (2007). "A New Institutional Database: Institutional Profiles 2006". Documents de Travail de la DGTPE 2007/09. Seligson, Mitchell (2008). "The AmericasBarometer Approach to Measuring the Quality of Governance". Lecture presented at the "Actionable Governance Indicators Conference," World Bank, Washington, D. C. April 24, 2008 26 Figure 1: Margins of Error for the WGI, 2007 Political Stability and Absence of Violence 2.5 2 1.5 1 DE SL CA CO BO NAD BE NM OVEN gn 0.5 HUN CH STA TSW A BUL ITA ARK IA Rati ILE GAR LGIUM cenanr 0 CUB UKRA BELARU GARI Y LGREEC LIBYA RI ANA E Y CA A veoG INE A S -0.5 PA GE -1 ECU OR INDO TH GI ADO A RAGUAY -1.5 BAN ZIM AILA BABW NE N R -2 GLAD SIA D E NI -2.5 GERIA ESH 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Percentile Rank Control of Corruption 2.5 DE NM 2 CAN AR AD K A 1.5 BE CHI LG 1 LE IUM SL BO OVEN ngitaR 0.5 TSW HU ITA IA AN A e NG LY nc 0 GREEC COSTA AR RI nare BUL CUB E Y CA ovG-0.5 TH GE UKRA NDOI AILA OR LIB GIA GARI A A -1 BANG NI PA BE ECU NE ND ZIM GERI RAG LARU ADO YA INE SIA -1.5 IR AQ BABW LAD A UA S R Y E ESH -2 -2.5 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Percentile Rank 27 Figure 2: Changes Over Time in Governance Indicators 1998-2007 Voice and Accountability 3 07 20 2 1 GHA HRV Y UG LSO KEN PER IDN 0 NER SLE LBR SGP -3 -2 NGA -1 V EN 0 THA 1 2 1998 3 AFG IRQ CIV -1 IRN ZW E BLR ERI -2 -3 Rule of Law 3 07 20 2 EST KIR 1 0 TTO GEO -3 -2 ARG RW A Y UG -1 0 1 2 1998 3 BOL LBR TJK ERI -1 CIVV EN ZW E -2 -3 28 Table 1: Sources of Governance Data Used in 2007 Update of WGI Country Represe Code Source Type* Public Coverage -ntative 1996 1998 2000 2002 2003 2004 2005 2006 2007 ADB African Development Bank Country Policy and Institutional Assessments Expert (GOV) Partial 52 x x x x x x x x AEO OECD Development Center African Economic Outlook Expert (GOV) Yes 33 x x x x x x x x x AFR Afrobarometer Survey Yes 18 x x x x x x x ASD Asian Development Bank Country Policy and Institutional Assessments Expert (GOV) Partial 25 x x x x x x x BPS Business Enterprise Environment Survey Survey Yes 27 x x x x x x x BRI Business Environment Risk Intelligence Business Risk Service Expert (CBIP) Yes 50 x x x x x x x x x BTI Bertelsmann Transformation Index Expert (NGO) Yes 120 x x x x x x CCR Freedom House Countries at the Crossroads Expert (NGO) Yes 63 x x x x DRI Global Insight Global Risk Service Expert (CBIP) Yes 142 x x x x x x x x x x EBR European Bank for Reconstruction and Development Transition Report Expert (GOV) Yes 29 x x x x x x x x x EGV Global E-Governance Index Expert (NGO) Yes 196 x x x x x x x EIU Economist Intelligence Unit Expert (CBIP) Yes 154 x x x x x x x x x x FRH Freedom House Expert (NGO) Yes 197 x x x x x x x x x x GCB Transparency International Global Corruption Barometer Survey Survey Yes 62 x x x x x x GCS World Economic Forum Global Competitiveness Report Survey Yes 125 x x x x x x x x x x GII Global Integrity Index Expert (NGO) Yes 41 x x x x x GWP Gallup World Poll Survey Yes 130 x x x HER Heritage Foundation Index of Economic Freedom Expert (NGO) Yes 157 x x x x x x x x x x HUM Cingranelli Richards Human Rights Database and Political Terror Scale Expert (GOV) Yes 192 x x x x x x x x x x IFD IFAD Rural Sector Performance Assessments Expert (GOV) Yes 100 x x x x IJT iJET Country Security Risk Ratings Expert (CBIP) Yes 187 x x x x x IPD Institutional Profiles Database Expert (GOV) Yes 85 x x x LOB Latinobarometro Survey Yes 18 x x x x x x x x x MIG Merchant International Group Gray Area Dynamics Expert (CBIP) Yes 156 x x x x x x x MSI International Research and Exchanges Board Media Sustainability Index Expert (NGO) Yes 38 x x x x x x OBI International Budget Project Open Budget Index Expert (NGO) Yes 59 x x x PIA World Bank Country Policy and Institutional Assessments Expert (GOV) Partial 136 x x x x x x x x x PRC Political Economic Risk Consultancy Corruption in Asia Survey Survey Yes 12 x x x x x x x x PRS Political Risk Services International Country Risk Guide Expert (CBIP) Yes 140 x x x x x x x x x x QLM Business Environment Risk Intelligence Financial Ethics Index Expert (CBIP) Yes 115 x x x x x x x x x x RSF Reporters Without Borders Press Freedom Index Expert (NGO) Yes 166 x x x x x x x TPR US State Department Trafficking in People report Expert (GOV) Yes 153 x x x x x x x x VAB Vanderbilt University Americas Barometer Survey Yes 22 x x x x x WCY Institute for Management and Development World Competitiveness Yearbook Survey Yes 53 x x x x x x x x x WMO Global Insight Business Conditions and Risk Indicators Expert (CBIP) Yes 202 x x x x x x x x x *CBIP -- Commercial Business Information Provider, GOV -- Public Sector Data Provider, NGO -- Non-Governmental Organization Data Provider 29 Table 2: Distribution of Data Points by Type of Data in 2007 WGI Commercial Business Surveys of Non- Information Firms or Governmental Public Sector Providers Households Organizations Organizations Total Number of Data Points Voice and Accountability 492 374 751 399 2016 Political Stability/Absence of Violence 1024 186 0 315 1525 Government Effectiveness 840 388 321 393 1942 Regulatory Quality 790 213 282 422 1707 Rule of Law 955 409 439 737 2540 Control of Corruption 954 493 282 393 2122 Total 5055 2063 2075 2659 11852 Shares of Total for Each Indicator Voice and Accountability 0.24 0.19 0.37 0.20 1.00 Political Stability/Absence of Violence 0.67 0.12 0.00 0.21 1.00 Government Effectiveness 0.43 0.20 0.17 0.20 1.00 Regulatory Quality 0.46 0.12 0.17 0.25 1.00 Rule of Law 0.38 0.16 0.17 0.29 1.00 Control of Corruption 0.45 0.23 0.13 0.19 1.00 Total 0.43 0.17 0.18 0.22 1.00 Weighted Shares of Total for Each Indicator Voice and Accountability 0.24 0.02 0.62 0.12 1.00 Political Stability/Absence of Violence 0.84 0.03 0.00 0.13 1.00 Government Effectiveness 0.65 0.11 0.06 0.18 1.00 Regulatory Quality 0.63 0.07 0.14 0.16 1.00 Rule of Law 0.67 0.10 0.12 0.10 1.00 Control of Corruption 0.65 0.13 0.11 0.11 1.00 Total 0.59 0.08 0.20 0.13 1.00 30 Table 3: Weights Used to Aggregate Individual Data Sources in 2007 WGI VA PV GE RQ RL CC Average Commercial Business Information Providers bri .. 0.058 0.092 .. 0.067 0.006 0.056 dri .. 0.116 0.030 0.024 0.025 0.019 0.043 eiu 0.071 0.126 0.084 0.063 0.104 0.050 0.083 ijt .. 0.094 .. .. .. .. 0.094 mig .. 0.074 0.040 0.038 0.052 0.126 0.066 prs 0.047 0.057 0.061 0.062 0.021 0.021 0.045 qlm .. .. .. .. 0.074 0.076 0.075 wmo 0.033 0.162 0.112 0.123 0.092 0.047 0.095 Surveys of Firms or Households afr 0.022 .. 0.055 .. 0.013 0.013 0.026 bps .. .. 0.001 0.000 0.001 0.021 0.006 gcb .. .. .. .. .. 0.006 0.006 gcs 0.007 0.029 0.065 0.042 0.060 0.045 0.041 gwp 0.002 .. 0.006 .. 0.003 0.006 0.004 lbo 0.001 .. 0.001 .. 0.004 0.000 0.001 prc .. .. .. .. .. 0.064 0.064 vab 0.018 .. .. .. 0.025 0.008 0.017 wcy 0.005 0.033 0.048 0.056 0.062 0.072 0.046 Non-Governmental Organization Data Providers bti 0.120 .. 0.047 0.084 0.013 0.042 0.061 ccr 0.177 .. .. .. 0.006 0.002 0.061 egv .. .. 0.008 .. .. .. 0.008 frh 0.178 .. .. .. 0.110 0.176 0.155 gii 0.074 .. .. .. 0.015 0.002 0.030 her .. .. .. 0.045 0.054 .. 0.050 msi 0.048 .. .. .. .. .. 0.048 obi 0.029 .. .. .. .. .. 0.029 rsf 0.032 .. .. .. .. .. 0.032 Public Sector Data Providers adb .. .. 0.079 0.170 0.045 0.045 0.085 aeo 0.001 0.032 .. .. .. .. 0.017 asd .. .. 0.131 0.038 0.004 0.007 0.045 ebr .. .. .. 0.086 .. .. 0.086 hum 0.035 0.067 .. .. 0.013 .. 0.038 ifd 0.005 .. 0.026 0.030 0.013 0.015 0.018 ipd 0.080 0.116 0.050 0.033 0.064 0.082 0.071 pia .. .. 0.049 0.086 0.045 0.041 0.055 tpr .. .. .. .. 0.004 .. 0.004 Commercial Business Information Providers Share of Sources 0.15 0.58 0.32 0.31 0.27 0.28 0.32 Share of Weights 0.15 0.71 0.43 0.32 0.44 0.35 0.40 Surveys of Firms or Households Share of Sources 0.30 0.17 0.32 0.19 0.27 0.36 0.27 Share of Weights 0.06 0.06 0.18 0.10 0.17 0.24 0.13 Non-Governmental Organization Data Providers Share of Sources 0.35 0.00 0.11 0.13 0.19 0.16 0.16 Share of Weights 0.67 0.00 0.06 0.13 0.20 0.22 0.21 Public Sector Data Providers Share of Sources 0.20 0.25 0.26 0.38 0.27 0.20 0.26 Share of Weights 0.12 0.22 0.34 0.45 0.19 0.19 0.25 31 Table 4: Summary Statistics on Governance Indicators Political Stability/ Voice and Absence of Government Regulatory Control of Accountability Violence Effectiveness Quality Rule of Law Corruption Overall Number of Countries 1996 194 180 182 183 171 154 177 1998 199 189 194 194 194 194 194 2000 200 190 196 196 196 196 196 2002 201 190 202 197 197 197 197 2003 201 200 202 197 202 198 200 2004 208 207 208 204 209 205 207 2005 208 208 209 204 209 205 207 2006 209 209 212 206 211 207 209 2007 209 209 212 207 211 208 209 Median Number of Sources Per Country 1996 4 4 3 4 6 4 4 1998 5 5 4 5 7 5 5 2000 5 5 5 6 8 6 6 2002 7 6 8 8 11 7 8 2003 8 6 8 8 11 8 8 2004 8 7 9 8 12 9 9 2005 9 7 9 8 12 9 9 2006 10 8 10 9 13 11 10 2007 11 8 11 9 13 11 11 Proportion of Countries with Only One Data Source 1996 15 16 21 11 6 18 15 1998 11 7 10 10 9 10 10 2000 11 8 8 7 7 8 8 2002 10 7 5 7 7 8 7 2003 3 10 5 7 5 7 6 2004 6 6 8 7 9 8 7 2005 6 5 8 7 8 7 7 2006 6 3 9 8 8 8 7 2007 6 3 8 9 8 8 7 Average Standard Error 1996 0.25 0.37 0.34 0.41 0.30 0.32 0.33 1998 0.27 0.31 0.18 0.30 0.22 0.24 0.25 2000 0.26 0.32 0.22 0.28 0.19 0.22 0.25 2002 0.21 0.30 0.22 0.25 0.19 0.22 0.23 2003 0.20 0.30 0.22 0.21 0.20 0.20 0.22 2004 0.21 0.29 0.23 0.21 0.19 0.20 0.22 2005 0.20 0.28 0.21 0.21 0.19 0.19 0.21 2006 0.18 0.26 0.23 0.21 0.19 0.19 0.21 2007 0.18 0.26 0.23 0.22 0.19 0.19 0.21 32 Table 5: Significant Changes in WGI Estimates of Governance 1998-2007 Governance Score Agree/ 2007 1998 No Dis- Sources Balanced Bal Chng/ Change Agree (agree+ (Level) (Level) change agree Added Change Actual Chng Disagree) Voice & Accountability THAILAND -0.61 0.40 -1.01 4 0 2 0.67 7 -0.75 0.75 ERITREA -2.15 -1.18 -0.97 2 1 0 1.00 5 -0.75 0.77 BELARUS -1.80 -0.86 -0.93 4 0 0 1.00 5 -0.94 1.01 SINGAPORE -0.43 0.27 -0.69 3 0 3 0.50 5 -0.42 0.61 ZIMBABWE -1.54 -0.86 -0.68 4 2 0 1.00 10 -0.88 1.28 IRAN -1.52 -0.87 -0.65 2 2 1 0.67 6 -0.40 0.62 COTE D'IVOIRE -1.26 -0.65 -0.61 5 1 0 1.00 4 -0.64 1.05 VENEZUELA -0.58 0.00 -0.58 6 0 1 0.86 8 -0.82 1.41 PERU 0.00 -0.57 0.56 3 1 2 0.60 10 0.68 1.20 IRAQ -1.29 -1.93 0.64 4 0 1 0.80 3 0.76 1.18 NIGERIA -0.54 -1.22 0.68 5 1 0 1.00 11 0.55 0.80 CROATIA 0.47 -0.31 0.77 5 0 0 1.00 7 0.79 1.02 LIBERIA -0.35 -1.12 0.77 4 0 0 1.00 5 0.77 0.99 KENYA -0.06 -0.92 0.85 4 2 0 1.00 11 0.54 0.63 INDONESIA -0.17 -1.04 0.87 5 0 1 0.83 9 1.03 1.18 AFGHANISTAN -1.17 -2.04 0.87 3 0 0 1.00 5 1.01 1.16 LESOTHO 0.12 -0.77 0.90 1 1 0 1.00 6 0.73 0.81 GHANA 0.50 -0.43 0.94 6 0 0 1.00 9 0.95 1.01 SIERRA LEONE -0.33 -1.47 1.14 3 0 0 1.00 8 1.18 1.03 NIGER -0.38 -1.54 1.16 4 0 0 1.00 7 1.09 0.94 SERBIA 0.20 -1.14 1.35 5 0 0 1.00 6 1.37 1.02 Average 3.90 0.52 0.52 0.90 7.00 Political Stability and Absence of Violence COTE D'IVOIRE -2.12 -0.28 -1.84 5 0 1 0.83 3 -1.63 0.88 THAILAND -1.07 0.37 -1.44 5 0 1 0.83 5 -1.37 0.95 GUINEA -2.02 -0.58 -1.43 2 0 1 0.67 4 -1.43 1.00 NEPAL -2.13 -0.73 -1.40 2 0 0 1.00 4 -1.07 0.76 NIGERIA -2.07 -0.84 -1.23 4 2 0 1.00 4 -1.20 0.97 LEBANON -2.09 -0.86 -1.23 3 0 2 0.60 3 -0.89 0.72 PHILIPPINES -1.38 -0.15 -1.23 4 1 1 0.80 5 -0.92 0.75 KYRGYZSTAN -1.11 0.01 -1.12 2 0 1 0.67 4 -0.80 0.72 PAKISTAN -2.44 -1.33 -1.12 6 0 0 1.00 4 -1.10 0.99 BANGLADESH -1.44 -0.49 -0.95 4 0 1 0.80 4 -0.96 1.01 UZBEKISTAN -1.42 -0.48 -0.94 2 0 1 0.67 5 -0.84 0.89 ETHIOPIA -1.72 -0.82 -0.90 5 0 0 1.00 4 -1.11 1.24 IRAN -1.33 -0.45 -0.88 5 1 0 1.00 3 -0.84 0.96 VENEZUELA -1.23 -0.38 -0.85 5 0 1 0.83 5 -0.80 0.95 ARMENIA -0.01 -0.86 0.85 4 0 0 1.00 4 1.36 1.60 SOUTH AFRICA 0.18 -0.83 1.01 6 0 1 0.86 5 1.06 1.05 ALGERIA -1.18 -2.33 1.15 5 0 1 0.83 4 1.31 1.14 SERBIA -0.77 -1.96 1.18 4 0 0 1.00 4 1.41 1.19 CONGO -0.83 -2.04 1.21 3 0 1 0.75 4 1.51 1.25 GUINEA-BISSAU -0.41 -1.79 1.39 3 0 0 1.00 0 1.46 1.05 TAJIKISTAN -0.87 -2.26 1.39 3 0 0 1.00 4 1.55 1.12 LIBYA 0.47 -1.23 1.70 5 0 0 1.00 4 1.74 1.02 ANGOLA -0.46 -2.23 1.77 5 0 0 1.00 3 1.99 1.13 SIERRA LEONE -0.30 -2.18 1.88 3 0 0 1.00 2 2.23 1.19 RWANDA -0.19 -2.15 1.96 2 0 0 1.00 3 1.47 0.75 Average 3.88 0.16 0.52 0.89 3.76 Note: Shaded countries correspond to increases in WGI estimates of governance, and non-shaded areas correspond to declines. 33 Table 5: Significant Changes in WGI Estimates of Governance, 1998-2007 Cont'd Governance Score Agree/ 2007 1998 No Dis- Sources Balanced Bal Chng/ Change Agree (agree+ (Level) (Level) change agree Added Change Actual Chng Disagree) Government Effectiveness MALDIVES -0.19 0.96 -1.15 2 0 0 1.00 3 -0.88 0.77 COTE D'IVOIRE -1.37 -0.36 -1.01 6 0 0 1.00 4 -0.96 0.95 ZIMBABWE -1.48 -0.48 -1.00 5 1 1 0.83 7 -0.79 0.79 CHAD -1.45 -0.61 -0.84 3 0 0 1.00 8 -0.59 0.70 TOGO -1.48 -0.68 -0.80 3 1 0 1.00 6 -0.76 0.95 BOLIVIA -0.83 -0.04 -0.79 4 1 0 1.00 8 -0.62 0.79 BELARUS -1.26 -0.51 -0.75 2 0 2 0.50 6 -0.73 0.97 SPAIN 1.00 1.70 -0.70 6 1 0 1.00 4 -0.63 0.89 QATAR 0.06 0.70 -0.63 2 0 2 0.50 3 -0.84 1.33 ITALY 0.33 0.92 -0.59 4 1 2 0.67 4 -0.59 0.99 ETHIOPIA -0.45 -1.09 0.64 4 1 0 1.00 7 0.70 1.09 ALGERIA -0.52 -1.16 0.64 5 1 0 1.00 6 0.83 1.29 RWANDA -0.37 -1.15 0.78 3 0 0 1.00 5 0.66 0.84 SERBIA -0.34 -1.18 0.84 3 0 0 1.00 8 0.93 1.10 HONG KONG 1.80 0.92 0.88 5 0 1 0.83 4 0.90 1.03 KOREA, SOUTH 1.26 0.36 0.90 7 1 0 1.00 5 0.82 0.91 AFGHANISTAN -1.33 -2.27 0.95 1 0 0 1.00 6 0.94 1.00 Average 3.82 0.47 0.47 0.90 5.53 Regulatory Quality ZIMBABWE -2.24 -0.68 -1.56 8 0 0 1.00 4 -1.64 1.05 BOLIVIA -1.18 0.30 -1.48 6 0 0 1.00 5 -1.58 1.07 VENEZUELA -1.56 -0.15 -1.41 8 0 0 1.00 4 -1.63 1.16 ARGENTINA -0.77 0.64 -1.40 8 0 0 1.00 3 -1.58 1.13 ERITREA -1.95 -0.63 -1.32 3 0 0 1.00 3 -1.13 0.85 ECUADOR -1.09 -0.05 -1.04 6 0 0 1.00 4 -1.18 1.13 COTE D'IVOIRE -0.98 -0.07 -0.91 5 2 0 1.00 3 -0.95 1.05 GEORGIA 0.21 -0.77 0.98 5 0 0 1.00 7 1.03 1.06 Congo, Dem. Rep. -1.35 -2.43 1.08 5 0 0 1.00 4 1.14 1.06 LIBYA -0.98 -2.20 1.21 5 0 0 1.00 3 1.32 1.09 IRAQ -1.35 -2.76 1.41 3 1 0 1.00 3 1.49 1.06 Average 5.64 0.27 0.00 1.00 3.91 Note: Shaded countries correspond to increases in WGI estimates of governance, and non-shaded areas correspond to declines. 34 Table 5: Significant Changes in WGI Estimates of Governance, 1998-2007, Cont'd Governance Score Agree/ 2007 1998 No Dis- Sources Balanced Bal Chng/ Change Agree (agree+ (Level) (Level) change agree Added Change Actual Chng Disagree) Rule of Law ZIMBABWE -1.67 -0.50 -1.17 9 0 1 0.90 9 -1.17 1.01 ERITREA -1.10 -0.22 -0.89 4 0 0 1.00 4 -0.61 0.69 VENEZUELA -1.47 -0.69 -0.78 10 1 1 0.91 8 -0.79 1.01 BOLIVIA -0.96 -0.30 -0.66 7 2 0 1.00 9 -0.61 0.93 COTE D'IVOIRE -1.54 -0.90 -0.64 6 2 0 1.00 4 -0.59 0.93 TRINIDAD AND TOBAGO -0.22 0.36 -0.59 6 0 1 0.86 4 -0.44 0.74 ARGENTINA -0.52 0.04 -0.56 9 2 1 0.90 6 -0.58 1.03 ESTONIA 1.00 0.50 0.49 7 2 0 1.00 8 0.51 1.04 TAJIKISTAN -1.13 -1.75 0.61 3 3 0 1.00 11 0.74 1.21 SERBIA -0.57 -1.30 0.72 3 1 1 0.75 9 0.74 1.02 GEORGIA -0.44 -1.18 0.74 4 2 1 0.80 11 0.75 1.01 RWANDA -0.65 -1.47 0.82 4 1 0 1.00 6 0.74 0.91 LIBERIA -1.06 -2.07 1.01 3 1 0 1.00 5 0.85 0.84 KIRIBATI 0.84 -0.69 1.53 1 0 0 1.00 3 0.77 0.50 Average 5.43 1.21 0.43 0.94 6.93 Control of Corruption ERITREA -0.60 0.77 -1.37 2 1 0 1.00 4 -1.52 1.11 ZIMBABWE -1.25 -0.38 -0.87 7 0 1 0.88 8 -0.88 1.01 COTE D'IVOIRE -1.09 -0.38 -0.71 4 2 0 1.00 3 -0.64 0.91 KUWAIT 0.49 1.11 -0.61 2 2 1 0.67 4 -0.29 0.47 POLAND 0.14 0.60 -0.46 6 2 2 0.75 6 -0.45 0.97 UKRAINE -0.73 -1.16 0.44 6 2 1 0.86 9 0.41 0.95 ESTONIA 0.94 0.42 0.52 5 1 1 0.83 7 0.26 0.50 TANZANIA -0.45 -1.09 0.64 5 2 0 1.00 7 0.59 0.93 SERBIA -0.41 -1.08 0.67 4 0 0 1.00 9 0.82 1.22 ICELAND 2.60 1.92 0.68 2 1 2 0.50 3 0.48 0.71 CAPE VERDE 0.76 -0.32 1.08 2 0 0 1.00 4 1.13 1.05 LIBERIA -0.41 -1.72 1.30 3 0 0 1.00 4 1.32 1.01 Average 4.00 1.08 0.67 0.87 5.67 Overall Average 4.35 0.55 0.47 0.91 5.47 0.98 Cases>1.25 5 Cases<0.75 13 0.75 < Cases < 1.75 68 Note: Shaded countries correspond to increases in WGI estimates of governance, and non-shaded areas correspond to declines. 35 Table 6: Agreement Ratio for Changes in WGI Estimates of Governance, 1998-2007 ALL CHANGES Agree / (Agree + Sample Agree No Change Disagree Disagree) Voice and Accountability 199 2.4 0.9 1.1 0.68 Political Stability/Absence Violence 189 2.6 0.6 1.0 0.72 Government Effectiveness 194 2.5 0.8 1.1 0.69 Regulatory Quality 194 3.0 0.8 1.3 0.70 Rule of Law 194 3.2 1.9 1.7 0.65 Control of Corruption 194 2.5 1.5 1.2 0.68 Average 194 2.7 1.1 1.2 0.69 SIGNIFICANT CHANGES (90%) Agree / (Agree + Agree No Change Disagree Disagree) Sample Voice and Accountability 21 3.9 0.5 0.5 0.88 Political Stability/Absence Violence 25 3.9 0.2 0.5 0.88 Government Effectiveness 17 3.8 0.5 0.5 0.89 Regulatory Quality 11 5.6 0.3 0.0 1.00 Rule of Law 14 5.4 1.2 0.4 0.93 Control of Corruption 12 4.0 1.1 0.7 0.86 Average 17 4.4 0.6 0.4 0.91 36 Table 7: Global Trends in Governance Indicators 1996-2007 for Selected Sources Sample Average Std Dev Across Ctrys Change 96- Sample 1996 2007 1996 2007 07* T-stat Voice and Accountability EIU 120 0.41 0.47 0.25 0.26 0.06 1.79 FRH 194 0.56 0.58 0.29 0.28 0.02 0.66 GCS (Press Freedom / Parliament) 94 0.57 0.46 0.15 0.16 -0.11 -4.76 HUM 155 0.63 0.62 0.34 0.30 -0.01 -0.33 PRS 140 0.63 0.67 0.25 0.25 0.04 1.28 WMO 182 0.54 0.58 0.27 0.25 0.04 1.53 RSF 137 .. 0.71 .. 0.22 .. .. Political Stability and Absence of Violence DRI 106 0.82 0.85 0.18 0.15 0.04 1.53 EIU 120 0.56 0.60 0.25 0.22 0.04 1.27 GCS (cost of terrorism) 95 0.66 0.75 0.17 0.13 0.09 3.98 HUM 155 0.63 0.59 0.29 0.26 -0.04 -1.34 PRS * 140 0.70 0.73 0.13 0.11 0.03 1.86 WMO 182 0.67 0.68 0.25 0.22 0.01 0.54 Government Effectiveness CPIA 125 0.41 0.50 0.16 0.13 0.09 4.87 DRI 106 0.57 0.73 0.28 0.21 0.16 4.75 EIU 120 0.43 0.37 0.31 0.26 -0.06 -1.69 GCS (infrastructure quality) 95 0.54 0.51 0.24 0.23 -0.03 -0.86 PRS * 140 0.58 0.54 0.24 0.28 -0.04 -1.33 WMO 182 0.53 0.57 0.24 0.23 0.04 1.54 Regulatory Quality CPIA 125 0.50 0.55 0.14 0.14 0.05 2.83 DRI 106 0.82 0.86 0.16 0.13 0.04 2.21 EIU 120 0.54 0.56 0.22 0.22 0.02 0.73 GCS (burden of regulations) 95 0.30 0.38 0.13 0.13 0.08 4.44 HERITAGE 153 0.54 0.51 0.17 0.19 -0.03 -1.36 PRS 140 0.41 0.72 0.13 0.23 0.31 14.23 WMO 182 0.55 0.60 0.25 0.25 0.04 1.68 Rule of Law CPIA 125 0.40 0.42 0.17 0.15 0.02 1.23 DRI 106 0.71 0.81 0.20 0.17 0.10 3.86 EIU 120 0.49 0.53 0.27 0.24 0.04 1.30 GCS (organized crime / police / independent judiciary) 94 0.57 0.60 0.21 0.19 0.03 1.18 HERITAGE 153 0.57 0.46 0.23 0.24 -0.11 -4.05 HUM 155 0.60 0.40 0.35 0.42 -0.20 -4.54 PRS 140 0.72 0.63 0.23 0.22 -0.09 -3.53 QLM 115 0.45 0.44 0.29 0.30 -0.01 -0.29 WMO 182 0.57 0.59 0.24 0.22 0.02 0.82 Control of Corruption CPIA 125 0.38 0.42 0.16 0.16 0.04 1.95 DRI 106 0.58 0.67 0.26 0.27 0.09 2.55 EIU 120 0.35 0.38 0.33 0.31 0.02 0.51 GCS (bribe frequency) 95 0.64 0.59 0.19 0.19 -0.05 -1.85 PRS 140 0.59 0.43 0.21 0.20 -0.16 -6.61 QLM 115 0.39 0.37 0.29 0.29 -0.02 -0.57 WMO 182 0.50 0.53 0.27 0.25 0.03 0.98 Average 0.02 # Significant Increases 9 # Significant Decreases 5 * Note that changes for GCS are calculated over 2002-2007 and for WMO and CPIA over 1998-2007 ** Note that there are small increases in the number of countries covered between 1996 and 2007 on HER and PRS. 37 Appendix A: Sources for Governance Indicators A1. African Development Bank Country Policy and Institutional Assessments (ADB) 39 A2. OECD Development Center African Economic Outlook (AEO) 40 A3. Afrobarometer (AFR) 41 A4. Asian Development Bank Country Policy and Institutional Assessments (ASD) 42 A5. Business Environment & Enterprise Performance Survey (BPS) 43 A6. Business Environment Risk Intelligence (BRI, QLM) 44 A7. Bertelsmann Transformation Index (BTI) 45 A8. Global Insight Global Risk Service (DRI) 46 A9. European Bank for Reconstruction and Development Transition Report (EBR) 47 A10. Global E-Government Index (EGV) 48 A11. Economist Intelligence Unit (EIU) 49 A12. Freedom House (FRH, CCR) 50 A13. Transparency International Global Corruption Barometer Survey (GCB) 51 A14. World Economic Forum Global Competitiveness Survey (GCS) 52 A15. Global Integrity Index (GII) 53 A16. Gallup World Poll (GWP) 54 A17. Heritage Foundation Index of Economic Freedom (HER) 55 A18. Cingranelli Richards Human Rights Database & Political Terror Scale (HUM) 56 A19. IFAD Rural Sector Performance Assessments (IFD) 57 A20. iJET Country Security Risk Ratings (IJT) 58 A21. Institutional Profile Database (IPD) 59 A22. Latino-Barometro (LBO) 60 A23. Merchant International Group Gray Area Dynamics (MIG) 61 A24. International Research and Exchanges Board Media Sustainability Index (MSI) 62 A25. International Budget Project Open Budget Initiative (OBI) 63 A26. World Bank Country Policy and Institutional Assessments (PIA) 64 A27. Political Economic Risk Consultancy Corruption in Asia (PRC) 65 A28. Political Risk Services International Country Risk Guide (PRS) 66 A29. Reporters without Borders Press Freedom Index (RSF) 67 A30. US State Department's Trafficking in People Report (TPR) 68 A31. Vanderbilt University Americas Barometer (VAB) 69 A32. Institute for Management Development World Competitiveness Yearbook (WCY) 70 A33. Global Insight Business Conditions and Risk Indicators (WMO) 71 Appendix B: Components of Aggregate Governance Indicators B1. Voice and Accountability...........................................................................72 B2. Political Stability and Lack of Violence......................................................... 73 B3. Government Effectiveness........................................................................ 74 B4. Regulatory Quality................................................................................... 75 B5. Rule of Law.............................................................................................76 B6. Control of Corruption.................................................................................78 Appendix C: Governance Indicators over Time C1. Voice and Accountability.......................................................................... 79 C2. Political Stability and Lack of Violence......................................................... 82 C3. Government Effectiveness........................................................................ 85 C4. Regulatory Quality................................................................................... 88 C5. Rule of Law............................................................................................ 91 C6. Control of Corruption................................................................................94 Appendix D: Technical Details on the Construction of the WGI .............................97 38 Table A1: African Development Bank Country Policy and Institutional Assessments (ADB) Data Provider African Development Bank. Description Multilateral development bank headquartered in Abidjan, Cote D'Ivoire Website www.afdb.org Data Source Country Policy and Institutional Assessments Type Expert Assessment Respondents African Development Bank country economists, subject to centralized review for comparability Frequency Annual since 1998 Country Coverage African Development Bank client countries Public Access Since 2005 Description Indicators on 16 dimensions of policy and institutional performance. Responses are coded on a 6-point scale. CPIA indicators are used to allocate concessional loans by the African Development Bank. 2007 2006 2005 2004 2003 2002 2000 1998 1996 Voice and Accountability NA .. .. .. .. .. .. .. .. .. Political Stability and Absence of Violence NA .. .. .. .. .. .. .. .. .. Government Effectiveness Policies to improve efficiency of public sector X X X X X X X X .. Budget Management X X X X X X X X .. Efficiency of Public Expenditures X X X X X X X X .. Management of public debt X X X X X X X X .. Quality of Public Administration X X X X .. .. .. .. .. Regulatory Quality Trade policy X X X X X X X X .. Competitive environment X X X X X X X X .. Labor Market Policies X X X X X X X X .. Rule of Law Property rights X X X X X X X X .. Control of Corruption Transparency / corruption X X X X X X X X .. Country Coverage 52 52 52 52 50 50 51 51 .. Year of Publication 2007 2006 2005 2004 2003 2002 2000 1998 .. 39 Table A2: OECD Development Centre African Economic Outlook (AEO) Data Provider OECD Development Centre Description Multilateral organization headquartered in Paris, France Website www.oecd.org/dev Data Source African Economic Outlook Type Expert Assessment Respondents OECD Development Center Staff Frequency Annual since 1996 Coverage African countries Public Access Publicly available through African Economic Outlook report tables. Description Indicators are based on the frequency of newspaper reports on incidents related to two indicators: "hardening of the regime" and "political troubles". Newpaper reports are taken from the weekly newspaper Marchés Tropicaux et Méditerranéens, and are either coded as 0-1 for the occurrence of relevant stories or 0-3 on the severity of reported incidents. Total scores are reported for each country and year, and the distribution is highly skewed by a few countries with very high frequency of reported events. We therefore convert to a three- point scale corresponding to observations in the first, second, and third terciles of the distribution in each year. 2007 2006 2005 2004 2003 2002 2000 1998 1996 Voice and Accountability Hardening of the Regime X X X X X X X X X Political Stability and Absence of Violence Political troubles X X X X X X X X X Government Effectiveness NA .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Regulatory Quality NA .. .. .. .. .. .. .. .. .. Rule of Law NA .. .. .. .. .. .. .. .. .. Control of Corruption NA .. .. .. .. .. .. .. .. .. Country Coverage 36 33 33 32 26 26 26 26 25 Year of Publication 2007 2006 2005 2004 2003 2002 2000 1998 1996 40 Table A3: Afrobarometer (AFR) Data Provider Michigan State University; Institute for Democracy (South Africa); Centre for Democracy and Development (Ghana). Description U.S-based university and African non-governmental organization Website www.afrobarometer.org Data Source Afrobarometer surveys Type Survey Respondents Households Frequency Irregular, approximately every three years since 1999 Coverage African countries Public Access Country level aggregates are publicly available through afrobarometer website. Record-level data is released with some lag through the Inter-University Consortium for Political and Social Research (www.icpsr.org). Description This household survey is designed to collect data on attitudes towards democracy and government in a sample of African countries. We do not use data from the 1999 survey as the questionnaire from this year differs substantially from subsequent years. 2007 2006 2005 2004 2003 2002 2000 1998 1996 Voice and Accountability How much do you trust the parliament? .. .. .. X X X .. .. .. Overall, howsatisfied are you with the way democracy works in your country? .. .. .. X X X .. .. .. Free and fair elections X X X .. .. .. .. .. .. Political Stability and Absence of Violence NA .. .. .. .. .. .. .. .. .. Government Effectiveness Based on your experiences, howeasy or difficult is it to obtain household services (like piped water, electricity or telephone)? X X X X X X .. .. .. Based on your experiences, howeasy or difficult is it to obtain an identity document (such as birth certificate, driver's license or passport)? X X X X X X .. .. .. Regulatory Quality NA .. .. .. .. .. .. .. .. .. Rule of Law Over the past year, how often have you or anyone in your family feared crime in your own home? .. .. .. X X X .. .. .. Over the past year, how often have you or anyone in your family had something stolen from your house? .. .. .. X X X .. .. .. Over the past year, how often have you or anyone in your family been physically attacked? .. .. .. X X X .. .. .. How much do you trust the courts of law? .. .. .. X X X .. .. .. Based on your experiences, howeasy or difficult is it to obtain help from the police when you need it? X X X X X X .. .. .. Control of Corruption How many elected leaders (parliamentarians) do you think are involved in corruption? X X X X X X .. .. .. How many judges and magistrates do you think are involved in corruption? X X X X X X .. .. .. How many government officials do you think are involved in corruption? X X X X X X .. .. .. How many border/tax officials do you think are involved in corruption? X X X X X X .. .. .. Country Coverage 18 18 18 15 15 15 .. .. .. Year of Publication 2005 2005 2005 2002 2002 2002 .. .. .. 41 Table A4: Asian Development Bank Country Policy and Institutional Assessments (ASD) Data Provider Asian Development Bank Description Multilateral development bank headquartered in Manila, the Philippines Website www.adb.org Data Source Country Policy and Institutional Assessments Type Expert Assessment Respondents Asian Development Bank country economists, subject to centralized review for comparability Frequency Annual since 2000 Coverage Asian Development Bank client countries Public Access Since 2005, only for countries eligible for concessional lending by the Asian Development Bank. Description Indicators on 16 dimensions of policy and institutional performance. Responses are coded on a 6-point scale. CPIA indicators are used to allocate concessional loans by the Asian Development Bank. 2007 2006 2005 2004 2003 2002 2000 1998 1996 Voice and Accountability NA .. .. .. .. .. .. .. .. .. Political Stability and Absence of Violence NA .. .. .. .. .. .. .. .. .. Government Effectiveness Quality of Public Administration X X X X X X X .. .. Efficiency of Revenue Mobilization X X X X X X X .. .. Quality of Budgetary & Financial Management X X X X X X X .. .. Regulatory Quality Trade policy X X X X X X X .. .. Competitive environment X X X X X X X .. .. Rule of Law Property rights X X X X X X X .. .. Control of Corruption Anticorruption and Accounting Institutions X X X X X X X .. .. Country Coverage 29 26 25 26 26 25 25 .. .. Year of Publication 2007 2006 2005 2004 2003 2002 2000 .. .. 42 Table A5: Business Environment and Enterprise Performance Survey (BPS) Data Provider World Bank and European Bank for Reconstruction and Development Description Multilateral development banks headquartered in Washington, United States and London, United Kingdom Website http://www.worldbank.org/eca/governance Data Source Business Environment and Enterprise Performance Survey. Type Survey Respondents Firms Frequency Every three years since 1999 Coverage Transition economies in Eastern Europe and Former Soviet Union Public Access Full access to firm-level data through website noted above Description This survey, part of the Investment Climate Survey project of the World Bank, collects a wide range of data on firms' financial performance and their perceptions of the regulatory and investment climate. 2007 2006 2005 2004 2003 2002 2000 1998 1996 Voice and Accountability NA .. .. .. .. .. .. .. .. .. Political Stability and Absence of Violence NA .. .. .. .. .. .. .. .. .. GovernmentEffectiveness How problematic are telecommunications for the growth of your business X X X X X X X .. .. How problematic is electricity for the growth of your business. X X X X X X X .. .. How problematic is transportation for the growth of your business. X X X X X X X .. .. Regulatory Quality Information on the laws and regulations is easy to obtain X X X X X X .. .. .. Unpredictability of changes of regulations X X X X X X X .. .. How problematic are labor regulations for the growth of your business. X X X X X X X .. .. How problematic are tax regulations for the growth of your business. X X X X X X X .. .. How problematic are custom, foreign currency and trade regulations for the growth of your business. X X X X X X X .. .. Rule of Law How often is following characteristic associated with the court system: Fair X X X X X X X .. .. How often is following characteristic associated with the court system: affordable X X X X X X X .. .. How often is following characteristic associated with the court system: enforceable X X X X X X X .. .. How often is following characteristic associated with the court system: Honesty X X X X X X X .. .. How often is following characteristic associated with the court system: Quickness X X X X X X X .. .. Are property rights adequately protected X X X X X X X .. .. How problematic is organized crime for the growth of your business. X X X X X X X .. .. How problematic is judiciary for the growth of your business. X X X X X X X .. .. How problematic is street crime for the growth of your business. X X X X X X X .. .. Control of Corruption How common is for firms to have to pay irregular additional payments to get things done X X X X X X X .. .. Percentage of total annual sales do firms pay in unofficial payments to public officials X X X X X X X .. .. How often do firms make extra payments for permits, in connection with utilities, in procurement, in taxes, in customs, in the judiciary and to influence the content of new legislation X X X X X X X .. .. Extent to which firms' payments to public officials impose costs on other firms X X X X X X X .. .. How problematic is corruption for the growth of your business. X X X X X X X .. .. Country Coverage 27 27 27 27 27 27 18 .. .. Year of Publication 2005 2005 2005 2002 2002 2002 2000 .. .. 43 Table A6: Business Environment Risk Intelligence (BRI, QLM) Data Provider BERI S.A. Description Commercial risk rating agency headquartered in Geneva, Switzerland Website www.beri.com Data Source Political Risk Index and Operational Risk Index (BRI), Quantitative Risk Measure in Foreign Lending (QLM) Type Expert assessments Respondents Permanent panel of experts convened by BERI Frequency Three times per year since 1980 for BRI and annual since 1996 for QLM Coverage Global sample of countries Public Access Full dataset is commercially available. Averages of sub-indicators are publicly available in this spreadsheet. Description PRI measures eight causes and two symptoms of political risk on a 7-point scale. ORI measures 15 obstacles to business development on a 5-point scale. QLM measures risk factors in foreign lending on a 100-point scale. We use data from latest trimester in each year. We treat BRI and QLM as separate sources in our aggregation procedure as BRI is a "non-representative" source and QLM is a "representative source". See Kaufmann, Kraay, and Mastruzzi (2004) for an explanation of how this distinction matters for aggregation. 2007 2006 2005 2004 2003 2002 2000 1998 1996 Voice and Accountability NA .. .. .. .. .. .. .. .. .. Political Stability and Absence of Violence Political Risk Index: External Causes of Political Risk: Dependence on/Importance to a X X X X X X X X X Hostile Major Power Political Risk Index: External Causes of Political Risk: Negative Influences of Regional X X X X X X X X X Political Forces Political Risk Index: Internal Causes of Political Risk: Social Conditions: Wealth Distribution, X X X X X X X X X Population Political Risk Index: Internal Causes of Political Risk: Fractionalization of political spectrum X X X X X X X X X and the power of these factions. Political Risk Index: Internal Causes of Political Risk: Fractionalization by language, ethnic X X X X X X X X X and/or religious groups and the power of these factions. Political Risk Index: Internal Causes of Political Risk: Restrictive (coercive) measures X X X X X X X X X required to retain power. Political Risk Index: Internal Causes of Political Risk: Organization and strength of forces X X X X X X X X X for a radical government. Political Risk Index: Symptoms of Political Risk: Societal conflict involving demonstrations, X X X X X X X X X strikes, and street violence. Political Risk Index: Symptoms of Political Risk: Instability as perceived by non- X X X X X X X X X constitutional changes, assassinations, and guerilla wars. Government Effectiveness Operation Risk Index: Bureaucratic delays X X X X X X X X X Regulatory Quality NA .. .. .. .. .. .. .. .. .. Rule of Law Operation Risk Index: Enforceability of contracts X X X X X X X X X Direct Financial Fraud, Money Laundering and Organized Crime (QLM) X X X X X X X X X Control of Corruption Political Risk Index: Internal Causes of Political Risk: Mentality, including xenophobia, nationalism, corruption, nepotism, willingness to compromise. X X X X X X X X X Indirect Diversion of Funds (QLM) X X X X X X X X X Country Coverage (BERI) 50 50 50 50 50 50 50 50 53 Country Coverage (QLM) 115 115 115 115 115 115 115 115 115 Year of Publication 2007 2006 2005 2004 2003 2002 2000 1998 1996 44 Table A7: Bertelsmann Transformation Index (BTI) Data Provider Bertelsmann Foundation Description Nongovernmental organization headquartered in Berlin, Germany, with goal to study social challenges and problems and propose solutions. Website www.bertelsmann-stiftung.de Data Source Bertelsmann Transformation Index Type Expert Assessment Respondents Staff of Bertelsmann Foundation Frequency Every three years since 2003 Coverage Global sample of countries Public Access Yes Description We use data on the subcomponents of the Status Index (SI -- rating countries along dimensions of democracy and market economy status) and the Management Index (MI -- rating countries according to progress in achieving democracy and market economy status). Note that the MI rating captures information up to two years earlier. For instance, the BTI 2008 MI looked at events from 2005 to 2007. We have mapped them however only to 2007. Note also that the corruption variable was drawn from one of the sub-components of resource efficiency. 2007 2006 2005 2004 2003 2002 2000 1998 1996 Voice and Accountability Political Participation (SI) X X X X X X .. .. .. Stability of Democratic Institutions (SI) X X X X X X .. .. .. Political and Social Integration (SI) X X X X X X .. .. .. Political Stability and Absence of Violence NA .. .. .. .. .. .. .. .. .. Government Effectiveness Consensus Building (MI) X X X X X X .. .. .. Governance Capability (MI) X X X X X X .. .. .. Resource Efficiency (MI) X X X X X X .. .. .. Regulatory Quality Competition (SI) X X X X X X .. .. .. Rule of Law Rule of Law (SI) X X X X X X .. .. .. Control of Corruption Anti-Corruption policy X X X X .. .. .. .. .. Country Coverage 125 119 119 119 116 116 .. .. .. Year of Publication 2007 2005 2005 2005 2002 2002 .. .. .. 45 Table A8: Global Insight Global Risk Service (DRI) Data Provider Global Insight Description Commercial business information provider headquartered in Boston, United States Website www.globalinsight.com Data Source Global Risk Service Type Expert Assessment Respondents Staff of Global Insight, subject to regional reviews Frequency Quarterly since 1996 Coverage Global sample of countries Public Access Full dataset is commercially available. Averages of sub-indicators are publicly available in this spreadsheet. Description The Global Risk Service, formerly known as the Country Risk Review, was introduced by Data Resources, Inc (DRI) in 1996. In 2001 DRI became part of Global Insight, which in 2003 also acquired the World Markets Research Center that produces the World Markets Online ratings (WMO, see Table A31). These two sets of ratings continue to be produced independently and so we continue to treat them as distinct sources as we did prior to 2003. The Global Risk Review provides assessments of the likelihood of various "risk events". We use their assessments of risk events occurring in the next five years. Although nominally these indicators measure the likelihood of future changes in dimensions of governance we find that in practice they are highly correlated with other assessments of the level of governance and we interpret them in this way. 2007 200 6 200 5 200 4 20 03 20 02 20 00 1 998 1 996 V oice and Accountability NA .. .. .. .. .. .. .. .. .. P olitical Stability and Absence of Violence Dom estic Po litical Risks: Military C oup Risk: A m ilita ry cou p d'eta t (or a series of su ch event s) th at red uces the G DP growth rat e by 2% during a ny 12-m onth period. X X X X X X X X X Dom estic Po litical Risks: Major Insurge ncy/R ebellion: An in crea se in sco pe o r intensity o f on e or m ore insurgen cies/rebe llion s that reduces t he G DP growth rate by 3% d uring any 12 - X X X X X X X X X m onth period. Dom estic Po litical Risks: Political Terrorism : A n incre ase in scope or in tensity of t errorism tha t redu ce s the GD P g ro wth rate by 1% durin g an y 1 2-mo nth p erio d. X X X X X X X X X Dom estic Po litical Risks: Political A ssassin ation: A p olitical assa ssination (o r a serie s of such event s) th at red uces the G DP growth rat e by 1% during a ny 12-m onth period. X X X X X X X X X Dom estic Po litical Risks: Civil W a r: An in crea se in sco pe o r inte nsity o f on e or m ore civil wars tha t redu ce s the G DP growt h rate by 4% d uring any 1 2-mon th p eriod . X X X X X X X X X Dom estic Po litical Risks: Major Urban Rio t: A n increase in scope , inten sity, or f re quen cy of rio tin g tha t redu ce s the GD P g ro wth rate by 1% durin g an y 1 2-mo nth p erio d. X X X X X X X X X Government Effe ctiveness Dom estic Po litical Risk: G ove rn me nt In stability: A n incre ase in go ve rn men t pe rson nel turno ve r rat e at senior le vels tha t redu ce s the GD P g ro wth rate by 2% durin g an y 1 2-mo nth X X X X X X X X X pe riod. Dom estic Po litical Risk: G ove rn me nt In effe ct ivene ss: A d ecline in g overn me nt p erso nnel qu ality at any le ve l th at red uces the G DP growth rate by 1% during a ny 12-m onth period. X X X X X X X X X Dom estic Po litical Risk: Institution al Fa ilure: A d eterioration o f governm ent capacity to cop e with na tio nal problem s as a re su lt of institutiona l rigid ity or g ridlock that reduces th e G DP X X X X X X X X X growth rate by 1% du ring any 12 -m ont h pe riod. Regulatory Quality P olicie s N on-Tax: Reg ula tio ns -- E xp orts: A 2% re duction in e xpo rt volum e a s a result of a worsening in e xpo rt regulations o r re st rictio ns (such as export lim its) d uring any 1 2-m on th X X X X X X X X X pe riod, with respect t o th e leve l a t th e time of the asse ssm ent. P olicie s N on-Tax: Reg ula tio ns -- I mp orts: A 2% red uctio n in imp ort volu me as a result o f a worsening in im port reg ula tio ns or restrictions (such as im port q uota s) du ring any 12 -m ont h X X X X X X X X X pe riod, with respect t o th e leve l a t th e time of the asse ssm ent. P olicie s N on-Tax: Reg ula tio ns -- O th er B usine ss: An increase in othe r re gulatory burde ns, with respect to t he level at t he tim e of the assessm ent, th at red uces tota l a ggrega te X X X X X X X X X inve stme nt in real LC U term s by 10% P olicie s N on-Tax: O wnership of Business by Non -Re side nts: A 1-po int in crea se on a sca le from "0" to "1 0" in lega l restriction s o n own ersh ip of b usine ss b y n on-reside nts du ring any 12 - X X X X X X X X X m onth period. P olicie s N on-Tax: O wnership of Equ ities by No n-Resid ents: A 1 -p oin t incre ase on a scale from "0" to "1 0" in lega l restriction s o n own ersh ip of e quitie s by non-resid ents d uring any 1 2- X X X X X X X X X m onth period. Rule of Law O utcom es No n-Price: Losses an d Costs o f Crim e: A 1-point increase o n a scale f ro m "0 " to "10 " in crim e du ring any 12-m onth period. X X X X X X X X X Dom estic Po litical Risk: Kidna pping of Foreigne rs: An increase in scop e, inte nsity, o r frequ ency of kidna pping o f foreign ers t hat re duces th e G DP growth ra te b y 1 % du ring any 12- X X X X X X X X X m onth period. P olicie s N on-Tax: En forceability of G ove rn me nt Co ntracts: A 1 point d ecline o n a scale f ro m "0" to "1 0" in th e en forceability of co ntracts du ring any 12-m onth period. X X X X X X X X X P olicie s N on-Tax: En forceability of Privat e Co ntracts: A 1-point decline on a sca le from "0" to "10 " in the le gal enf orce ability of con tracts during a ny 12-m onth period. X X X X X X X X X Control of C orruption Risk E vent Ou tcome non -p rice: L osse s and Costs of Corru ption: A 1 -p oint inc re ase on a scale from "0" to "10 " in corru ption d uring any 1 2-mon th p eriod . X X X X X X X X X Country Cove rage 142 142 12 2 11 8 1 18 1 17 1 11 106 106 Ye ar of P ublic ation 2007 200 6 200 5 200 4 20 03 20 02 20 00 1 998 1 996 46 Table A9: European Bank for Reconstruction and Development Transition Report (EBR) Data Provider European Bank for Reconstruction and Development Description Multilateral development bank based in London, United Kingdom Website www.ebrd.org Data Source Transition Report Type Expert Assessment Respondents EBRD staff Frequency Annual since 1996 Coverage Transition economies Public Access Yes Description The Transition Report includes scores on a 5-point scale for eight Transition Indicators measuring progress towards market economy status. Scores are based on a checklist of underlying criteria and reflect the views of EBRD staff. 2007 2006 2005 2004 2003 2002 2000 1998 1996 Voice and Accountability NA .. .. .. .. .. .. .. .. .. Political Stability and Absence of Violence NA .. .. .. .. .. .. .. .. .. Government Effectiveness NA .. .. .. .. .. .. .. .. .. Regulatory Quality Price liberalisation X X X X X X X X X Trade & foreign exchange system X X X X X X X X X Competition policy X X X X X X X X X Rule of Law NA .. .. .. .. .. .. .. .. .. Control of Corruption NA .. .. .. .. .. .. .. .. .. Country coverage 29 29 27 27 27 27 26 26 27 Year of Publication 2007 2006 2005 2004 2003 2002 2000 1998 1996 47 Table A10: Global E-Governance Index (EGV) Data Provider Brown University Center for Public Policy Description University located in Providence, United States Website www.insidepolitics.org Data Source Global E-Governance Index Type Expert assessment Respondents Research team led by Professor Darrell M. West Frequency Annual since 2002 Coverage Global sample of countries Public Access Yes Description This source reports an assessment of the quality of e-government based on reviews of official government websites. Features assessed include online publications, online database, audio clips, video clips, non-native languages or foreign language translation, commercial advertising, premium fees, user payments, disability access, privacy policy, security features, presence of online services, number of different services, digital signatures, credit card payments, email address, comment form, automatic email updates, website personalization, personal digital assistant (PDA) access, and an English version of the website. Assessments are scored on a 100-point scale with 72 points for availability of publications and databases and 28 points for the number of online services available. 2007 2006 2005 2004 2003 2002 2000 1998 1996 Voice and Accountability NA .. .. .. .. .. .. .. .. .. Political Stability and Absence of Violence NA .. .. .. .. .. .. .. .. .. Government Effectiveness Global E-governance Index X X X X X X .. .. .. Regulatory Quality NA .. .. .. .. .. .. .. .. .. Rule of Law NA .. .. .. .. .. .. .. .. .. Control of Corruption NA .. .. .. .. .. .. .. .. .. Country Coverage 196 196 195 192 195 194 .. .. .. Year of Publication 2007 2006 2005 2004 2003 2002 .. .. .. 48 Table A11: Economist Intelligence Unit (EIU) Data Provider Economist Intelligence Unit Description Commercial business information provider headquartered in London, United Kingdom Website www.eiu.com Data Source Country Risk Service, Country Forecasts Type Expert Assessment Respondents Network of over 500 correspondents, reviewed for consistency by panels of regional experts Frequency Quarterly since 1997 Coverage Global sample of countries Public Access Full dataset is commercially available. Averages of sub-indicators are publicly available in this spreadsheet. Description We use data on the components of these two data sources made available to us by the Economist Intelligence Unit. We use data from December of each year with exception of 1996 in which we draw data from first quarter of 1997. 2007 2006 2005 2004 2003 2002 2000 1998 1996 Voice and Accountability Vested interests X X X X X X X X X Accountablity of Public Officials X X X X X X X X X Human Rights X X X X X X X X X Freedom of association X X X X X X X X X Political Stability and Absence of Violence Orderlytransfers X X X X X X X X X Armed conflict X X X X X X X X X Violent demonstrations X X X X X X X X X Social Unrest X X X X X X X X X International tensions / terrorist threat X X X X X X X X X Government Effectiveness Qualityof bureaucracy / institutional effectiveness X X X X X X X X X Excessive bureacucracy / red tape X X X X X X X X X Regulatory Quality Unfair competitive practices X X X X X X X X X Price controls X X X X X X X X X Discriminatory tariffs X X X X X X X X X Excessive protections X X X X X X X X X Discriminatory taxes X X X X X X X X X Rule of Law Violent crime X X X X X X X X X Organized crime X X X X X X X X X Fairness of judicial process X X X X X X X X X Enforceabilityof contracts X X X X X X X X X Speediness of judicial process X X X X X X X X X Confiscation/expropriation X X X X X X X X X Intellectual property rights protection X X X X X X X X X Private property protection X X X X X X X X X Control of Corruption Corruption among public officials X X X X X X X X X Country coverage 150 152 127 125 120 120 120 120 120 Year of Publication 2007 2006 2005 2004 2003 2002 2000 1998 1996 49 Table A12: Freedom House (FRH, CCR) Data Provider Freedom House Description Freedom House is a non-governmental organization promoting democratic values around the world and is headquartered in New York, United States. Website www.freedomhouse.org Data Source Freedom in the World (FRW), Freedom of the Press (FRP), Nations in Transit (FNT) and Countries at the Crossroads (CCR) Type Expert assessments Respondents Freedom House staff and consultants, subject to centralized review process Frequency FRW: Annual since 1955 FRP: Annual since 1980 FNT: Annual since 1995 CCR: Annual since 2004 but covering alternating sets of countries Coverage FRW: Global sample of countries FRP: Global sample of countries FNT: Transition economies in Eastern Europe and the Former Soviet Union CCR: Developing country sample Public Access Yes Description FRW and FRP provide indicators of political rights (7-point scale), civil liberties (7-point scale), and press freedoms (100-point scale) based on checklists of underlying indicators listed below. The indicators are complemented with country narratives justifying the scores. FNT and CCR are series of more detailed narrative country reports including common sets of quantitative indicators on democratic and economic issues, typically scored on a 7-point scale. These too are based on a checklist of underlying indicators. We average data from FRW, FRP and FNT and treat it as a single source that we refer to as FRH, as these are produced by the same teams. We treat CCR as a distinct source as it is produced separately. Note that the indicators refer to data from the previous year: we therefore lag the data from this source by one year. 2007 2006 20 05 2004 20 03 2002 20 00 1998 19 96 Voice and Accountability Freedom of the World: Political Rights X X X X X X X X X Civil Liberties X X X X X X X X X Freedom of the Press Press Freedom Index X X X X X X X X X Nations in Transit Media X X X X X X X X X Civil Society X X X X X X X X X Electoral P rocess X X X X X X X X X Countries at the Crossroads Civil Liberties X X X X .. .. .. .. .. Accountability and public voice X X X X .. .. .. .. .. Political Stability and Absence of Violence NA .. .. .. .. .. .. .. .. .. Governm ent Effectiveness NA .. .. .. .. .. .. .. .. .. Regulatory Quality N/A .. .. .. .. .. .. .. .. .. Rule of Law Nations in Transit: Rule of Law X X X X X X X X X Countries at the Crossroads: Rule of Law X X X X .. .. .. .. .. Control of Corruption Nations in Transit: Corruption X X X X X X X X .. Countries at the Crossroads: Anti-Corruption and Trans parenc y X X X X .. .. .. .. .. Country coverage (FRH) 1 97 197 1 96 196 1 96 196 1 92 191 1 91 Country coverage (FRP) 1 95 195 1 94 194 1 93 193 1 87 186 1 87 Country coverage (FNT) 29 29 2 9 29 2 8 27 2 7 27 2 7 Country coverage (CCR) 62 62 6 2 60 3 0 .. .. .. .. Year of Publication (FRH, FRP & FNT) 2008 2007 20 06 2005 20 04 2003 20 01 1999 19 97 Year of Publication (CCR) 2007 2006 20 06 2005 20 04 .. .. .. .. 50 Table A13: Transparency International Global Corruption Barometer (GCB) Data Provider Transparency International Description Nongovernmental organization devoted to fighting corruption Website www.transparency.org Data Source Global Corruption Barometer Type Survey Respondents Households Frequency Annual since 2004 Coverage Global sample of countries Public Access Country-level aggregate responses and some breakdowns are reported on TI's website Description This survey commissioned by TI collects data on households' experiences with petty corruption and their perceptions of the overall incidence of corruption. Note that we do NOT use data from the TI Corruption Perceptions Index (TI-CPI). The TI-CPI, in contrast with the GCB, is a composite indicator of corruption based on an aggregation of a subset of the same data sources that we also use for aggregation into our Control of Corruption indicator. Note that in each year we have carried forward GCB scores for those countries that were covered in earlier years (up to two) but not in current year. 2007 2006 2005 2004 2003 2002 2000 1998 1996 Voice and Accountability NA .. .. .. .. .. .. .. .. .. Political Stability and Absence of Violence NA .. .. .. .. .. .. .. .. .. Government Effectiveness NA .. .. .. .. .. .. .. .. .. Regulatory Quality NA .. .. .. .. .. .. .. .. .. Rule of Law NA .. .. .. .. .. .. .. .. .. Control of Corruption Frequency of corruption among public institutions X X X X .. .. .. .. .. Frequency of household bribery X X X X .. .. .. .. .. Country coverage 79 79 74 62 .. .. .. .. .. Year of Publication 2007 2006 2005 2004 .. .. .. .. .. 51 Table A14: World Economic Forum Global Competitiveness Survey (GCS) Data Provider World Economic Forum Description Nongovernmental organization bringing together business, government, academic and media leaders to address economic, social and political issues Website www.weforum.org Data Source Global Competitiveness Survey Type Survey Respondents Firms Frequency Annual since 1996 Coverage Global sample of countries Public Access Full dataset is commercially available. Averages of sub-indicators are publicly available in this spreadsheet. Description This survey gathers the views of domestic and foreign-owned firms on a range of issues related to the business environment. Most questions are scored on a 7-point scale. 2007 2006 2005 2004 2003 2002 2000 1998 1996 VoiceandAccountability Firms are usually informed clearly and transparently by the Government on changes in policies affecting their industry X X .. X X X .. .. .. Newspapers can publishstoriesof their choosing without fearof censorship or retaliation X X X X X X .. .. .. Whendecidinguponpolicies and contracts, Government officials favorwell-connected firms X X X X X X X .. .. Influence of legal contributions topolitical parties onspecific public policy outcomes .. X .. X X X .. .. .. Effectiveness of national Parliament/Congress as alaw making andoversight institution X X X X X X .. .. .. Political Stabilityand Absenceof Violence The threat of terrorismin thecountry imposes significant costs on business X X X X X X .. .. .. Government Effectiveness Quality of general infrastructure X X X X X X X X X Quality of public schools X X X X X X X X X Timespent by senior management dealing with government officials .. X X X X X X X X RegulatoryQuality Administrativeregulationsareburdensome X X X X X X X X X Tax systemis distortionary X X X X X X X X X Import barriers / cost of tariffs as obstacle to growth X X X X X X X X X Competitionin local market is limited X X X X X X X X .. It is easy to start company X X .. X X X X X .. Anti monopoly policy is lax and ineffective X X X X X X X X X Environmental regulations hurt competitiveness X X X X X X X X .. Rule ofLaw Common crime imposes costs onbusiness X X X X X X .. .. .. Organized crime imposes costs onbusiness X X X X X X X X X Money launderingthroughbanks is pervasive .. X X X X X .. .. .. Effectiveness of Police X X X X X X X X X The judiciaryis independent frompolitical influences of government, citizens, or firms X X X X X X X X .. Legal framework to challenge thelegality of government actions is inefficient X X X X X X X X X Intellectual Property protection is weak X X X X X X X X X Protection of financial assets is weak X X X X X X X .. .. Illegal donationtoparties arefrequent .. X .. X X X .. .. .. Percentageof firms which are unofficial or unregistered / Tax evasion X X X X X X X X X Control of Corruption Public trust in financial honesty of politicians X X X X X X X X .. Diversionof public funds duetocorruption is common X X X X X X .. .. .. Frequent for firms to make extra payments connected to: public utilities, tax payments, loan applications, awarding of public contracts, influencing laws, policies regulations, decrees, getting favourable judicial X X X X X X X X X decisions Extent towhichfirms' illegal payments toinfluencegovernment policies imposecosts on other firms X X X X X X X .. .. Extent towhichinfluence of powerful firms withpolitical ties impose costs onother firms X X .. X X X .. .. .. Country Coverage: 131 126 117 104 102 90 76 53 58 Year ofPublication 2007 2006 2005 2004 2003 2002 2000 1998 1996 52 Table A15: Global Integrity Index (GII) Data Provider Global Integrity Description Nongovernmental organization located in Washington, United States, advocating integrity and accountability in government. Website www.globalintegrity.org Data Source Global Integrity Index Type Expert Assessment Respondents Local country experts and peer reviewers recruited by Global Integrity Frequency Every three years between 2003 and 2006, yearly since Coverage Mostly developing country sample Public Access Yes Description The Global Integrity Index uses some 300 indicators to assess the existence and effectiveness of anti-corruption mechanisms that promote public integrity. They typically pair an indication of the "in law'" existence of a particular institutions with an "in practice" assessment of its functioning. We use a simple average of the "in practice" components of each of the indicated GII indicators, in keeping with our practice of relying purely on perceptions-based data in the WGI. Note that in 2007 we have carried forward scores for those countries that were covered in 2006 but not in current year. 2007 2006 2005 2004 2003 2002 2000 1998 1996 Voiceand Accountability Civil Society Organizations X X X X X .. .. .. .. Media X X X X X .. .. .. .. Public Access toInformation X X X X X .. .. .. .. Voting & Citizen Participation X X X X X .. .. .. .. Election Integrity X X X X X .. .. .. .. Political Financing X X X X X .. .. .. .. Political Stabilityand Absenceof Violence NA .. .. .. .. .. .. .. .. .. Government Effectiveness NA .. .. .. .. .. .. .. .. .. RegulatoryQuality NA .. .. .. .. .. .. .. .. .. Rule of Law Executive Accountability X X X X X .. .. .. .. Judicial Accountability X X X X X .. .. .. .. Rule of Law X X X X X .. .. .. .. Law Enforcement X X X X X .. .. .. .. Control of Corruption Anti-Corruption Law X X X X X .. .. .. .. Anti-Corruption Agency X X X X X .. .. .. .. Countrycoverage 66 41 25 25 25 .. .. .. .. Year of Publication 2007 2006 2004 2004 2004 .. .. .. .. 53 Table A16: Gallup World Poll (GWP) Data Provider The Gallup Organization Description Commercial survey firm based in Washington, United States Website www.gallup.com Data Source Gallup World Poll Type Survey Respondents Households Frequency Annual starting in 2006 Coverage Global sample of countries Public Access Full dataset is commercially available. Averages of sub-indicators are publicly available in this spreadsheet. Description The Gallup World Poll is a new survey polling representative samples of households in a large sample of countries. The core survey instrument asks a wide range of questions, including some related to governance as indicated below. Note that in 2007 we have carried forward scores for those countries that were covered in 2006 but not in current year. 2007 2006 2005 2004 2003 2002 2000 1998 1996 Voice and Accountability Confidence in honesty of elections X X .. .. .. .. .. .. .. Political Stability and Absence of Violence NA .. .. .. .. .. .. .. .. .. Government Effectiveness Satisfaction with public transportation system X X .. .. .. .. .. .. .. Satisfaction with roads and highways X X .. .. .. .. .. .. .. Satisfaction with education system X X .. .. .. .. .. .. .. Regulatory Quality NA .. .. .. .. .. .. .. .. .. Rule of Law Confidence in the police force X X .. .. .. .. .. .. .. Confidence in judicial system X X .. .. .. .. .. .. .. Have you been a victim of crime? X X .. .. .. .. .. .. .. Control of Corruption Is corruption in governmnent widespread? X X .. .. .. .. .. .. .. Country coverage 140 122 .. .. .. .. .. .. .. Year of Publication 2007 2006 .. .. .. .. .. .. .. 54 Table A17: Heritage Foundation Index of Economic Freedom (HER) Data Provider Heritage Foundation Description The Heritage Foundation is a nongovernmental research and educational institute headquartered in Washington, United States, advocating conservative public policies. Website www.heritage.org Data Source Index of Economic Freedom Type Expert Assessment Respondents Staff of Heritage Foundation Frequency Annual since 1995 Coverage Global sample of countries Public Access Yes Description Heritage constructs an Index of Economic Freedom consisting of 10 components. There were major revisions to the methodology in 2006 and 2007. We use data from the three of these components that are based on subjective assessments of Heritage staff and are comparable over time: Investment Freedom, Financial Freedom, and Property Rights. These indicators are scored on a 100-point scale. Note that the indicators refer to data from the previous year: we therefore lag the data from this source by one year. 2007 2006 2005 2004 2003 2002 2000 1998 1996 Voiceand Accountability NA .. .. .. .. .. .. .. .. .. Political StabilityandAbsenceof Violence NA .. .. .. .. .. .. .. .. .. Government Effectiveness NA .. .. .. .. .. .. .. .. .. RegulatoryQuality Foreign investment X X X X X X X X X Banking / Finance X X X X X X X X X Rule of Law PropertyRights X X X X X X X X X Control of Corruption NA .. .. .. .. .. .. .. .. .. Countrycoverage 157 157 157 155 155 156 155 161 150 Year of Publication 2008 2007 2006 2005 2004 2003 2001 1999 1997 55 Table A18: Cingranelli Richards Human Rights Database & Political Terror Scale (HUM) Data Provider University of Binghamton Cingranelli-Richards Human rights database (CIRI) and University of North Carolina Political Terror Scale (PTS) Description United States based universities Website www.humanrightsdata.com Data Source Cingranelli-Richards Human Rights Dataset (CIRI) and the Political Terror Scale (PTS) Type Expert assessment Respondents Coding by Cingranelli-Richards and Gibney teams Frequency Annually since 1980 Coverage Global sample of countries Public Access Yes Description The Cingranelli-Richards dataset is a numerical coding on a 2 or 3 point scale of data on 13 human rights, as reported in Amnesty International Human Rights Reports and the U.S. Department of State Country Reports on Human Rights Practices. It is produced by Professor David Cingranelli at the University of Binghamton, U.S.A. and Professor David Richards at the University of Memphis, U.S.A. and is available at www.humanrightsdata.com. The Political Terror Scale is a numerical coding on a 5-point scale of state-sponsored domestic political terror through imprisonments, torture, disappearances and violations of the rule of law. It is produced by Prof. Marc Gibney at the University of North Carolina and is available electronically at: http://www.unca.edu/politicalscience/images/Colloquium/faculty-staff/gibney.html. Note that the two sources are averaged and treated as a single source in Political Stability and Absence of Violence since they are based on the same underlying publications. 2007 2006 2005 2004 2003 2002 2000 1998 1996 Voice and Accountability Restrictions on domestic and foreign travel (CIRI) X X X X X X X X X Freedom of political participation (CIRI) X X X X X X X X X Imprisonments because of ethnicity, race, or political, religious beliefs? (CIRI) X X X X X X X X X Government censorship (CIRI) X X X X X X X X X Political Stability and Absence of Violence Frequency of political killings (CIRI) X X X X X X X X X Frequency of disappearances (CIRI) X X X X X X X X X Frequency of tortures (CIRI) X X X X X X X X X Political terror scale (PTS) X X X X X X X X X Government Effectiveness NA .. .. .. .. .. .. .. .. .. Regulatory Quality NA .. .. .. .. .. .. .. .. .. Rule of Law Independence of judiciary (CIRI) X X X X X X X X X Control of Corruption NA .. .. .. .. .. .. .. .. .. Country coverage (CIRI) 192 192 192 192 159 159 159 159 159 Country coverage (PTS) 176 176 176 178 178 178 178 177 174 Year of Publication 2007 2007 2006 2005 2004 2003 2001 1999 1997 56 Table A19: IFAD Rural Sector Performance Assessments (IFD) Data Provider International Fund for Agricultural Development Description Multilateral development institution headquartered in Rome, Italy, financing agricultural investments in developing countries. Website www.ifad.org Data Source Rural Sector Performance Assessments Type Expert assessment Respondents IFAD country economists, subject to centralized review Frequency Annual since 2004 Coverage IFAD client countries Public Access Yes Description This source assesses 12 dimensions of the rural policy environment on a 6-point scale. The assessments are used in IFAD's performance-based allocation system for distributing resources across countries. 2007 2006 2005 2004 2003 2002 2000 1998 1996 Voiceand Accountability Policyandlegal frameworkfor rural organizations X X X X .. .. .. .. .. Dialoguebetweengovernment and rural organizations X X X X .. .. .. .. .. Political StabilityandAbsenceof Violence NA .. .. .. .. .. .. .. .. .. Government Effectiveness Allocation &management of publicresourcesforrural development X X X X .. .. .. .. .. RegulatoryQuality Enablingconditionsfor rural financial servicesdevelopment X X X X .. .. .. .. .. Investment climate forrural businesses X X X X .. .. .. .. .. Accessto agricultural input andproduce markets X X X X .. .. .. .. .. Ruleof Law Accessto land X X X X .. .. .. .. .. Accessto waterfor agriculture X X X X .. .. .. .. .. Control of Corruption Accountability, transparencyand corruptionin rural areas X X X X .. .. .. .. .. CountryCoverage 87 100 121 124 .. .. .. .. .. Year of publication 2007 2006 2005 2004 .. .. .. .. .. 57 Table A20: iJET Country Security Risk Ratings (IJT) Data Provider iJET Description Commercial security risk consulting company based in Annapolis, United States Website www.ijet.com Data Source Country Security Risk Ratings Type Expert assessment Respondents iJET staff Frequency Annual since 2004 Coverage Global sample of countries Public Access Commercially available Description iJET provides assessments of security risks faced by travelers, coded on a 5-point scale. 2007 2006 2005 2004 2003 2002 2000 1998 1996 Voice and Accountability NA .. .. .. .. .. .. .. .. .. Political Stability and Absence of Violence Security Risk Rating X X X X .. .. .. .. .. Government Effectiveness NA .. .. .. .. .. .. .. .. .. Regulatory Quality NA .. .. .. .. .. .. .. .. .. Rule of Law NA .. .. .. .. .. .. .. .. .. Control of Corruption NA .. .. .. .. .. .. .. .. .. Country Coverage 184 182 177 167 .. .. .. .. .. Year of publication 2007 2006 2005 2004 .. .. .. .. .. 58 Table A21: Institutional Profiles Database (IPD) Data Provider French Ministry of the Economy, Finance and Industry and the Agence Francais de Developpement Description French Government Website http://www.cepii.fr/ProfilsInstitutionnelsDatabase.htm Data Source Country Security Risk Ratings Type Expert assessment Respondents Country office staff of the two ministries Frequency Every three years since 2006 Coverage Global sample of countries Public Access Yes Description The Institutional Profiles database presents a set of indicators on the institutional characteristics of 85 developed and developing countries. The subject scope covers a broad spectrum of these institutional characteristics: functioning of political institutions, public security, public governance, markets' operating freedom, stakeholder co-ordination and strategic vision of the authorities and agents, security of transactions, market regulations and corporate governance, social dialogue, openness of society and markets, social cohesion. 2 007 20 06 2005 2 004 20 03 200 2 2000 1 998 1996 Voice and Accountability Political righ ts and function ing of political institution s X X .. .. .. .. .. .. .. Freedom of the press X X .. .. .. .. .. .. .. Freedom of asso ciation X X .. .. .. .. .. .. .. Freedom of asse mb ly and dem on stra tion X X .. .. .. .. .. .. .. R espect fo r minoritie s (e thnic, religious, linguistic, etc) X X .. .. .. .. .. .. .. Transp arency of p ublic action in the econom ic field X X .. .. .. .. .. .. .. Transp arency of e co nom ic p olicy (fisca l, taxation, m on etary, exchang e-ra te) X X .. .. .. .. .. .. .. Award o f pu blic procurem ent contracts an d de legation o f pu blic service X X .. .. .. .. .. .. .. Free mo ve men t of persons, information , etc X X .. .. .. .. .. .. .. Political Stability and Absence of Violence C onflicts o f eth nic, re ligious, region al natu re ... X X .. .. .. .. .. .. .. Viole nt a ctions by unde rg ro und political organisations X X .. .. .. .. .. .. .. Viole nt social co nflicts X X .. .. .. .. .. .. .. External public security X X .. .. .. .. .. .. .. Government Effectiveness Governm ent-citizen rela tio ns X X .. .. .. .. .. .. .. C apacity of the ta x a dm inistration to implem ent me asures decided on X X .. .. .. .. .. .. .. Quality of the sup ply of pu blic goo ds: education and b asic he alth X X .. .. .. .. .. .. .. C apacity of the p olitical a utho rities X X .. .. .. .. .. .. .. R egulatory Quality Adm in istrative bu siness start-up form alities X X .. .. .. .. .. .. .. Adm in iste red prices and m arket prices X X .. .. .. .. .. .. .. C omp etitio n: p ro ductive sector: ea se of market entry for new firm s X X .. .. .. .. .. .. .. C omp etitio n be tween businesses: com petition regulation arran gem ents X X .. .. .. .. .. .. .. R ule of Law R espect fo r law in re lation s betwe en citizens a nd the a dm inistration X X .. .. .. .. .. .. .. Security of perso ns and goo ds X X .. .. .. .. .. .. .. Organ ised criminal activity (drug-traffickin g, arm s-trafficking, e tc. X X .. .. .. .. .. .. .. Importance of th e inform al econo my X X .. .. .. .. .. .. .. Importance of ta x e vasion in the formal sector X X .. .. .. .. .. .. .. Importance of custom s evasio n (smu ggling , un der-decla ratio n, e tc) X X .. .. .. .. .. .. .. R unning of the justice system X X .. .. .. .. .. .. .. Security of trad ition al property rig hts X X .. .. .. .. .. .. .. Security of pro perty righ ts: form al property rights X X .. .. .. .. .. .. .. Security of con tra cts betwe en priva te a gents X X .. .. .. .. .. .. .. Governm ent respect for contracts X X .. .. .. .. .. .. .. Settle men t of econo mic disp utes: justice in com me rcial matters X X .. .. .. .. .. .. .. Intelle ctual prope rty X X .. .. .. .. .. .. .. Arrange men ts for th e protectio n of in tellectu al property X X .. .. .. .. .. .. .. Agricu ltu ra l secto r: secu rity of rights and property tran sa ction s X X .. .. .. .. .. .. .. C ontrol of Corruption C orru ption X X .. .. .. .. .. .. .. C ountry coverage 85 85 .. .. .. .. .. .. .. Year of Publication 2006 2006 .. .. .. .. .. .. .. 59 Table A22: Latinobarometro (LBO) Data Provider Latinobarometro Description Nongovernmental organization based in Santiago, Chile Website www.latinobarometro.org Data Source Latinobarometro surveys Type Survey Respondents Households Frequency Annual since 1995 Coverage Sample of Latin American countries Public Access Full dataset is commercially available. Averages of sub-indicators are publicly available in this spreadsheet. Description Latinobarometro administers a common questionnaire to households in Latin America with questions on areas such as Economy and International Trade, Integration and Regional Trading Blocks, Democracy, Politics and Institutions, Social Policies, Civic Culture, Social Capital and Social Fraud, the Environment, and Current Issues. 2007 2006 2005 2004 2003 2002 2000 1998 1996 Voice and Accountability Satisfaction with democracy X X X X X X X X X Trust in Parliament X X X X X X X X X Political Stability and Absence of Violence NA .. .. .. .. .. .. .. .. .. Government Effectiveness Trust in Government X X X X X X .. .. X Regulatory Quality NA .. .. .. .. .. .. .. .. .. Rule of Law Trust in Judiciary X X X X X X X X X Trust in Police X X X X X X X X X Have you been a victim of crime? X X X X X X X X X Control of Corruption Frequency of corruption X X X X X X X .. .. Country Coverage 18 18 18 18 17 17 17 17 17 Year of publication 2007 2006 2005 2004 2003 2002 2000 1998 1996 60 Table A23: Merchant International Group Gray Area Dynamics (MIG) Data Provider Merchant International Group Description Commercial risk rating agency headquartered in London, United Kingdom Website www.merchantinternational.com Data Source Gray Area Dynamics. Type Expert assessment Respondents Merchant International Group staff Frequency Quarterly since 1994 Coverage Global sample of countries Public Access Full dataset is commercially available. Averages of sub-indicators are publicly available in this spreadsheet. Description Provides assessments of risks to foreign investor posed by 10 risk factors assessed on a 10- point scale. 2007 2006 2005 2004 2003 2002 2000 1998 1996 Voice and Accountability NA .. .. .. .. .. .. .. .. .. Political Stability and Absence of Violence Extremism X X X X X X .. .. .. Government Effectiveness Bureaucracy X X X X X X .. .. .. Regulatory Quality Unfair Trade X X X X X X .. .. .. Unfair Competition X X X X X X .. .. .. Rule of Law Legal Safeguards X X X X X X .. .. .. Organized Crime X X X X X X .. .. .. Control of Corruption Corruption X X X X X X .. .. .. Country coverage 156 156 155 155 155 118 .. .. .. Year of Publication 2007 2006 2005 2004 2003 2002 .. .. .. 61 Table A24: International Research and Exchanges Board Media Sustainability Index (MSI) Data Provider International Research and Exchanges Board Description International nonprofit organization headquartered in Washington, United States, specializing in education, independent media, Internet development, and civil society programs. Website www.irex.org Data Source Media Sustainability Index Type Expert assessment Respondents Panel of local respondents in each country, subject to centralized review Frequency Annual since 2002 Coverage Developing country sample Public Access Yes Description Index rates countries on a variety of subcomponents relating to freedom of speech, plurality of media available to citizens, professional journalism standards, business sustainability of media, and the efficacy of institutions that support independent media. Note that for each year we have carried forward score from those countries that were covered in earlier years (up to two) but not in current year. 2007 2006 2005 2004 2003 2002 2000 1998 1996 Voice and Accountability Media Sustainability Index X X X X X X .. .. .. Political Stability and Absence of Violence NA .. .. .. .. .. .. .. .. .. Government Effectiveness NA .. .. .. .. .. .. .. .. .. Regulatory Quality NA .. .. .. .. .. .. .. .. .. Rule of Law NA .. .. .. .. .. .. .. .. .. Control of Corruption NA .. .. .. .. .. .. .. .. .. Country Coverage 63 63 37 18 18 18 .. .. .. Year of publication 2008 2007 2005 2005 2004 2002 .. .. .. 62 Table A25: International Budget Project Open Budget Index (OBI) Data Provider International Budget Project Description Nongovernmental organization based in Washington, United States, devoted to developing civil society capacity to influence government budget processes. Website www.internationalbudget.org Data Source Open Budget Index Type Expert assessment Respondents Local experts recruited by the International Budget Project subject to anonymous peer review Frequency First release in 2006, intended annual frequency Coverage Global country sample Public Access Yes Description The Open Budget Index is based on a questionnaire with 122 multiple choice questions on various dimensions of the availability, timeliness and quality of central government budget documents. Note that the 2006 index refers to data reflecting conditions in 2005. 2007 2006 2005 2004 2003 2002 2000 1998 1996 Voice andAccountability Open Budget Initiative X X X .. .. .. .. .. .. Political StabilityandAbsence ofViolence NA .. .. .. .. .. .. .. .. .. Government Effectiveness NA .. .. .. .. .. .. .. .. .. RegulatoryQuality NA .. .. .. .. .. .. .. .. .. Ruleof Law NA .. .. .. .. .. .. .. .. .. Control ofCorruption NA .. .. .. .. .. .. .. .. .. CountryCoverage 59 59 59 .. .. .. .. .. .. Yearof publication 2006 2006 2006 .. .. .. .. .. .. 63 Table A26: World Bank Country Policy and Institutional Assessments (PIA) Data Provider The World Bank. Description Multilateral development bank headquartered in Washington, United States Website www.worldbank.org Data Source Country Policy and Institutional Assessments Type Expert Assessment Respondents World Bank country economists subject to centralized review for comparability Frequency Annually since 1978 Coverage World Bank client countries Public Access Since 2005, only for countries eligible for concessional lending from the International Development Association. Description Indicators on 16 dimensions of policy and institutional performance. Responses are coded on a 6-point scale. CPIA indicators are used to allocate concessional lending across countries. 2007 2006 2005 2004 2003 2002 2000 1998 1996 Voice and Accountability NA .. .. .. .. .. .. .. .. .. Political Stability and Absence of Violence NA .. .. .. .. .. .. .. .. .. Government Effectiveness Management of external debt X X X X X X X X X Quality public administration X X X X X X X .. .. Budget management X X X X X X X X X Efficiency of revenue mobilization / public expenditures X X X X X X X X X Regulatory Quality Business regulatory environment X X X X X X X X .. Trade policy X X X X X X X X X Rule of Law Property rights X X X X X X X X .. Control of Corruption Transparency, accountability and corruption in public sector X X X X X X X X .. Country coverage 140 136 134 135 136 136 136 136 131 Year of Publication 2007 2006 2005 2004 2003 2002 2000 1998 1996 64 Table A27: Political and Economic Risk Consultancy Corruption in Asia Survey (PRC) Data Provider Political and Economic Risk Consultancy Description Commercial business information firm headquartered in Hong Kong, China Website www.asiarisk.com Data Source Corruption in Asia Type Survey Respondents Expatriate business people Frequency Annual since 1998 Coverage Asian countries Public Access Commercially available Description This survey asks respondents to rate severity of corruption, attitudes towards corruption, and effectiveness of efforts to reduce corruption, on a 10-point scale. 2007 2006 2005 2004 2003 2002 2000 1998 1996 Voice and Accountability NA .. .. .. .. .. .. .. .. .. Political Stability and Absence of Violence NA .. .. .. .. .. .. .. .. .. Government Effectiveness NA .. .. .. .. .. .. .. .. .. Regulatory Quality NA .. .. .. .. .. .. .. .. .. Rule of Law NA .. .. .. .. .. .. .. .. .. Control of Corruption To what extent does corruption exist in a way that detracts from the business environment for X X X X X X X X X foreign companies? Country Coverage 13 13 13 12 12 12 12 12 12 Year of publication 2007 2006 2005 2004 2003 2002 2000 1998 1997 65 Table A28: Political Risk Services International Country Risk Guide (PRS) Data Provider Political Risk Services Description Commercial business information provider headquartered in Syracuse, United States Website www.prsgroup.com Data Source International Country Risk Guide Type Expert assessments subject to peer review at the topic and regional levels Respondents Political Risk Services staff Frequency Monthly since 1984 Coverage Global sample of countries Public Access Full dataset is commercially available. Averages of sub-indicators are publicly available in this spreadsheet. Description The International Country Risk Guide includes a Political Risk Index, which in turn consists of 12 components measuring various dimensions of the political and business environment facing firms operating in a country. We use data from December reports of each year. 2007 2006 2005 2004 2003 2002 2000 1998 1996 Voice and Accountability Military in Politics The military are not elected by anyone, so their participation in government, either direct or indirect, reduces accountability and therefore represents a risk. The threat of military intervention might lead as well to an anticipated potentially inefficient change in policy or X X X X X X X X X even in government. It also works as an indication that the government is unable to function effectively and that the country has an uneasy environment for foreign business. Democratic Accountability. Quantifies how responsive government is to its people, on the basis that the less response there is the more likely is that the government will fall, peacefully or violently. It includes not only if free and fair elections are in place, but also how likely is the government to X X X X X X X X X remain in power or remain popular. Political Stability and Absence of Violence Government Stability. Measures the government's ability to carry out its declared programs, and its ability to stay in office. This will depend on issues as: the type of governance, the cohesion of the government and governing party or parties, the closeness of the next election, the government X X X X X X X X X command of the legislature, and approval of government policies. Internal Conflict. Assess political violence and its influence on governance. Highest scores go to countries with no armed opposition, and where the government does not indulge in arbitrary violence, direct or indirect. Lowest ratings go to civil war torn countries. Intermediate ratings are X X X X X X X X X awarded on the basis of the threats to the government and busines. External conflict: The external conflict measure is an assessment both of the risk to the incumbent government and to inward investment. It ranges from trade restrictions and embargoes, whether imposed by a single country, a group of countries, or the international community as a whole, X X X X X X X X X through geopolitical disputes, armed threats, exchanges of fire on borders, border incursions, foreign-supported insurgency, and full-scale warfare. Ethnic tensions : This component measures the degree of tension within a country attributable to racial, nationality, or language divisions. Lower ratings are given to countries where racial and nationality tensions are high because opposing groups are intolerant and unwilling to compromise. X X X X X X X X X Higher ratings are given to countries where tensions are minimal, even though such differences may still exist. Government Effectiveness Bureaucratic Quality. Measures institutional strength and quality of the civil service, assess how much strength and expertise bureaucrats have and how able they are to manage political alternations without drastic interruptions in government services, or policy changes. Good X X X X X X X X X performers have somewhat autonomous bureaucracies, free from political pressures, and an established mechanism for recruitment and training. Regulatory Quality Investment Profile. Includes the risk to operations (scored from 0 to 4, increasing in risk); taxation (scored from 0 to 3), repatriation (scored from 0 to 3) and labor costs (scored from 0 to 2). They all X X X X X X X X X look at the government's attitude towards investment. Rule of Law Law and Order. The Law sub-component is an assessment of the strength and impartiality of the X X X X X X X X X legal system, while the Order sub-component is an assessment of popular observance of the law. Control of Corruption Corruption. Measures corruption within the political system, which distorts the economic and financial environment, reduces the efficiency of government and business by enabling people to assume positions of power through patronage rather than ability, and introduces an inherently X X X X X X X X X instability in the political system. Country Coverage 140 140 140 140 140 140 140 140 130 Year of publication 2007 2006 2005 2004 2003 2002 2000 1998 1996 66 Table A29: Reporters Without Borders Press Freedom Index (RSF) Data Provider Reporters Without Borders Description International nongovernmental organization headquartered in Paris, France, devoted to the protection of reporters and respect of press freedom. Website www.rsf.org Data Source Worldwide Press Freedom Index Type Expert assessment Respondents Reporters, researchers, legal experts and press freedom advocates in assessed countries Frequency Annual since 2002 Coverage Global sample of countries Public Access Yes Description The press freedom index is based on a 50-question checklist on the incidence and severity of restrictions on reporters and the media 2007 2006 2005 2004 2003 2002 2000 1998 1996 Voice and Accountability Press Freedom Index X X X X X X .. .. .. Political Stability and Absence of Violence NA .. .. .. .. .. .. .. .. .. Government Effectiveness NA .. .. .. .. .. .. .. .. .. Regulatory Quality NA .. .. .. .. .. .. .. .. .. Rule of Law NA .. .. .. .. .. .. .. .. .. Control of Corruption NA .. .. .. .. .. .. .. .. .. Country Coverage 166 166 165 165 164 138 .. .. .. Year of Publication 2007 2006 2005 2004 2003 2002 .. .. .. 67 Table A30: U.S. Department of State Trafficking in People Report (TPR) Data Provider United States Department of State Description Foreign affairs department of the United States Government. Website www.state.gov Data Source Trafficking in People Report Type Expert assessments Respondents United States embassy staff worldwide subject to centralized review Frequency Annual since 2001 Coverage Global country sample Public Access Yes Description This report scores countries on a four-point scale based on the extent of government efforts to combat "severe trafficking in persons" defined as (a) sex trafficking in which a commercial sex act is induced by force, fraud, or coercion, or in which the person induced to perform such act has not attained 18 years of age; or (b) the recruitment, harboring, transportation, provision, or obtaining of a person for labor or services, through the use of force, fraud or coercion for the purpose of subjection to involuntary servitude, peonage, debt bondage, or slavery. Note that the reports refer to data from the previous year: we therefore lag the data from this source by one year. 2007 2006 2005 2004 2003 2002 2000 1998 1996 Voice and Accountability NA .. .. .. .. .. .. .. .. .. Political Stability and Absence of Violence NA .. .. .. .. .. .. .. .. .. Government Effectiveness NA .. .. .. .. .. .. .. .. .. Regulatory Quality NA .. .. .. .. .. .. .. .. .. Rule of Law Trafficking in People X X X X X X X .. .. Control of Corruption NA .. .. .. .. .. .. .. .. .. Country coverage 153 151 149 142 131 116 82 .. .. Year of Publication 2008 2007 2006 2005 2004 2003 2001 .. .. 68 Table A31: Vanderbilt University Americas Barometer (VAB) Data Provider Vanderbilt University Description United States university Website www.lapopsurveys.org Data Source Americas' Barometer Type Survey Respondents Households Frequency Bi-annual since 2004 Coverage Sample of Latin American countries Public Access Some country-level aggregates are freely available, the rest of the dataset is available via subscription Description The Americas Barometer is an effort by LAPOP to measure democratic values and behaviors in the Americas using common questionnaires to households in Latin America with questions on areas such as Democracy, Politics and Institutions, Social Policies, Civic Culture, and other Current Issues. 2007 2006 2005 2004 2003 2002 2000 1998 1996 Voice and Accountability Trust in Parliament X X X X .. .. .. .. .. Satisfaction with democracy X X X X .. .. .. .. .. Political Stabilityand Absence of Violence NA .. .. .. .. .. .. .. .. .. Government Effectiveness NA .. .. .. .. .. .. .. .. .. Regulatory Quality NA .. .. .. .. .. .. .. .. .. Rule of Law Trust in Supreme Court X X X X .. .. .. .. .. Trust in Justice system X X X X .. .. .. .. .. Trust in Police X X X X .. .. .. .. .. Have you been a victim of crime? X X X X .. .. .. .. .. Control of Corruption Frequency of corruption among government officials X X X X .. .. .. .. .. Country coverage 22 20 11 11 .. .. .. .. .. Year of Publication 2006 2006 2004 2004 .. .. .. .. .. 69 Table A32: Institute for Management Development World Competitiveness Yearbook (WCY) Data Provider Institute for Management Development Description Educational and research organization headquartered in Lausanne, Switzerland Website www.imd.ch Data Source World Competitiveness Yearbook Type Survey Respondents Businesspeople working in countries being assessed Frequency Annual since 1987 Coverage Global sample of countries Public Access Full dataset is commercially available. Averages of sub-indicators are publicly available in this spreadsheet. Description The World Competitiveness Yearbook ranks countries on a large number of factual and subjective indicators relating to the business environment. We use indicators drawn from their Executive Opinion Survey capturing the views of approximately 4000 respondents. 2007 2006 2005 2004 2003 2002 2000 1998 1996 Voice and Accountability Transparency of Government policy X X X X X X X X X Political Stability and Absence of Violence The risk of political instability is very high X X X X X X X .. .. Government Effectiveness Government economic policies do not adapt quickly to changes in the economy X X X X X X X .. X The public service is not independent from political interference X X X X X X X X .. Government decisions are not effectively implemented X X X X X X X X .. Bureaucracy hinders business activity X X X X X X X X X The distribution infrastructure of goods and services is generally inefficient X X X X X X X .. X Policy direction is not consistent X X X X .. .. .. .. .. Regulatory Quality The exchange rate policy of your country hinders the competitiveness of firms X X X X X X .. .. .. Protectionism in the country negatively affects the conduct of business X X X X X X X X .. Competition legislation in your country does not prevent unfair competition X X X X X X X X X Price controls affect pricing of products in most industries X X X X X X X X X Access to capital markets (foreign and domestic) is easily available X X X X X X .. .. .. Ease of doing business is not a competitive advantage for your country X X X X X X .. .. .. Financial institutions' transparency is not widely developed in your country X X X X X X .. .. .. Customs' authorities do not facilitate the efficient transit of goods X X X X X X X X .. The legal framework is detrimental to your country's competitiveness X X X X X X X X .. Foreign investors are free to acquire control in domestic companies X X X X X X X X X Public sector contracts are sufficiently open to foreign bidders X X X X X X X X X Real personal taxes are non distortionary X X X X X X X X X Real corporate taxes are non distortionary X X X X X X X X .. Banking regulation does not hinder competitiveness X X X X X X .. .. .. Labor regulations hinder business activities X X X X .. .. .. .. .. Subsidies impair economic development X X X X .. .. .. .. .. Ease to start a business X X X X .. .. .. .. .. Rule of Law Tax evasion is a common practice in your country X X X X X X X X .. Justice is not fairly administered in society X X X X X X X X X Personal security and private property are not adequately protected X X X X X X X X X Parallel economy impairs economic development in your country X X X X X X X X X Patent and copyright protection is not adequately enforced in your country X X X X X X .. X X Control of Corruption Bribing and corruption exist in the economy X X X X X X X X X Country coverage 55 53 51 51 51 49 49 46 46 Year of Publication 2007 2006 2005 2004 2003 2002 2000 1998 1996 70 Table A33: Global Insight Business Risk and Conditions (WMO) Data Provider Global Insight Description Commercial business information provider headquartered in Boston, United States Website www.globalinsight.com Data Source World Markets Online Type Expert Assessment Respondents Staff of World Markets Research Center, subject to regional reviews for comparability Frequency Annual assessments with daily online updates Coverage Global sample of countries Public Access Full dataset is commercially available. Averages of sub-indicators are publicly available in this spreadsheet. Description WMO produces assessments of the quality and stability of various dimensions of the business environment. It was acquired by Global Insight in 2003, which also owns and produces the DRI Global Risk Service (see Table A8). These two sets of ratings continue to be produced independently and so we continue to treat them as distinct sources as we did prior to 2003. 2007 2006 2005 2004 2003 2002 2000 1998 1996 Voice and Accountability Institutional permanence An assessment of how mature and well-established the political system is. It is also an assessment of how far political opposition operates X X X X X X X X .. within the system or attempts to undermine it from outside. Representativeness How well the population and organised interests can make their voices heard in the political system. Provided representation is handled fairly and X X X X X X X X .. effectively, it will ensure greater stability and better designed policies. Political Stability and Absence of Violence Civil unrest How widespread political unrest is, and how great a threat it poses to investors. Demonstrations in themselves may not be cause for concern, but they will cause major disruption if they escalate into severe violence. At the extreme, this factor X X X X X X X X .. would amount to civil war. Terrorism Whether the country suffers from a sustained terrorist threat, and from how many sources. The degree of localisation of the threat is assessed, and whether the X X X X X X X X .. active groups are likely to target or affect businesses. .. Government Effectiveness Bureaucracy : An assessment of the quality of the country's bureaucracy. The better the bureaucracy the quicker decisions are made and the more easily foreign investors X X X X X X X X .. can go about their business. Policy consistency and forward planning How confident businesses can be of the continuity of economic policy stance - whether a change of government will entail major policy disruption, and whether the current government has pursued a coherent X X X X X X X X .. strategy. This factor also looks at the extent to which policy-making is far-sighted, or conversely aimed at short-term economic advantage. Regulatory Quality Tax Effectiveness How efficient the country's tax collection system is. The rules may be clear and transparent, but whether they are enforced consistently. This factor looks X X X X X X X X .. at the relative effectiveness too of corporate and personal, indirect and direct taxation. Legislation An assessment of whether the necessary business laws are in place, and whether there any outstanding gaps. This includes the extent to which the country's X X X X X X X X .. legislation is compatible with, and respected by, other countries' legal systems. .. Rule of Law Judicial Independence An assessment of how far the state and other outside actors can influence and distort the legal system. This will determine the level of legal X X X X X X X X .. impartiality investors can expect. Crime How much of a threat businesses face from crime such as kidnapping, extortion, street violence, burglary and so on. These problems can cause major inconvenience X X X X X X X X .. for foreign investors and require them to take expensive security precautions. Control of Corruption Corruption : An assessment of the intrusiveness of the country's bureaucracy. The amount of red tape likely to countered is assessed, as is the likelihood of encountering X X X X X X X X .. corrupt officials and other groups. Country Coverage 202 202 201 202 186 186 181 181 .. Year of Publication 2007 2006 2005 2004 2003 2002 2000 1998 .. 71 Appendix B: Components of Aggregate Governance Indicators in 2007 Table B1: Voice and Accountability Code Concept Measured Representative Sources EIU Orderly transfers Vested interests Accountability of Public Officials Human Rights Freedom of association FRH Civil liberties : Freedom of speech, assembly, demonstration, religion, equal opportunity, excessive governmental intervention Political Rights: free and fair elections, representative legislative, free vote, political parties, no dominant group, respect for minorities FRP Freedom of the Press GCS Newspapers can publish stories of their choosing without fear of censorship or retaliation When deciding upon policies and contracts, Government officials favor well-connected firms Effectiveness of national Parliament/Congress as a law making and oversight institution Passive voice GWP Confidence in honesty of elections HUM Travel: domestic and foreign travel restrictions Freedom of political participation Imprisonments: Are there any imprisoned people because of their ethnicity, race, or their political, religious beliefs? Government censorship IPD Political rights and functioning of political institutions Freedom of the press Freedom of association Freedom of assembly and demonstration Respect for minorities (ethnic, religious, linguistic, etc) Transparency of public action in the economic field Transparency of economic policy (fiscal, taxation, monetary, exchange-rate, etc) Award of public procurement contracts and delegation of public service Free movement of persons, information, etc PRS Military in Politics The military are not elected by anyone, so their participation in government, either direct or indirect, reduces accountability and therefore represents a risk. The threat of military intervention might lead as well to an anticipated potentially inefficient change in policy or even in government. Democratic Accountability. Quantifies how responsive government is to its people, on the basis that the less response there is the more likely is that the government will fall, peacefully or violently. It includes not only if free and fair elections are in place, but also how likely is the government to remain in power. RSF Press Freedom Index WMO Institutional permanence: An assessment of how mature and well-established the political system is. Representativeness :How well the population and organized interests can make their voices heard in the political system Non-representative Sources AEO Hardening of the regime AFR Elections are free and fair BTI Stateness Political Participation Institutional Stability Political and Social Integration CCR Civil Liberties Accountability and public voice GII Civil Society Organizations Media Public Access to Information Voting & Citizen Participation Election Integrity Political Financing IFD Policy and legal framework for rural organizations Dialogue between government and rural organizations LBO Satisfaction with democracy Trust in Parliament MSI Media Sustainability Index OBI Open Budget Index VAB Trust in Parliament Satisfaction with democracy WCY Transparency of Government policy 72 Table B2: Political Stability & Absence of Violence/Terrorism Code Concept Measured Representative Sources DRI Military Coup Risk : A military coup d'etat (or a series of such events) that reduces the GDP growth rate by 2% during any 12-month period. Major Insurgency/Rebellion: An increase in scope or intensity of one or more insurgencies/rebellions that reduces the GDP growth rate by 3% during any 12-month period. Political Terrorism: An increase in scope or intensity of terrorism that reduces the GDP growth rate by 1% during any 12-month period. Political Assassination: A political assassination (or a series of such events) that reduces the GDP growth rate by 1% during any 12- month period. Civil War : An increase in scope or intensity of one or more civil wars that reduces the GDP growth rate by 4% during any 12-month period. Major Urban Riot: An increase in scope, intensity, or frequency of rioting that reduces the GDP growth rate by 1% during any 12-month period. EIU Armed conflict Violent demonstrations Social Unrest International tensions GCS Country terrorist threat : Does the threat of terrorism in the country impose significant costs on firms? HUM Frequency of political killings Frequency of disappearances Frequency of torture IJT Security Risk Rating IPD Conflicts of ethnic, religious, regional nature ... Violent actions by underground political organisations Violent social conflicts External public security MIG Extremism. The term "extremism" covers the threat posed by any individuals or organisations who hold a narrow set of fanatical beliefs. Extremists are likely to believe that any and all means are justified to eradicate the target of hostility, and are not afraid to destroy themselves in the process. This ideological aspect of extremism makes it highly unpredictable, and its close association with violence makes it highly dangerous. The extent to which extremism should be judged a threat to a particular business in a particular market can be assessed along the following lines: integration issues; religious tensions; pressure groups; terrorist activity; xenophobia. PRS Internal Conflict : Assesses political violence and its influence on governance. External conflict: The external conflict measure is an assessment both of the risk to the incumbent government and to inward investment. Government Stability. Measures the government's ability to carry out its declared programs, and its ability to stay in office. Ethnic tensions: This component measures the degree of tension within a country attributable to racial, nationality, or language divisions. PTS Political Terror Scale WMO Civil unrest How widespread political unrest is, and how great a threat it poses to investors. Demonstrations in themselves may not be cause for concern, but they will cause major disruption if they escalate into severe violence. At the extreme, this factor would amount to civil war. Terrorism Whether the country suffers from a sustained terrorist threat, and from how many sources. The degree of localization of the threat is assessed, and whether the active groups are likely to target or affect businesses. Non-representative Sources AEO Political Troubles BRI Fractionalization of political spectrum and the power of these factions. Fractionalization by language, ethnic and/or religious groups and the power of these factions. Restrictive (coercive) measures required to retain power. Organization and strength of forces for a radical government. Societal conflict involving demonstrations, strikes, and street violence. Instability as perceived by non-constitutional changes, assassinations, and guerrilla wars. WCY Risk of political instability 73 Table B3: Government Effectiveness Code Concept Measured Representative Sources DRI Government Instability: An increase in government personnel turnover rate at senior levels that reduces the GDP growth rate by 2% during any 12-month period. Government Ineffectiveness: A decline in government personnel quality at any level that reduces the GDP growth rate by 1% during any 12- month period. Institutional Failure: A deterioration of government capacity to cope with national problems as a result of institutional rigidity that reduces the GDP growth rate by 1% during any 12-month period. EGV Global E-government EIU Quality of bureaucracy Excessive bureaucracy / red tape GCS Quality of general infrastructure Quality of public schools GWP Satisfaction with public transportation system Satisfaction with roads and highways Satisfaction with education system IPD Government-citizen relations Capacity of the tax administration to implement measures decided on Quality of the supply of public goods: education and basic health Capacity of the political authorities MIG Quality of Bureaucracy. PRS Bureaucratic Quality. Measures institutional strength and quality of the civil service, assesses how much strength and expertise bureaucrats have and how able they are to manage political alternations without drastic interruptions in government services, or policy changes. WMO Policy consistency and forward planning: How confident businesses can be of the continuity of economic policy stance - whether a change of government will entail major policy disruption, and whether the current government has pursued a coherent strategy. Bureaucracy : An assessment of the quality of the country's bureaucracy. The better the bureaucracy the quicker decisions are made and the more easily foreign investors can go about their business. Non-representative Sources ADB Management of public debt Policies to improve efficiency of public sector Revenue Mobilization Budget Management AFR Based on your experiences, how easy or difficult is it to obtain household services (like electricity or telephone)? Based on your experiences, how easy or difficult is it to obtain an identity document (like birth certificate, passport)? Government handling of health services Government handling of education ASD Civil service Revenue Mobilization and Budget Management Management and Efficiency of Public Expenditures BPS How problematic are telecommunications for the growth of your business How problematic is electricity for the growth of your business. How problematic is transportation for the growth of your business. BRI Bureaucratic delays BTI Consensus Building Governance Capability Effective Use of Resources CPIA Management of external debt Quality public Administration Revenue Mobilization Budget Management IFD Allocation & management of publlic resources for rural development LBO Trust in Government WCY Government economic policies do not adapt quickly to changes in the economy The public service is not independent from political interference Government decisions are not effectively implemented Bureaucracy hinders business activity The distribution infrastructure of goods and services is generally inefficient Policy direction is not consistent 74 Table B4: Regulatory Quality Code Concept Measured Representative Sources DRI Regulations -- Exports: A 2% reduction in export volume as a result of a worsening in export regulations or restrictions (such as export limits) during any 12-month period, with respect to the level at the time of the assessment. Regulations -- Imports: A 2% reduction in import volume as a result of a worsening in import regulations or restrictions (such as import quotas) during any 12-month period, with respect to the level at the time of the assessment. Regulations -- Other Business: An increase in other regulatory burdens, with respect to the level at the time of the assessment, that reduces total aggregate investment in real LCU terms by 10% Ownership of Business by Non-Residents: A 1-point increase on a scale from "0" to "10" in legal restrictions on ownership of business by non-residents during any 12-month period. Ownership of Equities by Non-Residents : A 1-point increase on a scale from "0" to "10" in legal restrictions on ownership of equities by non-residents during any 12-month period. EIU Unfair competitive practices Price controls Discriminatory tariffs Excessive protections GCS Administrative regulations are burdensome Tax system is distortionary Import barriers as obstacle to growth Competition in local market is limited Anti monopoly policy is lax and ineffective Environmental regulations hurt competitiveness Complexity of tax System Easy to start company HER Foreign investment Banking / finance Wage/Prices IPD Administrative business start-up formalities Administered prices and market prices Competition: productive sector: ease of market entry for new firms Competition between businesses: competition regulation arrangements MIG Unfair Competition . Unfair Trade . PRS Investment Profile. WMO Tax Effectiveness: How efficient the country's tax collection system is. Legislation: An assessment of whether the necessary business laws are in place. Non-representative Sources ADB Trade policy Competitive environment Labor Market Policies ASD Trade Policy and Forex Regime Enabling Environment for Private Sector Development BPS Information on the laws and regulations is easy to obtain How problematic are anti competitive practices for the growth of your business. How problematic are unpredictable regulations for the growth of your business. How problematic are labor regulations for the growth of your business. How problematic are tax regulations for the growth of your business. How problematic are custom and trade regulations for the growth of your business. BTI Competition Price Stability CPIA Competitive environment Trade policy EBRD Price liberalization Trade & foreign exchange system Competition policy IFD Enabling conditions for rural financial services development Investment climate for rural businesses Access to agricultural input and produce markets WCY Access to capital markets (foreign and domestic) is easily available Ease of Doing Business Banking regulation does not hinder competitiveness Competition legislation in your country does not prevent unfair competition Customs' authorities do not facilitate the efficient transit of goods Financial institutions' transparency is not widely developed in your country Easy to start company Foreign investors are free to acquire control in domestic companies Price controls affect pricing of products in most industries Public sector contracts are sufficiently open to foreign bidders Real corporate taxes are non distortionary Real personal taxes are non distortionary The legal framework is detrimental to your country's competitiveness Protectionism in your country negatively affects the conduct of business in your country Labor regulations hinder business activities Subsidies impair economic development 75 Table B5: Rule of Law Code Concept Measured Representative Sources DRI Losses and Costs of Crime : A 1-point increase on a scale from "0" to "10" in crime during any 12-month period. Kidnapping of Foreigners : An increase in scope, intensity, or frequency of kidnapping of foreigners that reduces the GDP growth rate by 1% during any 12-month period. Enforceability of Government Contracts : A 1 point decline on a scale from "0" to "10" in the enforceability of contracts during any 12-month period. Enforceability of Private Contracts: A 1-point decline on a scale from "0" to "10" in the legal enforceability of contracts during any 12-month period. EIU Violent crime Organized crime Fairness of judicial process Enforceability of contracts Speediness of judicial process Confiscation/expropriation GCS Common crime imposes costs on business Organized crime imposes costs on business Quality of Police The judiciary is independent from political influences of members of government, citizens or firms Legal framework to challenge the legality of government actions is inefficient Intellectual Property protection is weak Protection of financial assets is weak Tax evasion GWP Confidence in the police force Confidence in judicial system Have you been a victim of crime? HER Property Rights HUM Independence of Judiciary IPD Respect for law in relations between citizens and the administration Security of persons and goods Organised criminal activity (drug-trafficking, arms-trafficking, etc. Importance of the informal economy Importance of tax evasion in the formal sector Importance of customs evasion (smuggling, under-declaration, etc) Running of the justice system Security of traditional property rights Security of property rights: formal property rights Security of contracts between private agents Government respect for contracts Settlement of economic disputes: justice in commercial matters Intellectual property Arrangements for the protection of intellectual property Agricultural sector: security of rights and property transactions MIG Organised Crime. Legal Safeguards. PRS Law and Order. The Law sub-component is an assessment of the strength and impartiality of the legal system, while the Order sub- component is an assessment of popular observance of the law (assessed separately). QLM Direct Financial Fraud, Money Laundering and Organized Crime TPR Trafficking in People Report WMO Judicial Independence An assessment of how far the state and other outside actors can influence and distort the legal system. This will determine the level of legal impartiality investors can expect. Crime - How much of a threat businesses face from crime such as kidnapping, extortion, street violence, burglary... 76 Table B5: Rule of Law - cont Code Concept Measured Non-representative Sources ADB Property Rights AFR Based on your experiences, how easy or difficult is it to obtain help from the police when you need it? ASD Rule of Law BPS Fairness, honesty, enforceability, quickness and affordability of the court system Property right protection How problematic is organized crime for the growth of your business. How problematic is judiciary for the growth of your business. How problematic is street crime for the growth of your business. BRI Enforceability of contracts BTI Rule of Law Private Property CCR Rule of Law CPIA Property rights FRH Rule of Law : Considers judicial/constitutional matters as well as the legal and de facto status of ethnic minorities. GII Executive Accountability Judicial Accountability Rule of Law Law Enforcement IFD Access to land Access to water for agriculture LBO Trust in Judiciary Trust in Police Have you been a victim of crime? VAB Trust in Justice Trust in Police Trust in Supreme Court Have you been a victim of crime? WCY Tax evasion is a common practice in your country Justice is not fairly administered in society Personal security and private property are not adequately protected Parallel economy impairs economic development in your country Patent and copyright protection is not adequately enforced in your country 77 Table B6: Control of Corruption Code Concept Measured Representative Sources DRI Risk Event Outcome non-price: Losses and Costs of Corruption: A 1-point increase on a scale from "0" to "10" in corruption during any 12- month period. EIU Corruption GCS Public trust in financial honesty of politicians Diversion of public funds due to corruption is common Frequent for firms to make extra payments connected to: import/export permits Frequent for firms to make extra payments connected to: public utilities Frequent for firms to make extra payments connected to tax payments Frequent for firms to make extra payments connected to: awarding of public contracts Frequent for firms to make extra payments connected to: getting favorable judicial decisions Extent to which firms' illegal payments to influence government policies impose costs on other firms Undue political influence GWP Is corruption in government widespread? IPD Corruption MIG Corruption. There is an immense variety of activities that may be construed as corrupt. Bribery is the most obvious. However, what is and is not a bribe is a matter of presentation and perception in much the same way as "corruption" itself. Some of the issues that executives should consider include: accounting standards; anti-corruption policy credibility and enforceability; cronyism, nepotism and vested interests; cultural differences; judicial independence; transparency of decision-making. PRS Corruption. Measures corruption within the political system, which distorts the economic and financial environment, reduces the efficiency of government and business by enabling people to assume positions of power through patronage rather than ability, and introduces an inherently instability in the political system. QLM Indirect Diversion of Funds WMO Corruption : This index assesses the intrusiveness of the country's bureaucracy. The amount of red tape likely to countered is assessed, as is the likelihood of encountering corrupt officials and other groups. Non-representative Sources ADB Transparency / corruption AFR How many elected leaders (parliamentarians or local councilors) do you think are involved in corruption? How many judges and magistrates do you think are involved in corruption? How many government officials do you think are involved in corruption? How many border/tax officials do you think are involved in corruption? ASD Anti-corruption BPS How common is for firms to have to pay irregular additional payments to get things done On average, what percent of total annual sales do firms pay in unofficial payments to public officials How often do firms make extra payments to influence the content of new legislation Extent to which firms' payments to public officials to affect legislation impose costs on other firms How problematic is corruption for the growth of your business. Frequency of bribery in utility, permits, procurement, health, fire inspection, environent, taxes, customs and judiciary BRI Internal Causes of Political Risk : Mentality, including xenophobia, nationalism, corruption, nepotism, willingness to compromise, etc BTI Corruption CCR Transparency / corruption CPIA Transparency / corruption FRH Corruption GCB Frequency of corruption Frequency of household bribery GII Anti-Corruption Law Anti-Corruption Agency IFD Accountability, transparency and corruption in rural areas LBO Have you heard of acts of corruption? PRC Corruption Index VAB Frequency of corruption among government officials WCY Bribing and corruption exist in the economy 78 APPENDIX C: Governance Indicators over Time TABLE C1: Voice and Accountability 2007 2006 2005 2004 2003 2002 2000 1998 1996 Country Code Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. AFGHANISTAN AFG -1.17 0.15 8 -1.24 0.14 9 -1.20 0.17 8 -1.22 0.17 8 -1.45 0.17 6 -1.43 0.20 5 -2.00 0.29 3 -2.04 0.29 3 -1.82 0.28 2 ALBANIA ALB 0.03 0.15 12 0.03 0.15 12 -0.03 0.17 10 0.03 0.18 8 0.02 0.16 7 -0.09 0.17 6 -0.32 0.25 4 -0.44 0.26 4 -0.57 0.26 3 ALGERIA DZA -1.01 0.12 14 -0.93 0.12 13 -0.73 0.14 13 -0.82 0.16 11 -1.07 0.17 9 -1.06 0.17 8 -1.25 0.22 6 -1.40 0.22 6 -1.36 0.23 5 AMERICAN SAMOA ASM 1.01 0.54 1 0.59 0.52 1 0.64 0.42 1 0.48 0.40 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ANDORRA ADO 1.34 0.23 3 1.35 0.24 3 1.45 0.28 3 1.48 0.28 3 1.32 0.26 3 1.45 0.29 2 1.59 0.32 2 1.62 0.33 2 1.49 0.30 1 ANGOLA AGO -1.11 0.13 12 -1.20 0.13 13 -1.21 0.16 11 -1.24 0.16 11 -1.07 0.17 8 -1.22 0.17 7 -1.51 0.22 5 -1.41 0.23 5 -1.52 0.23 4 ANGUILLA AIA 1.01 0.54 1 1.04 0.52 1 0.88 0.42 1 0.81 0.40 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ANTIGUA AND BARBUDA ATG 0.58 0.23 3 0.60 0.24 3 0.51 0.27 4 0.53 0.27 4 0.19 0.26 3 0.11 0.29 2 0.15 0.32 2 0.09 0.33 2 -0.03 0.30 1 ARGENTINA ARG 0.33 0.13 14 0.33 0.14 14 0.23 0.16 13 0.34 0.17 12 0.30 0.16 11 0.16 0.17 10 0.27 0.20 8 0.16 0.22 7 0.39 0.22 6 ARMENIA ARM -0.59 0.13 13 -0.67 0.13 13 -0.58 0.16 10 -0.53 0.16 9 -0.65 0.14 8 -0.56 0.17 6 -0.43 0.25 4 -0.54 0.26 4 -0.71 0.28 2 ARUBA ABW 1.01 0.54 1 1.04 0.52 1 1.13 0.42 1 0.70 0.40 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. AUSTRALIA AUS 1.34 0.18 9 1.36 0.18 9 1.52 0.19 9 1.51 0.19 9 1.41 0.19 9 1.40 0.20 8 1.51 0.21 7 1.43 0.23 6 1.34 0.23 5 AUSTRIA AUT 1.39 0.18 9 1.41 0.18 9 1.39 0.19 8 1.49 0.19 8 1.32 0.20 8 1.30 0.20 8 1.38 0.21 7 1.42 0.23 6 1.32 0.23 5 AZERBAIJAN AZE -1.13 0.12 14 -1.16 0.12 14 -1.03 0.14 12 -0.95 0.15 10 -0.92 0.14 9 -0.89 0.16 8 -0.98 0.22 5 -0.95 0.23 5 -1.13 0.25 3 BAHAMAS BHS 1.07 0.21 4 1.05 0.22 4 0.98 0.25 4 1.02 0.25 4 1.07 0.24 4 1.17 0.25 3 1.16 0.26 3 1.13 0.28 3 1.18 0.28 2 BAHRAIN BHR -0.82 0.13 10 -0.80 0.13 10 -0.73 0.15 10 -0.58 0.16 9 -0.69 0.15 8 -0.69 0.17 8 -0.92 0.22 5 -1.04 0.23 5 -1.19 0.23 4 BANGLADESH BGD -0.63 0.12 14 -0.50 0.13 13 -0.52 0.15 11 -0.66 0.16 10 -0.60 0.17 8 -0.45 0.17 8 -0.44 0.22 6 -0.25 0.23 5 -0.23 0.23 4 BARBADOS BRB 1.13 0.22 4 1.15 0.23 4 1.04 0.27 4 1.15 0.27 4 1.22 0.26 3 1.37 0.29 2 1.41 0.32 2 1.46 0.33 2 1.21 0.30 1 BELARUS BLR -1.80 0.15 9 -1.82 0.16 9 -1.71 0.18 7 -1.37 0.18 7 -1.36 0.16 7 -1.40 0.16 7 -1.35 0.25 4 -0.86 0.26 4 -1.54 0.28 2 BELGIUM BEL 1.44 0.18 9 1.42 0.18 9 1.42 0.19 8 1.47 0.19 8 1.48 0.20 8 1.38 0.20 8 1.39 0.21 7 1.36 0.23 6 1.24 0.23 5 BELIZE BLZ 0.69 0.20 6 0.70 0.21 5 0.73 0.27 4 0.76 0.27 4 0.88 0.26 3 0.83 0.26 3 0.90 0.29 3 0.81 0.29 3 0.99 0.28 2 BENIN BEN 0.32 0.14 14 0.27 0.14 14 0.15 0.20 9 0.09 0.21 7 0.10 0.20 5 0.11 0.20 5 0.39 0.29 3 0.37 0.29 3 0.68 0.28 2 BERMUDA BMU 1.01 0.54 1 1.04 0.52 1 1.13 0.42 1 1.08 0.40 1 1.09 0.49 1 1.05 0.52 1 0.87 0.48 1 1.10 0.47 1 .. .. .. BHUTAN BTN -0.88 0.15 6 -0.74 0.17 6 -1.01 0.22 6 -0.95 0.22 6 -1.22 0.25 4 -1.22 0.25 4 -0.98 0.29 3 -0.97 0.29 3 -1.39 0.28 2 BOLIVIA BOL 0.02 0.12 15 0.08 0.12 15 -0.22 0.15 13 -0.17 0.15 12 -0.03 0.17 9 0.07 0.17 9 0.08 0.20 7 0.27 0.22 6 0.34 0.22 5 BOSNIA-HERZEGOVINA BIH 0.14 0.15 11 0.21 0.16 10 0.08 0.16 9 0.08 0.16 9 -0.11 0.16 7 -0.23 0.16 7 -0.08 0.27 3 -0.12 0.27 3 -0.50 0.27 2 BOTSWANA BWA 0.49 0.14 15 0.50 0.14 15 0.67 0.16 12 0.81 0.17 11 0.86 0.17 10 0.72 0.17 9 0.74 0.22 6 0.75 0.22 6 0.83 0.23 5 BRAZIL BRA 0.41 0.13 16 0.43 0.13 16 0.43 0.16 13 0.35 0.17 12 0.48 0.16 11 0.33 0.17 10 0.17 0.20 8 0.19 0.22 7 0.18 0.22 6 BRUNEI BRN -1.08 0.21 4 -1.08 0.22 4 -0.99 0.25 4 -0.82 0.25 4 -1.01 0.24 4 -0.91 0.23 5 -0.75 0.25 4 -0.75 0.26 4 -1.14 0.26 3 BULGARIA BGR 0.65 0.13 14 0.59 0.13 14 0.50 0.15 10 0.56 0.16 9 0.49 0.15 9 0.58 0.15 9 0.48 0.22 6 0.38 0.23 5 0.11 0.23 4 BURKINA FASO BFA -0.31 0.12 15 -0.28 0.12 15 -0.46 0.17 10 -0.40 0.18 9 -0.45 0.19 7 -0.42 0.18 7 -0.28 0.25 5 -0.48 0.25 5 -0.23 0.25 4 BURUNDI BDI -0.80 0.15 11 -1.05 0.16 10 -1.02 0.22 6 -1.26 0.22 6 -1.11 0.20 5 -1.20 0.20 5 -1.64 0.29 3 -1.51 0.29 3 -1.54 0.28 2 CAMBODIA KHM -0.87 0.13 11 -0.87 0.13 11 -1.00 0.16 9 -0.87 0.17 8 -0.83 0.16 7 -0.73 0.18 6 -0.79 0.25 4 -0.88 0.25 4 -0.96 0.25 3 CAMEROON CMR -0.94 0.13 15 -0.96 0.14 13 -1.04 0.16 11 -0.99 0.17 9 -1.12 0.17 9 -1.02 0.17 8 -1.10 0.22 6 -1.12 0.22 6 -1.24 0.23 5 CANADA CAN 1.36 0.15 12 1.40 0.16 11 1.50 0.19 8 1.67 0.19 8 1.52 0.20 8 1.48 0.20 8 1.57 0.21 7 1.60 0.23 6 1.48 0.23 5 CAPE VERDE CPV 0.89 0.18 8 0.83 0.19 7 0.35 0.24 6 0.55 0.26 6 0.51 0.25 5 0.46 0.27 4 0.73 0.40 1 0.73 0.42 1 0.79 0.30 1 CAYMAN ISLANDS CYM 0.78 0.54 1 0.82 0.52 1 0.88 0.42 1 0.84 0.40 1 0.86 0.49 1 1.48 0.52 1 1.52 0.48 1 1.54 0.47 1 .. .. .. CENTRAL AFRICAN REPUBLIC CAF -0.93 0.17 7 -1.01 0.18 6 -1.11 0.22 6 -1.20 0.22 6 -1.41 0.20 5 -1.12 0.20 5 -0.73 0.29 3 -0.67 0.29 3 -0.45 0.28 2 CHAD TCD -1.43 0.14 13 -1.41 0.15 12 -1.40 0.19 9 -1.20 0.21 8 -1.05 0.20 7 -0.90 0.19 6 -0.97 0.29 4 -0.96 0.28 4 -0.90 0.27 3 CHILE CHL 0.98 0.14 13 0.98 0.14 13 1.21 0.17 11 1.17 0.17 11 1.04 0.17 10 1.04 0.17 10 0.81 0.20 8 0.45 0.22 7 0.77 0.22 6 CHINA CHN -1.70 0.12 13 -1.70 0.13 12 -1.52 0.16 11 -1.46 0.16 11 -1.53 0.17 9 -1.58 0.17 9 -1.29 0.21 7 -1.38 0.23 6 -1.66 0.23 5 COLOMBIA COL -0.28 0.12 17 -0.22 0.12 16 -0.24 0.15 14 -0.30 0.15 13 -0.52 0.17 10 -0.50 0.17 10 -0.59 0.20 8 -0.54 0.22 7 -0.43 0.22 6 COMOROS COM -0.45 0.21 5 -0.24 0.22 5 -0.50 0.26 5 -0.43 0.26 5 -0.34 0.25 4 -0.46 0.27 3 -0.80 0.32 2 -0.64 0.33 2 -0.04 0.30 1 CONGO COG -1.11 0.15 10 -1.06 0.18 9 -1.01 0.20 8 -0.85 0.23 7 -0.77 0.23 5 -0.83 0.23 5 -1.63 0.25 4 -1.67 0.26 4 -0.47 0.26 3 CONGO, DEM. REP. ZAR -1.46 0.15 11 -1.55 0.15 10 -1.66 0.18 9 -1.73 0.17 9 -1.58 0.19 6 -1.71 0.19 5 -1.89 0.26 3 -1.90 0.28 3 -1.63 0.28 2 COSTARICA CRI 0.88 0.14 14 0.87 0.15 13 0.81 0.16 12 1.00 0.17 11 1.03 0.17 9 1.10 0.17 9 1.07 0.20 7 1.17 0.22 6 1.13 0.22 5 COTE D'IVOIRE CIV -1.26 0.14 10 -1.34 0.14 10 -1.46 0.18 8 -1.36 0.17 9 -1.22 0.17 8 -1.24 0.17 8 -1.33 0.22 6 -0.65 0.22 6 -0.79 0.23 5 CROATIA HRV 0.47 0.15 12 0.47 0.15 12 0.49 0.15 11 0.71 0.16 10 0.61 0.15 9 0.53 0.15 9 0.41 0.22 5 -0.31 0.23 5 -0.34 0.25 3 CUBA CUB -1.93 0.15 9 -1.96 0.15 9 -1.83 0.18 8 -1.80 0.18 8 -1.68 0.17 7 -1.66 0.17 7 -1.64 0.22 5 -1.61 0.23 5 -1.78 0.23 4 CYPRUS CYP 1.08 0.18 8 1.12 0.19 8 0.97 0.19 7 0.99 0.20 7 1.05 0.20 6 1.18 0.21 5 1.14 0.22 5 1.01 0.23 5 1.11 0.23 4 CZECH REPUBLIC CZE 0.98 0.14 12 0.98 0.14 12 0.92 0.16 10 0.97 0.17 9 1.04 0.17 9 1.00 0.17 9 0.72 0.21 7 0.95 0.23 6 0.97 0.23 5 DENMARK DNK 1.57 0.18 9 1.62 0.18 9 1.78 0.19 8 1.83 0.19 8 1.60 0.20 8 1.53 0.20 8 1.57 0.21 7 1.50 0.23 6 1.46 0.23 5 DJIBOUTI DJI -1.06 0.20 6 -0.96 0.21 6 -1.03 0.26 5 -0.83 0.26 5 -0.74 0.25 4 -0.73 0.27 3 -0.79 0.32 2 -1.06 0.33 2 -0.72 0.30 1 DOMINICA DMA 1.02 0.23 3 1.03 0.24 3 0.96 0.27 4 0.99 0.27 4 1.09 0.26 3 1.10 0.29 2 1.03 0.32 2 1.03 0.33 2 1.21 0.30 1 DOMINICAN REPUBLIC DOM 0.18 0.14 13 0.17 0.14 13 -0.06 0.17 11 0.04 0.17 11 -0.01 0.17 8 0.22 0.17 7 0.17 0.22 5 -0.04 0.23 5 0.23 0.23 4 ECUADOR ECU -0.23 0.13 15 -0.33 0.13 14 -0.40 0.15 13 -0.29 0.15 12 -0.10 0.17 9 -0.09 0.17 9 -0.38 0.20 7 -0.04 0.22 6 0.14 0.22 5 EGYPT EGY -1.24 0.12 15 -1.26 0.12 15 -0.94 0.14 13 -0.99 0.16 11 -1.02 0.17 9 -1.06 0.17 9 -0.78 0.22 7 -0.89 0.22 6 -1.04 0.23 5 EL SALVADOR SLV 0.07 0.15 13 0.07 0.15 13 0.02 0.16 12 0.12 0.17 11 0.12 0.17 9 0.10 0.17 9 -0.10 0.20 7 -0.06 0.22 6 -0.01 0.22 5 EQUATORIAL GUINEA GNQ -1.89 0.18 7 -1.84 0.20 6 -1.64 0.21 6 -1.68 0.21 7 -1.66 0.21 6 -1.61 0.23 5 -1.60 0.27 4 -1.60 0.27 4 -1.56 0.26 3 ERITREA ERI -2.15 0.14 8 -2.01 0.14 8 -1.98 0.19 7 -1.86 0.19 7 -1.83 0.20 5 -1.75 0.20 5 -1.31 0.29 3 -1.18 0.29 3 -1.09 0.28 2 ESTONIA EST 1.05 0.15 11 1.02 0.15 11 1.01 0.17 9 1.09 0.17 9 1.12 0.17 9 1.06 0.17 8 0.96 0.21 7 1.00 0.23 5 0.91 0.25 3 ETHIOPIA ETH -1.19 0.12 15 -1.17 0.12 14 -1.17 0.16 11 -1.11 0.16 11 -1.20 0.17 9 -1.30 0.17 8 -1.02 0.22 6 -0.83 0.22 6 -0.88 0.23 5 FIJI FJI -0.51 0.21 4 -0.50 0.23 4 0.17 0.26 4 0.07 0.27 4 0.12 0.25 4 0.10 0.26 3 -0.57 0.29 3 0.01 0.29 3 -0.26 0.28 2 FINLAND FIN 1.49 0.18 9 1.55 0.18 9 1.72 0.19 8 1.81 0.19 8 1.57 0.20 8 1.57 0.20 8 1.64 0.21 7 1.49 0.23 6 1.39 0.23 5 FRANCE FRA 1.27 0.15 12 1.33 0.16 11 1.47 0.18 9 1.43 0.19 8 1.08 0.20 8 1.10 0.20 8 1.12 0.21 7 1.11 0.23 6 1.01 0.23 5 FRENCH GUIANA GUF 0.34 0.54 1 0.36 0.52 1 0.40 0.42 1 0.48 0.40 1 0.41 0.49 1 0.40 0.52 1 0.44 0.48 1 0.45 0.47 1 .. .. .. GABON GAB -0.83 0.16 9 -0.83 0.17 9 -0.86 0.20 8 -0.79 0.19 8 -0.70 0.20 7 -0.38 0.20 7 -0.41 0.22 6 -0.36 0.22 6 -0.36 0.23 5 GAMBIA GMB -0.96 0.17 9 -0.88 0.17 9 -1.04 0.22 7 -0.60 0.23 7 -0.43 0.22 6 -0.60 0.23 5 -1.06 0.25 4 -0.99 0.26 4 -1.30 0.26 3 GEORGIA GEO -0.19 0.13 13 -0.15 0.13 13 -0.16 0.16 10 -0.19 0.17 9 -0.45 0.15 7 -0.50 0.18 5 -0.26 0.29 3 -0.41 0.29 3 -0.39 0.28 2 GERMANY DEU 1.40 0.16 10 1.42 0.17 10 1.54 0.19 9 1.55 0.19 9 1.44 0.19 9 1.42 0.20 8 1.37 0.21 7 1.34 0.23 6 1.28 0.23 5 Note: "Est." refers to estimate, "S.E." refers to standard errors, and "N." refers to number of sources. The standard errors have the following interpretation: there is roughly a 70% chance that the level of governance lies within plus or minus one standard error of the point estimate of governance. 79 TABLE C1: Voice and Accountability (cont.) 2007 2006 2005 2004 2003 2002 2000 1998 1996 Country Code Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. GHANA GHA 0.50 0.13 15 0.46 0.13 15 0.27 0.16 13 0.14 0.17 12 0.16 0.17 11 -0.08 0.17 9 -0.06 0.22 6 -0.43 0.22 6 -0.29 0.23 5 GREECE GRC 0.96 0.16 10 0.99 0.17 10 1.09 0.19 8 1.12 0.19 8 0.99 0.20 8 1.02 0.20 8 0.93 0.21 7 1.12 0.23 6 0.72 0.23 5 GRENADA GRD 0.78 0.23 3 0.75 0.23 4 0.59 0.27 4 0.61 0.26 5 0.81 0.26 3 0.79 0.29 2 0.61 0.32 2 0.59 0.33 2 1.00 0.30 1 GUAM GUM 1.01 0.54 1 0.59 0.52 1 0.64 0.42 1 0.57 0.40 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. GUATEMALA GTM -0.30 0.12 16 -0.28 0.12 16 -0.39 0.15 14 -0.35 0.15 13 -0.51 0.14 11 -0.41 0.17 9 -0.36 0.20 7 -0.32 0.22 6 -0.21 0.22 5 GUINEA GIN -1.23 0.15 9 -1.15 0.16 9 -1.16 0.20 7 -1.22 0.20 7 -1.39 0.19 6 -1.39 0.19 6 -1.22 0.25 4 -1.21 0.26 4 -1.07 0.26 3 GUINEA-BISSAU GNB -0.51 0.20 6 -0.40 0.21 6 -0.50 0.24 6 -0.67 0.23 6 -1.14 0.23 5 -1.02 0.23 5 -0.85 0.25 4 -1.16 0.28 3 -0.32 0.26 3 GUYANA GUY 0.07 0.15 10 0.05 0.15 9 -0.15 0.20 7 0.20 0.24 5 0.68 0.24 4 0.69 0.23 4 0.54 0.25 4 0.48 0.26 4 0.83 0.26 3 HAITI HTI -0.77 0.14 10 -0.92 0.14 10 -1.32 0.18 8 -1.38 0.18 8 -1.22 0.16 8 -1.31 0.18 7 -0.83 0.25 4 -0.90 0.26 4 -0.51 0.26 3 HONDURAS HND -0.23 0.13 14 -0.24 0.13 14 -0.29 0.15 13 -0.31 0.15 12 -0.23 0.17 9 -0.23 0.17 8 -0.18 0.20 7 -0.16 0.22 6 -0.13 0.22 5 HONG KONG HKG 0.59 0.17 9 0.66 0.17 9 0.60 0.20 7 0.54 0.20 7 0.31 0.21 7 0.11 0.21 7 0.00 0.26 5 -0.11 0.28 4 0.21 0.25 4 HUNGARY HUN 1.10 0.15 11 1.11 0.15 11 1.16 0.17 9 1.18 0.17 9 1.22 0.17 9 1.17 0.17 9 1.17 0.21 7 1.08 0.23 6 1.05 0.23 5 ICELAND ISL 1.42 0.18 8 1.45 0.18 8 1.61 0.22 7 1.64 0.23 7 1.55 0.22 7 1.49 0.22 7 1.54 0.24 6 1.47 0.25 5 1.33 0.26 4 INDIA IND 0.38 0.13 14 0.41 0.14 14 0.40 0.16 12 0.39 0.17 11 0.31 0.17 10 0.38 0.17 9 0.26 0.21 7 0.32 0.23 6 0.12 0.23 5 INDONESIA IDN -0.17 0.12 15 -0.20 0.12 15 -0.16 0.15 13 -0.31 0.16 12 -0.39 0.15 11 -0.41 0.17 9 -0.40 0.21 7 -1.04 0.23 6 -1.17 0.23 5 IRAN IRN -1.52 0.13 11 -1.52 0.13 12 -1.24 0.15 10 -1.27 0.16 9 -1.28 0.17 7 -1.11 0.17 7 -0.95 0.22 5 -0.87 0.23 5 -1.35 0.23 4 IRAQ IRQ -1.29 0.15 8 -1.39 0.16 8 -1.38 0.16 8 -1.63 0.18 7 -1.60 0.17 7 -2.03 0.17 7 -2.00 0.22 5 -1.93 0.23 5 -1.96 0.23 4 IRELAND IRL 1.40 0.16 10 1.40 0.17 10 1.62 0.19 8 1.48 0.19 8 1.27 0.20 8 1.24 0.20 8 1.41 0.21 7 1.35 0.23 6 1.19 0.23 5 ISRAEL ISR 0.78 0.15 11 0.78 0.15 11 0.58 0.19 8 0.65 0.19 8 0.54 0.20 8 0.59 0.20 8 0.68 0.21 7 0.64 0.23 6 0.80 0.23 5 ITALY ITA 1.12 0.15 11 1.09 0.17 10 1.03 0.19 9 1.17 0.19 9 0.95 0.19 9 0.98 0.20 8 0.99 0.21 7 1.07 0.23 6 0.90 0.23 5 JAMAICA JAM 0.61 0.15 10 0.59 0.16 11 0.45 0.17 9 0.43 0.17 9 0.52 0.17 8 0.56 0.17 7 0.70 0.22 6 0.74 0.23 5 0.78 0.23 4 JAPAN JPN 0.93 0.15 11 0.90 0.17 10 0.98 0.19 9 0.99 0.19 9 1.01 0.19 9 0.99 0.20 8 0.87 0.21 7 0.89 0.23 6 0.87 0.23 5 JORDAN JOR -0.64 0.12 16 -0.62 0.12 15 -0.50 0.14 13 -0.57 0.16 11 -0.68 0.15 10 -0.77 0.17 8 -0.26 0.22 6 -0.37 0.23 5 -0.37 0.23 4 KAZAKHSTAN KAZ -1.06 0.12 14 -1.10 0.12 14 -0.94 0.14 12 -1.11 0.15 10 -1.05 0.14 9 -1.13 0.16 8 -0.90 0.22 6 -0.75 0.23 5 -0.93 0.25 3 KENYA KEN -0.06 0.12 17 -0.11 0.12 16 -0.19 0.15 14 -0.19 0.15 13 -0.41 0.15 12 -0.75 0.17 9 -0.82 0.22 6 -0.92 0.22 6 -0.82 0.23 5 KIRIBATI KIR 0.77 0.23 3 0.72 0.24 3 0.19 0.28 3 0.49 0.28 3 0.93 0.30 2 0.98 0.33 1 1.04 0.40 1 1.14 0.42 1 1.18 0.30 1 KOREA, NORTH PRK -2.31 0.17 6 -2.30 0.16 8 -2.16 0.18 8 -2.07 0.18 8 -2.15 0.19 6 -2.13 0.19 6 -2.09 0.25 4 -2.12 0.26 4 -2.03 0.26 3 KOREA, SOUTH KOR 0.66 0.14 12 0.61 0.14 12 0.75 0.16 10 0.71 0.17 9 0.75 0.17 9 0.74 0.17 9 0.61 0.21 7 0.62 0.23 6 0.50 0.23 5 KOSOVO LWI -0.65 0.22 4 -0.63 0.24 4 -0.44 0.26 3 -0.93 0.43 1 -0.89 0.34 1 -0.88 0.33 1 .. .. .. .. .. .. .. .. .. KUWAIT KWT -0.46 0.14 11 -0.28 0.16 10 -0.31 0.17 8 -0.36 0.20 6 -0.44 0.20 6 -0.38 0.20 7 -0.28 0.22 5 -0.27 0.23 5 -0.47 0.23 4 KYRGYZSTAN KGZ -0.64 0.13 12 -0.71 0.13 12 -0.80 0.17 9 -0.99 0.17 8 -1.08 0.15 7 -1.00 0.17 6 -1.17 0.29 3 -0.73 0.29 3 -0.69 0.28 2 LAOS LAO -1.66 0.14 9 -1.64 0.14 9 -1.67 0.19 7 -1.55 0.19 7 -1.73 0.20 5 -1.75 0.20 5 -1.23 0.29 3 -1.03 0.29 3 -1.08 0.28 2 LATVIA LVA 0.86 0.15 10 0.86 0.16 9 0.77 0.17 8 0.72 0.17 8 0.91 0.17 8 0.85 0.17 7 0.71 0.22 6 0.81 0.23 5 0.75 0.25 3 LEBANON LBN -0.45 0.13 12 -0.46 0.14 12 -0.34 0.16 9 -0.37 0.18 8 -0.67 0.17 7 -0.74 0.17 8 -0.29 0.23 4 -0.34 0.24 4 -0.39 0.25 3 LESOTHO LSO 0.12 0.18 8 0.23 0.19 8 -0.07 0.24 6 -0.15 0.26 6 0.14 0.25 5 0.04 0.26 4 -0.49 0.29 3 -0.77 0.33 2 -0.21 0.28 2 LIBERIA LBR -0.35 0.16 9 -0.55 0.16 7 -0.74 0.21 6 -1.31 0.20 7 -1.59 0.19 6 -1.59 0.19 6 -1.36 0.25 4 -1.12 0.26 4 -1.36 0.26 3 LIBYA LBY -1.94 0.13 11 -1.96 0.13 9 -1.87 0.15 9 -1.75 0.16 8 -1.77 0.17 7 -1.80 0.17 7 -1.60 0.22 5 -1.60 0.23 5 -1.82 0.23 4 LIECHTENSTEIN LIE 1.32 0.23 3 1.34 0.24 3 1.46 0.28 3 1.39 0.28 3 1.34 0.26 3 1.34 0.29 2 1.59 0.32 2 1.62 0.33 2 1.49 0.30 1 LITHUANIA LTU 0.93 0.15 11 0.91 0.15 10 0.91 0.17 8 0.90 0.17 8 1.03 0.17 8 0.92 0.17 7 0.85 0.22 6 0.89 0.23 5 0.93 0.25 3 LUXEMBOURG LUX 1.53 0.18 7 1.55 0.19 7 1.55 0.23 6 1.63 0.24 6 1.46 0.23 6 1.33 0.23 5 1.47 0.24 6 1.48 0.25 5 1.38 0.26 4 MACAO MAC 0.11 0.54 1 0.36 0.52 1 0.40 0.42 1 0.12 0.40 1 0.64 0.49 1 0.40 0.52 1 0.22 0.48 1 0.23 0.47 1 .. .. .. MACEDONIA MKD 0.16 0.16 10 0.15 0.16 10 -0.08 0.16 9 -0.11 0.16 9 -0.10 0.16 8 -0.29 0.17 6 -0.35 0.25 4 -0.30 0.25 4 -0.04 0.25 3 MADAGASCAR MDG -0.04 0.14 14 -0.07 0.14 14 -0.09 0.19 10 -0.06 0.19 9 -0.04 0.19 7 -0.24 0.19 6 0.08 0.25 4 0.12 0.26 4 0.38 0.26 3 MALAWI MWI -0.26 0.12 15 -0.29 0.13 15 -0.53 0.15 13 -0.52 0.17 10 -0.58 0.17 9 -0.64 0.17 8 -0.17 0.22 5 -0.09 0.23 5 0.01 0.23 4 MALAYSIA MYS -0.55 0.13 12 -0.54 0.13 13 -0.17 0.16 11 -0.25 0.16 11 -0.41 0.15 10 -0.44 0.17 9 -0.29 0.21 7 -0.21 0.23 6 -0.31 0.23 5 MALDIVES MDV -0.91 0.21 5 -1.01 0.22 5 -0.97 0.26 5 -1.09 0.26 5 -0.81 0.25 4 -0.83 0.29 2 -0.71 0.32 2 -0.67 0.33 2 -1.09 0.30 1 MALI MLI 0.26 0.15 13 0.30 0.15 13 0.38 0.19 10 0.26 0.19 10 0.30 0.18 9 0.30 0.18 8 0.19 0.25 5 0.00 0.25 5 0.71 0.25 4 MALTA MLT 1.18 0.19 6 1.19 0.19 6 1.21 0.24 5 1.34 0.24 5 1.32 0.23 5 1.29 0.25 3 1.27 0.26 3 1.24 0.28 3 1.16 0.28 2 MARSHALL ISLANDS MHL 1.18 0.24 2 1.17 0.26 2 1.16 0.35 2 1.18 0.37 2 1.14 0.30 2 1.26 0.33 1 1.27 0.40 1 1.29 0.42 1 1.35 0.30 1 MARTINIQUE MTQ 0.56 0.54 1 0.59 0.52 1 0.64 0.42 1 0.75 0.40 1 0.64 0.49 1 0.61 0.52 1 0.65 0.48 1 0.66 0.47 1 .. .. .. MAURITANIA MRT -0.75 0.13 11 -0.75 0.15 9 -0.98 0.22 6 -1.21 0.22 6 -0.89 0.25 4 -0.65 0.25 4 -0.76 0.29 3 -0.76 0.29 3 -0.95 0.28 2 MAURITIUS MUS 0.85 0.15 10 0.82 0.15 10 0.78 0.18 9 0.83 0.18 9 0.87 0.21 7 0.74 0.21 7 0.99 0.27 5 1.02 0.28 4 0.85 0.24 4 MEXICO MEX -0.02 0.13 16 0.06 0.13 16 0.19 0.16 14 0.33 0.17 13 0.27 0.16 11 0.28 0.17 10 0.19 0.20 8 -0.09 0.22 7 -0.16 0.22 6 MICRONESIA FSM 1.01 0.23 3 1.01 0.24 3 0.97 0.28 3 0.83 0.28 3 1.04 0.30 2 0.99 0.33 1 0.90 0.40 1 0.85 0.42 1 1.09 0.30 1 MOLDOVA MDA -0.38 0.14 12 -0.43 0.15 11 -0.59 0.16 10 -0.61 0.16 9 -0.62 0.15 8 -0.53 0.16 7 0.02 0.22 5 0.03 0.23 5 -0.12 0.25 3 MONACO MCO 0.85 0.24 2 0.82 0.26 2 0.73 0.35 2 0.95 0.37 2 0.92 0.30 2 1.13 0.33 1 1.13 0.40 1 1.15 0.42 1 1.20 0.30 1 MONGOLIA MNG 0.13 0.16 10 0.15 0.17 9 0.04 0.19 9 0.22 0.20 7 0.33 0.19 6 0.33 0.19 6 0.37 0.25 4 0.51 0.26 4 0.46 0.26 3 MONTENEGRO MNP 0.18 0.16 8 0.13 0.19 7 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. MOROCCO MAR -0.62 0.12 14 -0.61 0.12 15 -0.64 0.14 13 -0.58 0.16 11 -0.65 0.15 10 -0.37 0.17 9 -0.34 0.22 6 -0.23 0.22 6 -0.63 0.23 5 MOZAMBIQUE MOZ -0.06 0.12 16 -0.08 0.12 16 0.03 0.15 12 -0.04 0.16 12 -0.08 0.17 10 -0.15 0.17 9 -0.20 0.22 6 -0.13 0.22 6 0.05 0.23 5 MYANMAR MMR -2.16 0.16 7 -2.20 0.16 8 -2.18 0.18 8 -2.14 0.18 8 -2.06 0.17 7 -2.01 0.17 7 -2.07 0.22 5 -1.95 0.23 5 -2.10 0.23 4 NAMIBIA NAM 0.58 0.14 13 0.49 0.15 12 0.28 0.16 13 0.31 0.17 12 0.32 0.17 11 0.32 0.17 10 0.44 0.22 6 0.38 0.22 6 0.64 0.23 5 NAURU NRU 1.01 0.24 2 1.01 0.26 2 0.96 0.35 2 0.98 0.37 2 1.06 0.30 2 0.83 0.33 1 0.91 0.40 1 1.05 0.42 1 1.09 0.30 1 NEPAL NPL -0.89 0.14 11 -1.12 0.14 11 -1.17 0.16 9 -1.02 0.17 8 -0.81 0.17 6 -0.81 0.20 5 -0.22 0.29 3 -0.23 0.29 3 -0.06 0.28 2 NETHERLANDS NLD 1.53 0.18 9 1.57 0.18 9 1.69 0.19 8 1.73 0.19 8 1.53 0.20 8 1.48 0.20 8 1.58 0.21 7 1.61 0.23 6 1.45 0.23 5 NETHERLANDS ANTILLES ANT 0.56 0.54 1 0.59 0.52 1 0.64 0.42 1 0.48 0.40 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. NEW ZEALAND NZL 1.49 0.16 11 1.52 0.16 11 1.66 0.18 9 1.68 0.19 8 1.60 0.20 8 1.54 0.20 7 1.74 0.21 7 1.61 0.23 6 1.59 0.23 5 NICARAGUA NIC -0.10 0.13 15 -0.15 0.12 15 -0.22 0.15 14 -0.01 0.15 13 -0.01 0.14 11 -0.10 0.17 8 -0.22 0.20 7 0.03 0.22 6 0.17 0.22 5 NIGER NER -0.38 0.15 11 -0.33 0.15 11 -0.26 0.20 8 -0.23 0.20 8 -0.38 0.19 6 -0.33 0.19 6 -0.29 0.25 4 -1.54 0.26 4 -1.00 0.26 3 NIGERIA NGA -0.54 0.12 17 -0.49 0.12 16 -0.75 0.15 14 -0.72 0.15 13 -0.72 0.15 12 -0.76 0.17 10 -0.72 0.22 7 -1.22 0.22 6 -1.82 0.23 5 80 TABLEC1: VoiceandAccountability(cont.) 2007 2006 2005 2004 2003 2002 2000 1998 1996 Country Code Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. NORWAY NOR 1.53 0.16 11 1.54 0.16 11 1.65 0.18 9 1.73 0.19 8 1.52 0.20 8 1.50 0.20 8 1.56 0.21 7 1.53 0.23 6 1.51 0.23 5 OMAN OMN -1.03 0.15 8 -0.86 0.18 6 -0.73 0.18 6 -0.63 0.20 5 -0.92 0.20 6 -0.74 0.21 6 -0.66 0.22 5 -0.65 0.23 5 -1.02 0.23 4 PAKISTAN PAK -1.05 0.12 14 -1.02 0.12 14 -1.05 0.15 11 -1.20 0.16 10 -1.23 0.15 9 -1.19 0.17 7 -1.36 0.22 5 -0.74 0.23 5 -0.71 0.23 4 PALAU PCI 1.22 0.24 2 1.22 0.26 2 1.17 0.35 2 1.18 0.37 2 1.25 0.30 2 1.13 0.33 1 1.13 0.40 1 1.15 0.42 1 1.20 0.30 1 PANAMA PAN 0.52 0.15 12 0.50 0.16 12 0.37 0.16 12 0.47 0.17 12 0.46 0.19 9 0.57 0.20 8 0.59 0.20 7 0.51 0.22 6 0.24 0.22 5 PAPUA NEWGUINEA PNG 0.12 0.16 8 0.06 0.16 7 -0.19 0.17 7 -0.33 0.18 7 -0.06 0.18 6 -0.09 0.18 6 -0.01 0.22 5 0.07 0.23 5 0.44 0.23 4 PARAGUAY PRY -0.37 0.13 13 -0.40 0.13 13 -0.40 0.16 11 -0.47 0.16 11 -0.38 0.17 9 -0.50 0.17 9 -0.61 0.20 7 -0.45 0.22 6 0.06 0.22 5 PERU PER 0.00 0.12 16 0.01 0.12 15 0.03 0.15 12 -0.11 0.16 11 0.04 0.17 9 0.15 0.17 9 -0.16 0.20 7 -0.57 0.22 6 -0.27 0.22 5 PHILIPPINES PHL -0.17 0.12 15 -0.11 0.12 15 0.04 0.15 13 0.03 0.16 12 0.06 0.17 10 0.14 0.17 9 0.18 0.21 7 0.39 0.23 6 0.17 0.23 5 POLAND POL 0.81 0.14 12 0.81 0.14 12 0.96 0.16 10 1.02 0.17 9 1.09 0.17 9 1.08 0.17 9 1.04 0.21 7 1.05 0.23 6 0.98 0.23 5 PORTUGAL PRT 1.25 0.16 10 1.25 0.17 10 1.42 0.19 9 1.47 0.19 9 1.37 0.19 9 1.30 0.20 8 1.33 0.21 7 1.46 0.23 6 1.27 0.23 5 PUERTORICO PRI 1.27 0.24 4 1.28 0.26 3 1.10 0.30 2 0.93 0.30 2 1.06 0.29 2 1.07 0.29 2 0.87 0.48 1 0.88 0.47 1 .. .. .. QATAR QAT -0.64 0.14 9 -0.63 0.15 9 -0.40 0.16 9 -0.47 0.18 7 -0.67 0.17 7 -0.62 0.22 5 -0.54 0.23 4 -0.75 0.24 4 -0.94 0.25 3 REUNION REU 1.23 0.54 1 1.27 0.52 1 1.37 0.42 1 1.15 0.40 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ROMANIA ROM 0.47 0.13 14 0.50 0.13 14 0.36 0.15 12 0.36 0.16 11 0.34 0.15 10 0.46 0.15 9 0.40 0.22 6 0.36 0.23 5 0.18 0.23 4 RUSSIA RUS -1.01 0.12 15 -0.97 0.12 15 -0.67 0.14 13 -0.60 0.14 12 -0.59 0.15 11 -0.38 0.15 10 -0.46 0.21 7 -0.58 0.23 6 -0.43 0.23 5 RWANDA RWA -1.24 0.14 11 -1.24 0.14 10 -1.27 0.19 8 -1.34 0.19 8 -1.27 0.20 5 -1.49 0.20 5 -1.50 0.29 3 -1.34 0.29 3 -1.33 0.28 2 SAMOA SAM 0.67 0.23 3 0.65 0.24 3 0.59 0.28 3 0.57 0.28 3 0.70 0.26 3 0.68 0.29 2 0.70 0.32 2 0.52 0.33 2 0.71 0.30 1 SAN MARINO SMR 1.18 0.24 2 1.17 0.26 2 1.13 0.35 2 1.14 0.37 2 1.21 0.30 2 1.28 0.33 1 1.41 0.40 1 1.43 0.42 1 1.49 0.30 1 SAOTOME ANDPRINCIPE STP 0.44 0.20 4 0.39 0.21 5 0.09 0.27 4 0.09 0.27 4 0.41 0.26 3 0.59 0.29 2 0.36 0.32 2 0.27 0.33 2 0.51 0.30 1 SAUDI ARABIA SAU -1.59 0.14 10 -1.66 0.14 10 -1.32 0.16 8 -1.41 0.18 7 -1.63 0.17 7 -1.64 0.17 8 -1.49 0.22 5 -1.50 0.23 5 -1.62 0.23 4 SENEGAL SEN -0.02 0.13 15 0.08 0.13 14 0.08 0.17 10 0.11 0.17 10 0.12 0.17 10 0.23 0.17 9 0.03 0.22 6 -0.08 0.22 6 -0.12 0.23 5 SERBIA YUG 0.20 0.14 11 0.13 0.14 11 -0.19 0.16 9 -0.10 0.16 9 -0.03 0.15 9 -0.12 0.16 8 -0.72 0.22 5 -1.14 0.23 5 -1.38 0.23 4 SEYCHELLES SYC -0.06 0.19 5 -0.01 0.20 5 0.16 0.21 6 0.38 0.21 6 -0.08 0.25 4 0.11 0.27 3 0.00 0.32 2 0.02 0.33 2 0.04 0.30 1 SIERRA LEONE SLE -0.33 0.13 11 -0.43 0.13 11 -0.62 0.18 8 -0.43 0.18 8 -0.64 0.16 7 -0.73 0.19 6 -1.57 0.26 3 -1.47 0.28 3 -0.94 0.26 3 SINGAPORE SGP -0.43 0.15 11 -0.37 0.15 11 0.04 0.17 9 0.02 0.17 9 -0.01 0.17 9 0.07 0.17 8 0.25 0.21 7 0.27 0.23 6 -0.21 0.23 5 SLOVAKIA SVK 0.98 0.16 10 1.00 0.16 10 0.92 0.17 9 0.96 0.17 9 1.04 0.17 9 0.99 0.17 8 0.79 0.21 7 0.71 0.23 5 0.25 0.23 4 SLOVENIA SVN 1.08 0.15 11 1.09 0.16 11 1.06 0.16 10 1.10 0.17 9 1.16 0.17 9 1.12 0.17 9 1.05 0.21 7 1.20 0.23 5 1.10 0.25 3 SOLOMONISLANDS SLB 0.15 0.22 4 0.20 0.24 3 0.08 0.28 3 -0.20 0.28 3 0.35 0.30 2 0.42 0.33 1 0.20 0.40 1 1.02 0.42 1 1.10 0.30 1 SOMALIA SOM -1.89 0.17 6 -1.81 0.18 6 -1.89 0.20 7 -1.76 0.20 7 -1.56 0.19 6 -1.47 0.19 5 -1.86 0.26 3 -2.03 0.28 3 -1.91 0.28 2 SOUTHAFRICA ZAF 0.74 0.13 16 0.76 0.13 16 0.73 0.16 14 0.72 0.17 13 0.78 0.17 12 0.63 0.16 11 0.75 0.21 8 0.75 0.22 7 0.80 0.23 6 SPAIN ESP 1.05 0.15 11 1.04 0.17 10 1.11 0.19 8 1.30 0.19 8 1.24 0.20 8 1.25 0.20 8 1.26 0.21 7 1.29 0.23 6 1.15 0.23 5 SRI LANKA LKA -0.39 0.12 14 -0.27 0.13 13 -0.21 0.15 11 -0.16 0.16 10 -0.14 0.15 9 -0.14 0.17 8 -0.29 0.22 6 -0.15 0.23 5 -0.24 0.23 4 ST. KITTS AND NEVIS KNA 1.11 0.23 3 1.10 0.24 3 1.09 0.27 4 0.46 0.27 4 0.81 0.30 2 0.97 0.33 1 0.96 0.40 1 0.98 0.42 1 1.03 0.30 1 ST. LUCIA LCA 1.22 0.23 3 1.22 0.24 3 1.17 0.27 4 0.68 0.27 4 1.13 0.30 2 1.15 0.33 1 1.05 0.40 1 1.07 0.42 1 1.12 0.30 1 ST. VINCENTANDTHE GRENADINES VCT 1.03 0.23 3 1.03 0.24 3 1.06 0.27 4 0.74 0.27 4 1.09 0.30 2 0.99 0.33 1 1.00 0.40 1 1.02 0.42 1 1.07 0.30 1 SUDAN SDN -1.73 0.14 11 -1.74 0.15 9 -1.70 0.18 8 -1.66 0.18 8 -1.56 0.17 7 -1.53 0.17 7 -1.71 0.22 5 -1.75 0.23 5 -1.95 0.23 4 SURINAME SUR 0.36 0.21 5 0.29 0.21 6 0.10 0.25 5 0.13 0.24 5 0.38 0.24 4 0.35 0.25 3 0.19 0.26 3 -0.22 0.28 3 0.20 0.28 2 SWAZILAND SWZ -1.10 0.16 7 -1.09 0.16 7 -1.35 0.22 6 -1.32 0.22 6 -1.39 0.25 4 -1.25 0.25 4 -1.39 0.29 3 -1.23 0.29 3 -1.09 0.28 2 SWEDEN SWE 1.47 0.16 11 1.45 0.16 11 1.58 0.18 9 1.76 0.19 8 1.54 0.20 8 1.52 0.20 8 1.61 0.21 7 1.58 0.23 6 1.42 0.23 5 SWITZERLAND CHE 1.55 0.18 9 1.59 0.18 9 1.60 0.19 8 1.71 0.19 8 1.46 0.20 8 1.43 0.20 8 1.45 0.21 7 1.44 0.23 6 1.39 0.23 5 SYRIA SYR -1.77 0.13 12 -1.75 0.13 11 -1.51 0.15 10 -1.52 0.16 9 -1.57 0.17 7 -1.58 0.17 7 -1.53 0.22 5 -1.47 0.23 5 -1.61 0.23 4 TAIWAN TWN 0.74 0.15 11 0.70 0.15 11 0.93 0.17 9 0.86 0.17 9 0.97 0.17 9 0.93 0.17 9 0.78 0.21 7 0.82 0.23 6 0.59 0.23 5 TAJIKISTAN TJK -1.26 0.13 11 -1.32 0.13 12 -1.16 0.17 9 -1.30 0.17 8 -1.20 0.17 6 -1.25 0.17 6 -1.42 0.29 3 -1.71 0.29 3 -1.74 0.28 2 TANZANIA TZA -0.15 0.14 15 -0.20 0.14 14 -0.31 0.16 12 -0.46 0.17 11 -0.38 0.17 10 -0.27 0.17 9 -0.42 0.22 6 -0.49 0.22 6 -0.64 0.23 5 THAILAND THA -0.61 0.12 13 -0.60 0.13 13 0.03 0.16 11 0.12 0.16 11 0.26 0.17 9 0.34 0.17 9 0.51 0.21 7 0.40 0.23 6 0.29 0.23 5 TIMOR-LESTE TMP -0.12 0.16 7 -0.28 0.17 7 -0.19 0.21 7 0.07 0.22 6 0.19 0.19 5 0.28 0.29 2 0.07 0.40 1 .. .. .. .. .. .. TOGO TGO -1.16 0.15 9 -1.31 0.16 9 -1.43 0.20 7 -1.31 0.20 7 -1.41 0.19 6 -1.46 0.19 6 -1.26 0.25 4 -1.18 0.26 4 -1.04 0.26 3 TONGA TON -0.08 0.21 4 -0.02 0.23 4 -0.09 0.26 4 -0.26 0.27 4 -0.16 0.30 2 0.01 0.33 1 -0.04 0.40 1 -0.07 0.42 1 -0.09 0.30 1 TRINIDAD AND TOBAGO TTO 0.61 0.18 8 0.56 0.19 8 0.60 0.19 8 0.59 0.19 8 0.61 0.20 7 0.53 0.21 6 0.53 0.22 6 0.81 0.23 5 0.81 0.23 4 TUNISIA TUN -1.22 0.12 13 -1.20 0.12 13 -0.99 0.14 12 -0.84 0.16 11 -0.92 0.17 9 -1.00 0.17 9 -0.71 0.22 6 -0.75 0.22 6 -0.85 0.23 5 TURKEY TUR -0.19 0.13 14 -0.16 0.13 14 -0.07 0.15 13 -0.08 0.16 12 -0.15 0.17 10 -0.28 0.17 9 -0.48 0.21 7 -0.68 0.23 6 -0.44 0.23 5 TURKMENISTAN TKM -2.07 0.16 7 -2.00 0.17 6 -1.99 0.19 6 -2.01 0.22 5 -1.86 0.20 5 -1.93 0.20 5 -1.67 0.29 3 -1.63 0.29 3 -1.81 0.28 2 TUVALU TUV 0.83 0.23 3 0.79 0.24 3 0.64 0.28 3 0.56 0.28 3 1.04 0.30 2 1.15 0.33 1 1.41 0.40 1 1.43 0.42 1 1.49 0.30 1 UGANDA UGA -0.47 0.12 17 -0.46 0.12 17 -0.57 0.15 13 -0.69 0.16 12 -0.76 0.15 11 -0.95 0.17 9 -1.10 0.22 6 -0.82 0.22 6 -0.50 0.23 5 UKRAINE UKR -0.09 0.12 14 -0.17 0.13 12 -0.37 0.14 11 -0.58 0.15 11 -0.67 0.13 11 -0.58 0.15 9 -0.57 0.22 6 -0.32 0.23 5 -0.30 0.25 3 UNITEDARAB EMIRATES ARE -0.89 0.15 9 -0.92 0.16 9 -0.68 0.16 9 -0.78 0.17 8 -0.82 0.20 6 -0.72 0.21 6 -0.58 0.22 5 -0.56 0.23 5 -1.02 0.23 4 UNITEDKINGDOM GBR 1.38 0.16 11 1.41 0.16 11 1.47 0.18 9 1.60 0.19 8 1.29 0.20 8 1.27 0.20 8 1.36 0.21 7 1.30 0.23 6 1.02 0.23 5 UNITEDSTATES USA 1.09 0.15 12 1.07 0.15 12 1.25 0.18 9 1.27 0.19 9 1.23 0.19 9 1.33 0.20 8 1.37 0.21 7 1.37 0.23 6 1.29 0.23 5 URUGUAY URY 0.95 0.15 11 0.95 0.16 10 0.88 0.17 10 0.85 0.17 10 1.02 0.17 9 1.00 0.17 9 0.92 0.20 7 0.88 0.22 6 0.94 0.22 5 UZBEKISTAN UZB -1.91 0.13 10 -1.91 0.13 9 -1.82 0.15 8 -1.74 0.15 8 -1.76 0.14 8 -1.66 0.16 7 -1.64 0.28 3 -1.57 0.29 3 -1.52 0.25 3 VANUATU VUT 0.46 0.20 4 0.63 0.24 3 0.36 0.28 3 0.35 0.28 3 0.86 0.30 2 0.92 0.33 1 0.50 0.40 1 0.44 0.42 1 0.47 0.30 1 VENEZUELA VEN -0.58 0.13 15 -0.47 0.13 14 -0.57 0.15 13 -0.57 0.15 13 -0.50 0.14 12 -0.56 0.17 10 -0.13 0.20 8 0.00 0.22 7 0.08 0.22 6 VIETNAM VNM -1.61 0.12 14 -1.58 0.12 14 -1.43 0.15 11 -1.39 0.16 10 -1.55 0.15 9 -1.50 0.17 8 -1.27 0.22 6 -1.36 0.23 5 -1.50 0.23 4 VIRGINISLANDS (U.S.) VIR 0.78 0.54 1 0.82 0.52 1 1.13 0.42 1 0.72 0.40 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. WEST BANK GAZA WBG -1.28 0.21 5 -1.04 0.22 5 -0.75 0.22 5 -1.02 0.28 4 -1.29 0.27 3 -1.21 0.27 3 -1.09 0.32 2 -0.99 0.33 2 -0.70 0.30 1 YEMEN YEM -1.06 0.12 13 -1.05 0.12 13 -0.99 0.15 10 -0.89 0.16 9 -1.05 0.15 8 -1.21 0.17 7 -0.92 0.22 5 -0.77 0.23 5 -0.94 0.23 4 ZAMBIA ZMB -0.26 0.13 15 -0.33 0.13 15 -0.50 0.15 12 -0.38 0.16 12 -0.35 0.17 10 -0.43 0.17 9 -0.41 0.22 6 -0.54 0.22 6 -0.55 0.23 5 ZIMBABWE ZWE -1.54 0.12 16 -1.50 0.12 16 -1.70 0.15 13 -1.58 0.15 12 -1.47 0.15 11 -1.48 0.17 9 -1.16 0.22 7 -0.86 0.22 6 -0.63 0.23 5 81 TABLE C2: Political Stability & Absence of Violence/Terrorism 2007 2006 2005 2004 2003 2002 2000 1998 1996 Country Code Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. AFGHANISTAN AFG -2.37 0.29 4 -2.28 0.26 5 -2.02 0.26 5 -2.13 0.27 5 -2.03 0.32 3 -1.95 0.33 3 -2.73 0.32 3 -2.55 0.41 2 -2.07 0.49 1 ALBANIA ALB -0.27 0.24 7 -0.41 0.24 7 -0.59 0.26 6 -0.80 0.29 5 -0.43 0.31 4 -0.62 0.31 4 -0.96 0.30 4 -0.84 0.28 4 -0.12 0.36 3 ALGERIA DZA -1.18 0.21 10 -1.00 0.21 10 -1.14 0.23 9 -1.48 0.23 9 -1.85 0.23 8 -1.88 0.24 7 -1.90 0.26 6 -2.33 0.25 6 -2.44 0.29 5 AMERICAN SAMOA ASM 0.98 0.45 1 0.74 0.45 1 0.76 0.49 1 0.74 0.50 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ANDORRA ADO 1.36 0.39 2 1.39 0.39 2 1.41 0.40 2 1.42 0.41 2 1.45 0.38 2 1.20 0.49 1 1.13 0.52 1 1.11 0.55 1 .. .. .. ANGOLA AGO -0.46 0.23 8 -0.44 0.23 9 -0.78 0.23 8 -0.95 0.23 9 -1.09 0.25 7 -1.41 0.25 6 -2.39 0.26 5 -2.23 0.25 5 -2.27 0.33 4 ANGUILLA AIA 1.20 0.37 2 1.17 0.38 2 1.27 0.39 2 0.79 0.50 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ANTIGUA AND BARBUDA ATG 0.82 0.33 3 0.83 0.34 3 0.84 0.34 3 1.19 0.35 3 0.84 0.38 2 0.71 0.49 1 0.66 0.52 1 0.65 0.55 1 .. .. .. ARGENTINA ARG 0.14 0.20 11 0.05 0.20 11 -0.12 0.21 10 -0.30 0.22 10 -0.29 0.23 9 -1.02 0.22 9 0.00 0.22 7 0.10 0.23 6 0.11 0.29 5 ARMENIA ARM -0.01 0.23 8 -0.26 0.23 8 -0.20 0.25 7 -0.57 0.26 6 -0.31 0.28 5 -0.81 0.29 5 -1.25 0.30 4 -0.86 0.28 4 0.25 0.38 2 ARUBA ABW 1.38 0.37 2 1.36 0.38 2 1.44 0.39 2 0.99 0.50 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. AUSTRALIA AUS 0.86 0.22 10 0.88 0.22 10 0.87 0.21 10 0.89 0.22 10 0.82 0.23 9 1.18 0.23 8 1.25 0.22 7 1.20 0.23 6 1.10 0.29 5 AUSTRIA AUT 1.23 0.22 10 1.02 0.22 10 1.05 0.21 10 0.97 0.22 10 0.94 0.23 9 1.29 0.23 8 1.23 0.22 7 1.27 0.23 6 1.23 0.29 5 AZERBAIJAN AZE -0.69 0.23 8 -1.01 0.23 8 -1.25 0.23 8 -1.37 0.24 7 -1.40 0.25 6 -1.27 0.25 6 -0.91 0.26 5 -0.71 0.25 5 -0.64 0.34 3 BAHAMAS BHS 0.80 0.31 4 0.88 0.32 4 0.94 0.32 4 0.94 0.33 4 0.80 0.35 3 0.87 0.38 3 1.11 0.38 3 0.85 0.31 3 1.04 0.45 2 BAHRAIN BHR -0.28 0.23 8 -0.39 0.23 8 -0.29 0.23 8 -0.03 0.23 8 0.19 0.25 6 0.23 0.25 6 0.07 0.26 5 -0.21 0.25 5 -0.82 0.33 4 BANGLADESH BGD -1.44 0.21 9 -1.45 0.22 9 -1.68 0.23 8 -1.14 0.23 8 -1.09 0.25 7 -0.84 0.24 7 -0.55 0.26 5 -0.49 0.25 5 -0.89 0.33 4 BARBADOS BRB 1.20 0.29 5 1.05 0.30 5 1.22 0.31 4 1.24 0.31 4 1.04 0.34 3 1.03 0.42 2 0.99 0.42 2 0.99 0.41 2 1.05 0.49 1 BELARUS BLR 0.20 0.23 7 0.14 0.24 7 0.10 0.26 6 -0.21 0.26 6 0.16 0.28 5 -0.02 0.31 4 -0.14 0.30 4 -0.11 0.28 4 -0.11 0.38 2 BELGIUM BEL 0.75 0.22 10 0.75 0.22 10 0.75 0.21 10 0.78 0.22 10 1.03 0.23 9 1.18 0.22 9 0.99 0.22 7 1.02 0.23 6 0.94 0.29 5 BELIZE BLZ 0.24 0.27 5 0.19 0.27 5 0.27 0.31 4 0.78 0.31 4 0.69 0.34 3 0.32 0.42 2 0.29 0.42 2 0.58 0.41 2 0.77 0.49 1 BENIN BEN 0.38 0.23 8 0.39 0.23 8 0.29 0.29 6 -0.04 0.29 5 0.36 0.34 3 0.72 0.42 2 0.67 0.42 2 0.61 0.41 2 1.05 0.49 1 BERMUDA BMU 0.80 0.37 2 0.81 0.38 2 0.83 0.39 2 0.89 0.40 2 0.80 0.47 1 0.71 0.49 1 0.66 0.52 1 0.65 0.55 1 .. .. .. BHUTAN BTN 0.67 0.30 4 1.30 0.31 4 1.14 0.31 4 0.85 0.31 4 0.77 0.34 3 0.63 0.42 2 0.48 0.42 2 0.46 0.41 2 0.84 0.49 1 BOLIVIA BOL -0.99 0.21 9 -0.93 0.22 9 -1.13 0.23 8 -0.64 0.23 8 -0.67 0.25 7 -0.15 0.24 7 -0.25 0.26 5 -0.25 0.25 5 -0.16 0.33 4 BOSNIA-HERZEGOVINA BIH -0.56 0.24 7 -0.53 0.24 7 -0.63 0.24 7 -0.50 0.24 7 -0.72 0.26 5 -0.67 0.26 5 -0.62 0.34 3 -0.60 0.34 3 -0.50 0.42 2 BOTSWANA BWA 0.84 0.21 10 0.96 0.21 10 1.02 0.23 9 0.92 0.24 8 0.98 0.23 8 0.83 0.23 8 0.95 0.26 6 0.82 0.25 6 0.69 0.29 5 BRAZIL BRA -0.22 0.20 11 -0.14 0.20 11 -0.11 0.21 10 -0.09 0.22 10 0.01 0.23 9 -0.18 0.22 9 0.09 0.22 7 -0.42 0.23 6 -0.57 0.29 5 BRUNEI BRN 1.21 0.35 3 1.22 0.36 3 1.26 0.37 3 1.36 0.38 3 1.08 0.35 3 1.00 0.38 3 1.23 0.38 3 1.19 0.31 3 1.12 0.45 2 BULGARIA BGR 0.42 0.21 10 0.43 0.21 10 0.21 0.23 8 0.09 0.23 8 0.33 0.25 7 0.49 0.24 7 0.49 0.26 5 0.57 0.25 5 -0.22 0.33 4 BURKINA FASO BFA 0.09 0.21 10 -0.08 0.21 10 -0.01 0.29 6 -0.21 0.28 6 0.04 0.30 5 -0.38 0.34 4 -0.09 0.37 4 -0.10 0.31 4 0.04 0.36 3 BURUNDI BDI -1.42 0.24 7 -1.39 0.24 7 -1.41 0.31 4 -2.34 0.31 4 -2.08 0.34 3 -2.41 0.42 2 -2.22 0.42 2 -2.41 0.41 2 -2.00 0.49 1 CAMBODIA KHM -0.43 0.24 7 -0.40 0.24 7 -0.50 0.26 6 -0.47 0.27 5 -0.72 0.29 4 -0.71 0.30 4 -0.75 0.34 3 -1.17 0.34 3 -1.41 0.42 2 CAMEROON CMR -0.39 0.21 10 -0.31 0.21 10 -0.39 0.23 9 -0.60 0.23 8 -0.60 0.23 8 -0.65 0.24 7 -0.53 0.26 6 -0.77 0.25 6 -1.35 0.29 5 CANADA CAN 1.02 0.20 11 1.02 0.20 11 0.94 0.21 10 0.99 0.22 10 1.17 0.23 9 1.20 0.22 9 1.11 0.22 7 1.09 0.23 6 0.94 0.29 5 CAPE VERDE CPV 1.01 0.31 4 1.00 0.31 3 0.73 0.40 2 1.11 0.41 2 0.97 0.38 2 0.65 0.42 2 1.08 0.60 1 1.05 0.54 1 1.05 0.49 1 CAYMAN ISLANDS CYM 1.20 0.37 2 1.17 0.38 2 1.27 0.39 2 1.36 0.40 2 0.80 0.47 1 0.71 0.49 1 0.66 0.52 1 0.65 0.55 1 .. .. .. CENTRAL AFRICAN REPUBLIC CAF -1.78 0.30 4 -1.79 0.31 4 -1.14 0.31 4 -1.21 0.31 4 -1.44 0.34 3 -1.79 0.42 2 -1.32 0.42 2 -1.14 0.41 2 -0.20 0.49 1 CHAD TCD -1.96 0.23 8 -1.87 0.23 8 -1.32 0.29 6 -1.22 0.29 6 -1.23 0.30 5 -1.60 0.34 4 -1.36 0.41 3 -1.31 0.40 3 -0.74 0.38 2 CHILE CHL 0.55 0.20 11 0.69 0.20 11 0.91 0.21 10 0.81 0.22 10 0.87 0.23 9 0.94 0.22 9 0.61 0.22 7 0.13 0.23 6 0.44 0.29 5 CHINA CHN -0.33 0.20 11 -0.33 0.20 11 -0.26 0.21 10 -0.17 0.22 10 -0.36 0.23 9 -0.21 0.22 9 -0.11 0.22 7 -0.10 0.23 6 -0.26 0.29 5 COLOMBIA COL -1.65 0.20 11 -1.67 0.20 11 -1.81 0.21 10 -1.98 0.22 10 -2.21 0.23 9 -2.06 0.22 9 -1.85 0.22 7 -1.58 0.23 6 -1.42 0.29 5 COMOROS COM -0.40 0.39 2 -0.20 0.39 2 -0.18 0.40 2 0.02 0.41 2 -0.57 0.38 2 0.32 0.42 2 -0.18 0.42 2 0.47 0.41 2 1.05 0.49 1 CONGO COG -0.83 0.23 8 -0.97 0.23 8 -1.23 0.23 8 -1.09 0.28 6 -0.91 0.30 5 -1.28 0.32 5 -1.14 0.37 4 -2.04 0.31 4 -0.83 0.45 2 CONGO, DEM. REP. ZAR -2.26 0.25 7 -2.39 0.26 7 -2.32 0.23 8 -2.22 0.23 8 -2.19 0.28 5 -2.22 0.29 5 -2.64 0.30 4 -3.06 0.28 4 -1.88 0.36 3 COSTA RICA CRI 0.84 0.23 8 0.93 0.23 8 0.91 0.23 8 0.91 0.23 8 0.90 0.25 7 1.06 0.24 7 0.89 0.26 5 0.76 0.25 5 0.84 0.33 4 COTE D'IVOIRE CIV -2.12 0.21 9 -2.15 0.22 9 -2.45 0.23 8 -2.16 0.23 8 -1.89 0.24 7 -1.81 0.24 7 -0.86 0.26 6 -0.28 0.25 6 -0.14 0.29 5 CROATIA HRV 0.52 0.22 9 0.51 0.23 9 0.36 0.23 8 0.42 0.23 8 0.35 0.25 7 0.39 0.24 7 0.32 0.26 5 0.12 0.25 5 -0.10 0.34 3 CUBA CUB 0.11 0.22 8 0.16 0.22 8 -0.06 0.24 7 0.08 0.24 7 -0.05 0.25 6 -0.05 0.25 6 -0.35 0.26 5 -0.21 0.25 5 -0.37 0.33 4 CYPRUS CYP 0.49 0.24 7 0.48 0.24 7 0.35 0.24 7 0.33 0.25 7 0.41 0.27 5 0.24 0.26 5 0.48 0.26 5 0.29 0.25 5 0.54 0.33 4 CZECH REPUBLIC CZE 0.83 0.20 11 0.85 0.20 11 0.75 0.21 10 0.67 0.22 10 0.87 0.23 9 0.97 0.22 9 0.60 0.22 7 0.78 0.23 6 0.98 0.29 5 DENMARK DNK 0.94 0.22 10 0.83 0.22 10 0.96 0.21 10 1.03 0.22 10 1.18 0.23 9 1.26 0.23 8 1.20 0.22 7 1.21 0.23 6 1.03 0.29 5 DJIBOUTI DJI -0.05 0.33 3 -0.24 0.34 3 -0.64 0.40 2 -0.25 0.41 2 -0.91 0.38 2 -0.41 0.42 2 -0.50 0.42 2 -1.07 0.41 2 0.21 0.49 1 DOMINICA DMA 1.00 0.33 3 0.97 0.34 3 0.87 0.34 3 1.08 0.35 3 0.66 0.38 2 0.47 0.49 1 0.43 0.52 1 0.65 0.55 1 .. .. .. DOMINICAN REPUBLIC DOM 0.12 0.21 9 0.11 0.22 9 0.03 0.23 8 0.04 0.23 8 -0.12 0.25 7 0.23 0.24 7 0.10 0.26 5 -0.35 0.28 4 -0.48 0.40 3 ECUADOR ECU -0.91 0.23 8 -0.90 0.23 8 -0.81 0.23 8 -0.86 0.22 9 -0.94 0.24 8 -0.83 0.23 8 -0.97 0.24 6 -0.41 0.23 6 -0.85 0.29 5 EGYPT EGY -0.77 0.20 11 -0.94 0.20 11 -0.92 0.21 10 -0.99 0.22 10 -0.83 0.23 9 -0.71 0.22 8 -0.36 0.24 7 -0.42 0.23 7 -1.07 0.26 6 EL SALVADOR SLV 0.02 0.25 7 -0.14 0.25 7 -0.05 0.25 7 -0.08 0.26 7 -0.17 0.27 6 0.20 0.27 6 0.23 0.31 4 -0.16 0.28 4 -0.29 0.40 3 EQUATORIAL GUINEA GNQ -0.16 0.25 6 -0.09 0.26 6 -0.33 0.30 5 -0.16 0.29 5 -0.20 0.27 5 -0.38 0.28 5 -0.03 0.33 4 -0.26 0.33 4 -0.39 0.34 3 ERITREA ERI -1.04 0.27 5 -0.93 0.27 5 -0.78 0.31 4 -0.65 0.31 4 -0.75 0.34 3 -0.44 0.42 2 -1.25 0.42 2 -1.41 0.41 2 0.28 0.49 1 ESTONIA EST 0.68 0.21 10 0.81 0.21 10 0.71 0.22 9 0.93 0.23 9 1.07 0.24 8 0.99 0.23 8 0.81 0.24 6 0.68 0.25 5 0.67 0.34 3 ETHIOPIA ETH -1.72 0.22 9 -1.72 0.23 9 -1.52 0.25 8 -1.20 0.25 8 -1.35 0.26 7 -1.30 0.27 6 -1.25 0.31 5 -0.82 0.27 5 -1.16 0.33 4 FIJI FJI 0.09 0.33 3 -0.02 0.34 3 0.39 0.34 3 0.31 0.35 3 0.42 0.38 2 0.36 0.42 2 -0.03 0.42 2 0.84 0.41 2 0.77 0.49 1 FINLAND FIN 1.43 0.22 10 1.47 0.22 10 1.55 0.21 10 1.60 0.22 10 1.65 0.23 9 1.60 0.22 9 1.41 0.22 7 1.27 0.23 6 1.19 0.29 5 FRANCE FRA 0.51 0.20 11 0.48 0.20 11 0.43 0.21 10 0.51 0.22 10 0.52 0.23 9 0.94 0.22 9 0.89 0.22 7 0.82 0.23 6 0.91 0.29 5 FRENCH GUIANA GUF 0.04 0.37 2 0.07 0.38 2 0.24 0.49 1 0.20 0.50 1 0.27 0.47 1 0.22 0.49 1 -0.04 0.52 1 -0.04 0.55 1 .. .. .. GABON GAB 0.20 0.21 9 0.13 0.22 9 0.08 0.23 8 0.19 0.23 8 0.16 0.24 7 0.10 0.24 7 0.29 0.26 6 -0.04 0.27 5 -0.33 0.33 4 GAMBIA GMB -0.14 0.29 5 -0.03 0.28 5 0.24 0.34 4 0.25 0.36 4 0.37 0.34 4 0.68 0.38 3 0.47 0.38 3 0.62 0.31 3 0.11 0.45 2 GEORGIA GEO -0.70 0.24 7 -0.90 0.24 7 -0.69 0.26 6 -1.03 0.27 6 -1.61 0.30 4 -1.47 0.30 4 -1.46 0.32 3 -1.59 0.34 3 -0.93 0.38 2 GERMANY DEU 0.95 0.20 11 0.90 0.20 11 0.80 0.21 10 0.69 0.22 10 0.70 0.23 9 1.04 0.22 9 1.23 0.22 7 1.25 0.23 6 1.14 0.29 5 82 TABLE C2: Political Stability & Absence of Violence/Terrorism (cont.) 2007 2006 2005 2004 2003 2002 2000 1998 1996 Country Code Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. GHANA GHA 0.22 0.21 9 0.26 0.22 9 0.29 0.23 9 0.05 0.23 9 0.00 0.23 8 -0.05 0.24 7 -0.21 0.26 6 -0.05 0.25 6 -0.18 0.29 5 GREECE GRC 0.47 0.20 11 0.50 0.20 11 0.45 0.21 10 0.40 0.22 10 0.58 0.23 9 0.68 0.22 9 0.61 0.22 7 0.25 0.23 6 0.37 0.29 5 GRENADA GRD 0.42 0.33 3 0.47 0.34 3 0.46 0.34 3 0.93 0.35 3 0.94 0.38 2 0.85 0.42 2 0.83 0.42 2 0.86 0.41 2 1.05 0.49 1 GUAM GUM 0.46 0.45 1 0.74 0.45 1 0.76 0.49 1 0.64 0.50 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. GUATEMALA GTM -0.76 0.21 9 -0.72 0.22 9 -0.91 0.25 7 -0.81 0.26 7 -0.84 0.27 6 -0.85 0.27 6 -0.68 0.31 4 -0.81 0.28 4 -1.61 0.40 3 GUINEA GIN -2.02 0.23 7 -1.76 0.24 7 -1.10 0.30 5 -0.87 0.30 5 -0.61 0.32 4 -1.29 0.35 4 -1.79 0.38 3 -0.58 0.31 3 -1.42 0.45 2 GUINEA-BISSAU GNB -0.41 0.35 3 -0.41 0.36 3 -0.52 0.37 3 -0.34 0.38 3 -0.43 0.35 3 -0.70 0.38 3 -0.81 0.38 3 -1.79 0.31 3 -0.59 0.45 2 GUYANA GUY -0.32 0.25 7 -0.59 0.25 7 -0.23 0.28 6 -0.29 0.30 5 -0.32 0.32 4 -0.54 0.38 3 -0.56 0.38 3 -0.04 0.31 3 0.02 0.45 2 HAITI HTI -1.34 0.25 6 -1.40 0.26 6 -1.79 0.30 5 -1.94 0.30 5 -0.98 0.31 5 -1.30 0.35 4 -0.82 0.38 3 -1.41 0.31 3 -0.43 0.45 2 HONDURAS HND -0.39 0.23 8 -0.50 0.23 8 -0.61 0.25 7 -0.43 0.26 7 -0.45 0.27 6 -0.26 0.27 6 -0.23 0.31 4 -0.27 0.28 4 -0.46 0.40 3 HONG KONG HKG 1.05 0.22 9 1.12 0.22 9 1.17 0.24 8 1.04 0.24 8 0.80 0.26 7 0.78 0.24 7 0.82 0.26 5 0.57 0.27 4 -0.01 0.41 3 HUNGARY HUN 0.65 0.20 11 0.81 0.20 11 0.85 0.21 10 0.81 0.22 10 0.99 0.23 9 1.00 0.22 9 0.69 0.22 7 0.97 0.23 6 0.58 0.29 5 ICELAND ISL 1.65 0.24 8 1.60 0.24 8 1.65 0.27 7 1.68 0.28 7 1.69 0.30 6 1.53 0.33 5 1.42 0.32 4 1.28 0.31 3 1.07 0.45 2 INDIA IND -1.01 0.20 11 -0.94 0.20 11 -0.79 0.21 10 -0.94 0.22 10 -1.25 0.23 9 -1.01 0.22 9 -0.68 0.22 7 -0.87 0.23 6 -1.12 0.29 5 INDONESIA IDN -1.13 0.20 11 -1.25 0.20 11 -1.29 0.21 10 -1.57 0.22 10 -2.03 0.23 9 -1.61 0.22 9 -1.67 0.22 7 -1.35 0.23 6 -0.81 0.29 5 IRAN IRN -1.33 0.21 9 -1.33 0.21 9 -1.15 0.22 8 -1.08 0.23 8 -1.05 0.24 7 -0.82 0.23 7 -0.43 0.24 6 -0.45 0.23 6 -0.69 0.29 5 IRAQ IRQ -2.82 0.23 7 -2.89 0.24 7 -2.82 0.24 7 -3.07 0.26 6 -2.36 0.25 6 -1.90 0.25 6 -1.75 0.26 5 -2.34 0.25 5 -2.90 0.33 4 IRELAND IRL 1.15 0.20 11 1.08 0.20 11 1.15 0.21 10 1.10 0.22 10 1.23 0.23 9 1.30 0.23 8 1.23 0.22 7 1.21 0.23 6 0.97 0.29 5 ISRAEL ISR -1.20 0.21 10 -1.23 0.21 10 -1.04 0.22 9 -1.27 0.23 9 -1.41 0.24 8 -1.50 0.23 8 -0.74 0.24 6 -0.88 0.25 5 -0.68 0.29 5 ITALY ITA 0.44 0.20 11 0.40 0.20 11 0.29 0.21 10 0.27 0.22 10 0.48 0.23 9 0.70 0.22 9 0.70 0.22 7 0.77 0.23 6 0.54 0.29 5 JAMAICA JAM 0.00 0.25 7 -0.23 0.25 7 -0.31 0.25 7 -0.25 0.26 7 -0.49 0.27 6 -0.44 0.27 6 -0.09 0.31 4 -0.21 0.28 4 0.25 0.40 3 JAPAN JPN 1.02 0.20 11 1.08 0.20 11 1.01 0.21 10 1.04 0.22 10 1.17 0.23 9 1.17 0.22 9 1.06 0.22 7 1.18 0.23 6 0.90 0.29 5 JORDAN JOR -0.29 0.21 10 -0.64 0.21 10 -0.23 0.22 9 -0.34 0.23 9 -0.26 0.24 8 -0.42 0.24 7 0.01 0.26 5 -0.13 0.25 5 0.17 0.33 4 KAZAKHSTAN KAZ 0.37 0.21 10 0.13 0.21 10 -0.01 0.22 9 -0.15 0.23 8 0.08 0.24 7 0.09 0.23 7 0.05 0.24 6 0.09 0.23 6 -0.31 0.30 4 KENYA KEN -1.10 0.21 10 -1.02 0.21 10 -1.19 0.23 9 -1.05 0.23 9 -1.27 0.23 8 -1.21 0.24 7 -1.09 0.26 6 -1.02 0.25 6 -0.67 0.29 5 KIRIBATI KIR 1.36 0.39 2 1.39 0.39 2 1.41 0.40 2 1.20 0.41 2 1.23 0.55 1 .. .. .. .. .. .. .. .. .. .. .. .. KOREA, NORTH PRK 0.35 0.35 3 -0.18 0.29 4 -0.26 0.31 4 -0.15 0.32 4 -0.01 0.35 3 0.29 0.38 3 -0.09 0.38 3 -0.45 0.31 3 -1.83 0.45 2 KOREA, SOUTH KOR 0.45 0.20 11 0.38 0.20 11 0.55 0.21 10 0.48 0.22 10 0.32 0.23 9 0.31 0.22 9 0.17 0.22 7 0.11 0.23 6 0.15 0.29 5 KUWAIT KWT 0.40 0.21 9 0.24 0.22 9 0.06 0.23 8 0.06 0.24 7 0.00 0.25 6 -0.01 0.25 6 0.61 0.26 5 0.35 0.25 5 0.01 0.33 4 KYRGYZSTAN KGZ -1.11 0.24 7 -1.28 0.24 7 -1.14 0.26 6 -1.16 0.27 5 -1.25 0.30 4 -1.17 0.30 4 -0.48 0.32 3 0.01 0.34 3 0.57 0.38 2 LAOS LAO 0.00 0.24 6 0.01 0.25 6 -0.30 0.27 5 -0.59 0.31 4 -1.04 0.34 3 -0.27 0.37 3 -0.73 0.42 2 -0.31 0.41 2 1.05 0.49 1 LATVIA LVA 0.72 0.23 8 0.85 0.23 8 0.86 0.23 8 0.90 0.23 8 1.14 0.25 7 0.95 0.24 7 0.61 0.26 5 0.13 0.25 5 0.52 0.34 3 LEBANON LBN -2.09 0.22 8 -1.89 0.22 8 -1.16 0.24 7 -0.94 0.24 7 -0.69 0.25 6 -0.69 0.25 6 -0.61 0.26 5 -0.86 0.25 5 -0.52 0.33 4 LESOTHO LSO 0.04 0.25 6 0.16 0.26 6 0.30 0.30 4 0.43 0.30 4 0.22 0.30 4 0.02 0.33 3 0.01 0.42 2 -0.22 0.41 2 0.56 0.49 1 LIBERIA LBR -1.15 0.30 5 -1.30 0.32 4 -1.38 0.32 4 -1.48 0.33 4 -2.22 0.35 3 -2.26 0.38 3 -2.08 0.38 3 -1.74 0.31 3 -2.61 0.45 2 LIBYA LBY 0.47 0.22 9 0.26 0.24 7 0.18 0.24 7 0.03 0.26 6 -0.24 0.25 6 -0.38 0.25 6 -0.69 0.26 5 -1.23 0.25 5 -1.76 0.33 4 LIECHTENSTEIN LIE 1.36 0.39 2 1.39 0.39 2 1.41 0.40 2 1.52 0.41 2 1.45 0.38 2 1.20 0.49 1 1.13 0.52 1 1.11 0.55 1 .. .. .. LITHUANIA LTU 0.81 0.21 10 0.91 0.22 9 0.93 0.23 8 0.98 0.23 8 1.17 0.25 7 1.00 0.24 7 0.56 0.26 5 0.41 0.25 5 0.44 0.34 3 LUXEMBOURG LUX 1.57 0.24 8 1.50 0.24 8 1.47 0.27 7 1.48 0.28 7 1.65 0.30 6 1.68 0.32 5 1.55 0.32 4 1.43 0.31 3 1.08 0.45 2 MACAO MAC 0.40 0.37 2 1.00 0.38 2 1.28 0.49 1 1.34 0.50 1 1.06 0.47 1 0.47 0.49 1 0.43 0.52 1 0.19 0.55 1 .. .. .. MACEDONIA MKD -0.41 0.24 7 -0.66 0.24 7 -1.01 0.24 7 -1.03 0.24 7 -0.97 0.25 6 -0.99 0.27 4 -0.84 0.34 3 -0.92 0.34 3 0.22 0.42 2 MADAGASCAR MDG -0.06 0.21 10 0.07 0.21 10 -0.02 0.27 7 -0.04 0.28 7 0.44 0.31 5 -0.24 0.38 3 0.14 0.38 3 0.03 0.31 3 0.08 0.45 2 MALAWI MWI -0.01 0.23 8 0.00 0.23 9 0.04 0.25 8 -0.11 0.26 7 -0.20 0.27 6 -0.17 0.28 5 -0.56 0.31 4 -0.13 0.28 4 -0.25 0.40 3 MALAYSIA MYS 0.20 0.20 11 0.32 0.20 11 0.47 0.21 10 0.26 0.22 10 0.30 0.23 9 0.39 0.22 9 0.28 0.22 7 0.16 0.23 6 0.64 0.29 5 MALDIVES MDV 0.11 0.33 3 0.73 0.34 3 0.79 0.34 3 0.55 0.35 3 0.94 0.38 2 1.01 0.42 2 1.11 0.42 2 1.03 0.41 2 0.21 0.49 1 MALI MLI -0.13 0.22 9 -0.03 0.23 9 0.03 0.27 7 0.33 0.28 7 0.23 0.29 6 0.19 0.32 5 0.20 0.37 4 0.08 0.31 4 0.60 0.36 3 MALTA MLT 1.31 0.25 7 1.22 0.25 7 1.38 0.28 6 1.33 0.29 6 1.51 0.31 5 1.52 0.38 3 1.40 0.38 3 1.36 0.31 3 1.16 0.45 2 MARSHALL ISLANDS MHL 1.11 0.62 1 1.11 0.62 1 1.14 0.59 1 1.15 0.60 1 1.23 0.55 1 .. .. .. .. .. .. .. .. .. .. .. .. MARTINIQUE MTQ 1.20 0.37 2 1.17 0.38 2 1.27 0.39 2 1.38 0.40 2 0.80 0.47 1 0.47 0.49 1 0.43 0.52 1 0.19 0.55 1 .. .. .. MAURITANIA MRT -0.33 0.24 7 -0.13 0.25 7 -0.46 0.31 4 -0.13 0.31 4 -0.14 0.34 3 0.18 0.42 2 0.10 0.42 2 0.22 0.41 2 0.56 0.49 1 MAURITIUS MUS 0.76 0.24 7 0.67 0.24 7 1.01 0.31 5 0.98 0.31 5 0.93 0.28 5 0.93 0.28 5 0.73 0.40 3 1.00 0.39 3 0.70 0.34 3 MEXICO MEX -0.57 0.20 11 -0.49 0.20 11 -0.25 0.21 10 -0.06 0.22 10 -0.14 0.23 9 0.02 0.22 9 -0.09 0.22 7 -0.48 0.23 6 -0.82 0.29 5 MICRONESIA FSM 1.11 0.33 3 1.14 0.34 3 1.09 0.34 3 0.98 0.35 3 0.65 0.55 1 .. .. .. .. .. .. .. .. .. .. .. .. MOLDOVA MDA -0.22 0.23 8 -0.47 0.23 8 -0.59 0.25 7 -0.45 0.26 6 -0.21 0.25 6 -0.14 0.26 5 -0.21 0.26 5 0.15 0.25 5 0.05 0.34 3 MONACO MCO 1.04 0.45 2 1.05 0.46 2 1.05 0.43 2 1.08 0.44 2 1.23 0.55 1 .. .. .. .. .. .. .. .. .. .. .. .. MONGOLIA MNG 0.66 0.25 7 0.74 0.26 7 0.93 0.28 6 0.77 0.30 5 0.94 0.32 4 1.06 0.38 3 0.80 0.38 3 0.39 0.31 3 0.59 0.45 2 MONTENEGRO MNP -0.27 0.31 5 -0.38 0.36 4 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. MOROCCO MAR -0.52 0.21 10 -0.32 0.21 10 -0.48 0.23 9 -0.43 0.23 9 -0.33 0.23 8 -0.32 0.23 8 -0.21 0.26 6 0.11 0.25 6 -0.61 0.26 6 MOZAMBIQUE MOZ 0.37 0.21 10 0.52 0.21 10 0.11 0.23 9 -0.10 0.23 9 0.10 0.23 8 0.29 0.27 6 -0.01 0.31 5 0.00 0.27 5 -0.83 0.33 4 MYANMAR MMR -1.22 0.23 7 -0.82 0.24 7 -0.88 0.24 7 -0.94 0.24 7 -1.25 0.25 6 -1.33 0.25 6 -1.58 0.26 5 -1.28 0.25 5 -1.25 0.33 4 NAMIBIA NAM 0.90 0.22 9 0.81 0.23 9 0.58 0.23 9 0.56 0.23 9 0.35 0.23 8 0.23 0.23 8 -0.30 0.31 5 0.52 0.27 5 0.53 0.33 4 NAURU NRU 1.11 0.62 1 1.11 0.62 1 1.14 0.59 1 1.15 0.60 1 1.23 0.55 1 .. .. .. .. .. .. .. .. .. .. .. .. NEPAL NPL -2.13 0.26 6 -2.09 0.27 6 -2.35 0.25 6 -2.07 0.27 5 -1.83 0.34 3 -1.72 0.37 3 -1.18 0.42 2 -0.73 0.41 2 -0.55 0.49 1 NETHERLANDS NLD 0.81 0.22 10 0.77 0.22 10 0.85 0.21 10 0.95 0.22 10 1.13 0.23 9 1.23 0.22 9 1.41 0.22 7 1.43 0.23 6 1.23 0.29 5 NETHERLANDS ANTILLES ANT 1.20 0.37 2 1.17 0.38 2 0.95 0.39 2 0.69 0.50 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. NEW CALEDONIA NCL -0.03 0.40 2 -0.20 0.43 2 -0.18 0.55 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. -0.85 0.79 1 NEW ZEALAND NZL 1.24 0.21 10 1.27 0.21 10 1.23 0.22 9 1.44 0.23 9 1.24 0.24 8 1.24 0.24 7 1.15 0.24 6 1.28 0.25 5 1.09 0.33 4 NICARAGUA NIC -0.26 0.23 8 -0.41 0.23 8 -0.20 0.25 7 -0.17 0.26 7 -0.24 0.27 6 -0.09 0.27 6 -0.08 0.31 4 -0.57 0.28 4 -0.68 0.4 3 NIGER NER -0.55 0.23 8 -0.33 0.24 8 -0.39 0.29 6 -0.59 0.28 6 -0.14 0.32 4 -0.27 0.38 3 -0.15 0.38 3 -0.48 0.31 3 -0.03 0.45 2 NIGERIA NGA -2.07 0.21 10 -2.05 0.21 10 -1.73 0.23 9 -1.81 0.23 9 -1.65 0.23 8 -1.71 0.23 8 -1.58 0.26 6 -0.84 0.25 6 -1.63 0.26 6 83 TABLE C2: Political Stability & Absence of Violence/Terrorism (cont.) 2007 2006 2005 2004 2003 2002 2000 1998 1996 Country Code Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. NORWAY NOR 1.23 0.20 11 1.17 0.20 11 1.27 0.21 10 1.35 0.22 10 1.41 0.23 9 1.47 0.23 8 1.31 0.22 7 1.29 0.23 6 1.22 0.29 5 OMAN OMN 0.76 0.23 8 0.73 0.24 7 0.73 0.24 7 0.79 0.24 7 0.86 0.25 6 0.85 0.25 6 0.86 0.26 5 0.69 0.25 5 0.47 0.33 4 PAKISTAN PAK -2.44 0.21 10 -1.98 0.21 10 -1.71 0.22 9 -1.72 0.22 9 -1.70 0.24 8 -1.58 0.23 7 -1.01 0.24 6 -1.33 0.23 6 -1.45 0.29 5 PALAU PCI 1.11 0.62 1 1.11 0.62 1 1.14 0.59 1 1.15 0.60 1 1.23 0.55 1 .. .. .. .. .. .. .. .. .. .. .. .. PANAMA PAN 0.16 0.23 8 0.12 0.23 8 0.04 0.23 8 0.22 0.23 8 0.20 0.25 7 0.36 0.24 7 0.26 0.26 5 0.05 0.25 5 0.21 0.33 4 PAPUA NEW GUINEA PNG -0.76 0.23 7 -0.78 0.24 7 -0.78 0.24 7 -0.64 0.24 7 -0.72 0.25 6 -0.68 0.26 5 -0.45 0.26 5 -0.26 0.28 4 -1.36 0.40 3 PARAGUAY PRY -0.48 0.25 7 -0.60 0.25 7 -0.52 0.25 7 -0.37 0.26 7 -0.74 0.27 6 -1.07 0.27 6 -1.07 0.31 4 -1.03 0.28 4 -0.26 0.40 3 PERU PER -0.83 0.21 10 -0.93 0.21 10 -1.01 0.22 9 -0.87 0.22 9 -0.98 0.24 8 -0.83 0.23 8 -0.93 0.24 6 -0.78 0.23 6 -1.28 0.29 5 PHILIPPINES PHL -1.38 0.20 11 -1.33 0.20 11 -1.07 0.21 10 -1.24 0.22 10 -1.23 0.23 9 -0.70 0.22 9 -0.76 0.22 7 -0.15 0.23 6 -0.49 0.29 5 POLAND POL 0.58 0.20 11 0.31 0.20 11 0.32 0.21 10 0.20 0.22 10 0.64 0.23 9 0.66 0.22 9 0.41 0.22 7 0.60 0.23 6 0.55 0.29 5 PORTUGAL PRT 0.78 0.20 11 0.90 0.20 11 0.95 0.21 10 0.94 0.22 10 1.17 0.23 9 1.35 0.23 8 1.19 0.22 7 1.22 0.23 6 1.06 0.29 5 PUERTO RICO PRI 0.79 0.28 5 0.74 0.30 4 0.78 0.29 4 0.89 0.29 4 0.71 0.33 3 0.59 0.36 2 0.59 0.35 2 0.51 0.40 2 0.60 0.52 1 QATAR QAT 0.81 0.23 8 0.83 0.23 8 0.74 0.23 8 0.91 0.24 7 1.00 0.25 6 0.67 0.26 5 1.03 0.26 5 0.97 0.25 5 0.33 0.33 4 REUNION REU 0.72 0.45 1 0.74 0.45 1 0.50 0.49 1 0.45 0.50 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ROMANIA ROM 0.19 0.20 11 0.15 0.20 11 0.10 0.21 10 0.07 0.23 9 0.26 0.24 8 0.32 0.24 7 0.02 0.26 5 0.19 0.25 5 0.39 0.33 4 RUSSIA RUS -0.75 0.20 11 -0.80 0.20 11 -0.98 0.21 10 -1.04 0.22 10 -0.85 0.23 9 -0.60 0.22 9 -0.69 0.22 7 -0.81 0.23 6 -1.02 0.29 5 RWANDA RWA -0.19 0.28 5 -0.53 0.28 5 -0.66 0.39 3 -0.87 0.38 3 -1.15 0.38 2 -1.80 0.42 2 -1.81 0.42 2 -2.15 0.41 2 -2.00 0.49 1 SAMOA SAM 1.11 0.33 3 1.14 0.34 3 1.15 0.34 3 1.15 0.35 3 1.28 0.38 2 1.03 0.42 2 1.15 0.42 2 1.26 0.41 2 1.05 0.49 1 SAN MARINO SMR 1.11 0.62 1 1.11 0.62 1 1.14 0.59 1 1.15 0.60 1 1.23 0.55 1 .. .. .. .. .. .. .. .. .. .. .. .. SAO TOME AND PRINCIPE STP 0.28 0.32 3 0.37 0.31 3 0.70 0.40 2 0.68 0.41 2 0.25 0.38 2 0.48 0.42 2 0.99 0.42 2 0.99 0.41 2 1.05 0.49 1 SAUDI ARABIA SAU -0.59 0.21 10 -0.65 0.21 9 -0.71 0.22 8 -1.08 0.23 8 -0.42 0.24 7 -0.47 0.23 7 0.00 0.24 6 -0.14 0.23 6 -0.52 0.29 5 SENEGAL SEN -0.18 0.21 10 -0.27 0.22 9 -0.12 0.26 7 -0.10 0.25 7 -0.41 0.26 7 -0.42 0.27 6 -0.51 0.31 5 -0.94 0.27 5 -0.26 0.33 4 SERBIA YUG -0.77 0.23 8 -0.68 0.25 7 -0.87 0.23 8 -0.86 0.23 8 -0.83 0.25 7 -0.76 0.25 6 -1.70 0.31 4 -1.96 0.28 4 -1.11 0.40 3 SEYCHELLES SYC 1.01 0.27 5 1.08 0.27 5 1.16 0.28 5 0.74 0.27 5 0.60 0.34 3 0.83 0.42 2 1.15 0.42 2 0.99 0.41 2 1.05 0.49 1 SIERRA LEONE SLE -0.30 0.27 5 -0.46 0.28 5 -0.41 0.32 4 -0.38 0.33 4 -1.11 0.35 3 -0.93 0.38 3 -1.90 0.38 3 -2.18 0.31 3 -2.28 0.45 2 SINGAPORE SGP 1.17 0.20 11 1.29 0.20 11 1.15 0.21 10 1.11 0.22 10 0.98 0.23 9 1.32 0.22 9 1.20 0.22 7 1.06 0.23 6 1.08 0.29 5 SLOVAKIA SVK 0.94 0.22 9 0.77 0.23 9 0.81 0.22 9 0.63 0.23 9 0.93 0.24 8 0.87 0.23 8 0.55 0.24 6 1.09 0.25 5 0.68 0.33 4 SLOVENIA SVN 1.01 0.22 9 1.06 0.23 9 0.99 0.22 9 1.07 0.23 9 1.14 0.24 8 1.28 0.23 8 0.92 0.24 6 1.07 0.25 5 1.03 0.34 3 SOLOMON ISLANDS SLB 0.38 0.39 2 0.20 0.39 2 0.25 0.40 2 0.07 0.41 2 0.08 0.55 1 -0.56 0.63 1 -0.88 0.60 1 1.05 0.54 1 1.05 0.49 1 SOMALIA SOM -3.01 0.31 4 -2.75 0.32 4 -2.64 0.32 4 -2.60 0.38 3 -2.32 0.35 3 -2.31 0.38 3 -2.48 0.38 3 -2.38 0.31 3 -2.30 0.45 2 SOUTH AFRICA ZAF 0.18 0.20 12 0.05 0.20 12 -0.06 0.21 11 -0.22 0.21 11 -0.35 0.22 10 -0.42 0.21 10 -0.40 0.22 8 -0.83 0.23 7 -1.24 0.26 6 SPAIN ESP 0.04 0.20 11 0.14 0.20 11 0.42 0.21 10 0.30 0.22 10 0.38 0.23 9 0.56 0.22 9 0.81 0.22 7 0.46 0.23 6 0.34 0.29 5 SRI LANKA LKA -1.96 0.21 9 -1.62 0.22 9 -1.35 0.23 8 -1.14 0.23 8 -0.95 0.25 7 -0.95 0.24 7 -1.58 0.26 5 -1.38 0.25 5 -2.10 0.33 4 ST. KITTS AND NEVIS KNA 0.97 0.33 3 1.28 0.34 3 1.36 0.34 3 1.47 0.35 3 1.23 0.55 1 .. .. .. .. .. .. .. .. .. .. .. .. ST. LUCIA LCA 0.63 0.33 3 0.92 0.34 3 1.04 0.34 3 1.27 0.35 3 1.23 0.55 1 0.29 0.63 1 1.08 0.60 1 0.26 0.54 1 1.05 0.49 1 ST. VINCENT AND THE GRENADINES VCT 0.78 0.33 3 1.08 0.34 3 1.25 0.34 3 1.22 0.35 3 0.94 0.55 1 0.29 0.63 1 1.08 0.60 1 1.05 0.54 1 1.05 0.49 1 SUDAN SDN -2.30 0.23 7 -2.13 0.24 7 -2.12 0.24 7 -1.85 0.26 6 -2.13 0.25 6 -2.04 0.25 6 -2.39 0.26 5 -2.06 0.28 4 -2.58 0.40 3 SURINAME SUR 0.23 0.28 6 0.12 0.29 6 0.36 0.33 4 0.42 0.33 4 0.52 0.32 4 0.42 0.38 3 0.25 0.38 3 0.33 0.31 3 0.52 0.45 2 SWAZILAND SWZ 0.10 0.26 5 -0.12 0.26 5 -0.12 0.30 4 0.11 0.30 4 0.00 0.30 4 0.22 0.33 3 -0.09 0.42 2 -0.07 0.41 2 0.01 0.49 1 SWEDEN SWE 1.24 0.20 11 1.15 0.20 11 1.20 0.21 10 1.31 0.22 10 1.46 0.23 9 1.31 0.23 8 1.28 0.22 7 1.33 0.23 6 1.24 0.29 5 SWITZERLAND CHE 1.39 0.22 10 1.40 0.22 10 1.34 0.21 10 1.33 0.22 10 1.46 0.23 9 1.50 0.23 8 1.50 0.22 7 1.45 0.23 6 1.37 0.29 5 SYRIA SYR -0.61 0.21 9 -0.67 0.22 8 -0.96 0.24 7 -0.64 0.24 7 -0.32 0.25 6 -0.26 0.25 6 -0.65 0.26 5 -0.30 0.25 5 -0.82 0.33 4 TAIWAN TWN 0.47 0.20 11 0.57 0.20 11 0.60 0.21 10 0.59 0.22 10 0.75 0.23 9 0.76 0.22 9 0.40 0.22 7 0.83 0.23 6 0.99 0.29 5 TAJIKISTAN TJK -0.87 0.24 7 -1.35 0.24 7 -1.33 0.26 6 -1.41 0.27 5 -1.41 0.30 4 -1.41 0.30 4 -1.86 0.32 3 -2.26 0.34 3 -2.59 0.38 2 TANZANIA TZA -0.07 0.22 9 -0.10 0.23 9 -0.38 0.23 9 -0.44 0.23 9 -0.48 0.23 8 -0.17 0.24 7 -0.46 0.26 6 -0.09 0.25 6 -0.31 0.29 5 THAILAND THA -1.07 0.20 11 -0.93 0.20 11 -0.65 0.21 10 -0.46 0.22 10 -0.06 0.23 9 0.33 0.22 9 0.38 0.22 7 0.37 0.23 6 0.05 0.29 5 TIMOR-LESTE TMP -1.09 0.32 4 -1.17 0.33 4 -0.66 0.32 4 -0.32 0.35 3 -0.23 0.38 2 -0.59 0.42 2 0.30 0.60 1 .. .. .. .. .. .. TOGO TGO -0.52 0.23 7 -0.70 0.24 7 -1.50 0.30 5 -0.43 0.30 5 -0.40 0.32 4 0.02 0.38 3 -0.17 0.38 3 -0.71 0.31 3 -0.54 0.45 2 TONGA TON 0.38 0.33 3 0.53 0.34 3 0.77 0.34 3 0.83 0.35 3 0.65 0.55 1 .. .. .. .. .. .. .. .. .. .. .. .. TRINIDAD AND TOBAGO TTO 0.03 0.23 8 -0.12 0.23 8 -0.10 0.23 8 -0.03 0.26 7 -0.15 0.27 6 -0.16 0.29 5 0.08 0.31 4 0.44 0.28 4 0.46 0.40 3 TUNISIA TUN 0.10 0.21 10 0.33 0.21 10 0.07 0.23 9 0.10 0.23 9 0.16 0.23 8 0.10 0.23 8 0.25 0.26 6 0.28 0.25 6 0.16 0.29 5 TURKEY TUR -0.78 0.20 11 -0.62 0.20 11 -0.57 0.21 10 -0.87 0.22 10 -0.80 0.23 9 -1.01 0.22 9 -0.92 0.22 7 -1.01 0.23 6 -1.48 0.29 5 TURKMENISTAN TKM -0.08 0.24 6 -0.30 0.25 6 -0.23 0.25 6 -0.68 0.27 5 -0.60 0.30 4 -0.41 0.30 4 -0.01 0.32 3 0.12 0.34 3 0.21 0.38 2 TUVALU TUV 1.36 0.39 2 1.39 0.39 2 1.41 0.40 2 1.30 0.41 2 1.23 0.55 1 .. .. .. .. .. .. .. .. .. .. .. .. UGANDA UGA -1.15 0.21 10 -1.29 0.21 10 -1.38 0.23 9 -1.42 0.23 9 -1.53 0.23 8 -1.66 0.24 7 -1.53 0.26 6 -1.27 0.25 6 -1.31 0.29 5 UKRAINE UKR 0.16 0.20 11 -0.06 0.21 10 -0.37 0.22 9 -0.39 0.22 9 -0.31 0.24 8 -0.20 0.23 8 -0.37 0.24 6 -0.22 0.23 6 -0.23 0.30 4 UNITED ARAB EMIRATES ARE 0.76 0.23 8 0.72 0.23 8 0.59 0.23 8 0.61 0.23 8 0.82 0.25 6 0.80 0.25 6 0.80 0.26 5 0.73 0.25 5 0.74 0.33 4 UNITED KINGDOM GBR 0.56 0.20 11 0.58 0.20 11 0.33 0.21 10 0.40 0.22 10 0.57 0.23 9 0.73 0.22 9 1.06 0.22 7 0.87 0.23 6 0.93 0.29 5 UNITED STATES USA 0.30 0.20 11 0.43 0.20 11 0.04 0.21 10 0.12 0.22 10 0.29 0.23 9 0.30 0.22 9 1.18 0.22 7 0.96 0.23 6 0.94 0.29 5 URUGUAY URY 0.90 0.23 8 0.81 0.23 8 0.69 0.23 8 0.50 0.23 8 0.62 0.25 7 0.67 0.24 7 0.89 0.26 5 0.53 0.25 5 0.68 0.33 4 UZBEKISTAN UZB -1.42 0.22 8 -1.70 0.23 7 -1.95 0.25 6 -1.59 0.25 6 -1.50 0.26 5 -1.30 0.26 5 -1.30 0.31 3 -0.48 0.33 3 -0.19 0.34 3 VANUATU VUT 1.36 0.39 2 1.39 0.39 2 1.41 0.40 2 0.73 0.41 2 0.94 0.55 1 1.14 0.63 1 1.08 0.60 1 1.05 0.54 1 1.05 0.49 1 VENEZUELA VEN -1.23 0.20 11 -1.19 0.20 11 -1.19 0.21 10 -1.22 0.22 10 -1.28 0.23 9 -1.33 0.22 9 -0.51 0.22 7 -0.38 0.23 6 -0.83 0.29 5 VIETNAM VNM 0.31 0.21 10 0.42 0.21 10 0.36 0.22 9 0.19 0.22 9 0.16 0.24 8 0.31 0.23 8 0.22 0.24 6 0.34 0.23 6 0.31 0.29 5 VIRGIN ISLANDS (U.S.) VIR 0.67 0.37 2 0.60 0.38 2 0.62 0.39 2 0.84 0.50 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. WEST BANK GAZA WBG -2.07 0.34 3 -1.98 0.35 3 -1.68 0.36 3 -1.68 0.35 3 -1.69 0.34 3 -1.97 0.37 3 -1.74 0.42 2 -1.69 0.41 2 .. .. .. YEMEN YEM -1.48 0.22 8 -1.33 0.22 8 -1.42 0.26 6 -1.74 0.26 6 -1.48 0.28 5 -1.47 0.28 5 -1.34 0.31 4 -1.48 0.28 4 -1.15 0.40 3 ZAMBIA ZMB 0.24 0.22 9 0.31 0.23 9 0.00 0.23 8 0.08 0.23 9 -0.11 0.23 8 -0.33 0.24 7 -0.39 0.26 6 -0.09 0.25 6 -0.51 0.29 5 ZIMBABWE ZWE -1.30 0.21 10 -1.06 0.21 10 -1.55 0.23 9 -1.55 0.23 9 -1.61 0.23 8 -1.76 0.23 8 -1.44 0.26 6 -0.86 0.25 6 -0.60 0.29 5 84 TABLE C3: Government Effectiveness 2007 2006 2005 2004 2003 2002 2000 1998 1996 Country Code Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. AFGHANISTAN AFG -1.33 0.26 7 -1.37 0.22 8 -1.24 0.20 6 -0.97 0.21 6 -1.26 0.24 4 -1.57 0.24 4 -2.11 0.27 2 -2.27 0.19 1 .. .. .. ALBANIA ALB -0.38 0.20 11 -0.42 0.18 11 -0.62 0.18 9 -0.36 0.22 8 -0.56 0.20 7 -0.60 0.20 7 -0.82 0.22 5 -0.73 0.17 4 -0.11 0.36 3 ALGERIA DZA -0.52 0.17 12 -0.42 0.16 12 -0.32 0.16 11 -0.46 0.16 11 -0.51 0.16 10 -0.63 0.17 9 -0.95 0.19 6 -1.16 0.16 6 -0.39 0.27 4 AMERICANSAMOA ASM 0.48 0.39 1 0.21 0.37 1 0.21 0.28 1 -0.20 0.39 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ANDORRA ADO 1.59 0.38 2 1.42 0.36 2 1.29 0.28 2 1.34 0.37 2 1.27 0.32 2 1.36 0.30 2 1.45 0.32 1 1.48 0.19 1 .. .. .. ANGOLA AGO -1.16 0.19 11 -1.25 0.17 12 -1.01 0.17 10 -1.18 0.16 11 -1.11 0.16 10 -1.16 0.17 9 -1.39 0.19 6 -1.13 0.16 6 -1.44 0.27 4 ANGUILLA AIA 1.56 0.39 1 1.55 0.37 1 1.56 0.28 1 0.97 0.39 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ANTIGUA AND BARBUDA ATG 0.45 0.38 2 0.40 0.36 2 0.46 0.27 3 0.38 0.35 3 0.49 0.32 2 0.52 0.30 2 0.64 0.32 1 0.68 0.19 1 .. .. .. ARGENTINA ARG -0.14 0.17 14 -0.09 0.16 14 -0.23 0.15 13 -0.18 0.16 13 -0.26 0.15 12 -0.43 0.16 12 0.10 0.17 8 0.19 0.15 8 0.42 0.23 8 ARMENIA ARM -0.31 0.17 13 -0.22 0.16 13 -0.05 0.18 10 -0.13 0.21 9 -0.22 0.20 8 -0.21 0.20 8 -0.60 0.22 5 -0.46 0.17 4 -0.62 0.62 1 ARUBA ABW 1.29 0.39 1 1.29 0.37 1 1.29 0.28 1 1.19 0.39 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. AUSTRALIA AUS 1.96 0.19 10 1.90 0.18 10 1.89 0.16 9 2.06 0.18 9 1.99 0.17 9 1.82 0.17 8 1.81 0.18 7 1.87 0.15 7 1.43 0.25 6 AUSTRIA AUT 1.73 0.19 10 1.66 0.18 10 1.62 0.16 9 1.78 0.18 9 1.93 0.17 9 1.97 0.17 8 1.94 0.18 7 1.76 0.15 7 2.06 0.25 6 AZERBAIJAN AZE -0.65 0.17 13 -0.69 0.16 13 -0.66 0.15 12 -0.88 0.18 11 -0.76 0.17 10 -0.86 0.17 10 -0.84 0.17 7 -0.89 0.16 5 -0.91 0.28 3 BAHAMAS BHS 1.16 0.31 3 1.12 0.30 3 1.28 0.25 3 1.13 0.32 3 1.24 0.28 3 1.29 0.26 3 1.33 0.28 2 1.47 0.18 2 0.42 0.68 1 BAHRAIN BHR 0.41 0.20 8 0.30 0.19 8 0.42 0.17 8 0.64 0.19 8 0.47 0.19 7 0.65 0.17 8 0.71 0.21 4 0.81 0.16 4 0.43 0.31 3 BANGLADESH BGD -0.81 0.16 13 -0.78 0.16 13 -0.89 0.15 11 -0.82 0.17 11 -0.70 0.16 10 -0.72 0.16 10 -0.52 0.16 7 -0.60 0.16 5 -0.64 0.27 4 BARBADOS BRB 1.19 0.28 4 1.19 0.26 4 1.18 0.25 4 1.05 0.32 4 1.24 0.30 3 1.35 0.30 2 1.45 0.32 1 1.48 0.19 1 .. .. .. BELARUS BLR -1.26 0.21 10 -1.22 0.20 10 -1.16 0.20 8 -1.25 0.22 8 -1.07 0.20 8 -1.08 0.20 7 -0.81 0.22 5 -0.51 0.17 4 -1.42 0.40 2 BELGIUM BEL 1.59 0.19 10 1.76 0.18 10 1.66 0.16 9 1.79 0.18 9 1.90 0.17 9 1.98 0.17 9 1.73 0.18 7 1.71 0.15 7 2.02 0.25 6 BELIZE BLZ -0.21 0.24 7 -0.23 0.24 6 0.08 0.24 5 0.07 0.28 5 0.09 0.26 4 0.03 0.26 3 0.04 0.27 2 0.31 0.18 2 -0.38 0.48 1 BENIN BEN -0.57 0.17 12 -0.50 0.16 12 -0.63 0.18 9 -0.47 0.22 7 -0.34 0.22 6 -0.50 0.23 5 -0.21 0.25 3 -0.34 0.18 3 0.01 0.48 1 BERMUDA BMU 1.02 0.39 1 1.02 0.37 1 1.02 0.28 1 1.07 0.39 1 1.07 0.33 1 1.14 0.30 1 1.18 0.32 1 1.22 0.19 1 .. .. .. BHUTAN BTN 0.01 0.22 6 0.25 0.22 6 0.34 0.21 6 0.22 0.26 6 0.50 0.24 5 0.44 0.24 4 0.81 0.22 3 0.66 0.18 2 0.20 0.48 1 BOLIVIA BOL -0.83 0.18 13 -0.71 0.17 13 -0.80 0.16 11 -0.53 0.17 11 -0.36 0.16 10 -0.31 0.17 10 -0.23 0.18 6 -0.04 0.16 5 0.07 0.27 5 BOSNIA-HERZEGOVINA BIH -0.80 0.20 11 -0.61 0.19 11 -0.69 0.17 10 -0.68 0.18 10 -0.81 0.18 8 -0.98 0.18 8 -0.83 0.22 4 -1.17 0.17 3 -1.32 0.37 1 BOTSWANA BWA 0.70 0.16 14 0.62 0.15 14 0.83 0.15 12 0.79 0.15 12 0.71 0.15 11 0.69 0.16 11 0.63 0.19 6 0.65 0.16 6 0.24 0.27 4 BRAZIL BRA -0.12 0.16 15 -0.10 0.15 15 -0.08 0.15 13 0.03 0.16 13 0.11 0.15 12 -0.11 0.16 12 0.03 0.17 8 -0.12 0.15 8 -0.30 0.23 8 BRUNEI BRN 0.84 0.31 3 0.76 0.30 3 0.57 0.25 3 0.07 0.32 3 0.68 0.28 3 0.83 0.26 3 0.91 0.28 2 0.92 0.18 2 1.07 0.68 1 BULGARIA BGR 0.10 0.18 13 0.12 0.17 13 0.23 0.16 10 0.10 0.18 10 0.02 0.16 10 0.12 0.17 10 0.05 0.18 7 -0.08 0.16 5 -0.94 0.27 4 BURKINA FASO BFA -0.84 0.17 13 -0.80 0.16 13 -0.60 0.20 8 -0.55 0.21 8 -0.63 0.21 7 -0.72 0.22 6 -0.61 0.23 4 -0.83 0.17 4 -0.68 0.42 2 BURUNDI BDI -1.34 0.19 11 -1.26 0.17 11 -1.34 0.20 7 -1.35 0.22 7 -1.34 0.22 6 -1.57 0.23 5 -1.44 0.25 3 -1.73 0.18 3 -0.97 0.48 1 CAMBODIA KHM -0.82 0.18 11 -0.97 0.17 11 -0.92 0.16 9 -0.90 0.20 8 -0.77 0.19 7 -0.75 0.19 7 -0.84 0.19 4 -0.83 0.17 3 -1.12 0.30 2 CAMEROON CMR -0.87 0.17 13 -0.84 0.16 13 -0.93 0.16 11 -0.79 0.17 10 -0.64 0.16 10 -0.83 0.17 9 -0.75 0.19 6 -1.08 0.16 6 -1.17 0.27 4 CANADA CAN 1.92 0.18 11 2.09 0.17 11 1.94 0.16 9 2.05 0.18 9 2.09 0.17 9 2.07 0.17 9 1.92 0.18 7 1.84 0.15 7 2.07 0.25 6 CAPE VERDE CPV 0.36 0.21 7 0.18 0.21 7 -0.09 0.22 6 0.12 0.22 6 0.03 0.21 5 0.00 0.22 5 0.19 0.38 2 0.34 0.46 2 -0.12 0.48 1 CAYMAN ISLANDS CYM 1.29 0.39 1 1.29 0.37 1 1.29 0.28 1 1.17 0.39 1 1.33 0.33 1 1.97 0.30 1 1.99 0.32 1 2.02 0.19 1 .. .. .. CENTRALAFRICANREPUBLICCAF -1.38 0.23 7 -1.43 0.23 6 -1.57 0.20 7 -1.58 0.22 7 -1.51 0.22 6 -1.60 0.23 5 -1.41 0.25 3 -1.45 0.18 3 -0.91 0.48 1 CHAD TCD -1.45 0.18 11 -1.32 0.17 11 -1.20 0.18 8 -1.02 0.20 8 -0.83 0.20 7 -0.87 0.23 6 -0.62 0.25 3 -0.61 0.18 3 -0.65 0.48 1 CHILE CHL 1.22 0.17 14 1.13 0.16 14 1.27 0.15 13 1.34 0.16 13 1.24 0.15 12 1.24 0.16 12 1.15 0.17 8 1.35 0.15 8 0.96 0.23 8 CHINA CHN 0.15 0.16 14 0.04 0.16 13 -0.08 0.15 12 0.00 0.16 12 -0.06 0.15 11 -0.03 0.16 11 -0.06 0.17 8 -0.28 0.15 8 0.14 0.23 7 COLOMBIA COL 0.03 0.16 15 0.01 0.15 15 -0.09 0.15 13 -0.10 0.16 13 -0.20 0.15 12 -0.43 0.16 12 -0.32 0.17 8 -0.41 0.15 8 0.25 0.23 8 COMOROS COM -1.80 0.26 5 -1.71 0.25 5 -1.66 0.23 5 -1.56 0.25 5 -1.41 0.26 4 -0.97 0.25 4 -1.33 0.25 3 -1.76 0.18 3 -0.71 0.48 1 CONGO COG -1.34 0.19 10 -1.29 0.19 9 -1.35 0.18 9 -1.14 0.22 7 -1.30 0.22 6 -1.39 0.23 6 -1.52 0.23 4 -1.17 0.17 4 -1.22 0.42 2 CONGO, DEM. REP. ZAR -1.68 0.20 10 -1.68 0.19 9 -1.67 0.17 10 -1.48 0.17 10 -1.45 0.19 8 -1.77 0.20 8 -1.76 0.21 5 -1.86 0.16 5 -1.70 0.36 3 COOK ISLANDS COK -0.35 0.35 2 -0.04 0.37 2 0.51 0.42 2 -0.15 0.56 1 -0.24 0.51 2 -0.27 0.47 2 0.13 0.36 1 .. .. .. .. .. .. COSTARICA CRI 0.39 0.19 12 0.23 0.17 12 0.30 0.16 11 0.43 0.17 11 0.45 0.16 10 0.47 0.17 10 0.49 0.18 6 0.71 0.16 5 -0.01 0.25 6 COTE D'IVOIRE CIV -1.37 0.18 10 -1.37 0.18 10 -1.39 0.17 9 -1.32 0.17 10 -0.92 0.17 9 -0.97 0.17 9 -0.79 0.19 6 -0.36 0.16 6 0.08 0.27 4 CROATIA HRV 0.54 0.19 12 0.54 0.18 12 0.52 0.16 11 0.51 0.17 11 0.37 0.16 10 0.41 0.17 10 0.36 0.19 6 0.13 0.16 5 -0.06 0.28 3 CUBA CUB -0.61 0.21 9 -0.64 0.20 9 -0.84 0.19 8 -0.65 0.19 8 -0.59 0.19 7 -0.61 0.19 7 -0.48 0.21 4 -0.76 0.16 4 -0.42 0.31 3 CYPRUS CYP 1.37 0.23 7 1.22 0.21 7 1.16 0.18 6 1.12 0.20 6 1.22 0.21 5 1.31 0.20 5 1.16 0.21 4 1.21 0.16 4 1.35 0.31 3 CZECHREPUBLIC CZE 0.99 0.17 14 1.07 0.16 13 1.01 0.16 11 0.75 0.16 12 0.77 0.15 12 0.91 0.16 12 0.76 0.17 9 0.71 0.15 8 0.81 0.23 7 DENMARK DNK 2.21 0.19 10 2.32 0.18 10 2.14 0.16 9 2.26 0.18 9 2.21 0.17 9 2.15 0.17 8 1.97 0.18 7 1.92 0.15 7 2.16 0.25 6 DJIBOUTI DJI -0.98 0.26 5 -0.99 0.25 5 -0.86 0.23 5 -0.63 0.25 5 -0.74 0.26 4 -0.88 0.25 4 -1.09 0.25 3 -1.02 0.18 3 -0.98 0.48 1 DOMINICA DMA 0.71 0.32 3 0.73 0.32 3 0.53 0.25 4 0.35 0.30 4 0.25 0.27 3 0.30 0.26 3 0.46 0.27 2 0.53 0.18 2 -0.91 0.48 1 DOMINICANREPUBLIC DOM -0.46 0.18 13 -0.39 0.17 13 -0.42 0.16 11 -0.57 0.17 11 -0.40 0.16 9 -0.31 0.17 9 -0.17 0.19 5 -0.20 0.17 4 -0.78 0.28 3 ECUADOR ECU -1.04 0.19 12 -1.07 0.17 12 -1.01 0.16 11 -0.88 0.16 12 -0.75 0.16 11 -0.82 0.16 11 -0.83 0.17 7 -0.49 0.15 6 -0.90 0.25 6 EGYPT EGY -0.44 0.16 14 -0.51 0.15 14 -0.40 0.15 12 -0.26 0.16 12 -0.33 0.15 11 -0.43 0.16 11 -0.25 0.17 8 -0.52 0.15 8 -0.03 0.24 6 ELSALVADOR SLV -0.23 0.19 11 -0.27 0.18 11 -0.28 0.17 10 -0.24 0.18 10 -0.21 0.17 9 -0.42 0.17 9 -0.51 0.20 5 -0.57 0.17 4 -0.25 0.27 5 EQUATORIALGUINEA GNQ -1.37 0.22 7 -1.34 0.21 7 -1.36 0.20 6 -1.40 0.20 7 -1.18 0.20 6 -1.31 0.21 6 -1.46 0.22 4 -1.17 0.17 4 -1.46 0.30 2 ERITREA ERI -1.30 0.21 7 -1.28 0.20 8 -0.95 0.20 7 -1.09 0.22 7 -0.90 0.22 6 -0.79 0.23 5 -0.95 0.25 3 -1.06 0.18 3 -0.38 0.48 1 ESTONIA EST 1.19 0.18 13 1.22 0.18 12 1.11 0.16 11 1.09 0.17 11 1.14 0.16 11 0.87 0.16 11 0.93 0.18 8 0.74 0.16 5 0.56 0.28 3 ETHIOPIA ETH -0.45 0.17 12 -0.62 0.16 12 -0.89 0.16 10 -0.69 0.17 10 -0.85 0.17 9 -0.92 0.18 8 -0.96 0.20 5 -1.09 0.16 5 -1.04 0.28 3 FIJI FJI -0.52 0.32 3 -0.11 0.32 3 -0.09 0.26 3 -0.49 0.32 3 -0.11 0.27 3 0.19 0.26 3 -0.41 0.27 2 -0.17 0.18 2 -0.06 0.48 1 FINLAND FIN 1.94 0.19 10 2.14 0.18 10 2.09 0.16 9 2.09 0.18 9 2.21 0.17 9 2.20 0.17 9 2.00 0.18 7 1.90 0.15 7 2.12 0.25 6 FRANCE FRA 1.30 0.18 11 1.33 0.17 11 1.47 0.16 9 1.49 0.18 9 1.60 0.17 9 1.61 0.17 9 1.62 0.18 7 1.34 0.15 7 1.77 0.25 6 FRENCHGUIANA GUF 0.75 0.39 1 0.75 0.37 1 0.75 0.28 1 0.58 0.39 1 0.80 0.33 1 0.86 0.30 1 0.91 0.32 1 0.95 0.19 1 .. .. .. GABON GAB -0.66 0.19 10 -0.69 0.18 10 -0.71 0.18 9 -0.74 0.18 9 -0.51 0.18 8 -0.36 0.18 8 -0.60 0.19 6 -0.36 0.16 5 -0.99 0.28 3 GAMBIA GMB -0.71 0.20 8 -0.78 0.19 8 -0.69 0.19 7 -0.48 0.21 7 -0.48 0.21 6 -0.73 0.23 5 -0.46 0.23 4 -0.59 0.17 4 -0.38 0.42 2 GEORGIA GEO -0.13 0.18 12 -0.23 0.19 11 -0.39 0.18 9 -0.40 0.21 9 -0.65 0.21 7 -0.77 0.21 7 -0.62 0.23 4 -0.64 0.17 3 -0.31 0.40 2 85 TABLE C3: Government Effectiveness (cont.) 2007 2006 2005 2004 2003 2002 2000 1998 1996 Country Code Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. GERMANY DEU 1.68 0.18 11 1.66 0.17 11 1.51 0.16 9 1.43 0.18 9 1.49 0.17 9 1.81 0.17 9 1.93 0.18 7 1.82 0.15 7 2.08 0.25 6 GHANA GHA -0.04 0.17 13 -0.02 0.17 13 -0.10 0.15 12 -0.25 0.15 12 -0.27 0.15 11 -0.22 0.16 10 0.01 0.19 6 -0.21 0.16 6 -0.37 0.27 4 GREECE GRC 0.48 0.18 11 0.58 0.17 11 0.65 0.16 9 0.81 0.18 9 0.82 0.17 9 0.87 0.17 9 0.75 0.18 7 0.89 0.15 7 0.83 0.25 6 GRENADA GRD 0.24 0.32 3 0.12 0.29 4 0.23 0.25 4 0.11 0.30 4 0.19 0.27 3 0.41 0.26 3 0.42 0.27 2 0.59 0.18 2 -0.52 0.48 1 GUAM GUM 0.21 0.39 1 0.21 0.37 1 0.21 0.28 1 0.27 0.39 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. GUATEMALA GTM -0.59 0.18 13 -0.64 0.17 13 -0.70 0.17 10 -0.66 0.18 10 -0.51 0.17 9 -0.52 0.17 9 -0.48 0.20 5 -0.36 0.17 4 -0.48 0.27 5 GUINEA GIN -1.47 0.19 10 -1.39 0.18 10 -1.08 0.20 8 -0.89 0.21 8 -0.88 0.21 7 -0.97 0.21 7 -0.90 0.23 4 -1.11 0.17 4 -1.07 0.42 2 GUINEA-BISSAU GNB -1.21 0.24 6 -1.20 0.23 6 -1.41 0.22 6 -1.54 0.23 6 -1.28 0.23 5 -1.23 0.23 5 -1.10 0.23 4 -1.43 0.17 4 -0.63 0.42 2 GUYANA GUY -0.09 0.20 9 -0.14 0.19 8 -0.53 0.20 7 -0.23 0.25 6 -0.25 0.24 5 -0.28 0.24 4 -0.25 0.24 3 -0.37 0.18 3 -0.14 0.42 2 HAITI HTI -1.33 0.21 8 -1.38 0.21 8 -1.38 0.21 7 -1.69 0.23 7 -1.42 0.19 7 -1.47 0.20 6 -1.35 0.24 3 -0.98 0.18 3 -1.03 0.42 2 HONDURAS HND -0.57 0.19 12 -0.58 0.17 12 -0.63 0.17 10 -0.57 0.18 10 -0.53 0.17 9 -0.60 0.17 9 -0.50 0.20 5 -0.67 0.17 4 -0.82 0.27 5 HONG KONG HKG 1.80 0.19 10 1.80 0.19 10 1.64 0.18 8 1.59 0.19 8 1.43 0.18 8 1.28 0.18 8 1.10 0.19 6 0.92 0.16 6 1.20 0.27 5 HUNGARY HUN 0.70 0.17 14 0.80 0.16 14 0.75 0.15 12 0.82 0.16 12 0.91 0.15 12 1.02 0.16 12 0.93 0.17 9 0.93 0.15 8 0.59 0.23 7 ICELAND ISL 2.07 0.21 7 2.11 0.20 7 2.22 0.20 6 2.23 0.25 6 2.26 0.22 6 2.08 0.22 5 2.05 0.23 4 2.03 0.18 4 1.52 0.45 3 INDIA IND 0.03 0.16 14 -0.06 0.16 14 -0.11 0.15 12 -0.04 0.16 12 -0.04 0.15 11 -0.16 0.16 11 -0.17 0.17 8 -0.17 0.15 8 -0.20 0.23 7 INDONESIA IDN -0.41 0.15 15 -0.44 0.15 15 -0.46 0.14 13 -0.43 0.16 13 -0.55 0.15 12 -0.63 0.15 12 -0.52 0.16 9 -0.83 0.15 8 0.14 0.23 7 IRAN IRN -0.78 0.18 11 -0.72 0.17 12 -0.77 0.17 10 -0.58 0.17 10 -0.48 0.17 9 -0.54 0.17 9 -0.35 0.20 5 -0.54 0.16 5 -0.75 0.28 4 IRAQ IRQ -1.68 0.22 7 -1.85 0.21 7 -1.77 0.19 7 -1.60 0.20 7 -1.60 0.19 7 -1.95 0.19 7 -1.88 0.21 4 -2.12 0.16 4 -1.49 0.31 3 IRELAND IRL 1.67 0.18 11 1.61 0.17 11 1.64 0.16 9 1.58 0.18 9 1.58 0.17 9 1.68 0.17 8 1.75 0.18 7 1.71 0.15 7 1.78 0.25 6 ISRAEL ISR 1.18 0.19 10 1.26 0.19 10 0.98 0.18 8 1.12 0.19 8 0.98 0.18 8 0.91 0.18 8 1.08 0.19 6 0.78 0.16 6 1.31 0.25 6 ITALY ITA 0.33 0.18 11 0.41 0.17 11 0.59 0.16 9 0.68 0.18 9 0.93 0.17 9 0.93 0.17 9 0.90 0.18 7 0.92 0.15 7 0.96 0.25 6 JAMAICA JAM 0.12 0.20 9 0.18 0.18 10 -0.12 0.17 9 0.10 0.18 9 0.05 0.17 8 -0.05 0.17 8 0.05 0.20 5 0.09 0.17 4 -0.22 0.28 3 JAPAN JPN 1.32 0.18 11 1.46 0.17 11 1.17 0.16 9 1.11 0.18 9 1.16 0.17 9 1.03 0.17 9 1.08 0.18 7 1.03 0.15 7 1.38 0.25 6 JORDAN JOR 0.27 0.17 13 0.19 0.17 13 0.11 0.16 11 0.17 0.17 11 0.25 0.16 10 0.15 0.17 9 0.03 0.18 6 0.05 0.15 6 0.23 0.25 5 KAZAKHSTAN KAZ -0.58 0.17 13 -0.52 0.16 14 -0.57 0.15 12 -0.67 0.17 11 -0.64 0.17 10 -0.89 0.17 10 -0.64 0.17 8 -0.80 0.15 6 -1.00 0.26 4 KENYA KEN -0.59 0.16 14 -0.68 0.15 14 -0.83 0.15 12 -0.68 0.15 12 -0.72 0.15 11 -0.77 0.16 10 -0.65 0.19 6 -0.72 0.16 6 -0.26 0.27 4 KIRIBATI KIR -0.56 0.25 4 -0.50 0.25 4 -0.48 0.23 4 -0.60 0.29 4 -0.35 0.36 3 -0.18 0.36 3 -0.06 0.29 2 -0.33 0.55 1 -0.32 0.48 1 KOREA, NORTH PRK -2.10 0.28 4 -1.68 0.22 6 -1.80 0.20 6 -1.71 0.21 6 -1.79 0.25 4 -1.95 0.24 4 -1.88 0.28 2 -1.98 0.18 2 -0.89 0.68 1 KOREA, SOUTH KOR 1.26 0.17 13 1.14 0.16 13 1.00 0.15 11 0.94 0.16 11 0.92 0.15 11 0.95 0.16 11 0.77 0.17 8 0.36 0.15 8 0.92 0.25 6 KOSOVO LWI -0.35 0.91 1 -0.36 0.91 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. KUWAIT KWT 0.20 0.19 10 0.32 0.19 9 0.39 0.18 7 0.28 0.21 6 0.29 0.20 6 0.12 0.18 7 0.11 0.21 4 0.16 0.16 4 0.35 0.31 3 KYRGYZSTAN KGZ -0.75 0.18 12 -0.77 0.17 12 -0.87 0.17 10 -0.71 0.22 9 -0.65 0.20 8 -0.64 0.20 8 -0.51 0.20 5 -0.30 0.17 3 -0.49 0.40 2 LAOS LAO -0.81 0.19 10 -0.86 0.18 10 -1.04 0.19 8 -0.94 0.23 7 -1.03 0.22 6 -0.69 0.21 6 -0.77 0.22 3 -0.65 0.18 2 -0.06 0.48 1 LATVIA LVA 0.55 0.19 11 0.75 0.18 11 0.65 0.16 10 0.69 0.18 10 0.69 0.16 10 0.64 0.17 10 0.49 0.18 7 0.61 0.16 5 -0.46 0.28 3 LEBANON LBN -0.61 0.19 11 -0.46 0.19 11 -0.31 0.18 9 -0.34 0.18 9 -0.28 0.18 8 -0.29 0.17 9 -0.18 0.19 5 -0.10 0.16 5 0.21 0.27 4 LESOTHO LSO -0.42 0.19 10 -0.35 0.18 10 -0.29 0.20 8 -0.26 0.20 8 -0.34 0.19 7 -0.27 0.21 6 -0.16 0.25 3 -0.09 0.18 3 0.14 0.48 1 LIBERIA LBR -1.18 0.24 6 -1.24 0.23 5 -1.30 0.21 5 -1.65 0.23 6 -1.64 0.23 5 -1.62 0.23 5 -1.89 0.23 4 -1.86 0.17 4 -1.77 0.42 2 LIBYA LBY -1.07 0.20 8 -0.84 0.21 7 -0.96 0.19 7 -0.76 0.20 7 -0.95 0.19 7 -1.05 0.19 7 -1.10 0.21 4 -0.97 0.16 4 -1.02 0.31 3 LIECHTENSTEIN LIE 1.86 0.38 2 1.80 0.36 2 1.57 0.28 2 1.66 0.37 2 1.48 0.32 2 1.69 0.30 2 1.72 0.32 1 1.75 0.19 1 .. .. .. LITHUANIA LTU 0.78 0.18 13 0.80 0.18 11 0.90 0.16 10 0.82 0.18 10 0.94 0.16 10 0.67 0.17 10 0.38 0.18 7 0.57 0.16 5 -0.35 0.28 3 LUXEMBOURG LUX 1.76 0.21 7 1.71 0.20 7 1.95 0.20 6 2.11 0.25 6 2.09 0.22 6 2.18 0.24 5 2.08 0.23 4 2.06 0.18 4 2.20 0.45 3 MACAO MAC 1.02 0.39 1 1.02 0.37 1 1.29 0.28 1 1.09 0.39 1 1.33 0.33 1 0.86 0.30 1 0.64 0.32 1 0.41 0.19 1 .. .. .. MACEDONIA MKD -0.29 0.20 11 -0.15 0.19 11 -0.36 0.17 10 -0.16 0.18 10 -0.26 0.17 9 -0.48 0.19 7 -0.70 0.22 4 -0.63 0.17 3 -0.34 0.30 2 MADAGASCAR MDG -0.30 0.16 14 -0.33 0.15 14 -0.14 0.17 10 -0.25 0.19 9 -0.41 0.19 8 -0.41 0.22 6 -0.57 0.23 4 -0.46 0.17 4 -0.97 0.42 2 MALAWI MWI -0.59 0.18 12 -0.85 0.16 13 -0.75 0.16 11 -0.79 0.16 11 -0.74 0.15 10 -0.75 0.17 9 -0.34 0.20 5 -0.19 0.16 5 -0.67 0.28 3 MALAYSIA MYS 1.07 0.17 13 0.99 0.16 14 1.01 0.15 12 0.97 0.16 12 0.90 0.15 11 0.83 0.16 11 0.82 0.17 8 0.56 0.15 8 0.88 0.23 7 MALDIVES MDV -0.19 0.24 5 -0.04 0.24 5 0.16 0.22 5 0.24 0.27 5 0.39 0.25 4 0.59 0.24 4 0.48 0.22 3 0.96 0.18 2 -0.12 0.48 1 MALI MLI -0.55 0.17 13 -0.53 0.16 13 -0.49 0.17 10 -0.41 0.18 10 -0.25 0.17 9 -0.46 0.19 8 -0.78 0.23 4 -0.88 0.17 4 -0.69 0.42 2 MALTA MLT 1.30 0.22 6 1.21 0.21 6 0.95 0.21 5 1.06 0.26 5 1.04 0.23 5 1.11 0.26 3 1.12 0.28 2 0.95 0.18 2 -0.23 0.68 1 MARSHALL ISLANDS MHL -0.84 0.31 3 -0.95 0.32 3 -0.91 0.36 3 -0.99 0.39 3 -1.01 0.36 3 -0.32 0.36 3 -0.94 0.29 2 -0.53 0.55 1 .. .. .. MARTINIQUE MTQ 0.75 0.39 1 0.75 0.37 1 0.75 0.28 1 0.75 0.39 1 0.80 0.33 1 0.86 0.30 1 0.91 0.32 1 0.95 0.19 1 .. .. .. MAURITANIA MRT -0.68 0.19 11 -0.75 0.19 10 -0.23 0.22 6 -0.25 0.24 6 0.02 0.24 5 -0.11 0.25 4 -0.19 0.25 3 -0.14 0.18 3 0.20 0.48 1 MAURITIUS MUS 0.60 0.19 10 0.57 0.17 10 0.61 0.17 8 0.71 0.18 8 0.62 0.19 6 0.45 0.19 6 0.49 0.25 4 0.49 0.33 3 0.47 0.30 2 MEXICO MEX 0.13 0.16 15 0.11 0.15 15 0.02 0.15 13 0.15 0.16 13 0.15 0.15 12 0.27 0.16 12 0.30 0.17 8 0.32 0.15 8 -0.04 0.23 8 MICRONESIA FSM -0.44 0.25 4 -0.29 0.25 4 -0.10 0.23 4 -0.62 0.29 4 -0.57 0.36 3 -0.35 0.36 3 -0.70 0.29 2 -0.53 0.55 1 .. .. .. MOLDOVA MDA -0.83 0.19 12 -0.85 0.18 12 -0.74 0.16 11 -0.85 0.18 10 -0.64 0.17 9 -0.62 0.18 8 -0.65 0.19 6 -0.30 0.16 5 -0.55 0.28 3 MONACO MCO 0.13 0.88 1 0.37 0.87 1 -0.12 0.91 1 1.41 0.87 1 -0.63 0.88 1 -0.62 0.90 1 .. .. .. .. .. .. .. .. .. MONGOLIA MNG -0.70 0.18 11 -0.44 0.17 10 -0.38 0.17 9 -0.44 0.22 8 -0.28 0.20 7 -0.19 0.20 6 -0.35 0.21 4 -0.34 0.18 3 -0.53 0.42 2 MONTENEGRO MNP -0.19 0.27 7 -0.29 0.30 6 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. MOROCCO MAR -0.07 0.17 13 -0.05 0.16 13 -0.18 0.16 11 -0.09 0.16 11 -0.09 0.16 10 -0.12 0.16 10 0.01 0.19 6 -0.05 0.16 6 -0.05 0.25 5 MOZAMBIQUE MOZ -0.41 0.16 14 -0.37 0.15 14 -0.33 0.15 12 -0.35 0.15 12 -0.49 0.15 11 -0.36 0.17 9 -0.36 0.20 5 -0.06 0.16 5 -0.27 0.28 3 MYANMAR MMR -1.67 0.22 8 -1.55 0.20 9 -1.63 0.19 8 -1.57 0.19 8 -1.31 0.19 7 -1.39 0.19 7 -1.20 0.21 4 -1.18 0.16 4 -1.28 0.31 3 NAMIBIA NAM 0.17 0.17 12 0.15 0.16 11 0.08 0.15 12 0.09 0.15 12 0.14 0.15 11 0.11 0.16 11 0.29 0.20 5 0.38 0.16 5 0.46 0.28 3 NAURU NRU -0.53 0.35 2 -1.28 0.87 1 -0.44 0.91 1 -1.34 0.87 1 -1.72 0.88 1 -1.18 0.90 1 .. .. .. .. .. .. .. .. .. NEPAL NPL -0.81 0.19 10 -0.82 0.18 10 -0.96 0.17 9 -0.78 0.20 8 -0.55 0.22 6 -0.44 0.21 6 -0.40 0.22 3 -0.46 0.18 2 -0.25 0.48 1 NETHERLANDS NLD 1.80 0.19 10 1.89 0.18 10 1.96 0.16 9 2.09 0.18 9 2.04 0.17 9 2.08 0.17 9 2.09 0.18 7 2.10 0.15 7 2.21 0.25 6 NETHERLANDS ANTILLES ANT 0.75 0.39 1 0.75 0.37 1 1.02 0.28 1 1.09 0.39 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. NEW CALEDONIA NCL 0.07 0.64 1 -0.37 0.61 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.42 0.68 1 NEW ZEALAND NZL 1.90 0.19 10 1.88 0.19 10 1.91 0.18 8 2.16 0.19 8 1.99 0.18 8 1.80 0.18 7 1.64 0.19 6 1.76 0.16 6 2.20 0.27 5 NICARAGUA NIC -0.91 0.19 12 -0.97 0.17 12 -0.77 0.17 10 -0.62 0.18 10 -0.67 0.17 9 -0.76 0.17 9 -0.62 0.20 5 -0.43 0.17 4 -0.92 0.27 5 NIGER NER -0.85 0.19 11 -0.87 0.18 11 -0.80 0.20 8 -0.69 0.21 8 -0.82 0.21 7 -0.89 0.22 6 -1.12 0.23 4 -1.21 0.17 4 -1.07 0.42 2 86 TABLEC3: Government Effectiveness(cont.) 2007 2006 2005 2004 2003 2002 2000 1998 1996 Country Code Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. NIGERIA NGA -0.93 0.16 14 -0.89 0.15 14 -0.84 0.15 12 -0.94 0.15 12 -0.90 0.15 11 -1.04 0.16 11 -1.02 0.18 7 -1.07 0.16 6 -1.36 0.25 5 NIUE NIU -0.18 0.88 1 -0.62 0.87 1 -0.44 0.91 1 .. .. .. -0.19 0.88 1 -0.76 0.90 1 .. .. .. .. .. .. .. .. .. NORWAY NOR 2.12 0.18 11 2.11 0.17 11 2.01 0.16 9 2.13 0.18 9 2.04 0.17 9 2.01 0.17 8 1.94 0.18 7 2.03 0.15 7 2.19 0.25 6 OMAN OMN 0.38 0.20 8 0.45 0.23 6 0.48 0.20 6 0.53 0.21 6 0.59 0.20 6 0.52 0.18 7 0.54 0.21 4 0.54 0.16 4 0.86 0.31 3 PAKISTAN PAK -0.62 0.15 14 -0.55 0.15 14 -0.53 0.15 12 -0.53 0.16 12 -0.55 0.15 11 -0.60 0.16 10 -0.66 0.17 7 -0.65 0.15 6 -0.52 0.25 5 PALAU PCI -0.49 0.88 1 -0.62 0.87 1 -0.76 0.91 1 0.39 0.87 1 0.33 0.88 1 -0.34 0.90 1 .. .. .. .. .. .. .. .. .. PANAMA PAN 0.25 0.19 12 0.10 0.17 12 0.10 0.16 11 0.02 0.17 11 -0.05 0.17 9 -0.01 0.17 9 0.21 0.18 6 0.27 0.16 5 -0.29 0.27 5 PAPUA NEWGUINEA PNG -0.74 0.18 10 -0.81 0.18 10 -0.97 0.17 10 -0.75 0.18 10 -0.67 0.17 9 -0.62 0.17 8 -0.54 0.17 6 -0.44 0.17 4 -0.34 0.28 3 PARAGUAY PRY -0.85 0.19 11 -0.85 0.18 11 -0.83 0.17 10 -0.87 0.18 10 -0.91 0.17 9 -1.06 0.17 9 -1.10 0.20 5 -0.97 0.17 4 -0.77 0.28 4 PERU PER -0.44 0.17 14 -0.52 0.16 14 -0.60 0.15 12 -0.51 0.16 12 -0.44 0.16 11 -0.38 0.16 11 -0.16 0.17 7 0.07 0.15 7 -0.17 0.24 7 PHILIPPINES PHL -0.01 0.16 14 -0.06 0.16 14 -0.08 0.15 12 -0.21 0.16 12 -0.17 0.15 11 -0.20 0.16 11 -0.19 0.17 8 -0.22 0.15 8 -0.02 0.23 7 POLAND POL 0.38 0.17 14 0.49 0.16 14 0.54 0.15 12 0.44 0.16 12 0.54 0.15 12 0.57 0.16 12 0.62 0.17 9 0.69 0.15 8 0.77 0.23 7 PORTUGAL PRT 0.88 0.18 11 0.85 0.17 11 1.02 0.16 9 1.07 0.18 9 1.21 0.17 9 1.21 0.17 8 1.14 0.18 7 1.36 0.15 7 1.06 0.25 6 PUERTORICO PRI 0.65 0.27 5 0.71 0.30 4 1.01 0.24 3 1.11 0.29 3 1.16 0.26 3 1.19 0.26 2 1.38 0.27 2 1.29 0.17 2 1.47 0.62 1 QATAR QAT 0.06 0.22 7 0.44 0.20 7 0.56 0.18 7 0.63 0.21 6 0.57 0.20 6 0.66 0.19 6 0.60 0.21 4 0.70 0.16 4 0.49 0.31 3 REUNION REU 1.02 0.39 1 1.02 0.37 1 1.02 0.28 1 1.07 0.39 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ROMANIA ROM -0.09 0.17 14 -0.07 0.16 14 -0.08 0.15 13 -0.14 0.17 12 -0.14 0.16 11 -0.13 0.17 10 -0.38 0.18 7 -0.30 0.16 5 -0.69 0.27 4 RUSSIA RUS -0.40 0.17 14 -0.47 0.16 14 -0.38 0.15 12 -0.31 0.16 12 -0.23 0.15 12 -0.32 0.16 12 -0.60 0.17 9 -0.42 0.15 8 -0.62 0.23 7 RWANDA RWA -0.37 0.21 8 -0.38 0.20 8 -1.03 0.21 6 -0.63 0.23 6 -0.85 0.23 5 -0.99 0.23 5 -0.83 0.25 3 -1.15 0.18 3 -1.24 0.48 1 SAMOA SAM -0.21 0.25 4 0.01 0.25 4 0.32 0.23 4 0.05 0.29 4 0.35 0.25 4 0.11 0.24 4 0.41 0.22 3 0.37 0.18 2 -0.38 0.48 1 SAN MARINO SMR -0.08 0.88 1 -0.27 0.87 1 -0.50 0.91 1 -0.22 0.87 1 -0.67 0.88 1 -0.34 0.90 1 .. .. .. .. .. .. .. .. .. SAOTOME ANDPRINCIPE STP -0.79 0.24 5 -0.88 0.22 6 -0.77 0.23 5 -0.77 0.25 5 -0.59 0.26 4 -0.68 0.25 4 -0.60 0.25 3 -0.53 0.18 3 -0.65 0.48 1 SAUDI ARABIA SAU -0.18 0.18 11 -0.22 0.18 10 -0.38 0.17 8 -0.30 0.18 8 -0.30 0.18 8 -0.30 0.17 9 -0.13 0.20 5 -0.18 0.16 5 -0.34 0.28 4 SENEGAL SEN -0.34 0.16 14 -0.21 0.17 13 -0.11 0.17 10 -0.14 0.17 10 -0.21 0.15 10 0.05 0.17 9 -0.05 0.20 5 0.12 0.16 5 -0.16 0.28 3 SERBIA YUG -0.34 0.19 11 -0.27 0.18 11 -0.37 0.16 10 -0.24 0.18 10 -0.53 0.16 10 -0.61 0.18 9 -0.85 0.23 4 -1.18 0.17 3 -0.45 0.34 2 SEYCHELLES SYC -0.02 0.22 6 -0.04 0.22 6 0.02 0.20 7 -0.08 0.20 7 -0.10 0.24 5 0.03 0.25 4 0.00 0.25 3 0.50 0.18 3 -0.58 0.48 1 SIERRA LEONE SLE -1.08 0.21 9 -1.08 0.20 9 -1.24 0.20 7 -1.12 0.22 7 -1.39 0.21 6 -1.56 0.22 6 -1.47 0.23 4 -1.38 0.17 4 -0.59 0.42 2 SINGAPORE SGP 2.41 0.17 12 2.22 0.16 12 2.17 0.16 10 2.26 0.17 10 2.19 0.16 10 2.08 0.16 10 2.21 0.18 7 2.12 0.15 7 2.31 0.25 6 SLOVAKIA SVK 0.76 0.19 12 0.91 0.18 12 0.95 0.16 11 0.74 0.17 11 0.60 0.16 11 0.51 0.16 10 0.45 0.18 8 0.37 0.15 6 0.61 0.25 5 SLOVENIA SVN 1.08 0.19 12 1.09 0.18 11 1.01 0.17 10 1.00 0.18 10 1.07 0.16 11 0.93 0.16 11 0.81 0.18 8 0.98 0.16 5 0.81 0.28 3 SOLOMONISLANDS SLB -0.82 0.24 5 -0.90 0.25 4 -0.68 0.23 4 -1.56 0.29 4 -2.52 0.36 3 -1.03 0.36 3 -1.05 0.29 2 -0.94 0.55 1 -1.04 0.48 1 SOMALIA SOM -2.35 0.24 5 -2.20 0.23 5 -2.16 0.21 6 -2.16 0.23 6 -1.90 0.23 5 -1.61 0.24 4 -2.25 0.24 3 -2.09 0.18 3 -1.77 0.42 2 SOUTHAFRICA ZAF 0.72 0.15 15 0.75 0.15 15 0.88 0.14 14 0.77 0.14 14 0.67 0.14 13 0.67 0.15 13 0.66 0.17 9 0.83 0.15 9 0.42 0.23 7 SPAIN ESP 1.00 0.18 11 0.99 0.17 11 1.40 0.16 9 1.36 0.18 9 1.74 0.17 9 1.83 0.17 9 1.72 0.18 7 1.70 0.15 7 1.57 0.25 6 SRI LANKA LKA -0.29 0.16 13 -0.31 0.16 13 -0.41 0.15 11 -0.37 0.17 11 -0.17 0.16 10 -0.10 0.16 10 -0.26 0.16 7 -0.24 0.16 5 -0.44 0.27 4 ST. KITTSAND NEVIS KNA 0.70 0.32 3 0.75 0.32 3 0.94 0.25 4 -0.08 0.30 4 -0.57 0.45 2 -0.43 0.48 2 -0.10 0.45 1 -0.33 0.55 1 -0.19 0.48 1 ST. LUCIA LCA 0.86 0.32 3 0.94 0.32 3 1.06 0.25 4 0.21 0.30 4 0.02 0.45 2 -0.12 0.48 2 0.00 0.45 1 -0.23 0.55 1 0.27 0.48 1 ST. VINCENTANDTHE GRENADINES VCT 0.85 0.32 3 0.85 0.32 3 1.01 0.25 4 0.26 0.30 4 -0.30 0.45 2 -0.34 0.48 2 -0.10 0.45 1 -0.23 0.55 1 -0.38 0.48 1 SUDAN SDN -1.18 0.19 11 -1.12 0.18 10 -1.48 0.17 10 -1.19 0.17 10 -1.21 0.17 9 -1.14 0.17 9 -1.17 0.19 6 -1.14 0.16 5 -1.49 0.28 3 SURINAME SUR -0.03 0.25 5 -0.03 0.22 6 -0.04 0.24 5 -0.04 0.28 5 -0.18 0.27 4 -0.28 0.26 3 -0.16 0.28 2 -0.64 0.18 2 -0.89 0.68 1 SWAZILAND SWZ -0.71 0.21 8 -0.69 0.20 8 -0.92 0.21 7 -0.82 0.22 7 -0.79 0.22 6 -0.42 0.23 5 -0.71 0.25 3 -0.67 0.18 3 -0.32 0.48 1 SWEDEN SWE 2.08 0.18 11 2.06 0.17 11 1.94 0.16 9 2.07 0.18 9 2.09 0.17 9 2.06 0.17 8 2.01 0.18 7 2.04 0.15 7 2.14 0.25 6 SWITZERLAND CHE 2.24 0.19 10 2.17 0.18 10 2.06 0.16 9 2.30 0.18 9 2.10 0.17 9 2.22 0.17 8 2.16 0.18 7 1.97 0.15 7 2.43 0.25 6 SYRIA SYR -0.88 0.18 11 -1.01 0.19 10 -1.19 0.19 8 -1.06 0.19 8 -1.00 0.19 7 -0.88 0.19 7 -0.98 0.21 4 -0.89 0.16 4 -0.15 0.31 3 TAIWAN TWN 1.05 0.17 12 1.12 0.16 12 1.13 0.16 10 1.29 0.17 10 1.14 0.16 10 1.04 0.16 10 0.89 0.18 7 0.74 0.15 7 1.44 0.25 6 TAJIKISTAN TJK -0.97 0.18 12 -1.02 0.17 12 -1.07 0.17 10 -1.12 0.22 9 -1.15 0.20 8 -1.16 0.20 8 -1.25 0.20 4 -1.51 0.17 3 -1.62 0.40 2 TANZANIA TZA -0.42 0.17 13 -0.41 0.16 13 -0.37 0.15 12 -0.37 0.15 12 -0.34 0.15 11 -0.39 0.16 10 -0.43 0.19 6 -0.55 0.16 6 -0.84 0.27 4 THAILAND THA 0.16 0.17 13 0.25 0.16 14 0.40 0.15 12 0.29 0.16 12 0.26 0.15 11 0.16 0.16 11 0.06 0.17 8 0.08 0.15 8 0.46 0.23 7 TIMOR-LESTE TMP -0.91 0.23 5 -0.75 0.24 5 -0.92 0.22 4 -0.77 0.31 3 -0.96 0.29 3 -0.92 0.30 2 .. .. .. .. .. .. .. .. .. TOGO TGO -1.48 0.19 10 -1.59 0.18 11 -1.44 0.20 8 -1.45 0.21 8 -1.32 0.21 7 -1.26 0.22 6 -1.16 0.23 4 -0.68 0.17 4 -0.68 0.42 2 TONGA TON -0.58 0.25 4 -0.65 0.25 4 -0.48 0.23 4 -0.69 0.29 4 -0.61 0.36 3 -0.50 0.36 3 -0.54 0.29 2 -0.43 0.55 1 -0.19 0.48 1 TRINIDAD AND TOBAGO TTO 0.37 0.20 9 0.26 0.19 9 0.28 0.17 9 0.47 0.19 8 0.49 0.18 7 0.34 0.19 6 0.43 0.20 5 -0.01 0.17 4 0.12 0.28 3 TUNISIA TUN 0.46 0.17 13 0.50 0.16 12 0.46 0.16 11 0.48 0.16 11 0.57 0.16 10 0.63 0.16 10 0.55 0.19 6 0.52 0.16 6 0.51 0.27 4 TURKEY TUR 0.24 0.16 15 0.13 0.16 15 0.21 0.15 13 0.08 0.16 13 0.12 0.15 12 0.05 0.16 12 -0.06 0.17 9 -0.21 0.15 8 -0.14 0.23 7 TURKMENISTAN TKM -1.37 0.22 7 -1.44 0.22 7 -1.57 0.19 7 -1.51 0.24 6 -1.38 0.21 6 -1.52 0.21 6 -1.29 0.24 3 -1.23 0.17 3 -1.51 0.40 2 TUVALU TUV -0.41 0.27 3 -0.31 0.27 3 -0.03 0.24 3 -1.04 0.32 3 -0.96 0.51 2 -0.24 0.47 2 0.53 0.36 1 .. .. .. .. .. .. UGANDA UGA -0.40 0.16 14 -0.44 0.15 14 -0.49 0.15 12 -0.43 0.15 12 -0.47 0.15 11 -0.56 0.16 10 -0.43 0.19 6 -0.52 0.16 6 -0.57 0.27 4 UKRAINE UKR -0.60 0.17 14 -0.50 0.16 13 -0.40 0.16 11 -0.68 0.17 11 -0.53 0.16 11 -0.71 0.16 11 -0.65 0.17 8 -0.74 0.15 7 -0.75 0.25 5 UNITEDARABEMIRATES ARE 0.86 0.20 9 0.71 0.19 9 0.55 0.17 8 0.83 0.19 8 0.76 0.20 6 0.84 0.18 7 0.81 0.21 4 0.85 0.16 4 0.42 0.31 3 UNITEDKINGDOM GBR 1.77 0.18 11 1.86 0.17 11 1.71 0.16 9 1.92 0.18 9 1.88 0.17 9 1.93 0.17 9 1.90 0.18 7 2.01 0.15 7 2.03 0.25 6 UNITEDSTATES USA 1.62 0.18 11 1.67 0.17 11 1.60 0.16 9 1.81 0.18 9 1.79 0.17 9 1.79 0.17 9 1.91 0.18 7 1.63 0.15 7 2.15 0.25 6 URUGUAY URY 0.57 0.19 11 0.45 0.18 11 0.54 0.16 11 0.46 0.17 11 0.51 0.16 10 0.65 0.17 10 0.58 0.18 6 0.67 0.16 5 -0.08 0.27 5 UZBEKISTAN UZB -0.74 0.18 11 -1.08 0.18 10 -1.20 0.17 9 -1.09 0.19 9 -1.04 0.18 9 -1.10 0.18 9 -0.91 0.21 5 -0.84 0.29 3 -0.99 0.28 3 VANUATU VUT -0.34 0.25 4 -0.42 0.25 4 -0.32 0.23 4 -0.64 0.29 4 -0.88 0.36 3 -0.32 0.36 3 -0.62 0.29 2 -0.43 0.55 1 -0.19 0.48 1 VENEZUELA VEN -0.87 0.16 15 -0.72 0.15 15 -0.83 0.15 13 -0.94 0.16 13 -0.93 0.15 12 -0.96 0.16 12 -0.68 0.17 8 -0.48 0.15 8 -0.93 0.23 8 VIETNAM VNM -0.41 0.15 14 -0.38 0.15 14 -0.29 0.15 12 -0.43 0.16 12 -0.35 0.15 11 -0.45 0.15 11 -0.46 0.16 8 -0.60 0.15 7 -0.23 0.24 6 VIRGINISLANDS(U.S.) VIR 1.29 0.39 1 1.29 0.37 1 1.29 0.28 1 0.56 0.39 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. WEST BANK GAZA WBG -1.24 0.33 3 -1.10 0.32 3 -1.09 0.26 3 -0.86 0.32 3 -1.24 0.31 2 -1.06 0.29 2 -1.24 0.32 1 -1.20 0.19 1 .. .. .. YEMEN YEM -1.02 0.19 11 -1.01 0.19 11 -0.93 0.19 8 -0.92 0.19 8 -0.73 0.19 7 -0.78 0.19 7 -0.71 0.21 4 -0.63 0.17 4 -0.55 0.28 3 ZAMBIA ZMB -0.59 0.17 13 -0.74 0.16 13 -0.91 0.17 11 -0.86 0.15 12 -0.83 0.15 11 -0.81 0.16 10 -0.96 0.19 6 -1.01 0.16 6 -0.59 0.27 4 ZIMBABWE ZWE -1.48 0.16 14 -1.36 0.15 14 -1.49 0.15 12 -1.14 0.16 11 -1.10 0.16 10 -0.99 0.16 10 -0.90 0.18 7 -0.48 0.15 7 -0.36 0.25 5 87 TABLEC4:RegulatoryQuality 2007 2006 2005 2004 2003 2002 2000 1998 1996 Country Code Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. AFGHANISTAN AFG -1.75 0.24 5 -1.68 0.22 6 -1.64 0.22 5 -1.63 0.22 5 -1.79 0.24 3 -1.94 0.29 3 -2.67 0.38 2 -2.16 0.46 1 .. .. .. ALBANIA ALB 0.09 0.18 11 -0.12 0.18 11 -0.26 0.18 10 -0.16 0.19 9 -0.43 0.19 8 -0.23 0.22 8 -0.25 0.26 7 -0.28 0.28 6 0.02 0.35 5 ALGERIA DZA -0.66 0.16 11 -0.66 0.16 11 -0.56 0.16 11 -0.59 0.16 11 -0.57 0.17 10 -0.67 0.20 9 -0.76 0.23 7 -1.01 0.24 7 -0.94 0.33 5 AMERICANSAMOA ASM 0.35 0.39 1 0.35 0.35 1 0.36 0.31 1 0.47 0.33 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ANDORRA ADO 1.35 0.39 1 1.33 0.35 1 1.34 0.31 1 1.37 0.33 1 1.39 0.30 1 1.42 0.37 1 1.23 0.43 1 1.26 0.46 1 .. .. .. ANGOLA AGO -1.00 0.17 10 -1.08 0.16 11 -1.31 0.17 10 -1.18 0.17 10 -1.30 0.18 9 -1.46 0.21 8 -1.86 0.24 6 -1.66 0.24 7 -1.42 0.33 5 ANGUILLA AIA 1.35 0.39 1 1.33 0.35 1 1.09 0.31 1 0.87 0.33 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ANTIGUA AND BARBUDA ATG 0.60 0.39 1 0.60 0.35 1 0.53 0.30 2 0.54 0.31 2 0.65 0.30 1 0.68 0.37 1 0.75 0.43 1 0.77 0.46 1 .. .. .. ARGENTINA ARG -0.77 0.18 11 -0.70 0.18 11 -0.63 0.17 11 -0.70 0.17 11 -0.71 0.17 10 -1.06 0.19 10 0.31 0.20 8 0.64 0.23 8 0.79 0.23 7 ARMENIA ARM 0.24 0.17 13 0.22 0.17 13 0.11 0.18 11 0.03 0.18 10 0.06 0.19 9 -0.07 0.21 9 -0.27 0.26 7 -0.38 0.28 6 -1.33 0.40 3 ARUBA ABW 0.85 0.39 1 0.84 0.35 1 0.85 0.31 1 0.73 0.33 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. AUSTRALIA AUS 1.71 0.21 8 1.67 0.21 8 1.62 0.20 8 1.73 0.20 8 1.61 0.19 8 1.46 0.22 7 1.62 0.22 7 1.49 0.25 7 1.04 0.24 6 AUSTRIA AUT 1.62 0.21 8 1.61 0.21 8 1.56 0.20 8 1.50 0.20 8 1.52 0.19 8 1.59 0.22 7 1.59 0.22 7 1.39 0.25 7 1.16 0.24 6 AZERBAIJAN AZE -0.50 0.17 13 -0.51 0.17 13 -0.53 0.17 13 -0.63 0.17 12 -0.57 0.17 11 -0.71 0.20 11 -0.81 0.23 9 -0.94 0.25 7 -0.98 0.34 5 BAHAMAS BHS 1.01 0.29 3 1.03 0.28 3 1.09 0.26 3 1.11 0.27 3 1.13 0.25 3 1.30 0.29 3 1.15 0.36 3 1.01 0.38 3 0.45 0.53 2 BAHRAIN BHR 0.89 0.21 8 0.76 0.20 8 0.75 0.19 8 0.85 0.19 8 0.77 0.19 7 1.00 0.21 8 0.91 0.28 5 0.80 0.30 5 0.51 0.34 4 BANGLADESH BGD -0.86 0.18 12 -0.87 0.18 12 -0.95 0.18 11 -1.05 0.17 11 -0.89 0.17 10 -0.94 0.20 10 -0.70 0.23 8 -0.59 0.27 6 -0.22 0.33 5 BARBADOS BRB 0.97 0.28 4 0.83 0.26 4 1.16 0.27 4 1.04 0.27 4 1.08 0.27 3 1.06 0.34 2 1.26 0.37 2 1.29 0.40 2 0.87 0.66 1 BELARUS BLR -1.56 0.18 10 -1.67 0.18 10 -1.51 0.19 9 -1.42 0.19 9 -1.62 0.19 9 -1.71 0.22 8 -1.94 0.26 7 -2.01 0.28 6 -1.53 0.38 4 BELGIUM BEL 1.48 0.21 8 1.41 0.21 8 1.29 0.20 8 1.42 0.20 8 1.36 0.19 8 1.40 0.21 8 1.18 0.22 7 1.07 0.25 7 0.97 0.24 6 BELIZE BLZ -0.28 0.23 6 -0.25 0.23 6 -0.01 0.25 5 -0.06 0.25 5 0.15 0.25 4 -0.04 0.30 3 -0.02 0.32 3 0.11 0.35 3 0.14 0.57 2 BENIN BEN -0.44 0.17 10 -0.41 0.17 10 -0.47 0.18 8 -0.50 0.19 7 -0.54 0.21 6 -0.40 0.25 5 -0.13 0.27 4 -0.11 0.29 4 0.17 0.57 2 BERMUDA BMU 1.35 0.39 1 1.33 0.35 1 1.34 0.31 1 1.39 0.33 1 1.39 0.30 1 1.42 0.37 1 1.48 0.43 1 1.51 0.46 1 .. .. .. BHUTAN BTN -0.68 0.23 5 -0.17 0.25 5 -0.13 0.25 5 -0.71 0.25 5 -0.01 0.24 4 -0.48 0.32 3 -0.39 0.34 3 -0.43 0.38 2 0.27 0.81 1 BOLIVIA BOL -1.18 0.18 11 -0.98 0.18 11 -0.60 0.18 10 -0.15 0.18 10 -0.06 0.18 9 -0.03 0.20 9 0.15 0.23 7 0.30 0.27 6 0.81 0.33 5 BOSNIA-HERZEGOVINA BIH -0.29 0.18 11 -0.40 0.18 11 -0.40 0.18 11 -0.28 0.18 11 -0.61 0.18 9 -0.58 0.21 9 -0.53 0.25 6 -0.89 0.28 5 -0.64 0.57 2 BOTSWANA BWA 0.48 0.16 12 0.52 0.16 12 0.61 0.16 11 0.60 0.16 11 0.79 0.17 10 0.84 0.19 10 0.65 0.23 7 0.75 0.24 7 0.74 0.33 5 BRAZIL BRA -0.04 0.17 12 -0.04 0.17 12 0.05 0.17 11 0.07 0.17 11 0.31 0.17 10 0.21 0.19 10 0.35 0.20 8 0.30 0.23 8 0.31 0.23 7 BRUNEI BRN 1.00 0.32 2 0.96 0.30 2 0.95 0.27 2 1.19 0.28 2 1.00 0.26 2 1.07 0.31 2 0.92 0.40 2 0.88 0.43 2 3.41 0.70 1 BULGARIA BGR 0.61 0.17 13 0.54 0.16 13 0.64 0.17 11 0.66 0.17 11 0.58 0.17 11 0.55 0.19 11 0.20 0.21 9 0.11 0.25 7 0.20 0.32 6 BURKINA FASO BFA -0.34 0.16 12 -0.44 0.16 12 -0.44 0.18 8 -0.35 0.18 8 -0.27 0.20 7 -0.11 0.22 6 -0.08 0.27 5 -0.32 0.29 5 -0.08 0.48 3 BURUNDI BDI -1.21 0.17 10 -1.17 0.17 10 -1.24 0.19 7 -1.18 0.20 6 -1.26 0.22 5 -1.33 0.26 4 -1.19 0.29 3 -1.62 0.29 4 -1.55 0.57 2 CAMBODIA KHM -0.51 0.19 10 -0.61 0.19 10 -0.50 0.19 9 -0.52 0.19 8 -0.37 0.19 7 -0.35 0.23 7 -0.17 0.27 5 -0.21 0.31 4 0.04 0.46 3 CAMEROON CMR -0.71 0.16 12 -0.73 0.16 12 -0.72 0.16 11 -0.57 0.17 10 -0.80 0.17 10 -0.80 0.20 9 -0.47 0.23 7 -0.55 0.24 7 -0.79 0.33 5 CANADA CAN 1.61 0.21 9 1.55 0.20 9 1.54 0.20 8 1.64 0.20 8 1.53 0.19 8 1.59 0.21 8 1.49 0.22 7 1.49 0.25 7 0.92 0.24 6 CAPE VERDE CPV -0.20 0.20 6 -0.18 0.20 6 -0.24 0.22 5 -0.30 0.22 5 -0.21 0.24 4 -0.22 0.27 4 0.12 0.34 3 -0.26 0.36 3 -0.75 0.57 2 CAYMAN ISLANDS CYM 1.35 0.39 1 1.33 0.35 1 1.34 0.31 1 1.42 0.33 1 1.39 0.30 1 1.42 0.37 1 1.23 0.43 1 1.02 0.46 1 .. .. .. CENTRALAFRICANREPUBLICCAF -1.24 0.19 6 -1.26 0.19 6 -1.34 0.19 7 -1.25 0.19 7 -1.30 0.21 6 -1.12 0.25 5 -0.90 0.29 3 -0.96 0.31 3 -0.27 0.81 1 CHAD TCD -1.16 0.17 10 -1.09 0.17 10 -1.06 0.18 8 -0.78 0.19 8 -0.94 0.20 7 -0.86 0.24 6 -0.80 0.27 4 -0.94 0.29 4 -0.86 0.57 2 CHILE CHL 1.45 0.18 11 1.43 0.18 11 1.43 0.17 11 1.40 0.17 11 1.48 0.17 10 1.46 0.19 10 1.39 0.20 8 1.34 0.23 8 1.29 0.23 7 CHINA CHN -0.24 0.17 12 -0.33 0.17 12 -0.26 0.17 11 -0.29 0.17 11 -0.39 0.17 10 -0.51 0.19 10 -0.28 0.20 8 -0.26 0.23 8 0.15 0.23 7 COLOMBIA COL 0.21 0.17 12 0.12 0.17 12 0.04 0.17 11 -0.06 0.17 11 -0.05 0.17 10 0.05 0.19 10 0.11 0.20 8 0.09 0.23 8 0.52 0.23 7 COMOROS COM -1.43 0.22 4 -1.46 0.22 4 -1.58 0.22 4 -1.51 0.23 4 -1.45 0.25 3 -1.19 0.29 3 -1.36 0.29 3 -1.29 0.31 3 -0.82 0.81 1 CONGO COG -1.20 0.17 10 -1.07 0.18 9 -1.23 0.18 9 -0.98 0.20 7 -1.11 0.22 6 -1.07 0.24 6 -1.29 0.27 5 -1.25 0.29 5 -0.90 0.48 3 CONGO, DEM. REP. ZAR -1.35 0.18 8 -1.40 0.18 8 -1.62 0.17 9 -1.70 0.17 9 -1.67 0.20 7 -1.71 0.22 7 -2.34 0.27 5 -2.43 0.27 6 -2.56 0.36 4 COOK ISLANDS COK 0.09 0.61 1 0.57 0.71 1 0.61 0.80 1 0.18 0.62 1 0.28 0.57 1 0.35 0.92 1 0.36 0.94 1 .. .. .. .. .. .. COSTARICA CRI 0.49 0.19 10 0.41 0.18 10 0.60 0.18 10 0.62 0.18 10 0.52 0.18 9 0.43 0.20 9 0.66 0.23 7 0.88 0.27 6 0.62 0.29 6 COTE D'IVOIRE CIV -0.98 0.17 10 -0.94 0.17 10 -0.99 0.17 9 -0.99 0.17 10 -0.72 0.18 9 -0.48 0.20 9 -0.42 0.23 7 -0.07 0.24 7 -0.04 0.33 5 CROATIA HRV 0.43 0.17 12 0.39 0.17 12 0.49 0.17 12 0.49 0.17 12 0.39 0.17 11 0.31 0.19 11 0.00 0.23 8 -0.01 0.25 7 0.16 0.34 5 CUBA CUB -1.63 0.21 8 -1.59 0.20 8 -1.68 0.19 8 -1.62 0.19 8 -1.32 0.19 7 -1.30 0.22 7 -1.22 0.28 5 -1.08 0.30 5 -0.87 0.34 4 CYPRUS CYP 1.30 0.24 6 1.28 0.23 6 1.29 0.21 6 1.23 0.22 6 1.20 0.21 5 1.23 0.25 5 1.10 0.28 5 1.20 0.30 5 1.20 0.34 4 CZECHREPUBLIC CZE 0.96 0.17 13 1.03 0.17 12 1.06 0.17 11 1.03 0.17 12 1.12 0.16 12 1.15 0.18 12 0.75 0.19 10 0.86 0.22 9 0.94 0.23 8 DENMARK DNK 1.93 0.21 8 1.86 0.21 8 1.71 0.20 8 1.81 0.20 8 1.80 0.19 8 1.72 0.22 7 1.66 0.22 7 1.65 0.25 7 1.22 0.24 6 DJIBOUTI DJI -0.80 0.21 5 -0.85 0.21 5 -0.83 0.22 5 -0.76 0.22 5 -0.75 0.24 4 -0.59 0.27 4 -0.70 0.27 4 -1.10 0.29 4 0.17 0.57 2 DOMINICA DMA 0.77 0.31 2 0.89 0.30 2 0.66 0.27 3 0.60 0.27 3 0.78 0.27 2 0.69 0.32 2 0.47 0.35 2 0.45 0.38 2 0.00 0.81 1 DOMINICANREPUBLIC DOM -0.15 0.18 11 -0.17 0.18 11 -0.31 0.18 10 -0.31 0.18 10 -0.20 0.18 9 -0.13 0.20 9 -0.01 0.26 6 -0.14 0.30 5 0.00 0.41 4 ECUADOR ECU -1.09 0.19 10 -1.05 0.18 10 -0.84 0.18 10 -0.65 0.18 10 -0.56 0.18 9 -0.60 0.20 9 -0.45 0.23 7 -0.05 0.27 6 0.16 0.33 5 EGYPT EGY -0.31 0.16 12 -0.46 0.16 12 -0.46 0.16 11 -0.48 0.16 11 -0.51 0.17 10 -0.50 0.19 10 -0.30 0.21 8 -0.28 0.23 8 0.24 0.29 6 ELSALVADOR SLV 0.20 0.19 9 0.14 0.19 9 0.09 0.18 9 0.13 0.18 9 -0.09 0.18 8 0.02 0.21 8 0.17 0.24 6 0.30 0.30 5 0.52 0.33 5 EQUATORIALGUINEA GNQ -1.35 0.19 7 -1.34 0.19 7 -1.34 0.20 6 -1.41 0.20 7 -1.34 0.21 6 -1.43 0.24 6 -1.81 0.25 5 -1.74 0.27 5 -1.04 0.56 2 ERITREA ERI -1.95 0.19 6 -1.89 0.19 7 -1.73 0.20 6 -1.65 0.20 6 -1.33 0.22 5 -1.10 0.26 4 -0.87 0.29 3 -0.63 0.31 3 0.00 0.81 1 ESTONIA EST 1.50 0.17 13 1.42 0.17 12 1.41 0.16 12 1.38 0.17 12 1.40 0.16 12 1.41 0.18 12 1.27 0.19 10 1.24 0.25 7 1.30 0.34 5 ETHIOPIA ETH -0.90 0.16 11 -0.87 0.16 11 -1.00 0.16 10 -0.93 0.17 10 -1.12 0.18 9 -1.15 0.20 8 -1.23 0.24 6 -1.10 0.26 6 -1.82 0.41 4 FIJI FJI -0.46 0.28 3 -0.44 0.28 3 -0.41 0.26 3 -0.65 0.27 3 -0.32 0.26 3 0.02 0.30 3 -0.56 0.32 3 -0.21 0.35 3 -0.37 0.57 2 FINLAND FIN 1.67 0.21 8 1.75 0.21 8 1.76 0.20 8 1.82 0.20 8 1.90 0.19 8 1.89 0.21 8 1.85 0.22 7 1.74 0.25 7 1.09 0.24 6 FRANCE FRA 1.15 0.21 9 1.11 0.20 9 1.10 0.20 8 1.16 0.20 8 1.19 0.19 8 1.03 0.21 8 0.98 0.22 7 0.94 0.25 7 0.76 0.24 6 FRENCHGUIANA GUF 0.85 0.39 1 0.84 0.35 1 0.85 0.31 1 0.49 0.33 1 0.90 0.30 1 0.93 0.37 1 0.99 0.43 1 1.02 0.46 1 .. .. .. GABON GAB -0.49 0.18 10 -0.49 0.18 10 -0.34 0.18 9 -0.49 0.18 9 -0.16 0.19 8 -0.18 0.21 8 -0.05 0.23 7 0.21 0.26 6 0.04 0.41 4 GAMBIA GMB -0.39 0.18 8 -0.40 0.18 8 -0.48 0.19 7 -0.37 0.20 7 -0.44 0.21 6 -0.55 0.25 5 -0.23 0.27 5 -0.36 0.29 5 -1.77 0.48 3 88 TABLE C4: Regulatory Quality (cont.) 2007 2006 2005 2004 2003 2002 2000 1998 1996 Country Code Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. GEORGIA GEO 0.21 0.18 12 -0.26 0.18 11 -0.56 0.19 10 -0.52 0.19 10 -0.75 0.20 8 -0.83 0.23 8 -0.51 0.26 6 -0.77 0.28 5 -1.23 0.38 4 GERMANY DEU 1.50 0.21 9 1.48 0.20 9 1.42 0.20 8 1.44 0.20 8 1.51 0.19 8 1.55 0.21 8 1.59 0.22 7 1.30 0.25 7 1.08 0.24 6 GHANA GHA 0.00 0.17 11 -0.02 0.17 11 -0.11 0.16 11 -0.32 0.16 11 -0.33 0.17 10 -0.41 0.20 9 0.00 0.23 7 -0.10 0.24 7 0.11 0.33 5 GREECE GRC 0.83 0.21 9 0.79 0.20 9 0.88 0.20 8 0.86 0.20 8 1.02 0.19 8 1.00 0.21 8 0.88 0.22 7 0.72 0.25 7 0.74 0.24 6 GRENADA GRD 0.46 0.31 2 0.43 0.28 3 0.31 0.27 3 0.19 0.27 3 0.38 0.27 2 0.38 0.32 2 0.43 0.35 2 0.42 0.38 2 0.00 0.81 1 GUAM GUM 0.60 0.39 1 0.60 0.35 1 0.60 0.31 1 0.68 0.33 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. GUATEMALA GTM -0.15 0.18 11 -0.15 0.18 11 -0.32 0.18 9 -0.18 0.18 9 -0.29 0.18 8 -0.15 0.21 8 -0.11 0.24 6 0.08 0.30 5 0.16 0.33 5 GUINEA GIN -1.14 0.17 10 -1.02 0.17 10 -0.90 0.18 8 -0.91 0.18 8 -1.15 0.20 7 -0.95 0.22 7 -0.54 0.27 5 -0.56 0.29 5 0.19 0.48 3 GUINEA-BISSAU GNB -1.10 0.20 6 -1.00 0.20 6 -1.12 0.20 6 -1.14 0.20 6 -0.89 0.22 5 -0.97 0.25 5 -1.28 0.27 5 -1.34 0.29 5 0.13 0.60 2 GUYANA GUY -0.46 0.20 8 -0.44 0.20 8 -0.42 0.21 7 -0.26 0.22 6 -0.23 0.23 5 -0.41 0.27 4 -0.17 0.31 4 -0.01 0.34 4 0.21 0.48 3 HAITI HTI -0.86 0.20 7 -0.87 0.20 7 -1.24 0.20 7 -1.31 0.20 7 -1.08 0.20 7 -1.03 0.23 6 -0.97 0.31 4 -0.88 0.34 4 -1.10 0.48 3 HONDURAS HND -0.22 0.19 10 -0.40 0.18 10 -0.47 0.18 9 -0.34 0.18 9 -0.51 0.18 8 -0.40 0.21 8 -0.30 0.24 6 -0.12 0.30 5 -0.36 0.33 5 HONG KONG HKG 1.89 0.21 9 1.90 0.20 9 1.83 0.20 8 1.82 0.20 8 1.74 0.19 8 1.55 0.21 8 1.70 0.22 7 1.71 0.25 7 1.54 0.24 6 HUNGARY HUN 1.15 0.17 13 1.16 0.16 13 1.11 0.16 12 1.14 0.17 12 1.06 0.16 12 1.24 0.18 12 0.96 0.19 10 0.99 0.22 9 0.67 0.23 8 ICELAND ISL 1.57 0.22 7 1.60 0.21 7 1.64 0.22 6 1.68 0.23 6 1.65 0.21 6 1.46 0.24 5 1.50 0.25 5 1.25 0.29 5 0.35 0.28 4 INDIA IND -0.22 0.17 12 -0.19 0.17 12 -0.21 0.17 11 -0.35 0.17 11 -0.33 0.17 10 -0.35 0.19 10 -0.11 0.20 8 -0.39 0.23 8 -0.01 0.23 7 INDONESIA IDN -0.30 0.17 13 -0.31 0.17 13 -0.48 0.17 12 -0.63 0.17 12 -0.65 0.16 11 -0.71 0.19 11 -0.31 0.20 9 -0.27 0.23 8 0.35 0.23 7 IRAN IRN -1.61 0.19 9 -1.55 0.19 10 -1.46 0.18 9 -1.26 0.18 9 -1.11 0.18 8 -1.28 0.21 8 -1.54 0.28 5 -1.54 0.30 5 -1.72 0.34 4 IRAQ IRQ -1.35 0.23 6 -1.47 0.22 6 -1.59 0.20 6 -1.73 0.21 6 -1.42 0.20 6 -2.21 0.23 6 -2.41 0.28 5 -2.76 0.30 5 -2.95 0.34 4 IRELAND IRL 1.84 0.21 9 1.87 0.20 9 1.59 0.20 8 1.63 0.20 8 1.66 0.19 8 1.73 0.22 7 1.77 0.22 7 1.62 0.25 7 1.23 0.24 6 ISRAEL ISR 1.04 0.21 9 0.98 0.20 9 0.86 0.20 8 0.83 0.20 8 0.91 0.19 8 0.93 0.21 8 1.14 0.22 7 1.02 0.25 7 1.01 0.24 6 ITALY ITA 0.81 0.21 9 0.85 0.20 9 0.89 0.20 8 1.05 0.20 8 1.02 0.19 8 0.95 0.21 8 0.92 0.22 7 0.84 0.25 7 0.64 0.24 6 JAMAICA JAM 0.31 0.19 8 0.27 0.19 9 0.25 0.18 9 0.20 0.18 9 0.19 0.18 8 0.22 0.21 8 0.20 0.24 6 0.20 0.30 5 0.61 0.41 4 JAPAN JPN 1.05 0.21 9 1.19 0.20 9 1.17 0.20 8 1.12 0.20 8 1.00 0.19 8 0.58 0.21 8 0.83 0.22 7 0.65 0.25 7 0.50 0.24 6 JORDAN JOR 0.35 0.17 12 0.40 0.17 12 0.25 0.17 11 0.36 0.17 11 0.22 0.17 10 0.09 0.20 9 0.32 0.23 7 0.47 0.25 7 0.29 0.29 6 KAZAKHSTAN KAZ -0.45 0.17 12 -0.49 0.17 13 -0.45 0.17 12 -0.60 0.17 11 -0.69 0.17 10 -0.84 0.20 10 -0.65 0.21 9 -0.41 0.25 7 -0.43 0.38 4 KENYA KEN -0.21 0.16 12 -0.26 0.16 12 -0.25 0.16 11 -0.27 0.16 11 -0.15 0.17 10 -0.26 0.20 9 -0.32 0.23 7 -0.37 0.24 7 -0.36 0.33 5 KIRIBATI KIR -1.10 0.28 3 -1.01 0.28 3 -0.99 0.27 3 -0.53 0.27 3 -0.86 0.42 2 -1.04 0.54 2 -1.01 0.51 2 -1.03 0.60 1 -0.27 0.81 1 KOREA, NORTH PRK -2.26 0.25 4 -2.29 0.22 6 -2.24 0.20 6 -2.26 0.20 6 -2.02 0.22 4 -1.93 0.26 4 -2.15 0.36 3 -2.18 0.38 3 -2.23 0.53 2 KOREA, SOUTH KOR 0.88 0.18 11 0.70 0.18 11 0.79 0.17 10 0.79 0.18 10 0.68 0.17 10 0.78 0.19 10 0.58 0.20 8 0.33 0.23 8 0.46 0.24 6 KUWAIT KWT 0.29 0.20 9 0.43 0.21 8 0.53 0.21 7 0.60 0.22 6 0.38 0.21 6 0.41 0.23 7 -0.05 0.28 5 -0.02 0.30 5 -0.04 0.34 4 KYRGYZSTAN KGZ -0.40 0.18 12 -0.60 0.18 12 -0.72 0.19 11 -0.34 0.19 10 -0.22 0.19 9 -0.19 0.23 9 -0.23 0.26 7 -0.33 0.28 5 -0.52 0.43 3 LAOS LAO -1.08 0.20 9 -1.15 0.20 9 -1.20 0.21 8 -1.23 0.21 7 -1.37 0.21 6 -1.31 0.26 6 -1.48 0.31 4 -1.03 0.35 3 -1.62 0.57 2 LATVIA LVA 1.06 0.18 11 1.07 0.17 11 1.01 0.17 11 1.02 0.17 11 1.05 0.17 11 0.94 0.19 11 0.68 0.21 9 0.87 0.25 7 0.86 0.34 5 LEBANON LBN -0.21 0.19 10 -0.20 0.19 10 -0.19 0.18 9 -0.12 0.18 9 -0.19 0.18 8 -0.33 0.20 9 -0.28 0.26 6 -0.12 0.27 6 0.02 0.33 5 LESOTHO LSO -0.69 0.18 9 -0.58 0.18 9 -0.61 0.20 7 -0.58 0.21 7 -0.58 0.22 6 -0.37 0.26 5 -0.37 0.27 4 -0.41 0.29 4 -0.62 0.57 2 LIBERIA LBR -1.24 0.22 4 -1.40 0.21 4 -1.62 0.20 4 -1.86 0.20 5 -1.75 0.22 4 -1.79 0.25 4 -1.86 0.29 4 -2.06 0.30 4 -3.13 0.60 2 LIBYA LBY -0.98 0.21 8 -1.28 0.21 7 -1.29 0.20 7 -1.23 0.20 7 -1.60 0.19 7 -1.66 0.22 7 -1.82 0.28 5 -2.20 0.30 5 -2.10 0.34 4 LIECHTENSTEIN LIE 1.35 0.39 1 1.33 0.35 1 1.58 0.31 1 1.51 0.33 1 1.63 0.30 1 1.66 0.37 1 1.48 0.43 1 1.51 0.46 1 .. .. .. LITHUANIA LTU 1.12 0.17 13 1.05 0.18 11 1.12 0.17 11 1.16 0.17 11 1.10 0.17 11 1.09 0.19 11 0.72 0.21 9 0.79 0.25 7 0.74 0.34 5 LUXEMBOURG LUX 1.89 0.22 7 1.84 0.21 7 1.79 0.22 6 1.93 0.23 6 1.94 0.21 6 2.01 0.25 5 1.94 0.25 5 1.51 0.29 5 1.20 0.28 4 MACAO MAC 0.85 0.39 1 1.09 0.35 1 1.09 0.31 1 1.54 0.33 1 1.14 0.30 1 0.68 0.37 1 0.50 0.43 1 0.53 0.46 1 .. .. .. MACEDONIA MKD 0.08 0.18 11 -0.05 0.18 11 -0.17 0.18 11 -0.07 0.18 11 -0.26 0.18 10 -0.20 0.22 8 -0.13 0.26 5 -0.17 0.29 4 -0.29 0.51 3 MADAGASCAR MDG -0.20 0.16 12 -0.24 0.16 12 -0.32 0.17 9 -0.34 0.18 9 -0.24 0.19 8 -0.29 0.22 6 -0.56 0.27 5 -0.80 0.29 5 -0.52 0.48 3 MALAWI MWI -0.51 0.17 10 -0.67 0.16 11 -0.57 0.16 10 -0.55 0.17 10 -0.45 0.18 9 -0.54 0.20 8 -0.20 0.24 6 -0.14 0.26 6 -0.21 0.41 4 MALAYSIA MYS 0.53 0.18 11 0.51 0.17 12 0.52 0.17 11 0.48 0.17 11 0.67 0.17 10 0.48 0.19 10 0.38 0.20 8 0.58 0.23 8 0.68 0.23 7 MALDIVES MDV -0.04 0.27 4 0.25 0.27 4 0.36 0.26 4 -0.12 0.26 4 0.57 0.25 3 0.76 0.32 3 0.69 0.34 3 0.85 0.38 2 0.27 0.81 1 MALI MLI -0.33 0.17 11 -0.42 0.17 11 -0.46 0.17 9 -0.48 0.18 9 -0.45 0.19 8 -0.40 0.22 7 -0.17 0.27 5 -0.28 0.29 5 -0.01 0.48 3 MALTA MLT 1.29 0.23 6 1.25 0.22 6 1.15 0.23 5 1.26 0.24 5 1.27 0.23 5 1.06 0.29 3 1.09 0.36 3 1.01 0.38 3 0.80 0.53 2 MARSHALL ISLANDS MHL -0.91 0.39 2 -0.96 0.45 2 -0.77 0.47 2 -0.83 0.42 2 -0.50 0.42 2 -0.52 0.54 2 -0.70 0.51 2 -0.84 0.60 1 .. .. .. MARTINIQUE MTQ 0.85 0.39 1 0.84 0.35 1 0.85 0.31 1 0.77 0.33 1 0.90 0.30 1 0.93 0.37 1 0.99 0.43 1 1.02 0.46 1 .. .. .. MAURITANIA MRT -0.36 0.18 10 -0.29 0.18 9 -0.17 0.21 6 -0.05 0.21 6 -0.08 0.23 5 0.25 0.27 4 -0.41 0.27 4 -0.55 0.29 4 -0.86 0.57 2 MAURITIUS MUS 0.57 0.17 10 0.54 0.17 10 0.38 0.18 8 0.37 0.18 8 0.68 0.21 6 0.60 0.23 6 0.60 0.25 5 0.33 0.31 4 0.12 0.56 2 MEXICO MEX 0.39 0.17 12 0.39 0.17 12 0.33 0.17 11 0.45 0.17 11 0.37 0.17 10 0.46 0.19 10 0.37 0.20 8 0.37 0.23 8 0.64 0.23 7 MICRONESIA FSM -0.39 0.28 3 0.13 0.28 3 0.16 0.27 3 0.00 0.27 3 -0.47 0.42 2 -0.62 0.54 2 -0.90 0.51 2 -0.84 0.60 1 .. .. .. MOLDOVA MDA -0.31 0.17 12 -0.40 0.17 12 -0.49 0.17 12 -0.56 0.17 11 -0.60 0.17 10 -0.45 0.20 9 -0.43 0.23 8 -0.23 0.25 7 0.14 0.34 5 MONGOLIA MNG -0.34 0.18 11 -0.29 0.18 11 -0.37 0.19 9 -0.47 0.20 8 -0.37 0.20 7 -0.10 0.24 6 -0.11 0.30 5 -0.11 0.34 4 -0.76 0.48 3 MONTENEGRO MNP -0.26 0.24 6 -0.52 0.24 6 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. MOROCCO MAR -0.11 0.16 12 -0.15 0.16 12 -0.33 0.16 11 -0.22 0.16 11 -0.18 0.17 10 -0.11 0.19 10 0.00 0.23 7 0.01 0.24 7 0.15 0.33 5 MOZAMBIQUE MOZ -0.49 0.16 12 -0.53 0.16 12 -0.59 0.16 11 -0.47 0.16 11 -0.41 0.17 10 -0.27 0.20 8 -0.19 0.24 6 -0.32 0.26 6 -1.00 0.41 4 MYANMAR MMR -2.23 0.22 7 -2.25 0.20 8 -2.24 0.19 8 -2.32 0.19 8 -2.02 0.19 7 -2.07 0.22 7 -1.90 0.28 5 -1.54 0.30 5 -1.09 0.34 4 NAMIBIA NAM 0.02 0.17 10 0.10 0.17 10 0.07 0.16 11 0.10 0.16 11 0.30 0.17 10 0.42 0.19 10 0.25 0.24 6 0.18 0.26 6 0.06 0.41 4 NAURU NRU -0.72 0.61 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. NEPAL NPL -0.65 0.20 9 -0.62 0.20 9 -0.61 0.19 9 -0.55 0.19 8 -0.52 0.21 6 -0.55 0.26 6 -0.55 0.31 4 -0.42 0.35 3 -0.72 0.57 2 NETHERLANDS NLD 1.80 0.21 8 1.72 0.21 8 1.70 0.20 8 1.80 0.20 8 1.76 0.19 8 1.88 0.21 8 2.01 0.22 7 1.83 0.25 7 1.30 0.24 6 NETHERLANDS ANTILLES ANT 0.85 0.39 1 0.84 0.35 1 0.85 0.31 1 0.61 0.33 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. NEW CALEDONIA NCL 0.29 0.70 1 0.03 0.70 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.37 0.70 1 NEW ZEALAND NZL 1.74 0.21 9 1.73 0.20 9 1.68 0.20 8 1.80 0.20 8 1.71 0.19 8 1.62 0.22 7 1.56 0.22 7 1.88 0.25 7 1.58 0.24 6 NICARAGUA NIC -0.40 0.19 10 -0.45 0.18 10 -0.38 0.18 9 -0.30 0.18 9 -0.36 0.18 8 -0.41 0.21 8 -0.13 0.24 6 0.01 0.30 5 -0.17 0.33 5 89 TABLE C4: Regulatory Quality (cont.) 2007 2006 2005 2004 2003 2002 2000 1998 1996 Country Code Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. NIGER NER -0.56 0.17 10 -0.60 0.17 10 -0.48 0.18 8 -0.56 0.18 8 -0.69 0.20 7 -0.66 0.22 6 -0.61 0.27 5 -0.68 0.29 5 -1.19 0.48 3 NIGERIA NGA -0.89 0.16 12 -0.96 0.16 12 -0.89 0.16 11 -1.30 0.16 11 -1.16 0.17 10 -1.20 0.19 10 -0.67 0.21 8 -0.93 0.24 7 -1.13 0.33 5 NORWAY NOR 1.44 0.21 9 1.35 0.20 9 1.47 0.20 8 1.54 0.20 8 1.35 0.19 8 1.25 0.22 7 1.04 0.22 7 1.42 0.25 7 1.07 0.24 6 OMAN OMN 0.63 0.21 8 0.74 0.23 6 0.66 0.22 6 0.66 0.22 6 0.67 0.21 6 0.75 0.23 7 0.20 0.28 5 0.14 0.30 5 0.10 0.34 4 PAKISTAN PAK -0.56 0.18 12 -0.44 0.18 12 -0.59 0.18 11 -0.89 0.17 11 -0.73 0.17 10 -0.80 0.21 9 -0.70 0.25 7 -0.47 0.27 6 -0.38 0.33 5 PANAMA PAN 0.39 0.19 10 0.33 0.18 10 0.25 0.18 10 0.31 0.18 10 0.35 0.19 8 0.50 0.22 8 0.65 0.23 7 0.91 0.27 6 0.61 0.33 5 PAPUA NEW GUINEA PNG -0.51 0.19 9 -0.70 0.19 9 -0.88 0.19 9 -0.72 0.18 9 -0.67 0.18 8 -0.60 0.22 7 -0.51 0.25 7 -0.52 0.30 5 -0.63 0.41 4 PARAGUAY PRY -0.57 0.19 9 -0.64 0.19 9 -0.80 0.18 9 -0.72 0.18 9 -0.66 0.18 8 -0.55 0.21 8 -0.81 0.24 6 -0.67 0.30 5 0.83 0.41 4 PERU PER 0.20 0.18 11 0.10 0.18 11 0.08 0.18 10 0.21 0.18 10 0.08 0.18 9 0.08 0.20 9 0.45 0.23 7 0.57 0.25 7 0.57 0.29 6 PHILIPPINES PHL -0.13 0.17 12 -0.12 0.17 12 -0.05 0.17 11 -0.25 0.17 11 -0.06 0.17 10 -0.09 0.19 10 0.15 0.20 8 0.30 0.23 8 0.53 0.23 7 POLAND POL 0.71 0.17 13 0.68 0.16 13 0.79 0.16 12 0.78 0.17 12 0.65 0.16 12 0.70 0.18 12 0.64 0.19 10 0.69 0.22 9 0.62 0.23 8 PORTUGAL PRT 1.05 0.21 9 1.04 0.20 9 1.20 0.20 8 1.19 0.20 8 1.22 0.19 8 1.30 0.22 7 0.98 0.22 7 1.17 0.25 7 1.03 0.24 6 PUERTO RICO PRI 0.85 0.29 4 0.94 0.30 3 1.01 0.28 3 0.84 0.29 3 1.10 0.27 3 1.22 0.34 2 1.28 0.38 2 1.28 0.39 2 0.93 0.50 1 QATAR QAT 0.55 0.23 7 0.38 0.22 7 0.33 0.21 7 0.31 0.22 6 0.28 0.21 6 0.31 0.24 6 0.10 0.28 5 0.21 0.30 5 0.34 0.38 3 REUNION REU 1.10 0.39 1 1.09 0.35 1 1.09 0.31 1 1.16 0.33 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ROMANIA ROM 0.48 0.17 13 0.41 0.16 13 0.17 0.16 13 0.16 0.16 13 -0.11 0.16 12 0.02 0.19 11 -0.10 0.21 9 0.20 0.25 7 -0.24 0.32 6 RUSSIA RUS -0.44 0.17 13 -0.57 0.16 13 -0.33 0.16 12 -0.24 0.17 12 -0.37 0.16 12 -0.45 0.18 12 -0.78 0.19 10 -0.51 0.22 9 -0.39 0.23 8 RWANDA RWA -0.63 0.19 7 -0.54 0.18 7 -0.81 0.19 6 -0.57 0.20 6 -0.73 0.22 5 -0.75 0.25 5 -1.05 0.27 4 -1.08 0.29 4 -1.79 0.57 2 SAMOA SAM -0.08 0.28 3 -0.04 0.28 3 0.01 0.27 3 -0.04 0.27 3 0.03 0.25 3 -0.02 0.32 3 0.03 0.31 4 -0.21 0.35 3 -0.10 0.57 2 SAO TOME ANDPRINCIPE STP -0.76 0.21 4 -0.73 0.21 5 -0.85 0.22 4 -0.84 0.23 4 -0.63 0.25 3 -0.49 0.29 3 -0.89 0.29 3 -1.17 0.31 3 -0.27 0.81 1 SAUDI ARABIA SAU -0.10 0.20 9 -0.18 0.20 8 0.02 0.20 7 -0.02 0.20 7 -0.01 0.19 7 -0.09 0.21 8 -0.09 0.28 5 -0.18 0.30 5 -0.38 0.34 4 SENEGAL SEN -0.35 0.16 12 -0.32 0.17 11 -0.31 0.17 9 -0.28 0.17 9 -0.23 0.18 9 -0.23 0.20 8 -0.07 0.24 6 -0.19 0.26 6 -0.36 0.41 4 SERBIA YUG -0.34 0.18 10 -0.38 0.18 10 -0.53 0.17 10 -0.48 0.18 10 -0.63 0.17 10 -0.61 0.20 10 -0.70 0.33 4 -0.82 0.36 3 -1.28 0.48 3 SEYCHELLES SYC -0.63 0.21 5 -0.59 0.21 5 -0.61 0.20 6 -0.69 0.20 6 -0.26 0.24 4 -0.65 0.29 3 -0.70 0.29 3 -0.48 0.31 3 -1.36 0.81 1 SIERRA LEONE SLE -1.01 0.18 8 -1.07 0.18 8 -1.04 0.18 7 -1.02 0.19 7 -1.27 0.20 6 -1.29 0.22 6 -1.37 0.29 4 -1.29 0.29 5 -0.92 0.48 3 SINGAPORE SGP 1.87 0.19 10 1.76 0.18 10 1.80 0.18 9 1.82 0.19 9 1.84 0.18 9 1.89 0.20 9 1.96 0.22 7 2.03 0.25 7 1.66 0.24 6 SLOVAKIA SVK 0.99 0.17 12 1.10 0.17 12 1.16 0.16 12 1.12 0.17 12 0.96 0.16 12 0.91 0.18 12 0.48 0.19 10 0.46 0.24 8 0.39 0.28 7 SLOVENIA SVN 0.81 0.17 12 0.81 0.18 11 0.82 0.17 11 0.85 0.18 11 0.87 0.16 12 0.84 0.18 12 0.70 0.19 10 1.07 0.25 7 0.84 0.34 5 SOLOMONISLANDS SLB -1.14 0.27 4 -1.13 0.28 3 -1.06 0.27 3 -1.39 0.27 3 -2.66 0.42 2 -1.73 0.54 2 -1.44 0.51 2 -1.22 0.60 1 -1.09 0.81 1 SOMALIA SOM -2.72 0.22 4 -2.70 0.21 4 -2.34 0.20 5 -2.32 0.20 5 -2.14 0.22 4 -2.15 0.27 3 -2.50 0.34 3 -2.45 0.34 4 -2.91 0.48 3 SOUTHAFRICA ZAF 0.48 0.16 12 0.62 0.16 12 0.53 0.16 12 0.57 0.16 12 0.60 0.16 11 0.55 0.18 11 0.43 0.19 9 0.24 0.21 9 0.04 0.23 7 SPAIN ESP 1.15 0.21 9 1.11 0.20 9 1.23 0.20 8 1.29 0.20 8 1.29 0.19 8 1.35 0.21 8 1.30 0.22 7 1.26 0.25 7 0.88 0.24 6 SRI LANKA LKA -0.11 0.18 12 -0.10 0.18 12 -0.21 0.18 11 0.02 0.17 11 0.13 0.17 10 0.21 0.20 10 0.25 0.23 8 0.29 0.27 6 0.46 0.33 5 ST. KITTS AND NEVIS KNA 0.67 0.31 2 0.98 0.30 2 1.05 0.27 3 0.06 0.27 3 0.21 0.52 1 0.17 0.56 1 0.23 0.53 1 0.30 0.60 1 0.00 0.81 1 ST. LUCIA LCA 0.77 0.31 2 1.07 0.30 2 1.05 0.27 3 0.15 0.27 3 0.21 0.52 1 0.17 0.56 1 0.23 0.53 1 0.30 0.60 1 0.00 0.81 1 ST. VINCENT ANDTHE GRENADINES VCT 0.77 0.31 2 0.89 0.30 2 1.01 0.27 3 0.14 0.27 3 0.21 0.52 1 0.17 0.56 1 0.23 0.53 1 0.30 0.60 1 0.00 0.81 1 SUDAN SDN -1.25 0.17 9 -1.16 0.17 9 -1.25 0.17 9 -1.13 0.17 9 -1.20 0.18 8 -1.18 0.21 8 -1.32 0.24 6 -1.35 0.26 6 -1.88 0.41 4 SURINAME SUR -0.40 0.25 5 -0.40 0.23 6 -0.50 0.24 5 -0.52 0.24 5 -0.48 0.24 4 -0.72 0.29 3 -0.64 0.36 3 -0.57 0.38 3 -0.55 0.53 2 SWAZILAND SWZ -0.66 0.19 8 -0.57 0.19 8 -0.60 0.20 7 -0.63 0.21 7 -0.53 0.22 6 -0.23 0.26 5 -0.44 0.27 4 -0.42 0.29 4 0.14 0.57 2 SWEDEN SWE 1.64 0.21 9 1.53 0.20 9 1.54 0.20 8 1.73 0.20 8 1.69 0.19 8 1.63 0.22 7 1.45 0.22 7 1.25 0.25 7 1.08 0.24 6 SWITZERLAND CHE 1.56 0.21 8 1.44 0.21 8 1.46 0.20 8 1.59 0.20 8 1.62 0.19 8 1.69 0.22 7 1.75 0.22 7 1.58 0.25 7 1.09 0.24 6 SYRIA SYR -1.22 0.18 11 -1.32 0.19 10 -1.12 0.19 8 -1.02 0.19 8 -0.76 0.19 7 -0.94 0.22 7 -1.12 0.28 5 -1.17 0.30 5 -0.91 0.34 4 TAIWAN TWN 0.94 0.19 10 0.92 0.18 10 1.08 0.18 9 1.15 0.19 9 0.95 0.18 9 0.99 0.20 9 1.13 0.22 7 1.04 0.25 7 0.85 0.24 6 TAJIKISTAN TJK -1.02 0.18 12 -1.05 0.18 12 -1.03 0.19 11 -1.08 0.19 10 -1.10 0.19 9 -1.30 0.23 9 -1.26 0.26 6 -1.73 0.28 5 -2.28 0.43 3 TANZANIA TZA -0.37 0.16 11 -0.40 0.16 11 -0.45 0.16 11 -0.41 0.16 11 -0.43 0.17 10 -0.56 0.20 9 -0.23 0.23 7 -0.31 0.24 7 -0.06 0.33 5 THAILAND THA 0.11 0.18 11 0.23 0.17 12 0.41 0.17 11 0.23 0.17 11 0.25 0.17 10 0.16 0.19 10 0.46 0.20 8 0.16 0.23 8 0.45 0.23 7 TIMOR-LESTE TMP -1.59 0.26 4 -1.49 0.26 4 -1.12 0.27 3 -1.09 0.29 3 -1.29 0.27 2 -1.29 0.37 1 .. .. .. .. .. .. .. .. .. TOGO TGO -0.98 0.17 9 -0.99 0.17 10 -0.86 0.18 8 -0.77 0.18 8 -0.74 0.20 7 -0.72 0.22 6 -0.67 0.27 5 -0.52 0.29 5 0.58 0.60 2 TONGA TON -0.75 0.28 3 -0.77 0.28 3 -0.69 0.27 3 -0.78 0.27 3 -1.19 0.42 2 -1.13 0.54 2 -0.67 0.51 2 -1.22 0.60 1 0.00 0.81 1 TRINIDAD AND TOBAGO TTO 0.68 0.21 8 0.70 0.20 8 0.64 0.19 9 0.68 0.20 8 0.73 0.20 7 0.73 0.23 6 0.67 0.24 6 0.69 0.30 5 0.73 0.41 4 TUNISIA TUN 0.15 0.16 12 0.14 0.16 12 -0.07 0.16 11 0.09 0.16 11 0.08 0.17 10 -0.05 0.19 10 0.07 0.23 7 0.08 0.24 7 0.56 0.33 5 TURKEY TUR 0.23 0.17 13 0.19 0.17 13 0.18 0.17 12 0.05 0.17 12 0.08 0.17 11 0.04 0.19 11 0.23 0.20 9 0.49 0.23 8 0.54 0.23 7 TURKMENISTAN TKM -2.02 0.19 8 -2.19 0.19 8 -2.07 0.19 8 -1.96 0.20 7 -1.77 0.20 7 -1.95 0.23 7 -1.97 0.26 5 -2.20 0.28 5 -2.67 0.43 3 TUVALU TUV -0.87 0.34 2 -0.78 0.33 2 -0.49 0.30 2 -0.06 0.31 2 0.23 0.57 1 0.26 0.92 1 0.36 0.94 1 .. .. .. .. .. .. UGANDA UGA -0.20 0.16 12 -0.16 0.16 12 0.04 0.16 11 -0.06 0.16 11 -0.10 0.17 10 -0.10 0.20 9 -0.02 0.23 7 0.08 0.24 7 0.28 0.33 5 UKRAINE UKR -0.42 0.17 13 -0.48 0.17 12 -0.30 0.17 11 -0.46 0.17 11 -0.66 0.17 11 -0.65 0.19 11 -0.62 0.21 9 -0.82 0.24 8 -0.50 0.29 6 UNITEDARAB EMIRATES ARE 0.70 0.21 8 0.71 0.20 8 0.42 0.19 8 0.84 0.19 8 0.82 0.21 6 1.07 0.23 7 0.69 0.28 5 0.60 0.30 5 0.53 0.34 4 UNITEDKINGDOM GBR 1.86 0.21 9 1.88 0.20 9 1.57 0.20 8 1.78 0.20 8 1.66 0.19 8 1.71 0.21 8 1.73 0.22 7 1.89 0.25 7 1.48 0.24 6 UNITEDSTATES USA 1.45 0.21 9 1.54 0.20 9 1.54 0.20 8 1.51 0.20 8 1.49 0.19 8 1.48 0.21 8 1.61 0.22 7 1.57 0.25 7 1.26 0.24 6 URUGUAY URY 0.16 0.19 9 0.25 0.19 9 0.27 0.18 10 0.29 0.18 10 0.31 0.18 9 0.52 0.20 9 0.75 0.23 7 0.88 0.27 6 0.86 0.33 5 UZBEKISTAN UZB -1.45 0.18 12 -1.71 0.18 11 -1.71 0.18 10 -1.70 0.18 10 -1.49 0.18 10 -1.57 0.21 10 -1.99 0.27 7 -2.10 0.30 5 -1.74 0.38 4 VANUATU VUT -0.48 0.28 3 -0.11 0.28 3 0.05 0.27 3 -0.44 0.27 3 -1.31 0.42 2 -1.14 0.54 2 -0.44 0.51 2 -0.46 0.60 1 0.00 0.81 1 VENEZUELA VEN -1.56 0.17 12 -1.26 0.17 12 -1.21 0.17 11 -1.13 0.17 11 -1.13 0.17 10 -0.60 0.19 10 -0.42 0.20 8 -0.15 0.23 8 -0.10 0.23 7 VIETNAM VNM -0.43 0.18 12 -0.58 0.18 12 -0.57 0.18 11 -0.49 0.17 11 -0.56 0.17 10 -0.71 0.20 10 -0.68 0.23 8 -0.61 0.25 7 -0.32 0.29 6 VIRGINISLANDS (U.S.) VIR 0.60 0.39 1 0.60 0.35 1 1.09 0.31 1 1.23 0.33 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. WEST BANK GAZA WBG -1.38 0.34 2 -1.17 0.32 2 -1.03 0.29 3 -0.71 0.29 3 -1.10 0.28 2 -1.01 0.36 2 -0.97 0.43 1 -0.94 0.46 1 .. .. .. YEMEN YEM -0.71 0.19 10 -0.75 0.19 10 -0.79 0.19 8 -0.87 0.19 8 -0.91 0.19 7 -0.82 0.21 7 -0.65 0.27 5 -0.52 0.30 5 -0.44 0.41 4 ZAMBIA ZMB -0.48 0.16 11 -0.56 0.16 11 -0.60 0.17 10 -0.55 0.16 11 -0.58 0.17 10 -0.62 0.20 9 -0.16 0.23 7 -0.01 0.24 7 0.34 0.33 5 ZIMBABWE ZWE -2.24 0.16 12 -2.10 0.16 12 -2.33 0.16 11 -2.13 0.16 11 -2.17 0.17 10 -2.05 0.19 10 -1.44 0.21 8 -0.68 0.23 8 -0.81 0.29 6 90 TABLEC5:Ruleof Law 2007 2006 2005 2004 2003 2002 2000 1998 1996 Country Code Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. AFGHANISTAN AFG -2.00 0.24 9 -2.07 0.20 10 -1.89 0.20 8 -1.81 0.19 8 -1.77 0.22 6 -1.74 0.23 4 -2.02 0.23 3 -1.70 0.32 2 -1.34 0.77 1 ALBANIA ALB -0.70 0.15 14 -0.73 0.15 14 -0.80 0.16 12 -0.89 0.16 11 -1.03 0.17 10 -0.95 0.18 10 -1.10 0.18 9 -1.24 0.21 7 -0.12 0.28 5 ALGERIA DZA -0.72 0.13 17 -0.64 0.13 16 -0.72 0.14 15 -0.67 0.14 15 -0.69 0.14 12 -0.73 0.15 11 -1.08 0.15 9 -1.17 0.18 9 -1.21 0.23 6 AMERICANSAMOA ASM 1.16 0.35 1 1.14 0.37 1 1.14 0.33 1 0.86 0.30 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ANDORRA ADO 1.22 0.33 2 1.20 0.34 2 1.17 0.32 2 1.29 0.29 2 1.23 0.28 2 1.49 0.31 1 1.51 0.29 1 1.52 0.33 1 .. .. .. ANGOLA AGO -1.35 0.15 15 -1.28 0.14 16 -1.40 0.15 14 -1.35 0.14 14 -1.44 0.15 12 -1.46 0.16 11 -1.61 0.15 9 -1.56 0.18 9 -1.53 0.23 6 ANGUILLA AIA 1.70 0.35 1 1.66 0.37 1 1.67 0.33 1 1.16 0.30 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ANTIGUAAND BARBUDA ATG 0.98 0.33 2 0.97 0.34 2 0.66 0.31 3 0.91 0.28 3 0.98 0.28 2 0.96 0.31 1 0.98 0.29 1 1.00 0.33 1 .. .. .. ARGENTINA ARG -0.52 0.13 18 -0.53 0.12 18 -0.55 0.13 17 -0.73 0.13 17 -0.65 0.13 16 -0.89 0.14 14 -0.05 0.13 12 0.04 0.16 12 0.11 0.19 10 ARMENIA ARM -0.51 0.13 19 -0.54 0.13 19 -0.47 0.15 15 -0.58 0.15 14 -0.46 0.16 13 -0.48 0.16 12 -0.50 0.17 9 -0.41 0.19 8 -0.45 0.26 5 ARUBA ABW 0.89 0.35 1 0.87 0.37 1 0.88 0.33 1 0.93 0.30 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. AUSTRALIA AUS 1.79 0.14 13 1.79 0.14 13 1.73 0.14 13 1.80 0.14 13 1.81 0.14 13 1.75 0.15 10 1.74 0.14 10 1.77 0.16 10 1.81 0.19 9 AUSTRIA AUT 1.90 0.14 13 1.86 0.14 13 1.82 0.14 12 1.80 0.14 12 1.81 0.14 12 1.85 0.15 11 1.83 0.14 11 1.82 0.16 10 1.91 0.19 9 AZERBAIJAN AZE -0.83 0.13 19 -0.88 0.13 19 -0.80 0.13 17 -0.84 0.13 16 -0.84 0.14 15 -0.88 0.14 13 -1.06 0.14 11 -1.02 0.17 9 -0.94 0.21 6 BAHAMAS BHS 1.13 0.26 4 1.11 0.27 4 1.31 0.26 4 1.32 0.25 4 1.32 0.24 4 1.31 0.26 3 1.24 0.25 3 1.21 0.28 3 0.74 0.51 2 BAHRAIN BHR 0.66 0.15 12 0.59 0.15 12 0.70 0.15 12 0.85 0.15 12 0.73 0.15 11 0.76 0.15 11 0.56 0.16 8 0.64 0.19 7 0.17 0.23 6 BANGLADESH BGD -0.81 0.14 18 -0.82 0.14 17 -0.87 0.14 15 -0.95 0.14 15 -0.90 0.14 13 -0.79 0.14 13 -0.80 0.14 11 -0.85 0.18 8 -0.77 0.23 6 BARBADOS BRB 1.17 0.21 5 1.02 0.21 5 1.11 0.25 5 1.20 0.24 5 1.31 0.24 4 1.40 0.27 2 1.34 0.26 2 1.18 0.30 2 -0.24 0.62 1 BELARUS BLR -1.09 0.15 13 -1.22 0.16 13 -1.06 0.17 11 -1.24 0.16 11 -1.30 0.17 11 -1.25 0.18 10 -1.04 0.18 9 -0.73 0.21 7 -0.93 0.30 4 BELGIUM BEL 1.52 0.14 13 1.43 0.14 13 1.43 0.14 12 1.49 0.14 12 1.50 0.14 12 1.48 0.14 12 1.40 0.14 11 1.29 0.16 10 1.55 0.19 9 BELIZE BLZ 0.02 0.18 9 0.02 0.19 8 -0.02 0.22 7 0.05 0.21 7 0.20 0.22 6 -0.16 0.24 5 0.06 0.23 4 -0.08 0.27 4 0.79 0.54 2 BENIN BEN -0.56 0.15 15 -0.58 0.14 15 -0.63 0.18 11 -0.62 0.20 9 -0.55 0.21 8 -0.35 0.22 7 -0.26 0.22 6 -0.13 0.26 5 -0.30 0.54 2 BERMUDA BMU 0.89 0.35 1 0.87 0.37 1 0.88 0.33 1 1.11 0.30 1 1.20 0.30 1 1.22 0.31 1 1.25 0.29 1 1.26 0.33 1 .. .. .. BHUTAN BTN 0.49 0.23 7 0.60 0.24 7 0.58 0.23 7 0.42 0.22 7 0.44 0.24 5 0.18 0.24 4 0.22 0.23 4 0.29 0.29 3 -1.34 0.77 1 BOLIVIA BOL -0.96 0.14 18 -0.90 0.13 18 -0.87 0.14 16 -0.58 0.14 16 -0.47 0.14 13 -0.43 0.15 13 -0.39 0.14 10 -0.30 0.18 9 -0.29 0.23 7 BOSNIA-HERZEGOVINA BIH -0.52 0.14 15 -0.53 0.15 14 -0.62 0.14 13 -0.63 0.14 13 -0.86 0.15 11 -0.74 0.16 11 -0.64 0.16 8 -0.65 0.20 6 -0.03 0.32 2 BOTSWANA BWA 0.67 0.14 15 0.63 0.14 15 0.66 0.15 13 0.66 0.14 13 0.65 0.15 12 0.58 0.15 12 0.57 0.16 8 0.55 0.19 8 0.62 0.26 5 BRAZIL BRA -0.44 0.12 20 -0.45 0.12 20 -0.45 0.13 17 -0.34 0.13 17 -0.34 0.13 16 -0.35 0.14 15 -0.28 0.13 13 -0.28 0.16 12 -0.21 0.19 10 BRUNEI BRN 0.30 0.30 3 0.29 0.31 3 0.32 0.30 3 0.38 0.27 3 0.64 0.27 3 0.51 0.28 4 0.56 0.26 3 0.59 0.30 3 0.62 0.58 2 BULGARIA BGR -0.14 0.12 18 -0.19 0.12 18 -0.19 0.14 14 -0.06 0.13 14 -0.10 0.14 14 -0.02 0.14 14 -0.14 0.14 12 -0.23 0.17 9 -0.11 0.20 7 BURKINAFASO BFA -0.48 0.14 16 -0.50 0.14 16 -0.58 0.19 11 -0.58 0.19 11 -0.58 0.20 9 -0.59 0.21 8 -0.54 0.22 7 -0.71 0.25 6 -0.31 0.46 3 BURUNDI BDI -1.16 0.15 14 -1.04 0.15 13 -1.20 0.20 9 -1.51 0.22 8 -1.42 0.22 7 -1.42 0.24 6 -1.45 0.24 4 -1.42 0.26 5 -0.88 0.54 2 CAMBODIA KHM -1.06 0.14 15 -1.14 0.14 15 -1.14 0.15 13 -1.20 0.16 12 -1.17 0.16 11 -1.11 0.16 10 -0.93 0.16 8 -1.02 0.19 6 -1.09 0.26 4 CAMEROON CMR -1.09 0.14 16 -1.03 0.14 15 -1.07 0.15 13 -1.18 0.16 12 -1.04 0.15 12 -1.18 0.16 11 -1.19 0.16 9 -1.17 0.19 8 -1.50 0.26 5 CANADA CAN 1.86 0.13 16 1.83 0.13 15 1.75 0.14 12 1.79 0.14 12 1.77 0.14 12 1.74 0.14 12 1.73 0.14 11 1.78 0.16 10 1.76 0.19 9 CAPEVERDE CPV 0.62 0.18 8 0.61 0.18 8 0.36 0.21 7 0.31 0.20 7 0.17 0.21 6 0.16 0.22 5 0.78 0.35 3 0.84 0.40 3 0.51 0.62 1 CAYMAN ISLANDS CYM 1.16 0.35 1 1.14 0.37 1 0.88 0.33 1 1.16 0.30 1 1.20 0.30 1 1.49 0.31 1 1.51 0.29 1 1.52 0.33 1 .. .. .. CENTRALAFRICANREPUBLICCAF -1.52 0.20 9 -1.53 0.20 8 -1.50 0.20 9 -1.70 0.20 8 -1.73 0.21 7 -1.17 0.22 6 -1.45 0.24 4 -1.48 0.28 4 -0.28 0.77 1 CHAD TCD -1.40 0.15 13 -1.38 0.15 13 -1.33 0.18 10 -1.14 0.19 10 -1.07 0.20 8 -0.80 0.21 7 -0.91 0.22 5 -0.97 0.26 5 -0.88 0.54 2 CHILE CHL 1.17 0.13 18 1.16 0.12 18 1.16 0.13 16 1.16 0.13 16 1.15 0.13 15 1.19 0.14 14 1.22 0.13 12 1.11 0.16 12 1.22 0.19 10 CHINA CHN -0.45 0.13 18 -0.48 0.13 17 -0.42 0.13 16 -0.38 0.13 16 -0.45 0.14 14 -0.37 0.14 14 -0.44 0.13 12 -0.38 0.16 11 -0.25 0.19 9 COLOMBIA COL -0.57 0.12 21 -0.59 0.12 20 -0.72 0.13 18 -0.82 0.13 18 -0.92 0.13 15 -0.92 0.14 15 -0.88 0.13 13 -0.75 0.16 12 -0.67 0.19 10 COMOROS COM -0.93 0.24 5 -0.90 0.24 5 -0.96 0.24 5 -0.97 0.24 5 -0.87 0.25 4 -1.05 0.26 3 -1.28 0.25 3 -1.28 0.28 3 .. .. .. CONGO COG -1.26 0.15 13 -1.24 0.15 11 -1.46 0.15 11 -1.24 0.18 9 -1.17 0.19 8 -1.26 0.19 8 -1.38 0.19 7 -1.48 0.22 7 -1.38 0.36 4 CONGO, DEM. REP. ZAR -1.67 0.17 13 -1.73 0.17 12 -1.72 0.16 12 -1.78 0.15 12 -1.85 0.17 10 -1.84 0.18 10 -1.99 0.18 8 -2.10 0.20 8 -2.06 0.31 5 COOKISLANDS COK 0.61 0.90 1 1.06 0.70 1 1.18 0.59 1 0.58 0.53 1 0.71 0.70 1 0.87 0.48 1 0.86 0.57 1 .. .. .. .. .. .. COSTARICA CRI 0.44 0.14 17 0.51 0.14 16 0.56 0.14 15 0.61 0.14 15 0.66 0.14 13 0.67 0.15 13 0.63 0.14 11 0.71 0.18 9 0.57 0.21 8 COTED'IVOIRE CIV -1.54 0.15 12 -1.51 0.15 12 -1.59 0.16 11 -1.49 0.16 12 -1.49 0.16 11 -1.32 0.16 11 -0.99 0.16 9 -0.90 0.19 8 -0.69 0.26 5 CROATIA HRV 0.03 0.13 16 -0.05 0.13 16 0.06 0.13 15 0.11 0.13 15 0.06 0.14 14 0.02 0.14 14 0.11 0.14 10 -0.16 0.17 9 -0.56 0.21 6 CUBA CUB -0.79 0.15 12 -0.79 0.16 12 -1.13 0.16 11 -1.10 0.15 11 -1.17 0.15 10 -1.02 0.16 10 -0.87 0.16 7 -0.77 0.19 7 -0.99 0.23 6 CYPRUS CYP 0.96 0.17 10 0.93 0.16 10 0.85 0.16 9 0.86 0.15 9 0.86 0.16 8 0.86 0.17 7 0.87 0.16 7 0.82 0.19 7 0.76 0.23 6 CZECHREPUBLIC CZE 0.77 0.12 18 0.73 0.12 17 0.74 0.13 15 0.70 0.12 16 0.80 0.13 16 0.74 0.13 16 0.69 0.13 14 0.82 0.15 12 0.87 0.17 10 DENMARK DNK 1.95 0.14 13 1.94 0.14 13 1.94 0.14 12 1.94 0.14 12 1.91 0.14 12 1.84 0.15 11 1.78 0.14 10 1.86 0.16 10 1.87 0.19 9 DJIBOUTI DJI -0.51 0.21 7 -0.64 0.22 7 -0.90 0.22 7 -0.75 0.22 6 -0.82 0.23 5 -0.77 0.23 4 -0.78 0.23 4 -0.71 0.26 4 -0.24 0.62 1 DOMINICA DMA 0.69 0.28 3 0.70 0.29 3 0.62 0.27 4 0.62 0.25 4 0.69 0.26 3 0.63 0.28 2 0.47 0.26 2 0.52 0.30 2 .. .. .. DOMINICANREPUBLIC DOM -0.55 0.14 17 -0.52 0.14 17 -0.67 0.14 15 -0.57 0.14 15 -0.49 0.15 12 -0.50 0.15 12 -0.50 0.15 9 -0.50 0.19 7 -0.56 0.25 5 ECUADOR ECU -1.04 0.14 18 -1.03 0.14 17 -0.88 0.14 16 -0.73 0.13 17 -0.67 0.14 14 -0.69 0.14 13 -0.68 0.14 11 -0.66 0.17 10 -0.42 0.21 8 EGYPT EGY -0.13 0.13 18 -0.14 0.13 18 0.03 0.13 16 0.03 0.13 16 -0.03 0.14 14 -0.05 0.14 13 -0.05 0.14 11 -0.12 0.16 11 0.08 0.20 8 ELSALVADOR SLV -0.68 0.16 14 -0.59 0.16 14 -0.44 0.15 13 -0.40 0.16 13 -0.47 0.17 11 -0.51 0.17 11 -0.72 0.16 9 -0.60 0.20 7 -0.91 0.25 6 EQUATORIALGUINEA GNQ -1.16 0.17 9 -1.24 0.17 9 -1.33 0.18 8 -1.28 0.17 9 -1.18 0.18 8 -1.19 0.18 7 -1.22 0.18 5 -1.34 0.21 5 -1.23 0.33 1 ERITREA ERI -1.10 0.18 8 -0.99 0.18 9 -0.72 0.22 8 -0.63 0.22 8 -0.40 0.23 6 -0.39 0.24 5 -0.42 0.24 4 -0.22 0.28 4 -0.28 0.77 1 ESTONIA EST 1.00 0.13 17 0.94 0.13 16 0.81 0.13 15 0.83 0.13 15 0.71 0.13 15 0.71 0.13 15 0.57 0.13 12 0.50 0.17 9 0.51 0.21 6 ETHIOPIA ETH -0.54 0.14 16 -0.56 0.14 16 -0.80 0.15 13 -0.68 0.16 13 -0.70 0.17 11 -0.78 0.17 10 -0.82 0.17 8 -0.71 0.20 7 -0.94 0.28 4 FIJI FJI -0.37 0.24 5 -0.07 0.25 5 -0.05 0.24 4 -0.05 0.23 4 -0.08 0.23 4 -0.37 0.24 4 -0.56 0.23 4 0.06 0.27 4 0.22 0.54 2 FINLAND FIN 1.87 0.14 13 1.93 0.14 13 1.90 0.14 12 1.90 0.14 12 1.88 0.14 12 1.86 0.14 12 1.89 0.14 10 1.90 0.16 10 1.90 0.19 9 FRANCE FRA 1.32 0.13 15 1.35 0.13 14 1.33 0.14 12 1.39 0.14 12 1.35 0.14 12 1.26 0.14 12 1.35 0.14 11 1.37 0.16 10 1.47 0.19 9 FRENCHGUIANA GUF 0.62 0.35 1 0.87 0.37 1 0.88 0.33 1 0.55 0.30 1 0.94 0.30 1 0.96 0.31 1 0.98 0.29 1 1.00 0.33 1 .. .. .. GABON GAB -0.60 0.14 13 -0.64 0.14 13 -0.51 0.15 12 -0.66 0.15 12 -0.53 0.15 11 -0.34 0.15 11 -0.32 0.15 10 -0.41 0.19 8 -0.93 0.25 5 GAMBIA GMB -0.21 0.17 10 -0.27 0.16 10 -0.25 0.19 9 -0.24 0.19 9 0.17 0.20 8 -0.27 0.22 7 -0.12 0.22 6 0.02 0.25 6 0.40 0.46 3 GEORGIA GEO -0.44 0.13 18 -0.56 0.13 17 -0.75 0.15 14 -0.77 0.14 14 -1.20 0.16 12 -1.24 0.16 11 -1.08 0.17 9 -1.18 0.20 7 -0.84 0.26 5 91 TABLE C5: Rule of Law (cont.) 2007 2006 2005 2004 2003 2002 2000 1998 1996 Country Code Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. GERMANY DEU 1.78 0.13 14 1.77 0.13 14 1.73 0.14 13 1.71 0.14 13 1.70 0.14 13 1.71 0.14 12 1.68 0.14 11 1.66 0.16 10 1.79 0.19 9 GHANA GHA -0.08 0.14 17 -0.08 0.14 17 -0.21 0.14 16 -0.29 0.14 16 -0.19 0.14 15 -0.17 0.15 13 -0.06 0.15 10 -0.44 0.18 9 -0.39 0.23 6 GREECE GRC 0.65 0.13 14 0.68 0.13 14 0.65 0.14 12 0.82 0.14 12 0.77 0.14 12 0.72 0.14 12 0.81 0.14 11 0.68 0.16 10 0.94 0.19 9 GRENADA GRD 0.19 0.28 3 0.18 0.28 4 0.29 0.27 4 0.26 0.25 4 0.28 0.26 3 0.21 0.28 2 0.27 0.26 2 0.27 0.30 2 .. .. .. GUAM GUM 1.16 0.35 1 1.14 0.37 1 1.14 0.33 1 1.01 0.30 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. GUATEMALA GTM -1.11 0.13 19 -1.07 0.13 19 -1.06 0.14 16 -1.02 0.15 16 -1.10 0.15 14 -0.86 0.16 12 -0.82 0.15 10 -0.95 0.19 8 -0.92 0.23 7 GUINEA GIN -1.47 0.16 12 -1.42 0.16 12 -1.27 0.19 10 -1.11 0.19 10 -1.01 0.20 9 -0.88 0.21 8 -1.34 0.22 6 -1.23 0.25 6 -1.39 0.46 3 GUINEA-BISSAU GNB -1.36 0.21 8 -1.29 0.21 8 -1.28 0.21 8 -1.14 0.21 7 -1.23 0.22 6 -1.12 0.22 6 -1.38 0.22 6 -1.89 0.25 6 -1.68 0.58 2 GUYANA GUY -0.57 0.16 13 -0.64 0.16 12 -0.75 0.19 10 -0.56 0.21 8 -0.53 0.21 7 -0.47 0.23 5 -0.47 0.22 5 -0.29 0.25 5 0.07 0.46 3 HAITI HTI -1.42 0.17 11 -1.53 0.17 11 -1.70 0.21 9 -1.74 0.20 10 -1.71 0.20 9 -1.88 0.20 8 -1.56 0.22 6 -1.40 0.25 5 -1.43 0.46 3 HONDURAS HND -0.86 0.14 17 -0.93 0.14 17 -0.76 0.14 15 -0.75 0.15 15 -0.84 0.15 12 -0.85 0.16 12 -0.92 0.15 10 -0.84 0.19 8 -0.75 0.23 7 HONG KONG HKG 1.40 0.14 12 1.46 0.14 12 1.47 0.15 10 1.37 0.15 10 1.30 0.15 10 1.10 0.15 10 0.91 0.14 9 1.06 0.17 8 1.14 0.21 7 HUNGARY HUN 0.74 0.12 18 0.76 0.12 18 0.71 0.12 16 0.82 0.12 16 0.82 0.13 16 0.84 0.13 16 0.82 0.13 14 0.74 0.15 12 0.84 0.17 10 ICELAND ISL 1.97 0.15 9 2.01 0.15 9 2.05 0.17 8 2.02 0.17 8 1.99 0.18 8 1.92 0.19 7 1.86 0.18 7 1.76 0.20 7 1.64 0.27 6 INDIA IND 0.10 0.13 18 0.16 0.12 18 0.13 0.13 16 0.05 0.13 16 0.03 0.13 15 0.01 0.14 14 0.19 0.13 12 0.16 0.16 11 0.29 0.19 9 INDONESIA IDN -0.71 0.13 20 -0.77 0.12 20 -0.86 0.13 18 -0.82 0.13 18 -0.97 0.13 17 -1.01 0.13 15 -0.82 0.13 13 -0.77 0.16 11 -0.37 0.19 9 IRAN IRN -0.84 0.14 15 -0.81 0.14 16 -0.76 0.15 14 -0.53 0.14 14 -0.54 0.14 12 -0.55 0.15 11 -0.38 0.15 8 -0.44 0.18 8 -0.98 0.21 7 IRAQ IRQ -1.89 0.18 8 -1.86 0.18 8 -1.88 0.17 8 -1.94 0.16 8 -1.72 0.16 8 -1.53 0.17 8 -1.39 0.16 7 -1.52 0.19 7 -1.61 0.23 6 IRELAND IRL 1.77 0.13 14 1.68 0.13 13 1.59 0.14 12 1.57 0.14 11 1.55 0.14 11 1.64 0.15 10 1.59 0.14 10 1.63 0.16 10 1.71 0.19 9 ISRAEL ISR 0.76 0.14 14 0.79 0.14 14 0.73 0.15 11 0.75 0.14 11 0.74 0.15 11 0.90 0.15 11 0.99 0.14 10 1.00 0.17 9 1.22 0.19 9 ITALY ITA 0.43 0.13 15 0.36 0.13 14 0.52 0.14 13 0.67 0.14 13 0.76 0.14 13 0.78 0.14 12 0.86 0.14 11 0.84 0.16 10 0.98 0.19 9 JAMAICA JAM -0.63 0.15 13 -0.59 0.15 14 -0.60 0.15 12 -0.53 0.15 12 -0.63 0.16 11 -0.51 0.16 11 -0.48 0.15 8 -0.35 0.19 7 -0.30 0.25 5 JAPAN JPN 1.39 0.13 15 1.42 0.13 14 1.35 0.14 13 1.32 0.14 13 1.31 0.14 13 1.30 0.14 12 1.43 0.14 11 1.47 0.16 10 1.53 0.19 9 JORDAN JOR 0.51 0.13 18 0.46 0.13 17 0.43 0.14 15 0.40 0.14 14 0.33 0.14 13 0.23 0.15 11 0.36 0.14 9 0.37 0.17 9 0.44 0.22 7 KAZAKHSTAN KAZ -0.83 0.12 19 -0.91 0.12 19 -0.80 0.13 17 -1.02 0.13 16 -1.01 0.14 15 -1.00 0.14 14 -0.90 0.13 13 -0.90 0.16 10 -0.83 0.20 6 KENYA KEN -0.98 0.13 19 -0.93 0.13 19 -0.99 0.14 17 -0.99 0.14 17 -1.06 0.14 16 -1.05 0.15 13 -0.98 0.15 9 -1.11 0.18 9 -1.06 0.23 6 KIRIBATI KIR 0.84 0.28 4 0.89 0.28 4 0.77 0.26 4 0.27 0.23 4 0.34 0.44 3 0.62 0.38 2 0.40 0.40 2 -0.69 0.58 1 .. .. .. KOREA, NORTH PRK -1.03 0.25 6 -1.22 0.20 8 -0.98 0.19 8 -1.09 0.19 8 -0.85 0.23 6 -1.02 0.24 6 -0.79 0.24 4 -0.91 0.27 4 -1.23 0.46 3 KOREA, SOUTH KOR 0.82 0.13 16 0.69 0.13 16 0.78 0.13 14 0.70 0.13 14 0.65 0.14 14 0.79 0.14 14 0.74 0.13 12 0.71 0.16 11 0.70 0.19 9 KOSOVO LWI -0.84 0.32 2 -0.92 0.32 2 -0.97 0.32 1 -0.99 0.29 1 -1.14 0.39 1 .. .. .. .. .. .. .. .. .. .. .. .. KUWAIT KWT 0.69 0.15 13 0.70 0.15 12 0.73 0.16 10 0.71 0.16 9 0.69 0.16 9 0.74 0.16 10 0.76 0.16 7 0.81 0.19 7 0.74 0.23 6 KYRGYZSTAN KGZ -1.19 0.13 18 -1.23 0.13 18 -1.08 0.15 15 -0.83 0.14 14 -0.82 0.16 13 -0.77 0.16 12 -0.87 0.16 10 -0.71 0.20 7 -0.64 0.28 4 LAOS LAO -0.96 0.16 14 -0.94 0.16 14 -1.03 0.18 12 -1.00 0.18 11 -1.11 0.19 9 -1.02 0.19 9 -0.94 0.19 7 -0.87 0.23 5 -1.64 0.39 3 LATVIA LVA 0.57 0.13 16 0.50 0.14 15 0.47 0.14 14 0.51 0.13 14 0.51 0.14 14 0.34 0.14 14 0.22 0.14 11 0.18 0.17 9 0.13 0.21 6 LEBANON LBN -0.66 0.15 15 -0.57 0.15 15 -0.33 0.16 12 -0.21 0.15 12 -0.39 0.15 11 -0.27 0.15 12 -0.12 0.15 9 -0.19 0.18 8 -0.22 0.23 6 LESOTHO LSO -0.35 0.16 11 -0.25 0.15 11 -0.19 0.19 9 -0.08 0.18 9 -0.17 0.18 8 -0.01 0.19 7 -0.05 0.22 5 0.10 0.26 5 -0.30 0.54 2 LIBERIA LBR -1.06 0.24 8 -0.97 0.24 7 -1.46 0.25 5 -1.65 0.24 6 -1.65 0.25 5 -1.78 0.25 6 -2.00 0.23 5 -2.07 0.26 5 -2.27 0.58 2 LIBYA LBY -0.62 0.15 12 -0.73 0.17 11 -0.70 0.16 11 -0.52 0.16 11 -0.73 0.16 9 -0.85 0.16 9 -0.82 0.16 7 -0.92 0.19 7 -1.29 0.23 6 LIECHTENSTEIN LIE 1.27 0.33 2 1.24 0.34 2 1.04 0.32 2 1.17 0.29 2 1.10 0.28 2 1.50 0.30 2 1.51 0.29 1 1.52 0.33 1 .. .. .. LITHUANIA LTU 0.49 0.13 17 0.44 0.13 15 0.47 0.14 14 0.57 0.13 14 0.50 0.14 14 0.40 0.14 14 0.29 0.14 12 0.41 0.17 9 0.29 0.21 6 LUXEMBOURG LUX 1.85 0.16 9 1.81 0.16 9 1.90 0.19 8 1.96 0.19 8 1.91 0.20 7 1.97 0.22 6 1.88 0.20 6 1.81 0.22 6 1.61 0.31 5 MACAO MAC 0.35 0.34 2 0.53 0.36 2 0.78 0.33 2 1.39 0.30 1 1.20 0.30 1 0.69 0.31 1 0.18 0.29 1 0.21 0.33 1 .. .. .. MACEDONIA MKD -0.47 0.15 14 -0.50 0.15 14 -0.35 0.14 13 -0.23 0.14 13 -0.57 0.15 12 -0.59 0.16 10 -0.63 0.17 7 -0.52 0.21 5 -0.15 0.25 3 MADAGASCAR MDG -0.35 0.14 16 -0.39 0.14 16 -0.22 0.17 12 -0.14 0.18 11 -0.19 0.19 10 -0.22 0.21 7 -0.32 0.22 6 -0.67 0.25 6 -0.97 0.46 3 MALAWI MWI -0.39 0.15 17 -0.44 0.14 17 -0.26 0.14 15 -0.27 0.14 14 -0.36 0.15 13 -0.53 0.16 12 -0.53 0.16 8 -0.51 0.19 8 -0.55 0.25 5 MALAYSIA MYS 0.53 0.13 17 0.55 0.13 18 0.56 0.13 16 0.54 0.13 16 0.45 0.13 15 0.41 0.14 14 0.35 0.13 12 0.47 0.16 11 0.73 0.19 9 MALDIVES MDV 0.02 0.27 5 0.18 0.27 5 0.25 0.25 5 0.09 0.23 5 0.31 0.25 4 0.28 0.25 3 0.28 0.24 3 0.42 0.30 2 .. .. .. MALI MLI -0.37 0.16 15 -0.39 0.15 15 -0.16 0.17 12 -0.20 0.17 12 -0.09 0.18 11 -0.41 0.19 10 -0.47 0.22 7 -0.51 0.25 6 -0.60 0.46 3 MALTA MLT 1.55 0.18 8 1.47 0.17 8 1.39 0.21 7 1.37 0.21 6 1.54 0.21 6 1.38 0.26 3 1.32 0.25 3 1.26 0.28 3 0.43 0.51 2 MARSHALL ISLANDS MHL 0.01 0.42 3 -0.10 0.39 3 -0.08 0.37 3 -0.42 0.35 3 0.08 0.44 3 -0.09 0.38 2 -0.48 0.40 2 -0.33 0.58 1 .. .. .. MARTINIQUE MTQ 0.89 0.35 1 0.87 0.37 1 0.88 0.33 1 0.98 0.30 1 0.94 0.30 1 1.22 0.31 1 1.25 0.29 1 1.26 0.33 1 .. .. .. MAURITANIA MRT -0.60 0.16 14 -0.60 0.16 13 -0.54 0.20 9 -0.67 0.20 9 -0.42 0.21 7 -0.41 0.23 5 -0.33 0.22 5 -0.36 0.26 5 -0.88 0.54 2 MAURITIUS MUS 0.79 0.14 13 0.73 0.14 13 0.87 0.15 11 0.88 0.15 11 0.93 0.16 9 0.88 0.16 9 0.81 0.18 7 0.81 0.23 6 0.76 0.27 3 MEXICO MEX -0.58 0.12 20 -0.53 0.12 20 -0.51 0.13 18 -0.42 0.13 18 -0.40 0.13 16 -0.38 0.14 15 -0.40 0.13 13 -0.51 0.16 12 -0.51 0.19 10 MICRONESIA FSM 0.73 0.28 4 0.74 0.28 4 0.74 0.26 4 0.52 0.23 4 -0.08 0.44 3 -0.26 0.38 2 -0.40 0.40 2 -0.33 0.58 1 .. .. .. MOLDOVA MDA -0.66 0.13 17 -0.65 0.13 16 -0.57 0.13 15 -0.62 0.13 14 -0.78 0.14 13 -0.72 0.15 12 -0.59 0.14 11 -0.26 0.17 9 -0.10 0.21 6 MONACO MCO 0.91 0.71 1 0.90 0.71 1 0.70 0.78 1 0.82 0.77 1 0.79 0.75 1 .. .. .. .. .. .. .. .. .. .. .. .. MONGOLIA MNG -0.41 0.18 13 -0.31 0.17 12 -0.20 0.18 11 0.07 0.19 10 0.07 0.20 8 0.23 0.21 7 -0.03 0.21 6 -0.04 0.25 5 0.07 0.46 3 MONTENEGRO MNP -0.30 0.19 10 -0.55 0.19 9 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. MOROCCO MAR -0.15 0.13 17 -0.13 0.13 17 -0.08 0.14 15 0.05 0.14 15 -0.06 0.14 14 -0.02 0.15 13 0.11 0.15 10 0.17 0.18 9 0.12 0.21 7 MOZAMBIQUE MOZ -0.68 0.13 19 -0.64 0.13 19 -0.68 0.14 16 -0.68 0.14 16 -0.76 0.14 14 -0.65 0.16 12 -0.78 0.16 8 -0.87 0.19 8 -0.90 0.25 5 MYANMAR MMR -1.41 0.18 10 -1.42 0.18 11 -1.60 0.18 10 -1.61 0.17 10 -1.61 0.17 9 -1.58 0.17 9 -1.26 0.17 7 -1.33 0.20 6 -1.31 0.26 5 NAMIBIA NAM 0.12 0.15 13 0.15 0.15 12 -0.04 0.15 14 -0.03 0.14 14 0.15 0.15 13 0.23 0.15 12 0.26 0.17 7 0.30 0.20 7 0.32 0.28 4 NAURU NRU 0.46 0.66 2 0.90 0.71 1 0.70 0.78 1 0.82 0.77 1 0.79 0.75 1 .. .. .. .. .. .. .. .. .. .. .. .. NEPAL NPL -0.64 0.16 15 -0.62 0.16 15 -0.83 0.16 13 -0.63 0.16 12 -0.54 0.18 10 -0.38 0.19 9 -0.28 0.19 7 -0.10 0.23 5 -0.15 0.39 3 NETHERLANDS NLD 1.76 0.14 13 1.74 0.14 13 1.72 0.14 12 1.75 0.14 12 1.72 0.14 12 1.74 0.14 12 1.75 0.14 11 1.81 0.16 10 1.81 0.19 9 NETHERLANDS ANTILLES ANT 0.89 0.35 1 0.87 0.37 1 0.88 0.33 1 0.93 0.30 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. NEW CALEDONIA NCL -0.31 0.59 1 -0.63 0.60 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. -0.86 0.68 1 NEW ZEALAND NZL 1.91 0.14 13 1.87 0.14 13 1.90 0.15 11 1.90 0.14 11 1.85 0.15 11 1.78 0.15 9 1.76 0.14 9 1.88 0.17 9 1.97 0.20 8 NICARAGUA NIC -0.84 0.15 17 -0.81 0.15 17 -0.65 0.15 15 -0.82 0.16 15 -0.62 0.16 13 -0.77 0.17 11 -0.91 0.16 8 -0.73 0.20 7 -0.33 0.25 6 NIGER NER -0.89 0.17 13 -0.81 0.17 13 -0.85 0.19 10 -0.75 0.19 10 -0.74 0.20 9 -0.75 0.21 8 -0.89 0.22 6 -0.73 0.25 6 -0.89 0.46 3 92 TABLE C5: Rule of Law (cont.) 2007 2006 2005 2004 2003 2002 2000 1998 1996 Country Code Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. NIGERIA NGA -1.20 0.13 19 -1.19 0.13 19 -1.41 0.14 17 -1.54 0.14 17 -1.65 0.14 16 -1.50 0.14 14 -1.17 0.14 11 -1.35 0.18 9 -1.35 0.21 7 NORWAY NOR 2.00 0.13 14 2.01 0.13 14 1.94 0.14 12 1.99 0.14 12 1.94 0.14 12 1.88 0.15 11 1.84 0.14 10 1.98 0.16 10 2.03 0.19 9 OMAN OMN 0.73 0.16 11 0.73 0.17 9 0.69 0.17 9 0.85 0.16 9 0.76 0.16 8 0.76 0.16 9 0.79 0.16 7 0.87 0.19 7 0.87 0.23 6 PAKISTAN PAK -0.93 0.13 19 -0.85 0.13 19 -0.87 0.14 16 -0.87 0.13 16 -0.83 0.14 15 -0.79 0.14 13 -0.80 0.14 11 -0.79 0.17 9 -0.59 0.21 7 PALAU PCI 0.91 0.71 1 0.90 0.71 1 0.70 0.78 1 -0.08 0.77 1 0.79 0.75 1 .. .. .. .. .. .. .. .. .. .. .. .. PANAMA PAN -0.20 0.14 16 -0.14 0.14 16 -0.14 0.14 16 -0.10 0.14 16 -0.13 0.15 13 -0.10 0.15 11 -0.13 0.14 10 -0.15 0.18 9 -0.15 0.23 7 PAPUA NEW GUINEA PNG -0.85 0.16 12 -0.90 0.16 12 -0.99 0.16 11 -0.84 0.15 11 -1.07 0.16 10 -1.03 0.16 9 -0.86 0.15 9 -0.62 0.19 7 -0.56 0.25 5 PARAGUAY PRY -0.97 0.15 16 -0.99 0.14 16 -1.00 0.15 14 -1.03 0.15 14 -1.15 0.15 12 -1.16 0.16 11 -0.99 0.15 9 -1.00 0.19 8 -0.46 0.24 6 PERU PER -0.71 0.13 20 -0.76 0.13 19 -0.78 0.14 16 -0.63 0.13 16 -0.62 0.14 14 -0.56 0.14 13 -0.65 0.14 11 -0.67 0.16 11 -0.58 0.20 9 PHILIPPINES PHL -0.59 0.13 19 -0.48 0.12 19 -0.44 0.13 17 -0.64 0.13 17 -0.60 0.13 15 -0.56 0.14 14 -0.53 0.13 12 -0.16 0.16 11 -0.02 0.19 9 POLAND POL 0.28 0.12 18 0.25 0.12 18 0.33 0.12 16 0.40 0.12 16 0.51 0.13 16 0.56 0.13 16 0.60 0.13 14 0.69 0.15 12 0.64 0.17 10 PORTUGAL PRT 0.95 0.13 14 0.94 0.13 14 1.08 0.14 13 1.18 0.14 13 1.24 0.14 13 1.24 0.15 11 1.14 0.14 10 1.22 0.16 10 1.14 0.19 9 PUERTO RICO PRI 0.58 0.23 5 0.57 0.28 4 0.62 0.27 3 0.75 0.23 3 0.72 0.23 3 1.06 0.25 2 1.01 0.24 2 1.00 0.29 2 0.74 0.56 1 QATAR QAT 0.89 0.17 10 0.89 0.17 10 0.86 0.17 10 0.69 0.17 9 0.62 0.17 9 0.75 0.17 7 0.70 0.17 6 0.50 0.21 5 0.10 0.28 3 REUNION REU 1.16 0.35 1 1.14 0.37 1 1.14 0.33 1 1.09 0.30 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ROMANIA ROM -0.17 0.12 19 -0.21 0.12 19 -0.23 0.12 17 -0.17 0.12 16 -0.22 0.13 15 -0.24 0.14 14 -0.19 0.14 12 -0.11 0.17 9 -0.15 0.20 7 RUSSIA RUS -0.97 0.12 20 -0.96 0.12 20 -0.88 0.12 18 -0.84 0.12 18 -0.92 0.13 17 -0.89 0.13 16 -1.05 0.13 14 -0.84 0.15 12 -0.73 0.17 10 RWANDA RWA -0.65 0.18 11 -0.65 0.18 11 -0.90 0.21 9 -0.81 0.21 9 -0.90 0.21 7 -0.99 0.22 7 -1.28 0.22 5 -1.47 0.26 5 -1.45 0.54 2 SAMOA SAM 0.93 0.28 4 0.95 0.28 4 1.09 0.26 4 0.86 0.23 4 1.07 0.25 4 1.04 0.25 3 0.71 0.22 4 0.61 0.28 3 -0.24 0.62 1 SAN MARINO SMR 0.91 0.71 1 0.90 0.71 1 0.70 0.78 1 0.82 0.77 1 0.79 0.75 1 .. .. .. .. .. .. .. .. .. .. .. .. SAO TOME AND PRINCIPE STP -0.41 0.20 5 -0.54 0.20 6 -0.61 0.24 5 -0.48 0.24 5 -0.51 0.25 4 -0.55 0.26 3 -0.11 0.25 3 -0.30 0.28 3 .. .. .. SAUDI ARABIA SAU 0.27 0.14 14 0.20 0.15 13 0.19 0.15 11 0.26 0.15 11 0.28 0.15 11 0.21 0.15 12 0.17 0.15 9 0.41 0.18 8 0.45 0.21 7 SENEGAL SEN -0.39 0.13 18 -0.35 0.14 17 -0.18 0.15 13 -0.25 0.15 13 -0.30 0.15 13 -0.18 0.16 12 -0.08 0.16 8 -0.15 0.19 8 -0.39 0.25 5 SERBIA YUG -0.57 0.15 14 -0.59 0.15 14 -0.86 0.15 12 -0.70 0.14 12 -0.97 0.15 12 -0.91 0.15 12 -1.20 0.18 7 -1.30 0.21 5 -0.98 0.30 3 SEYCHELLES SYC 0.21 0.19 6 0.18 0.19 6 0.13 0.18 7 0.18 0.18 7 0.24 0.24 5 0.50 0.26 3 0.59 0.25 3 0.57 0.28 3 .. .. .. SIERRA LEONE SLE -1.13 0.19 13 -1.15 0.19 13 -1.20 0.20 10 -1.10 0.20 10 -1.27 0.21 9 -1.33 0.21 8 -1.38 0.23 6 -1.19 0.25 6 -1.30 0.46 3 SINGAPORE SGP 1.79 0.13 15 1.76 0.13 15 1.81 0.14 13 1.81 0.14 13 1.69 0.14 13 1.54 0.14 12 1.42 0.14 11 1.57 0.16 10 1.74 0.19 9 SLOVAKIA SVK 0.35 0.13 16 0.41 0.13 16 0.44 0.13 15 0.48 0.13 15 0.36 0.13 15 0.28 0.13 15 0.33 0.13 12 0.23 0.16 10 0.23 0.19 8 SLOVENIA SVN 0.84 0.13 16 0.79 0.13 15 0.79 0.13 14 0.87 0.13 14 0.92 0.13 15 0.97 0.13 15 0.98 0.13 13 1.07 0.17 9 0.87 0.21 6 SOLOMON ISLANDS SLB -0.83 0.27 5 -0.82 0.28 4 -0.93 0.26 4 -1.10 0.23 4 -0.72 0.44 3 -1.62 0.38 2 -1.70 0.40 2 -0.69 0.58 1 .. .. .. SOMALIA SOM -2.64 0.26 4 -2.57 0.26 4 -2.21 0.24 6 -2.31 0.24 6 -1.93 0.25 5 -1.95 0.27 4 -2.26 0.24 4 -2.25 0.25 5 -2.10 0.46 3 SOUTH AFRICA ZAF 0.15 0.12 19 0.24 0.12 19 0.18 0.13 18 0.13 0.13 18 0.03 0.13 17 0.05 0.13 16 0.12 0.13 13 0.24 0.16 12 0.26 0.19 9 SPAIN ESP 1.12 0.13 15 1.08 0.13 14 1.10 0.14 12 1.20 0.14 12 1.29 0.14 12 1.24 0.14 12 1.36 0.14 11 1.29 0.16 10 1.35 0.19 9 SRI LANKA LKA 0.06 0.14 18 0.08 0.14 17 0.05 0.14 15 0.01 0.14 15 0.04 0.14 14 0.16 0.14 13 0.00 0.14 11 -0.08 0.18 8 -0.12 0.23 6 ST. KITTS AND NEVIS KNA 0.86 0.28 3 0.86 0.29 3 0.79 0.27 4 0.74 0.25 4 0.61 0.49 2 0.27 0.52 1 0.45 0.49 1 -0.33 0.58 1 .. .. .. ST. LUCIA LCA 0.86 0.28 3 0.86 0.29 3 0.79 0.27 4 0.69 0.25 4 0.61 0.49 2 0.27 0.52 1 0.45 0.49 1 -0.33 0.58 1 .. .. .. ST. VINCENT ANDTHE GRENADINES VCT 0.86 0.28 3 0.86 0.29 3 0.79 0.27 4 0.74 0.25 4 0.61 0.49 2 0.59 0.52 1 0.45 0.49 1 -0.33 0.58 1 .. .. .. SUDAN SDN -1.46 0.17 13 -1.34 0.17 12 -1.61 0.17 11 -1.51 0.16 11 -1.53 0.17 10 -1.24 0.17 10 -1.45 0.16 8 -1.56 0.20 7 -1.63 0.28 4 SURINAME SUR -0.24 0.20 7 -0.26 0.20 8 -0.22 0.23 7 -0.23 0.22 7 -0.15 0.23 6 -0.23 0.26 4 -0.15 0.25 3 -0.20 0.28 3 -0.62 0.51 2 SWAZILAND SWZ -0.76 0.17 10 -0.67 0.17 10 -0.78 0.19 9 -0.89 0.18 9 -0.88 0.19 7 -0.69 0.20 6 -0.65 0.22 5 -0.62 0.26 5 0.79 0.54 2 SWEDEN SWE 1.90 0.13 14 1.87 0.13 14 1.79 0.14 12 1.86 0.14 12 1.88 0.14 12 1.84 0.15 11 1.80 0.14 11 1.80 0.16 10 1.84 0.19 9 SWITZERLAND CHE 2.01 0.14 13 1.95 0.14 13 1.97 0.14 12 1.98 0.14 12 1.97 0.14 12 1.94 0.15 11 1.95 0.14 11 2.04 0.16 10 2.08 0.19 9 SYRIA SYR -0.55 0.14 15 -0.66 0.15 14 -0.43 0.16 12 -0.30 0.15 12 -0.40 0.16 9 -0.36 0.16 9 -0.33 0.16 7 -0.28 0.19 7 -0.49 0.23 6 TAIWAN TWN 0.67 0.13 15 0.69 0.13 15 0.85 0.14 13 0.82 0.14 13 0.84 0.14 13 0.82 0.14 13 0.86 0.14 11 0.89 0.16 10 0.85 0.19 9 TAJIKISTAN TJK -1.13 0.14 17 -1.06 0.14 17 -0.98 0.16 14 -1.14 0.15 13 -1.07 0.17 11 -1.29 0.17 11 -1.53 0.18 7 -1.75 0.22 6 -1.55 0.32 3 TANZANIA TZA -0.45 0.14 17 -0.52 0.14 17 -0.42 0.14 15 -0.44 0.14 15 -0.42 0.14 14 -0.49 0.15 13 -0.45 0.15 9 -0.42 0.18 9 -0.42 0.23 6 THAILAND THA -0.06 0.13 18 0.00 0.13 18 0.10 0.13 16 0.05 0.13 16 0.06 0.14 14 0.23 0.14 14 0.45 0.13 12 0.40 0.16 11 0.58 0.19 9 TIMOR-LESTE TMP -1.28 0.23 8 -1.19 0.22 7 -0.58 0.25 6 -0.84 0.25 6 -0.74 0.27 4 -1.17 0.31 1 .. .. .. .. .. .. .. .. .. TOGO TGO -0.94 0.16 12 -1.01 0.16 13 -1.09 0.19 10 -1.04 0.19 10 -0.98 0.20 9 -0.72 0.21 8 -0.65 0.22 7 -0.67 0.25 6 -1.36 0.58 2 TONGA TON 0.50 0.28 4 0.59 0.28 4 0.55 0.26 4 0.19 0.23 4 0.08 0.44 3 0.02 0.38 2 -0.07 0.40 2 -0.69 0.58 1 .. .. .. TRINIDAD AND TOBAGO TTO -0.22 0.15 11 -0.27 0.15 11 -0.11 0.15 11 -0.07 0.15 10 0.13 0.16 9 0.29 0.17 8 0.36 0.15 8 0.36 0.19 7 0.54 0.25 5 TUNISIA TUN 0.32 0.14 16 0.34 0.13 15 0.22 0.14 15 0.28 0.14 14 0.03 0.14 12 0.10 0.15 12 -0.02 0.15 9 -0.03 0.18 9 -0.20 0.23 6 TURKEY TUR 0.00 0.13 19 -0.01 0.13 19 0.08 0.13 18 0.11 0.13 18 0.02 0.13 16 -0.14 0.14 15 -0.06 0.13 13 -0.05 0.16 11 -0.01 0.19 9 TURKMENISTAN TKM -1.33 0.15 10 -1.43 0.15 10 -1.45 0.15 10 -1.47 0.15 9 -1.31 0.16 9 -1.20 0.17 9 -1.13 0.17 7 -1.15 0.20 7 -1.26 0.28 4 TUVALU TUV 1.03 0.32 3 1.09 0.32 3 1.27 0.29 3 0.83 0.26 3 1.30 0.59 2 1.77 0.48 1 1.69 0.57 1 .. .. .. .. .. .. UGANDA UGA -0.54 0.13 19 -0.50 0.13 19 -0.69 0.14 16 -0.73 0.14 16 -0.64 0.14 15 -0.74 0.15 13 -0.83 0.15 10 -0.63 0.18 9 -0.64 0.23 6 UKRAINE UKR -0.70 0.12 20 -0.77 0.12 18 -0.57 0.13 17 -0.71 0.12 17 -0.85 0.13 17 -0.84 0.13 15 -0.97 0.13 13 -0.96 0.16 11 -0.54 0.19 8 UNITEDARAB EMIRATES ARE 0.66 0.16 12 0.68 0.15 12 0.58 0.15 11 0.83 0.15 11 0.90 0.16 9 0.95 0.16 10 0.92 0.16 8 0.98 0.19 7 0.84 0.23 6 UNITEDKINGDOM GBR 1.75 0.13 14 1.75 0.13 14 1.63 0.14 12 1.71 0.14 12 1.74 0.14 12 1.73 0.14 12 1.72 0.14 11 1.80 0.16 10 1.83 0.19 9 UNITEDSTATES USA 1.59 0.13 14 1.58 0.13 14 1.52 0.14 11 1.48 0.14 12 1.56 0.14 12 1.56 0.14 11 1.66 0.14 10 1.68 0.16 10 1.75 0.19 9 URUGUAY URY 0.49 0.15 15 0.41 0.15 14 0.40 0.15 14 0.41 0.14 14 0.57 0.14 12 0.57 0.15 12 0.56 0.14 10 0.53 0.18 9 0.56 0.23 7 UZBEKISTAN UZB -1.06 0.13 17 -1.38 0.14 16 -1.41 0.14 14 -1.36 0.13 14 -1.30 0.14 14 -1.41 0.14 13 -1.06 0.16 9 -1.02 0.20 7 -0.99 0.22 5 VANUATU VUT 0.63 0.27 5 0.53 0.28 4 0.54 0.26 4 0.03 0.23 4 -0.05 0.44 3 -0.25 0.38 2 -0.22 0.40 2 -0.69 0.58 1 .. .. .. VENEZUELA VEN -1.47 0.13 20 -1.36 0.13 19 -1.26 0.13 18 -1.20 0.13 18 -1.23 0.13 17 -1.13 0.14 15 -0.82 0.13 12 -0.69 0.16 12 -0.68 0.19 10 VIETNAM VNM -0.53 0.13 19 -0.51 0.13 19 -0.41 0.14 16 -0.53 0.13 16 -0.56 0.14 15 -0.61 0.14 14 -0.49 0.13 12 -0.52 0.16 10 -0.65 0.20 8 VIRGIN ISLANDS (U.S.) VIR 0.89 0.35 1 1.14 0.37 1 1.14 0.33 1 1.21 0.30 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. WEST BANK GAZA WBG -0.84 0.28 3 -0.63 0.30 3 -0.46 0.29 3 -0.37 0.27 3 -0.30 0.27 2 -0.36 0.29 2 -0.09 0.29 1 -0.06 0.33 1 .. .. .. YEMEN YEM -0.94 0.14 16 -0.99 0.14 16 -1.11 0.16 12 -1.06 0.16 12 -1.11 0.16 10 -1.27 0.17 9 -1.20 0.16 7 -1.03 0.19 7 -1.15 0.25 5 ZAMBIA ZMB -0.64 0.14 17 -0.67 0.14 17 -0.62 0.15 15 -0.61 0.14 16 -0.64 0.14 14 -0.50 0.15 13 -0.56 0.15 9 -0.60 0.18 9 -0.60 0.23 6 ZIMBABWE ZWE -1.67 0.13 19 -1.56 0.13 19 -1.62 0.14 17 -1.68 0.14 16 -1.67 0.14 15 -1.47 0.15 13 -1.25 0.14 10 -0.50 0.17 10 -0.69 0.22 7 93 TABLE C6: Control of Corruption 2007 2006 2005 2004 2003 2002 2000 1998 1996 Country Code Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. AFGHANISTAN AFG -1.53 0.23 7 -1.46 0.20 9 -1.47 0.20 7 -1.49 0.19 7 -1.62 0.29 3 -1.54 0.31 2 -1.91 0.30 2 -1.92 0.37 1 .. .. .. ALBANIA ALB -0.57 0.14 12 -0.68 0.13 12 -0.72 0.14 10 -0.74 0.15 9 -0.77 0.16 6 -0.82 0.18 6 -0.82 0.18 6 -1.08 0.20 5 0.03 0.48 2 ALGERIA DZA -0.47 0.13 13 -0.48 0.14 12 -0.49 0.15 12 -0.65 0.15 12 -0.62 0.16 9 -0.76 0.17 8 -0.76 0.19 7 -0.81 0.19 7 -0.37 0.26 4 AMERICAN SAMOA ASM 0.34 0.42 1 0.33 0.40 1 0.78 0.34 1 0.77 0.38 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ANDORRA ADO 1.28 0.42 1 1.27 0.40 1 1.25 0.34 1 1.08 0.38 1 1.29 0.37 1 1.32 0.39 1 1.39 0.39 1 1.44 0.37 1 .. .. .. ANGOLA AGO -1.12 0.14 12 -1.21 0.14 13 -1.24 0.16 11 -1.30 0.15 12 -1.18 0.16 9 -1.19 0.17 8 -1.49 0.19 7 -1.37 0.19 7 -1.06 0.26 4 ANGUILLA AIA 1.28 0.42 1 1.27 0.40 1 1.25 0.34 1 0.81 0.38 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ANTIGUA AND BARBUDA ATG 1.28 0.42 1 1.27 0.40 1 0.75 0.33 2 0.83 0.35 2 0.82 0.37 1 0.86 0.39 1 0.92 0.39 1 0.96 0.37 1 .. .. .. ARGENTINA ARG -0.45 0.12 16 -0.40 0.13 16 -0.41 0.14 15 -0.41 0.13 15 -0.43 0.15 12 -0.70 0.16 11 -0.29 0.16 10 -0.15 0.16 9 -0.18 0.20 7 ARMENIA ARM -0.68 0.12 17 -0.57 0.12 16 -0.62 0.13 12 -0.69 0.14 11 -0.62 0.14 9 -0.69 0.16 8 -0.71 0.17 7 -0.78 0.18 6 -0.70 0.41 2 ARUBA ABW 1.28 0.42 1 1.27 0.40 1 1.25 0.34 1 1.12 0.38 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. AUSTRALIA AUS 2.05 0.14 10 2.00 0.16 10 1.97 0.15 10 2.09 0.15 10 2.03 0.16 10 1.92 0.17 8 1.96 0.17 8 1.97 0.17 8 1.85 0.20 7 AUSTRIA AUT 2.02 0.14 11 2.00 0.15 11 1.98 0.15 10 2.10 0.15 10 2.09 0.16 9 2.04 0.17 8 1.93 0.17 8 1.92 0.17 8 1.98 0.20 7 AZERBAIJAN AZE -1.04 0.12 16 -0.98 0.12 16 -1.01 0.12 14 -1.14 0.13 13 -1.02 0.13 11 -1.03 0.13 10 -1.12 0.15 9 -1.13 0.17 7 -1.04 0.27 3 BAHAMAS BHS 1.36 0.36 2 1.37 0.34 2 1.32 0.30 2 1.36 0.33 2 1.37 0.33 2 1.44 0.34 2 1.39 0.36 2 1.42 0.35 2 0.37 0.70 1 BAHRAIN BHR 0.60 0.15 9 0.46 0.16 9 0.53 0.16 9 0.63 0.16 9 0.76 0.18 7 0.93 0.18 7 0.69 0.21 5 0.67 0.21 5 0.02 0.26 4 BANGLADESH BGD -1.05 0.13 15 -1.26 0.14 14 -1.23 0.15 12 -1.32 0.15 12 -1.17 0.15 9 -1.02 0.15 9 -0.94 0.16 8 -0.72 0.20 6 -0.49 0.26 4 BARBADOS BRB 1.33 0.21 3 1.20 0.25 3 1.21 0.30 3 1.16 0.31 3 1.22 0.32 2 1.32 0.39 1 1.39 0.39 1 1.44 0.37 1 .. .. .. BELARUS BLR -0.88 0.13 10 -0.77 0.14 10 -0.89 0.15 8 -1.01 0.15 8 -0.95 0.15 7 -0.89 0.18 6 -0.57 0.18 6 -0.72 0.20 5 -1.00 0.57 1 BELGIUM BEL 1.45 0.14 10 1.41 0.16 10 1.46 0.15 9 1.51 0.15 9 1.55 0.16 9 1.62 0.16 9 1.55 0.17 8 1.42 0.17 8 1.40 0.20 7 BELIZE BLZ -0.27 0.18 6 -0.31 0.23 5 -0.24 0.26 4 -0.30 0.27 4 -0.07 0.26 3 -0.22 0.32 2 -0.15 0.31 2 -0.09 0.31 2 .. .. .. BENIN BEN -0.49 0.14 12 -0.59 0.15 12 -0.88 0.19 8 -0.54 0.22 6 -0.63 0.25 4 -0.83 0.30 3 -0.61 0.29 3 -0.75 0.29 3 .. .. .. BERMUDA BMU 1.28 0.42 1 1.27 0.40 1 1.25 0.34 1 1.26 0.38 1 1.29 0.37 1 1.32 0.39 1 1.39 0.39 1 1.44 0.37 1 .. .. .. BHUTAN BTN 0.92 0.19 6 0.89 0.25 6 0.87 0.25 6 0.81 0.26 6 0.89 0.23 4 0.55 0.23 3 0.56 0.24 3 0.66 0.31 2 .. .. .. BOLIVIA BOL -0.49 0.13 16 -0.51 0.14 16 -0.78 0.15 14 -0.78 0.15 14 -0.81 0.16 9 -0.85 0.17 9 -0.54 0.18 8 -0.40 0.20 6 -0.94 0.26 4 BOSNIA-HERZEGOVINA BIH -0.43 0.13 13 -0.30 0.13 12 -0.25 0.13 11 -0.35 0.13 11 -0.39 0.14 7 -0.45 0.16 7 -0.60 0.19 5 -0.37 0.19 4 -0.26 0.33 1 BOTSWANA BWA 0.90 0.13 13 0.86 0.14 13 1.08 0.16 11 0.91 0.16 11 1.10 0.17 9 0.69 0.18 9 0.74 0.21 6 0.75 0.22 6 0.38 0.28 3 BRAZIL BRA -0.24 0.12 17 -0.20 0.13 18 -0.23 0.14 15 0.00 0.13 15 0.05 0.15 12 -0.14 0.16 11 0.04 0.16 10 0.04 0.16 9 -0.18 0.20 7 BRUNEI BRN 0.23 0.36 2 0.24 0.34 2 0.25 0.30 2 0.39 0.33 2 0.29 0.33 2 0.33 0.34 2 0.34 0.36 2 0.43 0.35 2 0.37 0.70 1 BULGARIA BGR -0.22 0.11 16 -0.09 0.11 16 0.01 0.12 12 0.10 0.12 12 -0.06 0.13 10 -0.14 0.14 10 -0.23 0.15 9 -0.33 0.17 7 -0.76 0.26 4 BURKINA FASO BFA -0.40 0.13 13 -0.40 0.14 13 -0.20 0.20 8 -0.18 0.21 8 0.07 0.24 5 0.03 0.28 4 0.00 0.28 4 -0.03 0.29 4 -0.33 0.70 1 BURUNDI BDI -1.06 0.15 11 -1.12 0.16 10 -0.93 0.22 6 -0.96 0.22 6 -0.95 0.25 4 -0.97 0.30 3 -1.14 0.29 3 -1.30 0.29 3 .. .. .. CAMBODIA KHM -1.08 0.13 13 -1.17 0.14 13 -1.13 0.15 11 -1.02 0.17 9 -0.90 0.17 7 -0.96 0.17 6 -0.91 0.19 5 -1.04 0.22 4 -1.11 0.29 2 CAMEROON CMR -0.93 0.13 14 -1.00 0.14 13 -1.15 0.16 11 -1.05 0.16 10 -0.79 0.18 8 -1.07 0.19 7 -1.09 0.21 6 -1.23 0.22 6 -1.15 0.28 3 CANADA CAN 2.09 0.13 14 1.95 0.14 13 1.92 0.15 10 1.92 0.15 10 2.06 0.16 9 2.05 0.16 9 2.02 0.17 8 2.06 0.17 8 2.22 0.20 7 CAPE VERDE CPV 0.76 0.21 6 0.60 0.21 6 0.38 0.25 5 0.35 0.25 5 0.32 0.27 4 0.36 0.29 4 0.18 0.41 2 -0.32 0.44 2 .. .. .. CAYMAN ISLANDS CYM 1.28 0.42 1 1.27 0.40 1 1.25 0.34 1 1.21 0.38 1 1.29 0.37 1 1.32 0.39 1 1.39 0.39 1 1.44 0.37 1 .. .. .. CENTRAL AFRICAN REPUBLIC CAF -0.90 0.18 6 -1.00 0.21 5 -1.17 0.22 6 -1.26 0.22 6 -1.15 0.25 4 -1.09 0.30 3 -1.30 0.29 3 -1.18 0.29 3 .. .. .. CHAD TCD -1.22 0.14 10 -1.20 0.15 10 -1.33 0.20 7 -1.17 0.20 7 -1.13 0.23 5 -0.93 0.29 4 -0.88 0.29 3 -1.00 0.29 3 .. .. .. CHILE CHL 1.35 0.12 16 1.34 0.13 16 1.34 0.14 14 1.41 0.14 13 1.21 0.15 11 1.48 0.16 11 1.45 0.16 10 1.27 0.16 9 1.29 0.20 7 CHINA CHN -0.66 0.12 16 -0.58 0.12 15 -0.70 0.12 14 -0.61 0.12 14 -0.43 0.13 11 -0.48 0.14 11 -0.28 0.14 10 -0.38 0.15 10 -0.15 0.17 8 COLOMBIA COL -0.28 0.12 19 -0.21 0.13 18 -0.23 0.14 16 -0.24 0.14 15 -0.45 0.15 11 -0.49 0.16 11 -0.59 0.16 10 -0.72 0.16 9 -0.52 0.20 7 COMOROS COM -0.69 0.25 4 -0.65 0.25 4 -0.84 0.26 4 -0.84 0.26 4 -0.83 0.28 3 -0.81 0.30 3 -1.10 0.29 3 -1.23 0.29 3 .. .. .. CONGO COG -1.04 0.14 11 -1.08 0.16 10 -1.04 0.17 9 -0.95 0.20 7 -0.97 0.20 6 -0.98 0.22 6 -1.01 0.22 5 -1.23 0.24 5 -0.87 0.45 2 CONGO, DEM. REP. ZAR -1.27 0.15 11 -1.44 0.16 10 -1.41 0.16 10 -1.39 0.15 10 -1.43 0.19 7 -1.46 0.20 7 -1.60 0.20 6 -1.73 0.22 6 -2.09 0.37 3 COOK ISLANDS COK 1.05 0.78 1 0.67 0.76 1 0.63 0.69 1 0.08 0.74 1 -0.19 0.43 1 -0.19 0.32 1 -0.10 0.37 1 .. .. .. .. .. .. COSTARICA CRI 0.39 0.14 15 0.39 0.15 14 0.44 0.15 13 0.48 0.15 13 0.80 0.16 9 0.82 0.17 9 0.87 0.18 8 0.90 0.20 6 0.73 0.24 5 COTE D'IVOIRE CIV -1.09 0.14 9 -1.22 0.16 9 -1.27 0.17 8 -1.18 0.17 9 -1.00 0.19 7 -0.83 0.19 7 -0.52 0.21 6 -0.38 0.22 6 0.38 0.28 3 CROATIA HRV 0.01 0.11 14 0.03 0.12 14 0.14 0.12 13 0.13 0.12 13 0.06 0.13 10 0.19 0.14 10 -0.01 0.16 8 -0.30 0.17 7 -0.59 0.27 3 CUBA CUB -0.21 0.15 8 -0.26 0.16 8 -0.26 0.17 8 -0.31 0.17 8 -0.30 0.18 6 -0.16 0.19 6 -0.23 0.21 5 -0.02 0.21 5 0.02 0.26 4 CYPRUS CYP 0.78 0.19 7 0.82 0.18 7 0.70 0.17 6 0.75 0.18 6 0.94 0.19 5 0.89 0.19 5 0.79 0.21 5 0.83 0.21 5 1.62 0.26 4 CZECH REPUBLIC CZE 0.26 0.11 16 0.32 0.11 15 0.44 0.12 13 0.36 0.11 14 0.40 0.12 12 0.35 0.13 12 0.29 0.14 11 0.45 0.14 10 0.58 0.20 7 DENMARK DNK 2.42 0.14 11 2.40 0.15 11 2.24 0.15 10 2.37 0.15 10 2.31 0.16 9 2.27 0.17 8 2.18 0.17 8 2.19 0.17 8 2.29 0.20 7 DJIBOUTI DJI -0.48 0.25 4 -0.62 0.25 4 -0.68 0.26 4 -0.50 0.26 4 -0.83 0.28 3 -0.69 0.30 3 -0.88 0.29 3 -0.69 0.29 3 .. .. .. DOMINICA DMA 0.63 0.32 2 0.65 0.31 2 0.66 0.28 3 0.61 0.29 3 0.45 0.29 2 0.54 0.32 2 0.44 0.31 2 0.59 0.31 2 .. .. .. DOMINICAN REPUBLIC DOM -0.65 0.13 15 -0.63 0.14 15 -0.65 0.15 13 -0.52 0.15 12 -0.53 0.16 8 -0.43 0.17 8 -0.40 0.19 6 -0.41 0.21 5 -0.37 0.28 3 ECUADOR ECU -0.87 0.14 16 -0.80 0.15 15 -0.79 0.15 14 -0.76 0.14 15 -0.79 0.16 10 -0.97 0.17 10 -0.86 0.17 9 -0.83 0.20 7 -0.83 0.25 5 EGYPT EGY -0.58 0.13 15 -0.54 0.13 15 -0.46 0.15 13 -0.45 0.15 13 -0.43 0.16 10 -0.33 0.16 10 -0.38 0.17 9 -0.27 0.17 9 0.06 0.23 6 EL SALVADOR SLV -0.13 0.16 11 -0.14 0.17 11 -0.34 0.17 10 -0.28 0.18 10 -0.34 0.19 7 -0.53 0.20 7 -0.43 0.22 6 -0.70 0.25 4 -0.84 0.28 3 EQUATORIAL GUINEA GNQ -1.37 0.17 6 -1.52 0.21 6 -1.53 0.21 5 -1.61 0.20 6 -1.48 0.21 5 -1.49 0.22 5 -1.61 0.25 4 -1.39 0.24 4 -1.06 0.33 1 ERITREA ERI -0.60 0.17 7 -0.32 0.19 8 -0.32 0.22 7 -0.27 0.22 7 -0.07 0.25 4 0.16 0.30 3 0.65 0.29 3 0.77 0.29 3 .. .. .. ESTONIA EST 0.94 0.11 14 0.90 0.11 14 0.91 0.11 13 0.94 0.12 13 0.80 0.12 11 0.69 0.13 11 0.62 0.14 10 0.42 0.17 7 -0.02 0.27 3 ETHIOPIA ETH -0.70 0.14 14 -0.65 0.14 14 -0.80 0.16 11 -0.72 0.17 10 -0.67 0.19 7 -0.52 0.21 6 -0.46 0.24 5 -0.56 0.24 5 -1.13 0.31 2 FIJI FJI -0.46 0.31 3 -0.33 0.29 3 -0.60 0.29 2 -0.08 0.31 2 -0.29 0.29 2 0.09 0.32 2 0.15 0.31 2 0.25 0.31 2 .. .. .. FINLAND FIN 2.59 0.14 11 2.58 0.15 11 2.40 0.15 10 2.46 0.15 10 2.42 0.16 9 2.46 0.16 9 2.34 0.17 8 2.24 0.17 8 2.30 0.20 7 FRANCE FRA 1.32 0.13 13 1.46 0.14 12 1.40 0.15 10 1.44 0.15 10 1.47 0.16 9 1.37 0.16 9 1.50 0.17 8 1.51 0.17 8 1.45 0.20 7 FRENCH GUIANA GUF 0.81 0.42 1 0.80 0.40 1 0.78 0.34 1 0.77 0.38 1 0.82 0.37 1 0.86 0.39 1 0.92 0.39 1 0.96 0.37 1 .. .. .. GABON GAB -0.85 0.14 11 -0.90 0.15 11 -0.66 0.17 9 -0.68 0.16 9 -0.50 0.17 8 -0.53 0.17 8 -0.59 0.19 7 -0.73 0.21 6 -1.27 0.28 3 GAMBIA GMB -0.78 0.19 7 -0.71 0.18 7 -0.71 0.21 6 -0.60 0.22 6 -0.36 0.23 5 -0.48 0.28 4 -0.40 0.28 4 -0.54 0.29 4 0.37 0.70 1 94 TABLE C6: Control of Corruption (cont.) 2007 2006 2005 2004 2003 2002 2000 1998 1996 Country Code Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. GEORGIA GEO -0.38 0.12 16 -0.26 0.12 15 -0.43 0.13 12 -0.63 0.13 12 -0.93 0.14 8 -1.07 0.17 7 -0.90 0.17 6 -0.84 0.18 5 -1.12 0.41 2 GERMANY DEU 1.80 0.13 12 1.84 0.14 12 1.92 0.15 11 1.91 0.15 11 1.99 0.16 10 1.99 0.16 9 2.00 0.17 8 2.08 0.17 8 2.09 0.20 7 GHANA GHA -0.17 0.13 15 -0.10 0.14 15 -0.36 0.14 14 -0.32 0.14 14 -0.31 0.16 11 -0.38 0.17 9 -0.25 0.19 7 -0.35 0.19 7 -0.50 0.26 4 GREECE GRC 0.28 0.13 12 0.40 0.14 12 0.40 0.15 10 0.57 0.15 10 0.57 0.16 9 0.55 0.16 9 0.73 0.17 8 0.69 0.17 8 0.38 0.20 7 GRENADA GRD 0.36 0.32 2 0.57 0.29 3 0.66 0.28 3 0.61 0.29 3 0.62 0.29 2 0.70 0.32 2 0.61 0.31 2 0.73 0.31 2 .. .. .. GUAM GUM 0.81 0.42 1 0.80 0.40 1 0.78 0.34 1 0.36 0.38 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. GUATEMALA GTM -0.75 0.13 17 -0.76 0.14 17 -0.78 0.15 14 -0.55 0.15 14 -0.67 0.17 10 -0.61 0.18 8 -0.56 0.19 7 -0.62 0.21 5 -1.03 0.25 4 GUINEA GIN -1.33 0.15 9 -1.00 0.17 9 -0.86 0.20 7 -0.91 0.21 7 -0.80 0.24 5 -0.66 0.27 5 -0.79 0.28 4 -0.83 0.29 4 0.37 0.70 1 GUINEA-BISSAU GNB -1.11 0.24 5 -0.99 0.23 5 -1.07 0.24 5 -1.16 0.24 5 -1.04 0.26 4 -0.88 0.28 4 -0.88 0.28 4 -1.12 0.29 4 -1.04 0.70 1 GUYANA GUY -0.64 0.16 10 -0.61 0.19 9 -0.57 0.21 7 -0.49 0.25 5 -0.41 0.25 4 -0.44 0.29 3 -0.38 0.29 3 -0.41 0.30 3 -0.33 0.70 1 HAITI HTI -1.28 0.17 9 -1.43 0.19 9 -1.51 0.21 7 -1.43 0.22 7 -1.73 0.22 6 -1.70 0.25 4 -1.44 0.29 3 -1.38 0.30 3 -1.04 0.70 1 HONDURAS HND -0.69 0.14 14 -0.77 0.15 14 -0.72 0.15 12 -0.72 0.16 12 -0.72 0.17 8 -0.82 0.18 8 -0.72 0.19 7 -0.63 0.21 5 -1.03 0.25 4 HONG KONG HKG 1.61 0.13 12 1.77 0.13 12 1.68 0.13 10 1.58 0.13 10 1.47 0.14 9 1.45 0.15 9 1.19 0.14 8 1.25 0.16 8 1.52 0.17 7 HUNGARY HUN 0.44 0.11 15 0.57 0.11 15 0.61 0.12 13 0.68 0.12 13 0.62 0.12 12 0.58 0.13 12 0.69 0.14 11 0.67 0.14 10 0.63 0.20 7 ICELAND ISL 2.60 0.15 8 2.46 0.16 8 2.49 0.17 7 2.35 0.17 7 2.39 0.19 6 2.22 0.20 5 2.21 0.21 5 1.92 0.20 5 1.82 0.26 4 INDIA IND -0.39 0.12 17 -0.25 0.12 17 -0.31 0.12 15 -0.34 0.12 15 -0.34 0.13 12 -0.41 0.14 11 -0.38 0.14 10 -0.29 0.15 10 -0.36 0.17 8 INDONESIA IDN -0.72 0.12 19 -0.78 0.12 19 -0.88 0.12 17 -0.92 0.12 17 -0.97 0.13 14 -1.12 0.13 12 -0.97 0.13 11 -1.15 0.15 10 -0.55 0.17 8 IRAN IRN -0.56 0.14 12 -0.53 0.15 13 -0.54 0.16 11 -0.52 0.16 11 -0.34 0.17 8 -0.30 0.17 8 -0.51 0.20 6 -0.47 0.21 6 -0.91 0.25 5 IRAQ IRQ -1.39 0.16 7 -1.50 0.18 7 -1.40 0.17 7 -1.54 0.17 7 -1.13 0.18 6 -1.46 0.19 6 -1.46 0.21 5 -1.52 0.21 5 -1.39 0.26 4 IRELAND IRL 1.75 0.13 12 1.70 0.14 12 1.69 0.15 10 1.51 0.15 10 1.67 0.16 9 1.61 0.17 8 1.59 0.17 8 1.74 0.17 8 1.85 0.20 7 ISRAEL ISR 0.79 0.13 12 0.93 0.14 12 0.77 0.15 9 0.83 0.15 9 0.97 0.16 8 1.04 0.16 8 0.98 0.18 7 1.05 0.17 7 1.47 0.20 7 ITALY ITA 0.45 0.13 13 0.41 0.14 12 0.39 0.15 11 0.61 0.15 11 0.75 0.16 10 0.77 0.16 9 0.98 0.17 8 0.69 0.17 8 0.49 0.20 7 JAMAICA JAM -0.49 0.15 10 -0.40 0.15 11 -0.47 0.15 9 -0.51 0.16 9 -0.54 0.17 7 -0.49 0.18 7 -0.25 0.19 6 -0.24 0.21 5 -0.37 0.28 3 JAPAN JPN 1.20 0.13 14 1.35 0.13 13 1.25 0.13 12 1.19 0.13 12 1.19 0.14 11 1.05 0.14 10 1.35 0.14 9 1.31 0.16 9 1.14 0.17 8 JORDAN JOR 0.32 0.12 15 0.28 0.13 14 0.25 0.14 12 0.37 0.14 12 0.30 0.15 10 0.01 0.17 8 0.04 0.18 7 0.10 0.17 7 -0.15 0.24 5 KAZAKHSTAN KAZ -0.91 0.11 16 -0.88 0.12 16 -0.93 0.12 14 -1.14 0.13 13 -1.10 0.13 11 -1.08 0.15 10 -0.97 0.15 10 -0.90 0.16 8 -0.92 0.26 4 KENYA KEN -0.94 0.12 17 -0.89 0.13 17 -0.99 0.14 15 -0.85 0.14 15 -0.87 0.16 12 -1.01 0.17 9 -0.98 0.19 7 -1.11 0.19 7 -1.11 0.26 4 KIRIBATI KIR 0.11 0.31 3 0.08 0.30 3 0.22 0.27 3 0.36 0.30 3 0.12 0.31 2 -0.04 0.27 2 -0.22 0.30 2 -0.61 0.51 1 .. .. .. KOREA, NORTH PRK -1.69 0.29 3 -1.51 0.22 5 -1.30 0.21 5 -1.48 0.22 5 -1.98 0.33 2 -1.13 0.34 2 -1.93 0.36 2 -1.86 0.35 2 -0.33 0.70 1 KOREA, SOUTH KOR 0.36 0.12 15 0.29 0.12 15 0.50 0.12 13 0.29 0.12 13 0.29 0.13 11 0.37 0.14 11 0.19 0.14 10 0.10 0.15 10 0.32 0.17 8 KOSOVO LWI -0.75 0.22 3 -0.61 0.21 3 -0.66 0.20 2 -0.97 0.22 1 -0.89 0.21 1 .. .. .. .. .. .. .. .. .. .. .. .. KUWAIT KWT 0.49 0.14 9 0.73 0.16 8 0.83 0.17 7 0.88 0.18 6 0.92 0.18 6 1.08 0.18 7 1.04 0.21 5 1.11 0.21 5 0.61 0.26 4 KYRGYZSTAN KGZ -1.08 0.12 15 -1.10 0.13 15 -1.08 0.13 12 -1.01 0.14 11 -0.85 0.14 9 -0.85 0.15 8 -0.87 0.15 7 -0.71 0.18 5 -0.85 0.41 2 LAOS LAO -1.00 0.15 10 -1.07 0.17 10 -1.11 0.18 9 -1.05 0.19 8 -0.98 0.19 5 -0.92 0.19 5 -0.90 0.20 4 -0.68 0.25 3 -1.00 0.53 1 LATVIA LVA 0.31 0.12 13 0.34 0.12 13 0.34 0.12 12 0.23 0.12 12 0.25 0.13 10 0.07 0.14 10 0.04 0.15 9 0.10 0.17 7 -0.65 0.27 3 LEBANON LBN -0.65 0.14 12 -0.77 0.15 12 -0.49 0.16 9 -0.55 0.16 9 -0.46 0.17 7 -0.38 0.17 8 -0.31 0.19 6 -0.24 0.20 6 -0.23 0.26 4 LESOTHO LSO -0.19 0.16 9 -0.05 0.17 9 -0.12 0.22 7 -0.20 0.21 7 -0.33 0.22 6 -0.31 0.26 5 -0.19 0.29 3 -0.21 0.29 3 .. .. .. LIBERIA LBR -0.41 0.24 6 -0.66 0.23 5 -1.15 0.24 4 -1.25 0.24 5 -1.18 0.32 3 -1.11 0.32 3 -1.66 0.28 4 -1.72 0.29 4 -1.74 0.70 1 LIBYA LBY -0.83 0.15 9 -0.87 0.18 8 -0.87 0.17 8 -0.84 0.17 8 -0.82 0.18 6 -0.82 0.19 6 -0.83 0.21 5 -0.78 0.21 5 -0.97 0.26 4 LIECHTENSTEIN LIE 1.25 0.40 2 1.27 0.40 1 1.25 0.34 1 1.30 0.38 1 1.29 0.37 1 1.32 0.39 1 1.39 0.39 1 1.44 0.37 1 .. .. .. LITHUANIA LTU 0.17 0.11 15 0.17 0.12 13 0.27 0.12 12 0.33 0.12 12 0.27 0.13 10 0.25 0.14 10 0.33 0.15 9 0.19 0.17 7 -0.18 0.27 3 LUXEMBOURG LUX 2.27 0.16 7 2.03 0.17 7 1.84 0.19 6 2.01 0.19 6 1.89 0.22 5 2.21 0.26 4 2.05 0.25 4 1.99 0.23 4 1.95 0.30 3 MACAO MAC 0.50 0.29 2 0.39 0.26 2 0.55 0.20 2 1.35 0.38 1 0.82 0.37 1 -0.06 0.39 1 0.45 0.39 1 0.48 0.37 1 .. .. .. MACEDONIA MKD -0.28 0.13 12 -0.34 0.13 12 -0.40 0.13 11 -0.47 0.13 11 -0.59 0.14 8 -0.76 0.17 6 -0.54 0.19 5 -0.45 0.19 4 -1.06 0.33 1 MADAGASCAR MDG -0.16 0.13 13 -0.24 0.14 13 -0.01 0.18 9 -0.13 0.19 8 0.12 0.22 6 0.11 0.28 4 -0.06 0.28 4 -0.40 0.29 4 0.37 0.70 1 MALAWI MWI -0.74 0.14 14 -0.72 0.14 14 -0.82 0.15 12 -0.80 0.15 11 -0.83 0.17 9 -0.96 0.18 8 -0.44 0.20 6 -0.39 0.21 6 -0.50 0.28 3 MALAYSIA MYS 0.19 0.12 16 0.30 0.12 17 0.26 0.12 15 0.37 0.12 15 0.26 0.13 12 0.33 0.14 11 0.36 0.14 10 0.54 0.15 10 0.49 0.17 8 MALDIVES MDV -0.78 0.28 5 -0.52 0.28 4 -0.32 0.27 4 -0.15 0.28 4 0.06 0.24 3 -0.13 0.23 3 -0.14 0.24 3 0.11 0.31 2 .. .. .. MALI MLI -0.43 0.14 12 -0.42 0.15 12 -0.38 0.18 9 -0.47 0.18 9 -0.48 0.22 7 -0.38 0.26 6 -0.64 0.28 4 -0.61 0.29 4 -0.33 0.70 1 MALTA MLT 1.20 0.18 5 1.20 0.21 5 1.04 0.24 4 1.20 0.25 4 1.23 0.26 4 0.82 0.34 2 0.83 0.36 2 0.54 0.35 2 0.37 0.70 1 MARSHALL ISLANDS MHL -0.58 0.42 2 -0.53 0.42 2 -0.44 0.42 2 -0.60 0.43 2 -0.84 0.31 2 -0.95 0.27 2 -0.68 0.30 2 -0.61 0.51 1 .. .. .. MARTINIQUE MTQ 0.81 0.42 1 0.80 0.40 1 0.78 0.34 1 0.86 0.38 1 0.82 0.37 1 0.86 0.39 1 0.92 0.39 1 0.96 0.37 1 .. .. .. MAURITANIA MRT -0.50 0.14 11 -0.60 0.17 10 -0.21 0.24 6 -0.17 0.24 6 0.31 0.25 4 0.26 0.30 3 -0.19 0.29 3 -0.14 0.29 3 .. .. .. MAURITIUS MUS 0.41 0.15 10 0.36 0.14 10 0.33 0.16 8 0.30 0.16 8 0.39 0.18 6 0.47 0.18 6 0.43 0.21 5 0.44 0.25 4 0.45 0.29 2 MEXICO MEX -0.35 0.12 18 -0.34 0.13 18 -0.39 0.14 16 -0.35 0.13 16 -0.19 0.15 12 -0.26 0.16 11 -0.37 0.16 10 -0.53 0.16 9 -0.39 0.20 7 MICRONESIA FSM -0.45 0.42 2 -0.28 0.42 2 -0.28 0.42 2 0.01 0.30 3 -0.36 0.31 2 -0.38 0.27 2 -0.32 0.30 2 -0.24 0.51 1 .. .. .. MOLDOVA MDA -0.68 0.12 15 -0.68 0.12 14 -0.75 0.12 13 -0.99 0.13 12 -0.88 0.13 9 -0.91 0.15 8 -0.70 0.16 8 -0.35 0.17 7 -0.26 0.27 3 MONGOLIA MNG -0.61 0.16 10 -0.49 0.18 9 -0.52 0.19 8 -0.39 0.22 7 -0.19 0.22 5 0.06 0.22 4 -0.31 0.24 4 -0.33 0.30 3 0.37 0.70 1 MONTENEGRO MNP -0.44 0.15 8 -0.47 0.15 8 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. MOROCCO MAR -0.24 0.13 15 -0.25 0.13 15 -0.17 0.15 12 -0.07 0.15 12 -0.09 0.16 10 -0.07 0.16 9 0.06 0.19 7 0.13 0.19 7 0.22 0.25 5 MOZAMBIQUE MOZ -0.59 0.12 16 -0.65 0.13 16 -0.65 0.15 13 -0.71 0.14 13 -0.68 0.16 10 -0.72 0.18 8 -0.69 0.20 6 -0.72 0.21 6 -0.39 0.28 3 MYANMAR MMR -1.46 0.18 6 -1.71 0.20 7 -1.59 0.19 7 -1.67 0.19 7 -1.36 0.21 5 -1.35 0.21 5 -1.37 0.25 4 -1.37 0.24 4 -1.21 0.28 3 NAMIBIA NAM 0.19 0.15 11 0.14 0.16 10 0.04 0.16 12 -0.04 0.16 12 0.05 0.17 10 0.03 0.18 9 0.55 0.24 5 0.67 0.24 5 0.70 0.31 2 NAURU NRU -0.30 0.78 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. NEPAL NPL -0.66 0.15 12 -0.67 0.16 12 -0.75 0.16 10 -0.61 0.17 9 -0.23 0.19 6 -0.33 0.19 5 -0.43 0.20 4 -0.35 0.25 3 -0.31 0.53 1 NETHERLANDS NLD 2.25 0.14 11 2.06 0.15 11 1.99 0.15 10 2.02 0.15 10 2.08 0.16 9 2.18 0.16 9 2.18 0.17 8 2.18 0.17 8 2.22 0.20 7 NETHERLANDS ANTILLES ANT 1.28 0.42 1 1.27 0.40 1 1.25 0.34 1 0.59 0.38 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. NEW CALEDONIA NCL -0.95 0.60 1 -1.32 0.58 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. -1.04 0.70 1 NEW ZEALAND NZL 2.36 0.13 10 2.34 0.14 10 2.24 0.15 8 2.39 0.15 8 2.34 0.16 8 2.28 0.17 7 2.16 0.18 7 2.20 0.17 7 2.29 0.20 6 NICARAGUA NIC -0.78 0.15 15 -0.73 0.16 15 -0.62 0.17 13 -0.38 0.18 12 -0.45 0.19 9 -0.50 0.20 7 -0.93 0.22 6 -0.79 0.25 4 -0.21 0.28 3 95 TABLE C6: Control of Corruption (cont.) 2007 2006 2005 2004 2003 2002 2000 1998 1996 Country Code Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. Est. S.E. N. NIGER NER -0.89 0.15 10 -0.95 0.16 10 -0.80 0.20 7 -0.85 0.21 7 -1.02 0.24 5 -1.07 0.28 4 -0.97 0.28 4 -1.04 0.29 4 -0.33 0.70 1 NIGERIA NGA -1.01 0.12 17 -1.14 0.13 17 -1.21 0.14 15 -1.32 0.14 15 -1.26 0.16 12 -1.38 0.16 10 -1.17 0.17 8 -1.12 0.19 7 -1.25 0.25 5 NORWAY NOR 2.09 0.13 12 2.14 0.14 12 2.05 0.15 10 2.03 0.15 10 2.13 0.16 9 2.18 0.17 8 2.14 0.17 8 2.22 0.17 8 2.30 0.20 7 OMAN OMN 0.62 0.15 8 0.72 0.20 6 0.69 0.18 6 0.79 0.18 6 0.62 0.18 6 0.95 0.18 7 0.83 0.21 5 0.84 0.21 5 0.06 0.26 4 PAKISTAN PAK -0.83 0.13 17 -0.78 0.13 17 -0.99 0.14 14 -1.03 0.14 14 -0.74 0.15 11 -0.83 0.15 9 -0.76 0.17 8 -0.89 0.20 7 -1.04 0.25 5 PANAMA PAN -0.34 0.14 14 -0.34 0.15 14 -0.34 0.15 14 -0.19 0.15 13 -0.22 0.16 10 -0.28 0.17 9 -0.37 0.18 8 -0.22 0.20 6 -0.52 0.26 4 PAPUA NEW GUINEA PNG -1.05 0.15 10 -1.04 0.16 10 -1.06 0.16 10 -0.93 0.16 10 -0.89 0.16 8 -0.77 0.16 7 -0.79 0.17 7 -0.68 0.21 5 -0.31 0.28 3 PARAGUAY PRY -0.96 0.14 14 -1.12 0.15 14 -1.28 0.15 12 -1.23 0.16 11 -1.24 0.17 8 -1.26 0.18 8 -1.30 0.19 7 -1.30 0.21 5 -0.52 0.28 3 PERU PER -0.38 0.13 18 -0.33 0.14 17 -0.47 0.15 14 -0.39 0.15 14 -0.15 0.16 10 -0.30 0.17 10 -0.33 0.17 9 -0.34 0.17 8 -0.14 0.23 6 PHILIPPINES PHL -0.79 0.12 18 -0.78 0.12 18 -0.61 0.12 16 -0.60 0.12 16 -0.48 0.13 12 -0.49 0.14 11 -0.53 0.14 10 -0.35 0.15 10 -0.27 0.17 8 POLAND POL 0.14 0.11 16 0.19 0.11 16 0.19 0.11 14 0.20 0.11 14 0.40 0.12 12 0.34 0.13 12 0.51 0.14 11 0.60 0.14 10 0.39 0.20 7 PORTUGAL PRT 1.13 0.13 12 1.09 0.14 12 1.15 0.15 11 1.22 0.15 11 1.29 0.16 10 1.35 0.17 8 1.24 0.17 8 1.31 0.17 8 1.57 0.20 7 PUERTO RICO PRI 0.46 0.20 5 0.68 0.29 4 1.11 0.27 3 0.96 0.26 3 1.01 0.26 3 1.22 0.31 2 1.18 0.30 2 0.83 0.31 2 1.22 0.57 1 QATAR QAT 1.00 0.18 7 0.82 0.20 7 0.82 0.19 7 0.70 0.21 6 0.69 0.21 6 0.88 0.20 5 0.84 0.25 4 0.83 0.24 4 -0.12 0.28 3 REUNION REU 0.81 0.42 1 0.80 0.40 1 0.78 0.34 1 0.95 0.38 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ROMANIA ROM -0.19 0.11 17 -0.15 0.11 17 -0.22 0.11 15 -0.25 0.11 14 -0.30 0.12 11 -0.35 0.14 10 -0.30 0.15 9 -0.35 0.17 7 -0.24 0.26 4 RUSSIA RUS -0.92 0.11 18 -0.79 0.11 18 -0.77 0.11 16 -0.77 0.11 16 -0.78 0.12 13 -0.91 0.13 12 -0.98 0.14 11 -0.88 0.14 10 -0.84 0.20 7 RWANDA RWA -0.09 0.20 8 -0.11 0.19 8 -0.57 0.23 6 -0.49 0.23 6 -0.70 0.28 3 -0.59 0.30 3 -0.72 0.29 3 -0.87 0.29 3 .. .. .. SAMOA SAM 0.24 0.31 3 0.23 0.30 3 0.17 0.27 3 0.10 0.30 3 0.10 0.24 3 0.03 0.23 3 -0.03 0.24 3 -0.09 0.31 2 .. .. .. SAO TOME AND PRINCIPE STP -0.48 0.23 4 -0.53 0.22 5 -0.81 0.26 4 -0.76 0.26 4 -0.59 0.28 3 -0.27 0.30 3 -0.03 0.29 3 -0.38 0.29 3 .. .. .. SAUDI ARABIA SAU -0.10 0.14 10 -0.03 0.16 9 0.07 0.17 8 0.05 0.17 8 0.32 0.18 7 0.51 0.17 8 0.50 0.20 6 0.43 0.21 6 -0.42 0.25 5 SENEGAL SEN -0.51 0.12 16 -0.45 0.14 15 -0.23 0.15 11 -0.25 0.16 10 -0.35 0.17 9 -0.13 0.18 8 -0.27 0.20 6 -0.31 0.21 6 -0.42 0.28 3 SERBIA YUG -0.41 0.13 13 -0.32 0.13 13 -0.44 0.13 11 -0.47 0.13 10 -0.52 0.14 9 -0.75 0.16 8 -1.11 0.20 5 -1.08 0.20 4 -0.99 0.31 2 SEYCHELLES SYC 0.04 0.18 5 0.07 0.22 5 0.12 0.21 6 0.20 0.20 6 0.28 0.25 4 0.42 0.30 3 0.61 0.29 3 0.47 0.29 3 .. .. .. SIERRA LEONE SLE -1.02 0.20 10 -1.10 0.19 10 -1.03 0.21 7 -0.87 0.22 7 -0.89 0.26 5 -0.79 0.28 4 -0.93 0.28 4 -0.94 0.29 4 -1.74 0.70 1 SINGAPORE SGP 2.20 0.12 14 2.20 0.12 14 2.19 0.12 12 2.33 0.13 12 2.33 0.14 10 2.39 0.14 10 2.20 0.14 9 2.20 0.16 9 2.24 0.17 8 SLOVAKIA SVK 0.28 0.11 13 0.37 0.12 13 0.45 0.12 12 0.45 0.12 12 0.34 0.12 11 0.10 0.13 11 0.24 0.14 10 -0.03 0.15 8 0.40 0.24 5 SLOVENIA SVN 0.90 0.11 13 0.94 0.12 12 0.87 0.12 11 1.00 0.12 11 0.84 0.12 11 0.79 0.13 11 0.76 0.14 10 0.94 0.17 7 1.05 0.27 3 SOLOMON ISLANDS SLB -0.63 0.29 4 -0.29 0.30 3 0.02 0.27 3 -0.53 0.30 3 -1.27 0.31 2 -1.35 0.27 2 -0.98 0.30 2 -0.61 0.51 1 .. .. .. SOMALIA SOM -1.87 0.25 4 -1.82 0.23 4 -1.66 0.23 5 -1.77 0.24 5 -1.72 0.32 3 -1.13 0.34 2 -1.75 0.29 3 -1.72 0.30 3 -1.74 0.70 1 SOUTH AFRICA ZAF 0.32 0.12 17 0.44 0.12 17 0.54 0.13 16 0.44 0.13 16 0.35 0.15 13 0.35 0.15 12 0.56 0.16 10 0.64 0.16 10 0.62 0.20 7 SPAIN ESP 1.16 0.13 13 1.16 0.14 12 1.34 0.15 10 1.41 0.15 10 1.46 0.16 9 1.42 0.16 9 1.43 0.17 8 1.38 0.17 8 1.08 0.20 7 SRI LANKA LKA -0.13 0.13 15 -0.13 0.14 14 -0.26 0.15 12 -0.14 0.15 12 -0.21 0.15 10 -0.21 0.15 9 -0.18 0.16 8 -0.17 0.20 6 -0.27 0.26 4 ST. KITTS AND NEVIS KNA 0.90 0.32 2 0.93 0.31 2 0.97 0.28 3 0.23 0.29 3 0.26 0.42 1 0.30 0.49 1 0.09 0.45 1 0.12 0.51 1 .. .. .. ST. LUCIA LCA 1.09 0.32 2 1.11 0.31 2 1.11 0.28 3 0.28 0.29 3 0.26 0.42 1 0.30 0.49 1 0.47 0.45 1 0.12 0.51 1 .. .. .. ST. VINCENT ANDTHE GRENADINES VCT 0.90 0.32 2 0.93 0.31 2 0.97 0.28 3 0.28 0.29 3 0.26 0.42 1 0.30 0.49 1 0.09 0.45 1 0.12 0.51 1 .. .. .. SUDAN SDN -1.25 0.15 11 -1.15 0.17 10 -1.37 0.17 9 -1.31 0.17 9 -1.26 0.19 7 -1.01 0.19 7 -0.90 0.21 6 -1.00 0.24 5 -1.13 0.31 2 SURINAME SUR -0.26 0.20 4 -0.21 0.22 5 0.06 0.27 4 0.33 0.28 4 0.36 0.30 3 0.19 0.34 2 0.42 0.36 2 0.00 0.35 2 -0.33 0.70 1 SWAZILAND SWZ -0.47 0.17 8 -0.41 0.20 8 -0.61 0.23 7 -0.63 0.21 7 -0.49 0.22 5 -0.28 0.26 4 -0.19 0.29 3 -0.02 0.29 3 .. .. .. SWEDEN SWE 2.37 0.13 12 2.22 0.14 12 2.10 0.15 9 2.17 0.15 9 2.21 0.16 9 2.25 0.17 8 2.23 0.17 8 2.21 0.17 8 2.27 0.20 7 SWITZERLAND CHE 2.32 0.14 11 2.20 0.15 11 2.12 0.15 10 2.10 0.15 10 2.17 0.16 9 2.17 0.17 8 2.13 0.17 8 2.17 0.17 8 2.20 0.20 7 SYRIA SYR -0.88 0.13 12 -0.80 0.15 11 -0.64 0.17 9 -0.64 0.17 9 -0.50 0.18 6 -0.30 0.19 6 -0.61 0.21 5 -0.59 0.21 5 -0.79 0.26 4 TAIWAN TWN 0.41 0.12 14 0.58 0.12 14 0.70 0.12 12 0.73 0.13 12 0.67 0.14 10 0.69 0.14 10 0.77 0.14 9 0.76 0.16 9 0.66 0.17 8 TAJIKISTAN TJK -0.86 0.13 14 -0.93 0.13 14 -1.09 0.14 11 -1.17 0.15 10 -1.03 0.15 7 -1.03 0.16 7 -1.20 0.17 5 -1.34 0.20 4 -1.75 0.57 1 TANZANIA TZA -0.45 0.13 14 -0.42 0.14 14 -0.74 0.15 12 -0.66 0.14 12 -0.88 0.16 10 -1.00 0.17 9 -1.08 0.19 7 -1.09 0.19 7 -1.10 0.26 4 THAILAND THA -0.44 0.12 17 -0.28 0.12 17 -0.19 0.12 15 -0.21 0.12 14 -0.28 0.13 11 -0.32 0.14 11 -0.20 0.14 10 0.00 0.15 10 -0.31 0.17 8 TIMOR-LESTE TMP -0.92 0.25 6 -0.88 0.23 5 -0.79 0.27 4 -0.52 0.33 4 -0.52 0.29 3 -0.53 0.39 1 .. .. .. .. .. .. .. .. .. TOGO TGO -0.98 0.16 10 -1.09 0.17 11 -0.85 0.20 8 -0.90 0.21 7 -0.76 0.24 5 -0.65 0.28 4 -0.64 0.28 4 -0.61 0.29 4 -1.04 0.70 1 TONGA TON -1.00 0.31 3 -1.28 0.30 3 -1.28 0.27 3 -0.51 0.30 3 -0.62 0.31 2 -0.72 0.27 2 -0.59 0.30 2 -0.24 0.51 1 .. .. .. TRINIDAD AND TOBAGO TTO -0.19 0.15 9 -0.14 0.17 9 0.02 0.16 9 0.03 0.17 8 0.06 0.17 7 -0.06 0.18 6 0.14 0.19 6 0.30 0.21 5 0.87 0.28 3 TUNISIA TUN 0.08 0.13 13 0.02 0.13 13 -0.04 0.15 12 0.28 0.15 12 0.42 0.16 9 0.47 0.16 9 0.14 0.19 7 0.14 0.19 7 -0.10 0.26 4 TURKEY TUR 0.04 0.12 17 0.02 0.12 17 -0.05 0.13 16 -0.16 0.13 16 -0.24 0.15 12 -0.43 0.15 11 -0.20 0.16 10 -0.17 0.16 9 0.01 0.20 7 TURKMENISTAN TKM -1.18 0.13 8 -1.27 0.14 8 -1.31 0.13 8 -1.36 0.14 7 -1.13 0.15 6 -1.19 0.17 6 -1.03 0.17 5 -1.06 0.18 5 -1.52 0.41 2 TUVALU TUV -0.20 0.40 2 -0.06 0.38 2 -0.09 0.32 2 0.56 0.35 2 -0.72 0.43 1 0.13 0.32 1 0.11 0.37 1 .. .. .. .. .. .. UGANDA UGA -0.76 0.12 16 -0.73 0.13 16 -0.81 0.15 13 -0.75 0.14 13 -0.78 0.16 11 -0.98 0.17 9 -0.97 0.19 7 -0.88 0.19 7 -0.55 0.26 4 UKRAINE UKR -0.73 0.11 18 -0.65 0.12 16 -0.59 0.12 15 -0.90 0.12 15 -0.90 0.13 13 -0.97 0.14 11 -1.01 0.15 10 -1.16 0.15 9 -0.82 0.24 5 UNITEDARAB EMIRATES ARE 1.00 0.15 8 0.96 0.16 8 0.96 0.16 8 1.16 0.16 8 1.18 0.18 6 1.16 0.18 7 0.83 0.21 5 0.74 0.21 5 0.13 0.26 4 UNITEDKINGDOM GBR 1.89 0.13 12 1.90 0.14 12 1.93 0.15 10 1.99 0.15 10 2.08 0.16 9 2.10 0.16 9 2.13 0.17 8 2.16 0.17 8 2.21 0.20 7 UNITEDSTATES USA 1.44 0.13 14 1.34 0.14 14 1.56 0.15 11 1.75 0.15 11 1.74 0.16 10 1.88 0.16 9 1.77 0.17 8 1.75 0.17 8 1.75 0.20 7 URUGUAY URY 0.96 0.14 13 0.83 0.15 12 0.83 0.15 12 0.69 0.15 12 0.73 0.16 9 0.75 0.17 9 0.68 0.18 8 0.80 0.20 6 0.43 0.26 4 UZBEKISTAN UZB -0.95 0.12 14 -0.99 0.13 13 -1.17 0.13 11 -1.15 0.13 11 -1.07 0.13 10 -1.02 0.14 9 -0.93 0.16 7 -1.02 0.19 5 -1.05 0.27 3 VANUATU VUT 0.21 0.30 4 0.18 0.30 3 0.26 0.27 3 -0.61 0.30 3 -0.65 0.31 2 -0.79 0.27 2 -0.85 0.30 2 -0.24 0.51 1 .. .. .. VENEZUELA VEN -1.04 0.12 18 -0.98 0.13 17 -1.02 0.14 16 -0.99 0.13 16 -1.08 0.15 13 -1.06 0.16 11 -0.67 0.16 10 -0.86 0.16 9 -0.83 0.20 7 VIETNAM VNM -0.69 0.12 18 -0.75 0.13 17 -0.77 0.13 14 -0.79 0.13 14 -0.63 0.13 12 -0.71 0.13 11 -0.77 0.13 10 -0.68 0.16 9 -0.54 0.19 7 VIRGIN ISLANDS (U.S.) VIR 0.81 0.42 1 0.80 0.40 1 0.78 0.34 1 0.63 0.38 1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. WEST BANK GAZA WBG -0.77 0.23 3 -1.08 0.32 3 -0.99 0.30 3 -0.48 0.31 3 -0.95 0.32 2 -0.93 0.36 2 -0.96 0.39 1 -0.96 0.37 1 .. .. .. YEMEN YEM -0.62 0.14 13 -0.68 0.15 13 -0.72 0.16 9 -0.87 0.17 9 -0.68 0.18 7 -0.69 0.19 6 -0.66 0.21 5 -0.60 0.21 5 -0.29 0.28 3 ZAMBIA ZMB -0.60 0.13 14 -0.71 0.14 14 -0.75 0.15 12 -0.82 0.14 13 -0.86 0.16 10 -0.95 0.17 9 -0.90 0.19 7 -0.88 0.19 7 -1.04 0.26 4 ZIMBABWE ZWE -1.25 0.12 16 -1.32 0.13 16 -1.28 0.15 14 -1.29 0.15 13 -1.19 0.16 11 -1.20 0.16 9 -0.96 0.17 8 -0.38 0.17 8 -0.17 0.24 5 96 Appendix D: Technical Details on the Construction of the WGI This appendix summarizes all of the relevant technical information regarding the construction of the Worldwide Governance Indicators (WGI). All of the technical details provided here can be found in various papers in the "Governance Matters" series (Kaufmann, Kraay and Zoido-Lobatón (1999a, 1999b and 2002) and Kaufmann, Kraay and Mastruzzi (2004, 2005, 2006 and 2007). The first section explains the Unobserved Components Model that provides the statistical basis for the WGI. The second section explains in detail two types of rescaling applied to the aggregate WGI. D1. The Unobserved Components Model (UCM) This section deals with the specification and estimation of the unobserved components model on which the WGI are based. The basic premise of the UCM is simple: each of our observed underlying data sources provides a noisy or imperfect signal of the true, but unobserved, level of governance in a country. The UCM provides a framework for extracting a minimum-variance estimate of governance from the observed data. Specification of the UCM Let gj denote the unobserved true level of a particular dimension of governance in country j, for example, Control of Corruption. The observed data on corruption consists of a cluster of k=1,...,K indicators, each one providing a numerical rating of some aspect of corruption in each of the j=1,..,Jk countries covered by that indicator. Note that each indicator might cover a different number of countries, hence Jk depends on the indicator k. Note also that each country j might appear in a different set of indicators, and let Kj denote the set of indicator in which country j appears. To conserve on notation we will also let Kj denote the number of indicators available for country j. Finally note that we are suppressing time subscripts here to keep notation simple. Let yjk denote the score of country j on indicator k. We assume that we can write the observed score as a linear function of unobserved governance, gj, and an error term, jk, as follows: (1) yjk = k + k gj + jk ( ) where k and k are unknown parameters which map unobserved governance gj into the observed data yjk. As a choice of units, we assume that g(j) is a normal random variable with mean zero and variance one. We assume that the error term is also normally distributed with mean zero and standard deviation k which varies across data sources k. We also assume that the error term is uncorrelated across data sources.19 The parameters of the unobserved components model, k, k and k have very straightforward interpretations. Since the mean of unobserved governance and the error term are by assumption both zero, the parameter k simply captures the mean of the 19This is a strong assumption, but one that is necessary for identification. See Kaufmann, Kraay, and Zoido-Lobaton (1999a) and Kaufmann, Kraay, and Mastruzzi (2006) for detailed discussion of the validity of this assumption and the consequences of relaxing it. 97 observed data from indicator k. The parameter k captures the slope of the relationship between true but unobserved governance and the observed data in indicator k. Since unobserved governance has a standard deviation of one, k is the increase in the observed data associated with a one standard deviation improvement in unobserved true governance. Finally, the standard deviation of the error term, k captures how informative the observed indicator of governance is about true governance. If k is large (small), the observed data provides a very imprecise (precise) signal of true governance. The Conditional Distribution of Governance The assumptions of the UCM detailed above allow us to summarize our knowledge about the unobserved level of governance in each country by calculating the distribution of unobserved governance conditional on the observed data for each country. Let yj = yj ,...,yjKj ( ) 1 denote the observed data for country j from each of the Kj data sources in which it appears. Since we have assumed that unobserved governance gj and the error terms jk are jointly normally distributed, this implies that the joint distribution of the observed data, yj, and unobserved governance, gj, is also normal. This in turn means that the distribution of governance conditional on the observed data for each country will also be normal. Our estimate of governance for each country will simply be the mean of this conditional distribution, and the precision of this estimate will be the standard deviation of this conditional distribution. Applying standard results for the multivariate normal distribution, the conditional distribution of gj given the observed data yj is normal, with the following mean and variance: (2) E gj | yj = wjk [ ] kKj yjk - k k -1 (3) V gj | yj =1+ [ ] -2 k kKj In particular, the mean of governance conditional on the data available for country j, that we use as our estimate of governance, is just a weighted average of the standardized scores from each data source. The weights applied to each data source are inversely -1 proportional to the precision of each data source, i.e. wk = k 1+-2 -2 k' k'Kj . In other words, data sources that provide a more precise signal of governance receive a greater weight in the conditional mean, and hence in our estimate of governance. The variance of the conditional distribution summarizes how reliable or precise is this estimate of governance. This variance is smaller the larger is the number of data sources available for each country, and the more precise are each of those data sources. We refer to the expression in Equation (2) as the "governance estimate" for each country, and the square root of the variance in Equation (3) as the "standard error" of the 98 estimate of governance for each country. We can also use these expressions to form confidence intervals for governance, that we sometimes also informally refer to as "margins of error". In particular, given our assumptions there is a 90 percent probability that the true level of governance falls in a range of +/- 1.64 x SD(gj|yj) around the estimate of governance.20 Estimating the Parameters of the UCM In order to implement (2) and (3), we need to first estimate the unknown parameters k, k and k for every indicator k. This in turn requires us to distinguish between "representative" and "non-representative" indicators, which we treat differently in the estimation process. Representative indicators are indicators that cover a set of countries in which the distribution of governance is likely to be similar to that in the world as a whole. Practically these include all of our indicators with large cross-country coverage of developed and developing indicators. In contrast non-representative indicators cover either specific regions (for example the BEEPS survey of transition economies or the Latinobarometer survey of Latin American countries), or particular income levels (for example the World Bank CPIA ratings that cover only developing countries). Our classification of "representative" and "non-representative" indicators is given in Table 1 of this paper. For the set of representative indicators, we use the assumption of normality of gj and jk to write down the likelihood function of the observed data. The assumption of representativeness is crucial here because it justifies our assumption of a common distribution of governance across these different sources. As useful notation, let = 1,...,Kj , = 1,...,Kj , 2 = 1,...,Kj and let B and be diagonal matrices ( ) ( ) ( 2 2) with and 2 on the diagonal. Using this notation, the mean of yj is and the variance of yj is '+BB'. The contribution to the log-likelihood of country j therefore given by: (4) lnL(,,;yj) ln| | +(yj - )'-1(yj - ) Summing these over all countries j and then maximizing over the unknown parameters delivers our maximum-likelihood estimates of k, k and k for every representative indicator k. Identification requires that we have a minimum of three representative indicators. Note that the number of data sources available for each country varies, and so the dimension of yj and is Kjx1, and conformably is KjxKj. This way we are able to compile the likelihood function even though there potentially are missing observations for each country even among the representative indicators. We cannot apply this method to non-representative indicators. To see why, consider the maximum-likelihood estimate of k, which unsurprisingly is the mean score across countries on indicator k. It is straightforward to see from Equation (1) that the expected value of the sample mean of scores on indicator k is k+k gk , where gk denotes the average level of governance in the sample of countries covered by indicator 20See Kaufmann, Kraay and Zoido-Lobatón (1999a) for the Bayesian interpretation of these expressions. 99 k. For representative indicators, our choice of units for governance normalizes gk = 0 , and so the sample mean delivers a consistent estimate of k. However, for a non- representative indicator where the average level of governance is different from the world as a whole, gk 0 and the sample mean does not provide a consistent estimate of k. We can nevertheless obtain consistent estimates of the unknown parameters of the non-representative indicators by using the following simple argument. If gj were observable, we could estimate k, k and k for any indicator by regressing the observed scores yjk on gj. Although gj is itself not observable, we do have an estimate of gj based on the representative indicators. In particular, let g*j denote this preliminary estimate of gj based on only on the data from the representative indicators. We can decompose this conditional mean into observed governance plus its deviation from the mean, i.e. g*j=gj+uj. Since uj is independent of gj, we can view g*j as measuring gj with classical measurement error. It is well-known that OLS estimates of k from a regression of yjk on g*j will produce downward-biased estimates due to the usual attenuation bias. In particular, the probability limit of the OLS slope coefficient is k 1- V[g*j] V[uj] . Since the variance of uj is simply the variance of the conditional mean of gj given in Equation (3), and since V[g*j] is observable, we can correct the OLS coefficients for this attenuation bias to arrive at consistent estimates of the parameters of the non- representative indicators. Finally, we collect all of the parameter estimates from the representative and non-representative surveys, and insert them into the expressions in Equations (2) and (3) to arrive at estimates of governance and standard errors for each country. As discussed in the next section, there are two further rescaling steps before we arrive at the final estimates that we report. D2. Rescaling the Aggregate Governance Indicators We next perform two rescalings of the aggregate indicators obtained using the procedure described above. We first rescale the data to set the mean of the governance estimates to zero, and their standard deviation to one. The estimates of governance obtained from the UCM theoretically have a mean of zero, and a standard deviation slighly less than one. In any particular sample, however, the mean could be different. To avoid confusion in interpreting the data, we begin by setting the mean of the governance estimates for each indicator and year to zero, and the standard deviation to one. In particular, for each indicator and year, we subtract the sample mean (across countries) from each country, and divide by the sample standard deviation (across countries). We then also divide the standard errors of the governance estimates for each country by the sample standard deviation of the governance estimates. This first rescaling is just a renormalization of the scores, and of course has no impact on countries' relative positions on the governance indicators. It is also consistent with our choice of units for governance noted above, and notably that it has a mean of zero and a standard deviation of one in each period. If there were trends in global averages of governance over time, this choice of units would not be appropriate. 100 However, as we have documented in Kaufmann, Kraay and Mastruzzi (2004, 2005, 2006, and 2007) and in this paper, we do not find strong evidence of significant trends in world averages of governance in our underlying indicators. We therefore think this choice of units is appropriate. Moreover, absent any changes in global averages of governance, changes over time in countries' relative positions on the WGI can also be interpreted as changes in their absolute governance scores. The second rescaling is substantively more interesting, and addresses the fact that the sample of countries covered by our governance indicators has expanded since 1996, and quite considerably for some of our indicators. If the new countries added each year were broadly representative of the worldwide distribution of governance, this too would pose no special difficulties. However, for some of our indicators, we find that countries added in later years score on average somewhat higher than countries that were continuously in the sample. This in turn means that it would be inappropriate to impose a global average governance score of zero in earlier periods for the smaller set of countries for which data is available in the earlier periods, since our earlier estimates did not include the better-than-average performers added later. It also means that some countries in our aggregate indicators in the earlier years would have showed small declines in some dimensions of governance over time that were driven by the addition of better-performing countries in later years. We address this issue with a second simple re-scaling of the aggregate governance indicators. We take the most recent year of our indicators as a benchmark. In particular, the 2006 indicators cover between 206 and 212 countries, which we can think of as representative of the world as a whole. Consistent with our choice of units for governance, the estimates for 2006 have zero mean and standard deviation of one across countries due to the first standardization noted above. We next consider the countries that were added in 2006 relative to 2005. We then adjust the world-wide average score in 2005 so that it would have a mean of zero had we included the 2006 scores for those countries added in 2006 relative to 2005.21 We then continue backwards in time in the same way to adjust the data for each previous year back to 1996. In particular, to arrive at the final score reported for each country, we need to subtract the adjusted mean and divide by the adjusted standard deviation. The standard error of the governance estimate also needs to be divided by the indicated adjusted standard deviation. 21The adjustment factor for the mean is simply - yT (NT -NT )/NT -1 -1where NT is the number of countries with data in period T and yT is the average score of the additional countries in period T. The higher is the average score of the new entrants and/or the more new entrants there are, the more we lower the mean in the previous period. This ensures that a hypothetical sample consisting of our year T-1 adjusted scores for all countries combined with the year T scores for the countries added in year T relative to T-1 would have a mean of zero and standard deviation of one. We also adjust the standard deviation of the year T scores to ensure that the standard deviation of this hypothetical sample would be one. We do this by multiplying the scores (and the standard errors) for each country in year T-1 by a factor of NT /NT-1 - ((NT -NT- )/NT-1)VT + y2T - yT-1 2 , where VT is the variance across countries in our estimates of governance in year T for the new entrants to the sample in period T. The greater is the dispersion in the scores of new entrants, the more we need to reduce the dispersion of scores in the previous years. 101 Four points are worth noting about this adjustment. · Since we adjust the scores for all countries in a given year and indicator by the same amount, this adjustment also has no effect on the relative positions of countries on that indicator in that year. It does however make countries' scores more comparable over time, since the adjustment is designed to remove the effect of adding new countries on the scores of countries already in the sample. · As a consequence of this adjustment, global averages of the adjusted data show moderate trends over time, mostly improvements as the countries added over time typically have slightly better scores than those countries continuously in the sample. It is important to remember though that this improvement does not reflect an average improvement for all countries in the world. Rather it reflects the changing composition of our sample since the new entrants during this period have had above-average performance in this dimension of governance. As noted above there is no evidence of any significant improvement in the world average for the country sample that has been consistently covered over time. · This rescaling of the aggregate indicators is perfectly consistent with the unobserved components model that we use to construct the aggregate indicators in each period. In particular, rescaling the mean and standard deviation of the aggregate indicators in the way that we do is equivalent to imposing slightly different means and standard deviations of governance as a choice of units in each of the periods. And as we have argued this changing choice of units is an appropriate way to correct for changes in the composition of countries covered by the indicators over time. · Finally, for some purposes it is useful to look just at countries' percentile ranks rather than their scores on our governance indicators. Without similar adjustments these percentile ranks too would not be fully comparable over time as they too would be influenced by new entrants. Thus, we also perform such adjustment to the percentile ranks, and when we report countries' scores in the form of percentile ranks on our website, we compute the percentile ranks based on a sample consisting of the actual data we have for that indicator and year, combined with imputed data from the nearest year as described above. 102