Lao PDR 2015 Census-Based Poverty Map – June 2016 3 Authors Harold Coulombe, Consultant, World Bank Michael Epprecht, Centre for Development and Environment (CDE) Obert Pimhidzai, Economist, GPV02, World Bank Vilaysouk Sisoulath – Director of Research and Analysis Division, Social Statistics Department, LSB Supervisors Dr. Samaychanh Boupha - Vice Minister, Head of Lao Statistics Bureau Phonesaly Souksavath, Deputy Head of Lao Statistics Bureau Thirakha Chanthalanouvong, Deputy Director General of Social Statistics Department, LSB Salman Zaidi - Practice Manager, GPV02, World Bank Copyright © 2016 by Ministry of Planning and Investment, Lao Statistics Bureau Ban Sithan Neua, Souphanoungvong Road Vientiane Capital, Lao PDR Tel: + 856 21 214740; 242023 Fax: + 856 21 242022; 219129 Email: lsbadmin@etlaol.com Webpage: http://www.lsb.gov.la 4 Lao PDR 2015 Census-Based Poverty Map – June 2016 Abstract This report documents the construction of, and presents the main results from a poverty map of Lao PDR based on the 2012/13 LECS-5 survey and the 2015 Population and Housing Census. Monetary and non-monetary poverty indicators are presented at two different administrative levels: province and district. The non-monetary poverty indicators – closely related to the SDGs – were easily calculated directly from the Census databases. However, monetary poverty indicators are more challenging to compute as no income or expenditure information was collected by the Census. Based on a statistical methodology linking survey and Census datasets, poverty headcount and other monetary poverty indicators have been estimated at local levels. Two main findings stand out from the analysis of the results. First, the results show that for most indicators there is a relatively high level of heterogeneity across provinces and districts. Variations in poverty level (monetary or not) raises the possibility of more efficient geographical targeting. Second, we found that correlations between the different indicators are quite low in most cases. In such circumstances, policy makers need to have indicators specific to different projects or programmes. A one-size-fits-all indicator does not yield efficient outcomes for any intervention. Lao PDR 2015 Census-Based Poverty Map – June 2016 5 Foreword Over the last four years, the Lao Statistics Bureau has conducted two major activities that significantly improve our understanding of poverty in the Lao PDR. The fifth round of the Lao Expenditure and Consumption Survey (LECS 5) was conducted over a 12 month period spanning 2012 and 2013, and then the third national Population and Housing Census was conducted in 2015. Based on the former, the Lao Statistics Bureau and the World Bank Group published a poverty profile in 2014. It provided an update of poverty statistics from previous surveys and presented poverty estimates at the provincial level. Such information is very useful to monitor poverty over time and across provinces but does not permit to identify variation in poverty within districts or pinpoint where poverty is concentrated at the local level. The 2015 Population and Housing Census data was therefore combined with the LECS 5 using a sophisticated and reliable small-area statistical technique that made it possible to estimate poverty rates at the local level and therefore improve our knowledge of poverty at lower administrative levels and reveal pockets of poverty. Such local-level information greatly increases the targeting efficiency of projects and programs aiming at reducing poverty. This report presents poverty indices at the district level based on small-area estimations, and uses the results to present maps of poverty in the country. Acknowledging that poverty is multi- dimensional, this report also presents non-monetary indicators that fit perfectly in the recently approved Sustainable Development Goals (SDG) framework. This report is a product of a joint collaborative effort among the Lao Statistics Bureau (LSB), the Centre for Development and Environment (CDE) and the World Bank Group. It was made possible with financial support from the Australian Government, Department of Foreign Affairs and Trade, the Swiss Agency for Development and Cooperation through financing of the Lao DECIDE Info Project and the World Bank Group, through the LAOSTAT Project. The Lao Statistics Bureau greatly appreciates both the support received from these organizations and the great collaboration that ensured. As this report comes at the start of the implementation of the 8th National Socio-Economic Development Plan, it is my hope that the results presented here will be used to prioritize the poorest districts and target programs to areas most in need, be it in terms of lack of income, or in terms of low level of education and employment activities or simply as not having basic infrastructure. The findings presented here will also serve as a benchmark for monitoring progress in reducing poverty during the implementation of the 8th National Socio-Economic Development Plan. Dr. Samaychanh Boupha, Vice Minister, Head of Lao Statistics Bureau 6 Lao PDR 2015 Census-Based Poverty Map – June 2016 Table Of Contents I. Introduction 8 II. Poverty Mapping Methodology 10 Monetary Poverty 10 Non-monetary Poverty 10 III. Results 11 Monetary Poverty Indicators 11 Non-Monetary Indicators 18 Relationship between the Different Poverty Indicators 22 IV. Concluding Remarks 24 References 25 Appendix 1: Monetary Poverty Methodology 26 First stage 26 Second stage 26 Third stage 27 Appendix 2: 30 Databases and Lao PDR Administrative Layers 30 Census 30 LECS-5 Survey 30 Administrative Layers 31 Appendix 3: Monetary Poverty Methodology in Practice 32 Stage 1: Aligning the data 32 Stage 2: Survey-based regressions 32 Stage 3: Welfare indicators 34 How low can we go? 34 Appendix 4: Survey-Based Regression Models 38 Appendix 5: Administrative Unit Labels 43 Appendix 6: Monetary and Non-Monetary Maps at Different Administrative Levels 46 Appendix 7: Correlation Matrix between the different Poverty Indicators 89 Appendix 8: Monetary Poverty Indices, by Province and District 91 Appendix 9: Non-Monetary Indicators (Education), by Province and District 100 Appendix 10: Non-Monetary Indicators (Others), by Province and District 108 8 Lao PDR 2015 Census-Based Poverty Map – June 2016 I. Introduction This report documents the construction of, and geographic units in order to optimize the shows some results from, a monetary poverty efficiency of their decisions. Telling Laotian map based on data from the 2012/13 Lao policy makers that the neediest people are in Expenditure and Consumption Survey (LECS- the rural areas would not be too impressive, 5) and the 2015 Population & Housing Census. since that information is well known and not Based on a methodology developed by Elbers, very useful because it is too vague; telling Lanjouw and Lanjouw (2003), we calculate them in which districts the poorest households monetary poverty indicators at low levels of are concentrated would be more useful and aggregation, using the detailed information convincing! Using regional information often found in the survey and the exhaustive coverage hides the existence of poverty pockets in of the population found in the Census. Results otherwise relatively well-off regions, leading for the 18 provinces and 148 districts are to poorly targeted programmes. Inefficient presented and briefly analysed in this report. targeting could also occur if relatively well-off areas are contained in otherwise poor regions. In past decades poverty profiles 1 have been Having better information at the local level developed into useful tools to characterise, would necessarily minimise leaks and therefore assess and monitor poverty. Based on permit more cost-effective and efficient anti- information collected in household surveys, poverty programmes. Poverty indicators are including detailed information on expenditures needed at a local level as spatial inequalities and incomes, these profiles present the can be considerable within a given region. characteristics of the population according to levels of monetary and non-monetary For a first time, such information was standards of living, while helping to assess the developed in 2007 using small-area estimation poverty reducing effect of some policies and techniques producing high-resolution poverty to compare poverty levels between regions or maps based on 2005 Lao PDR Population groups or over time. While these household and Housing Census data and 2002/3 Lao survey-based studies have greatly improved Expenditure and Consumption Survey data our knowledge of welfare levels of households (Epprecht et al, 2008). Spatially disaggregated in general and of the poorer ones in particular, poverty indicators have not been updated the approach has a number of limitations. In since. particular, policy makers and planners need finely disaggregated information in order The methodology used in this report to compute to implement their anti-poverty programs. up-to-date monetary poverty indicators at Typically, they need information for small a high level of spatial disaggregation using 1 See Pimhidzai et al. (2014) for the latest published poverty profile in Lao PDR. Lao PDR 2015 Census-Based Poverty Map – June 2016 9 information on household expenditure, is fully The paper is structured as follows: we first consistent with poverty profile figures, and present the methodology used to compute permits the computation of standard errors the monetary and non-monetary poverty for these poverty indicators. Since these types indicators in less technical language. Section of poverty maps are fully compatible with 3 follows, containing the main results for the poverty profile results, they should be seen as a monetary and non-monetary indicators. In natural extension to poverty profiles, a way to the last section some concluding remarks operationalise poverty profile results. focus on the policy implications of the different findings. More technical presentations of the Apart from monetary poverty indicators, this methodology and how it was applied in practice report also presents a series of non-monetary are found in Appendices 1 to 4. The results indicators, many of them being Sustainable are presented in two different ways, maps Development Goal (SDG) indicators. From the (Appendices 5 and 6) and tables (Appendices 8, Census database it is possible to compute 9 and 10). Appendix 7 presents the correlation 29 non-monetary indicators at the same matrix between the different indicators. administrative levels as the monetary indicators (province and district). 10 Lao PDR 2015 Census-Based Poverty Map – June 2016 II. Poverty Mapping Methodology The indicators presented in this report use two statistic. These standard errors are important different methodologies, one for the monetary because they tell us to what extent we can poverty indicators and a second for the non- disaggregate the poverty indicators. As we monetary indicators. disaggregate our results at lower and lower levels, the number of households to which the Monetary Poverty econometric models are applied decreases as well, therefore they yield less and less precise The basic idea behind the methodology is estimates. At a certain point, the estimated rather straightforward. First a regression poverty indicators become too imprecise to model of per-capita expenditure is estimated be used with confidence. Computation of using LECS-5 survey data, limiting the set standard errors helps us decide where to stop of explanatory variables to those that are the disaggregation process. The methodology common to both that survey and the latest used to estimate monetary poverty is further Census. Next, the coefficients from that model discussed in more technical terms in Appendix are applied to the Census data set to predict 1, while the datasets used are described in the expenditure level of every household in the detail in Appendix 2. Appendices 3 and 4 Census. And finally, these predicted household show intermediate output in producing these expenditures are used to construct a series of monetary poverty indicators and argue that welfare indicators (e.g. poverty level, depth, our results are reliable. severity, inequality2) for different geographical subgroups. Non-monetary Poverty Although it is conceptually simple, proper Contrary to the monetary poverty indicators, implementation of this methodology requires which are very complex and time-consuming to complex computations. These complexities compute, the non-monetary indicators are very mainly arise from the need to account for straightforward to calculate and do not involve spatial autocorrelation (expenditures of any estimation procedures. In most cases we households within the same local area are simply take the proportion of individuals or correlated) and heteroskedasticity in the household with a particular characteristics, development of the predictive model. Taking like having electricity at home, for example. into account these econometric issues ensures unbiased predictions. A further factor making computation non-trivial is our desire to compute standard errors for each welfare 2 Although a series of inequality measures were computed at the local level, the results are not presented in this report. Inequality at the local level is rather difficult to analyse and its interpretation can be misleading. However, inequality measurements are available to researchers on request. Lao PDR 2015 Census-Based Poverty Map – June 2016 11 III. Results This section presents the main results for both poverty figures reveal a more detailed the monetary and non-monetary indicators. pattern of poverty. These maps clearly show how different parts of the 18 provinces are Monetary Poverty Indicators far from homogeneous. For example, the Borikhamxay province has both one of the Based on the methodology described in the poorest three district (Xaychamphone) in Lao previous section and in Appendices 1 to 4, we PDR as well as two of the richest ones (Pakxane obtained a series of poverty estimates for each and Thaphabath). Some other provinces province and district in Lao PDR. Those results (Luangprabang, Xayaboury and Vientiane can be found in Appendix 8. In these tables Province) also experience large variation in we present the three most common poverty poverty headcount among their districts. In this indices found in the literature as well as in type of environment, the usefulness of poverty the latest Lao PDR Poverty Profile: poverty maps becomes evident. Such variations in headcount, poverty gap index and poverty poverty headcount within a given province severity index3. Along with these poverty would make district-level targeting much more estimates for each administrative unit, we also efficient that a simple province-level targeting. present the population and the number of poor In other words, district level targeting would people. We converted these poverty figures lead to more resources going to the poorest into a series of maps for each administrative districts than otherwise. Poverty gap indices unit under study. Maps 1a and 1b present are presented in Maps 2, showing a similar the poverty headcount estimates while the spatial pattern as the poverty headcount. poverty gap index maps are found in Appendix 6 (Maps 2a and 2b). In order to better identify Maps 1c shows side-by-side district-level maps the different administrative units, the names for 2005 and 2015. There has been an overall of the different province and districts are found decline in poverty across the board, but poverty on a map in Appendix 5. declined more in the north. The geographical pattern of poverty has changed as a result, The use of maps rather than tables makes it with more of the poorest districts now located possible to visualise a geographical pattern in provinces in the south. which is difficult to detect in the latter. It is also an efficient way to present the different Figure 1 is a more formal way to examine these figures. Examining Maps 1a and 1b, which show within-region variations in poverty rate. For the poverty headcount by province and district each of the four regions (Vientiane Capital, respectively, it is notable how disaggregating North, Central and South), the vertical bar 3 These three poverty indices are part of the FGT class of indices as developed by Foster et al. (1984) 12 Lao PDR 2015 Census-Based Poverty Map – June 2016 presents the range of poverty headcounts being the poorest province in Lao PDR. In any along with a bullet point showing the regional poverty reduction scheme, those two areas poverty headcount rate. Looking at the first would clearly call for different type of targeting panel showing the variation in poverty rates at strategies. In Saravane, the high poverty the province-level, a considerable within-region headcount and poverty density would call for spread of poverty rates in all three regions geographical targeting covering potentially all outside the capital can be observed. The individuals in the province. However, such type poverty rates differ by around 17 percentage of targeting rule would yield a much higher points within provinces in the North and by level of leakage in Vientiane Capital. The large almost 30 percentage points in the South. leakage (i.e. covering non-poor individuals) The bottom panel presents the same figures would demand a different targeting approach at the district level and shows a significantly aiming at better reaching the poor individuals larger range of poverty headcount rates. The in an otherwise much richer province. incidence of poverty is estimated to be 12.9 percent and 73 percent respectively, in the two districts with the lowest (Xaysetha District in Attapeu Province) and highest poverty rates (Toomlarm District in Saravane Province) in the South. This figure shows a considerable increase in information by moving from province to the district level. The highlighted large spread in poverty rates, particularly at the district level, demonstrates that poverty maps provide policy-makers with useful information for targeting the poorest districts. Combining information on the level of poverty headcount and the actual number of individuals, Map 2 presents poverty density for Lao PDR. In that map, each red dot represents 100 poor individuals and it permits to geo-localize where the poor people are concentrated. Map 2 shows that poor people are mainly concentrated in two separate locations, a first one in the capital Vientiane and a second one around Saravane Province. Those two locations are very different. Vientiane, has the lowest poverty headcount but is the most populated part of the country, while the high poverty density in Saravane Province is mainly the result of Lao PDR 2015 Census-Based Poverty Map – June 2016 13 Map 1: Poverty Headcount (P0) A. Province Sources: Authors’ calculation based on 2012/13 LECS-5 and 2015 Lao PDR Census 14 Lao PDR 2015 Census-Based Poverty Map – June 2016 B. District Sources: Authors’ calculation based on 2012/13 LECS-5 and 2015 Lao PDR Census Lao PDR 2015 Census-Based Poverty Map – June 2016 15 C. 2005 versus 2015 District-level Poverty Headcount Maps 2015 District-level 2005 District-level Poverty Headcount Maps Poverty Headcount Maps 16 Lao PDR 2015 Census-Based Poverty Map – June 2016 Map 2: Poverty Density !! ! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! !!! ! !! ! ! ! ! ! ! ! !! ! ! ! ! ! !! ! ! ! ! ! ! Phongsaly ! ! !! ! ! !! !! !! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! . ! ! ! ! !! ! ! ! ! ! ! ! ! !! ! ! ! ! ! !! ! ! ! ! ! ! ! !! ! ! ! ! ! ! !! ! ! ! !! ! ! ! ! ! ! ! ! ! ! !! ! !! ! !! ! ! ! !! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! !!! ! ! ! ! !! !! ! ! ! !! ! ! ! ! !! ! ! ! ! ! ! ! ! !! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! !! !! ! !! ! ! ! ! ! ! !! ! ! ! !! ! ! !! ! ! ! ! ! !!! ! ! !! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! !! !! ! ! !! ! ! ! ! !!! !! ! ! ! ! ! ! ! ! ! !! ! !! ! ! ! ! !! ! ! ! ! ! ! ! !! ! ! ! ! !! ! ! !! !! ! ! ! ! !! !! ! Luang Namtha ! ! ! ! !! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! !! ! ! ! !! ! ! ! !! ! ! !! ! ! ! ! ! ! !! ! ! ! !! ! ! ! ! ! ! ! ! ! !! ! ! ! ! !! ! ! !! ! ! ! ! !! ! ! ! ! ! ! ! ! !! ! ! ! ! ! !! !! ! ! ! !! ! !!! ! !! ! ! ! . ! ! ! ! !! ! ! ! ! ! !! ! ! ! ! ! !!! ! ! ! ! ! ! !! ! !! ! ! ! ! ! ! ! ! ! ! ! ! ! !! !! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! !! !! ! ! ! !!! !! ! ! !! !!! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! !! ! ! ! !! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! !! ! !! ! ! ! ! ! ! ! !! ! ! ! !! ! ! ! ! ! ! ! ! !! !! ! ! ! !! ! ! !! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! !!! !!! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! !! ! ! ! !! !! ! Muang Xay ! !! ! ! !!! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! !! ! !! !! ! ! ! ! !!!! ! ! !! ! !!! !! ! !! ! !! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! !! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! !! ! !! !! ! ! ! !! !! ! ! ! ! ! !! ! ! ! ! !! !! ! !! ! !! ! ! ! !!! ! ! ! ! ! ! !! ! ! ! ! ! ! ! !! ! ! !! !! ! ! !! ! ! ! !! ! ! ! ! !! ! ! ! ! ! ! !!!!!! ! !! ! ! ! !!! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! !!! ! ! !! ! !! ! ! !!! !!! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! !! ! !! ! !! ! ! ! ! ! ! ! !! ! . ! ! ! ! ! !! ! ! ! ! ! ! !! ! ! ! !! !! ! ! ! ! ! ! !! ! !! ! ! !! ! ! ! !! !! ! !! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! !! !! ! ! ! ! ! !! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! !! ! ! ! ! !! ! ! !! ! ! ! ! ! ! ! !! ! ! ! ! ! ! !!! ! ! !! ! ! ! ! ! ! ! !! ! ! !! ! !! ! ! !! !! ! ! ! ! ! !! ! ! !! ! ! ! !! ! !! ! ! ! ! ! ! ! ! !!! ! !! !! ! ! !!! !!! ! ! ! !! ! ! ! ! ! ! ! !! ! !! ! !! !! ! ! ! !!! ! ! !!!!! ! ! ! ! ! ! ! ! ! ! ! ! ! !! !! ! ! ! !! ! ! !! ! !! ! ! !!! ! !!! ! ! ! !! ! !! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! !! ! !! ! ! ! ! !! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! !!! ! ! ! ! ! !! ! ! ! ! ! !! ! !! !!! ! !! ! !! !! ! ! ! ! ! ! ! ! ! ! ! !! ! !! ! ! ! ! ! !! !! ! !! ! ! ! ! ! !! ! ! ! ! ! !! ! ! ! ! ! ! ! ! !! ! ! !! !! ! ! !!! ! !! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! !! Xamneua ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! !! ! !!! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! !! ! ! ! !! ! ! ! ! ! ! !!! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! !! !!! ! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! !! ! ! ! ! ! !! ! ! ! !! ! ! ! ! !! ! ! ! ! ! ! ! ! !! ! ! !! !! ! !! ! ! !! ! ! ! ! ! !! ! ! ! ! ! !! ! ! ! ! !! ! ! ! ! ! ! ! ! ! !! !!! !! !! ! ! ! ! ! !! ! ! ! !! !!! ! ! ! ! ! ! ! !! !! !! ! ! ! ! !!! ! Huay Xay !!! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! !!! ! ! ! ! !! ! ! ! !!! !! ! ! !! ! !! ! ! ! ! ! ! ! ! ! ! !! ! !! ! ! ! ! !! ! ! ! ! ! !! ! !! ! ! ! !! ! !! !! ! !!! ! ! ! . ! ! ! !! ! ! ! ! !!! ! ! ! ! ! ! ! ! ! ! !! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! !! !! ! ! ! ! !! !!! ! !! ! ! !! ! ! ! ! !!! ! !! ! ! !! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! !! ! ! ! !! ! ! ! ! !! ! ! ! ! ! !! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! !!! ! !! ! !! ! ! ! ! ! ! ! ! ! ! !! ! ! !!! !! ! ! ! ! !!!!! !! ! ! !! ! ! ! ! ! !! ! ! ! ! !! ! ! . ! ! ! ! ! ! ! ! !! ! ! !! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! !! ! !! ! ! !! ! ! ! ! ! ! ! ! ! ! ! ! ! !! !! ! ! !! ! !! !! ! ! ! ! ! ! !! ! ! ! ! ! ! ! !! ! ! ! !! ! ! ! ! ! ! !! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !!! !! ! ! ! !! ! ! ! !! ! !! !! ! ! ! ! ! ! ! ! ! !! !! !! !! ! ! ! ! ! !! ! !! ! ! ! ! ! ! ! !! ! !! !! !! ! ! ! ! ! ! ! ! ! !! ! !! ! ! ! ! ! ! ! ! !!!! ! ! ! !! ! ! !! ! ! ! !! !! ! ! ! ! ! ! ! ! ! !!! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! !! !! ! !! ! !!! ! ! ! ! !! ! ! ! !! ! ! ! ! ! ! ! !! ! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !!! ! ! !! !! ! ! ! ! ! !! !! ! ! ! ! ! !! !!! !! ! !!! ! ! ! ! ! !! ! ! ! ! ! !! ! ! !!! ! ! ! ! ! ! !! ! ! !! ! ! ! ! !! ! ! ! ! ! ! ! ! !! ! ! ! ! !! ! ! ! ! ! ! ! ! ! !! ! ! ! ! !! ! ! ! !!! ! ! ! !! !! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! !! !! ! ! ! !! ! ! !! !!!! ! ! ! ! ! ! ! !! ! ! !! ! ! ! ! !! ! !! !!! ! ! ! ! !! ! ! ! !! ! ! ! ! ! !! ! ! ! ! ! ! ! ! !! ! ! ! ! !! ! ! !! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! !! ! !! !!!! ! ! ! ! ! !! !! ! ! ! ! ! !! !! ! ! ! ! !! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! ! ! !!! ! !! ! ! !! !!!! ! !!! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! !! ! ! ! !! ! ! ! ! !!!! ! ! ! ! !! ! ! ! ! ! ! ! ! !!! !! !! ! ! !! ! ! ! !! !! ! ! ! ! ! ! !! ! ! !! !! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! !! !! !!!! ! ! !! ! !! ! ! ! !! ! ! ! !! !! ! ! ! ! !! ! !!! ! ! ! ! !! ! ! ! ! ! !!! ! ! ! !! ! ! !! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !!! ! ! ! ! ! ! ! ! !! !!!! ! !!! ! ! ! !! ! ! ! ! !! ! ! ! ! !! !! ! !! ! ! ! ! Luang Prabang !! ! !! ! !! ! !! ! ! !! ! ! ! ! ! !! ! ! ! !! ! !! !!! ! !! ! ! ! !! ! ! !! !!!! ! !! !! ! ! ! ! ! ! !! ! ! ! ! !! ! ! ! !! ! ! ! ! ! !! ! ! ! ! !! !! ! ! ! ! ! !! ! ! !! ! ! ! ! !! ! ! ! ! ! ! ! ! ! !! !! ! ! ! ! ! ! !! !! ! !! ! !!! ! ! !! ! ! !! ! ! ! ! !! !! !! ! ! ! ! ! ! !! !! ! ! ! !!! !! ! ! !! ! !! ! ! !! !! !! !! ! ! ! ! ! !! ! !!! !!!! ! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! ! !! ! ! !! ! ! !! ! ! ! ! !! ! ! ! ! ! !! ! !! ! !! ! ! ! ! ! ! ! ! !! ! ! !! ! ! ! ! !! ! ! ! !!!! ! ! ! ! !! ! !! !! ! !! !! ! ! !! ! ! ! ! ! ! ! ! !! ! ! ! ! !!! !! ! ! ! !! ! ! ! ! !!!! ! ! ! !! ! ! ! ! ! ! ! !! ! !! ! !! ! !! ! . ! ! ! ! !! !! !!!! ! ! ! ! ! ! !! ! ! !! ! ! ! ! ! ! !! ! ! ! ! !! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! !! ! !! ! ! !! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! !! !!! ! ! ! ! !! ! ! !! !! ! !! ! ! ! ! ! ! ! !! !!! ! ! ! ! ! ! ! ! ! ! !! ! !!!! ! ! ! !! !! ! !! ! !! ! ! !! ! ! !! ! ! ! ! ! ! ! ! ! !! ! !! ! ! ! !! ! ! ! ! ! !! !! ! !! ! ! ! !! !! !!! !! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! !!! ! ! ! !!!! ! !! ! ! !!! ! !! ! ! !! ! ! ! !! ! ! ! ! !!! ! !! ! ! ! ! ! ! ! !! ! ! !! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! !! ! ! !! ! ! ! ! ! ! ! !! ! ! ! ! ! ! !! !! ! ! !! ! ! !! ! ! ! ! ! !! ! ! ! ! !! ! ! !! ! !! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! !! ! ! !! ! !! ! ! ! ! !!!! ! ! ! ! ! !! ! ! ! ! ! ! !! ! ! ! ! !! ! ! !! ! ! ! ! ! ! !! ! ! !! ! ! ! !! ! ! ! ! ! !! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! !! ! ! ! !! ! ! ! ! ! !! ! !! ! ! ! ! ! ! !! ! !! ! ! ! !!! ! ! ! ! !!! ! ! !! !! ! ! ! ! ! !! ! ! !!! !! !!! ! !! ! ! ! ! ! ! ! !! ! ! ! ! ! ! !! !! ! ! !!!! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! !! !! ! ! ! !! ! ! ! ! ! !! ! !!! ! !! !!! ! !! !! ! ! !! ! !! ! ! ! ! ! !! ! ! !! ! ! ! !! ! !! !!! ! ! ! !! ! ! !! !! !! !! !! ! ! ! !! ! ! ! ! !! !! ! ! !!!! ! ! !!! ! ! ! ! ! ! !! ! ! ! !! !! ! ! !! ! ! ! ! !! ! !! ! ! !! ! ! !! ! !! ! !! ! ! !! !! ! ! ! ! ! ! ! ! !! ! !! ! ! !! ! !! ! ! !! ! !! ! ! ! ! ! ! ! ! ! ! ! !! ! !! ! ! ! ! ! ! !!!! ! ! ! ! ! !!! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! !! !! !! ! !!! ! ! ! ! ! ! !! !! ! ! !! ! ! ! ! ! !! ! ! ! ! ! !! ! ! ! ! !! ! ! ! ! ! !! ! ! ! ! !! ! !! !! ! ! ! ! !! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! !! ! !!!! ! ! ! ! ! ! !! ! !! !! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! !! ! !!!! !! ! ! !! ! ! ! ! ! !! ! ! ! ! ! !! ! ! ! ! ! !! ! ! !! ! Phonsavan ! ! ! ! ! !! ! ! ! ! ! ! !!! ! !! ! ! ! ! ! !! ! ! ! ! ! ! ! !! !! !! ! ! ! !! !! !!! ! ! ! ! ! ! ! ! !! ! ! !! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! !! !! ! !!! ! ! ! !! ! ! ! ! ! !! ! ! ! !! ! ! ! !! !! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! !! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! !! ! ! !! !! ! ! ! ! !! ! ! ! !! ! ! ! !! ! ! ! ! ! !! ! !! ! !! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! . ! !!!! ! !! ! ! ! ! ! ! ! !! ! ! ! !! ! !! !! ! !! ! ! ! ! ! !! ! !! ! ! ! ! ! !! ! ! !! ! ! ! ! ! !! ! !! ! ! ! ! ! ! ! ! !! ! ! !! ! ! ! ! !! ! ! ! !! ! ! ! ! ! !! ! ! ! ! ! ! ! !!!! ! ! ! !! !! ! ! !!! !! ! ! ! !! ! ! ! ! !!! ! !!! ! !! !! ! ! ! ! ! ! ! !! ! !! ! !! ! !!! ! ! ! ! ! ! ! !! ! ! ! ! !!! ! ! ! !! !! ! ! !! ! ! ! ! !! ! ! ! ! ! ! ! ! ! !! ! ! !!! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! !! ! !! ! ! ! !! ! ! !! ! ! ! ! ! ! ! ! ! ! ! ! ! !! !! !! !! ! ! ! ! !! ! ! . ! ! ! !! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !!! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! !! ! ! ! ! !! ! ! ! ! ! ! ! ! !! !! !! ! !! ! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! !! ! !! ! ! ! ! ! ! ! ! ! ! ! ! !! !! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! !! ! ! ! ! !! ! ! ! ! ! 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Sekong ! ! !!!! !! !!!! ! ! ! !! !! !!!!! !! ! !!!!! !! ! !!! ! ! ! ! !! ! ! ! !! ! ! ! !!!!! ! !!! ! !!! ! ! ! ! !! !! ! ! ! ! ! !!! !! !!!! ! !! !! ! ! !!! ! !! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! !!!! ! !! !! !! !!! ! ! !!! ! !! ! !! !!! ! !! !! ! !! ! ! ! !! ! ! !! !!! !! !!! !! ! !! ! ! ! ! ! ! !! ! ! ! ! !!! ! ! !! !! ! !! ! !! ! !! ! !! !! !! ! ! !!!!! !!!! !! !!! !! !!! !! ! ! ! ! !!! ! !! ! ! ! !! !! ! ! ! ! ! ! ! ! ! ! ! !!! ! ! !! ! ! !! ! !! ! !! !! ! !!! !!! !! ! ! ! ! ! ! ! !! !! !! ! !! ! ! ! ! !! ! ! ! !! ! ! !!!! ! ! !! !! ! ! !!! ! ! !! ! !!! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! !! ! !! !! ! ! ! !! ! !! ! !! ! ! ! ! ! ! ! . ! ! ! ! ! !! ! !! ! ! ! ! ! !! ! ! ! ! !! ! !!! ! !! ! ! ! ! ! ! !! !! !! ! ! !! !! ! ! !! !! ! ! ! ! ! ! !! !! !!! !! !! ! ! !! ! ! ! !! !!! ! ! !!!! !!!!!! ! ! ! ! !! !!! ! ! !! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! !!! ! !!! ! ! ! !! ! !!!!!! !!!! ! !!!! ! ! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! ! !! ! ! !! !! !! !! ! !!! ! !! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! !!! ! ! ! !!! !! ! !! ! !! ! ! !! ! ! ! ! ! !! !! ! ! ! ! ! ! Pakxe !! ! ! ! !! ! ! ! ! !!!!!!! ! !! !! ! ! ! ! ! ! ! ! ! ! !! !! ! !!! ! !! ! ! ! !! !! ! ! !!! ! !! ! ! !! ! ! ! ! ! !! !!! ! !!! ! !!!! ! !! !!!! !! ! !! !!! !! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! ! !! !! !! ! !! ! !! ! ! ! ! ! ! ! ! ! ! ! ! ! !!!! ! ! !! ! !!!! ! ! !! !! ! ! ! !! !! !! !! ! ! ! ! ! ! ! ! !! ! !! ! ! ! ! ! !!! ! ! ! ! !!!!! !!! !! !!! !!! ! ! !! ! ! !! ! . !! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! ! !! !!! ! ! !! !! ! ! ! !! !! !!! !! ! !! ! ! ! ! !! !! ! !! ! ! !! !!! ! ! ! !! !!! ! !!! ! !! !! !! ! !!!!!! !! !!!! ! ! !! ! ! ! !! ! ! ! ! ! ! ! ! ! !! !!!! ! !! ! !! ! ! !! ! !! ! ! ! ! ! ! ! ! ! ! !! ! !! ! ! ! ! ! ! !!! ! ! ! ! !!! ! !! ! !!! !! ! ! ! ! !! ! ! !! !! !! ! ! !! ! ! ! ! ! !! !! !! ! ! ! ! ! ! ! ! ! ! ! ! ! !!!! ! ! !! !! !! ! !! !! !! ! !! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! !! ! ! ! ! !! !! ! ! !! ! ! ! ! ! !! ! ! ! ! !! !! !! ! !! ! ! ! ! !! !!! ! !! !! ! ! ! ! ! ! !! ! ! !! ! ! ! ! !! ! !! !! !! !! ! ! ! ! ! ! ! ! ! !! ! Attapeu ! ! !! ! !!! !! ! ! !! !! ! !! ! ! ! ! ! ! ! !!! !! !! !!! ! !! !! ! ! ! ! ! ! !! ! !! !! !! !!! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! !! ! !! ! ! ! ! ! !! ! ! ! !! !! ! !!! ! ! !! ! ! ! ! ! ! ! ! !! !!!!!! ! ! !! !! ! ! !! ! ! ! !! !! ! ! ! ! ! ! ! ! . ! ! ! !! ! ! ! ! ! ! ! !! Poverty density ! ! !!! !! ! ! ! ! ! !!! ! ! !! ! !! ! !! ! ! ! ! ! !! ! ! !! !! ! ! !! ! ! ! ! !! ! ! ! ! !!! ! ! ! !! ! ! ! ! ! ! !! ! ! !! ! !!! !!! ! ! ! ! ! ! ! ! ! !! ! ! ! !! ! ! !! ! ! ! ! ! ! !! ! !!! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! !! ! ! ! ! !! ! !! ! ! ! !! !! ! ! ! ! !! !!! ! ! !! ! ! ! ! ! !! !! ! !! ! !! !!! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! !!!! ! ! ! ! !!!! ! ! !! ! ! !! ! ! !! !! ! ! ! ! !! !! ! ! ! ! ! !! !! ! ! ! ! ! !! !!!! ! ! ! ! ! ! ! ! ! !! ! ! !! ! !! ! !! ! ! ! ! !!!! ! ! ! ! ! ! ! ! ! !!! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! ! !! ! !!! ! ! !! ! ! !! ! ! ! ! ! ! ! ! ! ! ! ! !! ! ! !! ! ! ! ! ! ! (Absolute number of poor) !! ! !! ! ! ! ! ! ! ! ! !! !!! ! ! ! ! ! ! ! !! !!!! ! ! ! !! ! ! ! ! ! !! ! ! !!! ! ! ! !! ! ! ! ! ! !!! ! !! ! ! ! ! ! ! !! ! ! ! !! ! ! ! ! !! ! !! ! ! ! ! ! ! !! !! ! ! !! ! ! ! ! !! ! !! ! ! ! ! ! ! ! !! !! ! ! !! !! ! ! ! ! ! !! ! ! ! !! !!!! ! !! ! ! ! ! ! ! !! ! ! ! ! ! ! !! ! ! ! ! !!! ! !!!! ! ! ! ! ! !! ! !!! !! ! ! ! ! !! ! ! !! ! ! ! ! !! !! ! ! ! !! ! ! ! ! !! ! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! !! ! ! !! ! !!! ! ! ! !! ! ! ! ! ! ! ! !! !! ! ! ! ! ! ! !! ! !! ! ! !!! !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !! !!! !! ! 1 Dot = 100 people !! ! ! !!!! ! ! ! !! ! ! ! !! ! ! ! ! ! ! ! ! ! ! ! !! !! ! !! !! ! ! ! ! ! ! ! ! ! !!! ! ! !! ! ! !! ! !! ! ! ! ! ! !! ! ! !! !! ! ! !!!!! ! ! !! ! !! ! ! ! ! !! ! !! ! !! ! !! below the poverty line !!! ! ! ! !! !! ! ! !! ! !! ! ! !! ! ! ! !! !! ! ! !! ! ! !! !! !! ! !! ! !!! !! Sources: Authors’ calculation based on 2012/13 LECS-5 and 2015 Lao PDR Census Lao PDR 2015 Census-Based Poverty Map – June 2016 17 Figure 1: Local-Level Poverty Headcount Intervals, by region A. Province Sources: Authors’ calculation based on 2012/13 LECS-5 and 2015 Lao PDR Census Note: For each region the black dot gives the regional poverty headcount while the vertical line shows the range of poverty estimates at province level. B. District Sources: Authors’ calculation based on 2012/13 LECS-5 and 2015 Lao PDR Census Note: For each region the black dot gives the regional poverty headcount while the vertical line shows the range of poverty estimates at district level. 18 Lao PDR 2015 Census-Based Poverty Map – June 2016 Non-Monetary Indicators different panels map the figures by province and district. The index numbers, as shown in The 18 Sustainable Development Goals the first column of Table 1, are reproduced in (SDGs)4 are currently monitored by around the Map titles to simplify reading of the maps. 250 different indicators. Many of them have Tables showing point estimates for the same already been computed at the national level statistics can be found in Appendix 9, for the in the case of Lao PDR. Having national level education-related indicators, and Appendix 10 SDG indicators is useful for monitoring trends for the other indicators. but policy-makers prefer disaggregated figures at the local level. SDG indicators at In all cases, the different province and district these administrative levels permit better maps clearly show large spatial disparities geographical targeting and are therefore likely between the different geographical units. Such to reduce poverty more for a given budget. spatial heterogeneity means that geographical However many indicators are only meant targeting could yield significant efficiency to be computed at the national level (e.g. gains if any of these indicators are used for proportion of women in parliament). The first targeting. two indicators (poverty headcount and poverty gap ratio) have already been presented above. Maps 4 to 14 present the different education- This section presents the results of 29 non- related indicators while the other ones are monetary indicators computed from the 2015 found in Maps 15 to 24. Net school enrolment Lao PDR Census at the province and district rates at the primary and, lower and upper levels. Although we could not, in some cases, secondary levels are presented in Maps 6, 7 compute SDG indicators according to their and 8, respectively. At 75.5% (Table 1), primary official definition, our non-monetary indicators school enrolment rates are clearly on the low are all inspired by SDGs even if in many cases side when compared to other countries. But we go beyond them. Since poverty is a multi- that nationwide rate obviously hides large dimensional issue, these 29 indicators should spatial disparities. Urban districts tend to have be seen as complementary to the monetary much higher rates while some isolated rural poverty map indicators. areas, suffer from very low rates. In particular, the isolated group of districts in the south-east Table 1 defines each of these indicators and part of the country along the Vietnam border presents their computed values at the national has the lowest enrolment rates. The northern level as well as the average by gender when most districts also present below average appropriate. The province- and district-level enrolment rates. The same pattern holds for figures are presented in a series of maps (Maps both lower and upper secondary enrolment but 4 to 24) in Appendix 6. In each case, two at much lower levels. This is particularly the 4 Although no data assessment of the different Sustainable Development Goal (SDG) indicators has been performed yet in Lao PDR, we believe we are presenting most SDG indicators that can be computed from 2015 Lao PDR Census database. Such data assessment has been done in only a handful of countries, including neighboring Myanmar (see Coulombe and Dietsch, 2016). Lao PDR 2015 Census-Based Poverty Map – June 2016 19 case of female population. The next three Maps somehow reciprocal to net or gross enrollment (9,10 and 11), present the gross enrolment rates rate. For both age-groups the northern tip for the same education levels. Having higher and the southern part of the country have the gross rates and net rates clearly shows that highest rates. However the actual numbers many children either start school at a later age of out-of-school children would also depend than planned or do not progress as fast as they on the population. Therefore, Vientiane has a should. Otherwise the geographical pattern for significant number of out-of-school children the net and gross rates are similar. even if the rate is not so high. Since literacy rates depends from past Maps 15 present the employment5 rate for enrolment rates it is unsurprising that literacy the 15 to 64 age group at both administrative rates – for both males and females – follow levels, though we concentrate our discussion on a geographical pattern similar to the school district-level figures – the most disaggregated enrolment rate (Maps 4 and 5). level presented in this report. A close examination reveals a very large spread in For both primary and secondary levels, we employment rates, from only 61% to a much computed the girl-to-boy ratio among children higher 92%. No clear pattern emerges from attending school as a measure of gender the maps although districts with lower rates inequality (see Maps 12). Nationwide, the ratio tend to be found in clusters, particularly in the slightly favours boys at all education levels, case of female in districts close to the capital. (Table 1). Although these ratios vary widely Further investigation focussing on types of across provinces and districts, no geographical economic activities and infrastructure would pattern is discernible except that southwest be needed to fully explain that geographical districts along the Thai border seem to be pattern. closer to gender equality than elsewhere. We came to the same conclusion – that there is Nationwide, the percentage of self-employed no discernible geographical pattern – for the workers stands at 85% (Table 1), but this figure other gender inequality indicator, namely the conceals huge differences across districts. proportion of women in wage employment in Map 16 shows that district-level figures range the non-agricultural sector (Maps 21). from relatively low level in districts around the capital to almost 100% in most remaining rural Out-of-school children is becoming more and districts. more the focus of policy makers (UIS and The unemployment rate among prime-age UNICEF, 2015). Maps 13 and 14 shows out- individuals (indicator [21]) is rather low at 1.1%, of-school rates and numbers of out-of-school but the unemployment rate for the younger children for respectively the 6-11 and 12-18 age population (indicator [20]) is almost four groups. Obviously the geographical pattern is times higher at 4.2%. Maps 17 and 18 show 5 In this report we define “employment” in its broadest meaning and therefore we include wage earners as well as non- employee workers such as employers, own account workers and unpaid family workers. 20 Lao PDR 2015 Census-Based Poverty Map – June 2016 that unemployment rates for both groups are breadwinners. Map 21 shows no real have a similar geographical pattern, with high geographical pattern except a lower ratio unemployment rates essentially being a city in the four major cities and in the districts phenomenon. surrounding them. The proportion of non-agricultural workers From the Census questionnaire, a series of reflect the economic transformation of a infrastructure indicators were calculated and countries away from agricultural and toward are presented in Maps 23 & 24. Improved manufacturing and services. Maps 19 and sanitation, improved source of drinking water, 20 show, without surprise, that the capital not using wood as the main source of cooking Vientiane and other predominately urban fuel, access to electricity and ownership of a districts have most non-agricultural workers phone all follow a rather similar geographical and that the rural areas remain deeply based pattern although the levels are very different. on farming. For all those indicators rates are much higher in Vientiane and the surrounding provinces The demographic dependence rate is defined and districts. Otherwise, households living in as the proportion of individuals unlikely districts along the Thai border are better off to economically active, i.e. the population when standard of living is measured by those below 18 or older than 64 years old. A higher physical indicators. dependency rate makes households more likely to be poor, since fewer household members Lao PDR 2015 Census-Based Poverty Map – June 2016 21 Table 1: List of indicators computed at local levels National average No Indicator Male Female Total 1 Poverty Headcount (in %) n/a n/a 24.8 2 Poverty Gap Index (in %) n/a n/a 6.0 3 Proportion of individuals aged 15-24 being literate (in %) 94.0 90.1 92.0 4 Proportion of individuals aged 25-64 being literate (in %) 88.5 76.7 82.5 5 Net school enrolment rate in primary (in %) 75.8 75.3 75.5 6 Net school enrolment rate in lower secondary (in %) 41.0 41.0 41.0 7 Net school enrolment rate in upper secondary (in %) 23.4 20.1 21.7 8 Gross school enrolment rate in primary (in %) 101.9 97.6 99.8 9 Gross school enrolment rate in lower secondary (in %) 52.6 50.3 51.4 10 Gross school enrolment rate in upper secondary (in %) 39.2 33.3 36.2 11 Girl-to-boy ratio at primary school n/a n/a 0.93 12 Girl-to-boy ratio at lower secondary school n/a n/a 0.94 13 Girl-to-boy ratio at upper secondary school n/a n/a 0.90 14 Proportion of out-of-school 6-11 children (in %) 20.6 20.4 20.5 15 Proportion of out-of-school 12-18 children (in %) 35.0 39.8 37.4 16 Number of out-of-school 6-11 children 85800 83050 188850 17 Number of out-of-school 12-18 children 171020 195844 366864 18 Employment rate for the 15-64 age group (in %) 82.9 79.5 81.1 19 Self-employment rate for the 15-64 age group (in %) 79.2 87.1 83.1 20 Youth unemployment rate for the 15-24 age group (in %) 4.9 3.9 4.4 21 Unemployment rate for the 25-64 age group (in %) 1.2 1.1 1.2 22 Percentage of non-agric. wage earner workers in total employment 20.3 12.6 16.5 (in %) 23 Percentage of non-agric. own-account workers in total employment 8.9 12.6 10.7 (in %) 24 Proportion of individuals aged less than 18 or more than 64 years n/a n/a 37.2 old (in %) 25 Female in wage employment in non-agricultural Sector (in %) n/a n/a 37.2 26 Proportion of married 17-year-old girls (in %) n/a n/a 18.1 27 Proportion of population using improved sanitation facility (in %) n/a n/a 71.1 28 Proportion of population using improved water source (in %) n/a n/a 83.9 29 Proportion of population NOT using firewood as cooking fuel (in %) n/a n/a 29.4 30 Proportion of population using electricity (in %) n/a n/a 85.6 31 Proportion of population having at least one phone at home (in %) n/a n/a 91.3 Sources: Authors’ calculation based on 2012/13 LECS-5 and 2015 Census Note: n/a means non applicable 22 Lao PDR 2015 Census-Based Poverty Map – June 2016 Relationship between the more than one indicator to properly target the Different Poverty Indicators needy population. For example, we can imagine that an investment in public infrastructure It has become customary to suggest that could use both infrastructure and poverty monetary poverty maps, which provide detailed indicators if the objective is to both reduce information on monetary poverty at low levels poverty and increase access to public services. of geographic disaggregation, can be used to target a wide range of programs. However, it is not clear whether an education or health program should also be targeted on the basis of monetary poverty indicators, as opposed to a map of education or infrastructure deprivation, however how that would be defined. This is why a substantial part of this study consists of providing different maps based on the 29 non- monetary indicators that could be computed from the Population and Housing Census 2015. In the previous sub-section, we saw that in many cases the poverty headcount tends to be weakly associated with non-monetary indicators – we here formalize our examination of correlations between the different poverty indicators. A table of correlations between all 31 poverty indicators previously analysed at the district level can be found in Appendix 7. A close examination reveals that correlations are low in many cases, though some pairs of indicators are rather highly correlated. For example, electrification [30] is somehow correlated with improved sanitation [27] and phone ownership [31]; but its correlation with school enrolment depends on the level (mildly positive with secondary, but lower with primary). Overall, the lack of high correlation between the monetary poverty headcount and other indicators (employment, education or infrastructure) clearly reveals the need to use Lao PDR 2015 Census-Based Poverty Map – June 2016 23 24 Lao PDR 2015 Census-Based Poverty Map – June 2016 IV. Concluding Remarks This report has documented the construction lowest access to electricity and incidentally of a series of province- and district-level is also of the poorest district. However monetary poverty maps for Lao PDR, based on multiple indicators approach would be trickier the most recent Population and Housing Census in districts such as Samphanh (in Phongsaly conducted in 2015 and the 2012/13 LECS-5 Province) which has a relatively low poverty household survey. These results are consistent headcount ratio but have a massive lack of with the ones from the latest Poverty Profile access to electricity. and therefore can be viewed as an extension of the poverty profile – a way to operationalise These maps could be a key tool in support of the its results. The monetary poverty maps are decentralisation process currently undertaken complemented by a series of non-monetary in Lao PDR. For example, we can imagine that indicators focussing on employment, education the Government would distribute a budget to and infrastructure. All the different indicators provinces or districts according to their level of were computed for each of the 18 provinces monetary poverty, and then the local authority and 148 districts of Lao PDR. would use that budget to prioritise investment (in health, education, infrastructure etc.) However interesting these results may be, they according to its own local needs, using non- are only valuable if properly used. How? Among monetary indicators as guidelines. other possibilities, these results can be used to design budget allocation rules to be applied Others uses of the poverty map might include by different administrative levels to their the evaluation of locally targeted anti-poverty subdivisions. For example, when the Central programs, for example monitoring progress in Government has a budget to be distributed priority districts. Finally, researchers could use amongst the different districts and wishes to it in a multitude of ways, such as for studying maximise its effect on poverty alleviation, a key relationships between poverty distribution and question is should that budget be distributed? different socio-economic outcomes. Based on monetary poverty indicators, different rules can be adopted. Using non-monetary indicators to raise the standard of living of the population can be easier, although it would necessarily target with different objectives. For example, if policy- makers want to improve access to electricity, it is straightforward to target districts such as Xaychamphone (in Borikhamxay province) – along with many others – that have the Lao PDR 2015 Census-Based Poverty Map – June 2016 25 References Coulombe, Harold and Quentin Wodon, 2007, Combining Census and household survey data for better targeting: The West and Central Africa Poverty Mapping Initiative, Findings Africa Region No. 280, The World Bank, Washington, D.C. Coulombe, Harold and Marie-Noelle Dietsch, 2016, Readiness of Myanmar’s Official Statistics for the Sustainable Development Goals, Naw Pyi Taw: CSO and UNDP Elbers, Chris, Jean O. Lanjouw and Peter Lanjouw, 2003, “Micro-Level Estimation of Poverty and Inequality” Econometrica, 71(1), 355-364 Epprecht, Michael, Nicholas Minot, Reno Dewina, Peter Messerli, Andreas Heinimann, 2008, “The Geography of Poverty and Inequality in the Lao PDR” Centre for Development and Environment CDE, University of Bern, and International Food Policy Research Institute IFPRI), Bern: Geographica Bernensia. Foster, J.E., J. Greer and E. Thorbecke, 1984, A Class of Decomposable Poverty Measures, Econometrica 52: 761-766 Pimhidzai, Obert, Nina Fenton, Phonesaly Souksavath and Vilaysouk Sisoulath, 2014, Poverty Profile in Lao PDR: Poverty Report for the Lao Consumption and Expenditure, Vientiane: LSB Mistiaen, Johan, Berk Ozler, Tiaray Razafimanantena and Jean Razafindravonona, 2002, Putting Welfare on the Map in Madagascar, Africa Region Working Paper Series, Number 34, The World Bank. Washington, D.C. UIS and UNICEF, 2015, Fixing the Broken Promise of Education for All – Findings from the Global Initiative on Out-of-School Children, Montreal: UNESCO Institute of Statistics. Zhao, Qinghua and Peter Lanjouw, 2012, Using PovMap 2: A User’s Guide, mimeo, Development research Group, The World Bank, Washington, D.C. 26 Lao PDR 2015 Census-Based Poverty Map – June 2016 Appendix 1: Monetary Poverty Methodology The basic idea behind the methodology First stage developed by Elbers, Lanjouw and Lanjouw (2003) is straightforward. First, a regression In the first instance, we need to determine a set model of log of per-capita expenditure is of explanatory variables from both databases estimated using survey data, employing that meet some criteria of comparability. In a set of explanatory variables which are order to be able to produce a poverty map common to both a survey and a Census. Next, consistent with the associated poverty profile, parameters from the regression are used to it is important to only select variables that are predict expenditure for every household in the fully comparable between the Census and the Census. And third, a series of welfare indicators survey. We start by checking the wording of are constructed for different geographical the different questions as well as the proposed subgroups. answer options. From the set of selected questions we then build a series of variables The term “welfare indicator” embraces a which are tested for comparability. Although whole set of indicators based on household we might want to test the comparability of the expenditures. This note emphasises the whole distributions of each variable, in practice poverty headcount (P0), but the usual poverty we only test the equality of their means. In and inequality indicators can be computed order to maximise the predictive power of (Atkinson inequality measures, generalised the second-stage models, all analyses are Entropy class inequalities index, FGT poverty performed at the strata level, including tests measures and Gini). of the comparability of the different variables on which the definitive models are estimated. Although the idea is rather simple, its proper implementation requires complex computation The list of all potential variables and their if one is to account for spatial autocorrelation equality of means test results are available on and heteroskedasticity in the regression request. model. Furthermore, proper calculation of the different welfare indicators and their standard Second stage errors increase the complexity greatly. We first model per-capita household The discussion below is divided into three expenditure using the survey database. In parts, one for each stage necessary in the order to maximise accuracy, we estimate the construction of a poverty map. This discussion model separately for the urban areas and rural borrows from the original theoretical papers of areas. Elbers, Lanjouw and Lanjouw as well as from Mistiaen et al. (2002). Lao PDR 2015 Census-Based Poverty Map – June 2016 27 Let us specify a household level expenditure where ŋc is the location effect and εch is the ( ych ) model for household h in location c, xch individual component of the error term. is a set of explanatory variables, and uch is the residual: In practice, we first estimate equation (2) by simple OLS and use the residuals as estimates of ln ych = E[ln ych | xch ] + uch (1) the overall disturbances, given by ûch. We then decompose these residuals into uncorrelated The locations represent clusters as defined in household and location components: the first stage of typical household sampling design. Typically, they correspond to Census ̑ c + еch (4) ûch = ŋ enumeration areas, although this is not necessary. The explanatory variables need to The location term ( ̑c) ŋ is estimated as the be present in both the survey and the Census, cluster mean of the overall residuals, and and need to be defined similarly. They also need therefore the household component ( еch ) is to have the same moments in order to properly simply subtracted. The heteroskedasticity in measure the different welfare indicators. The the last error component is modelled by the set of potential variables is defined in the first regressing its square ( е2ch ) on a long list of stage. all independent variables of model (2), their squares and interactions as well as imputed If we linearize the previous equation, we welfare. A logistic model is used6. model the household’s logarithmic per-capita expenditure as Both error computations are used to produce two matrices, which are then summed to Ʃ̂, ln ych = x’ch ß + uchּ (2) the estimated variance-covariance matrix of the original model (2). This matrix is used The vector of disturbances u is distributed to estimate the final set of coefficients of the Ϝ(0,Σ). Model (2) is estimated by Generalised main model (2). Least Square (GLS). To estimate this model we need first to estimate the error variance- Third stage covariance matrix Σ in order to take into account possible spatial autocorrelation (expenditure To complete the map, we associate the from households within a same cluster are estimated parameters from the second stage surely correlated) and heteroskedasticity. To with the corresponding characteristics of each do so we first specify the error terms as household found in the Census to predict the log of per-capita expenditure and the simulated uch = ŋc + εch (3) disturbances. 6. See Mistiaen et al. (2002) for further details on how the theoretical model is estimated in practice. 28 Lao PDR 2015 Census-Based Poverty Map – June 2016 Since the very complex disturbance structure the disturbance terms: has made computation of the variance of the imputed welfare index intractable, ŷ rch = exp(x'ch ß̃ c + ŋ̃ rc + ε̃ rch ) (5) bootstrapping techniques were used to obtain a measure of the dispersion of that imputed That process is repeated 100 times, each welfare index. From the previous stage, a time redrawing the full set of coefficients and series of coefficients and disturbance terms disturbance terms. The mean of the simulated have been drawn from their corresponding welfare index becomes our point estimate distributions. Then, for each household found and the standard deviation of our welfare in the Census, we simulate a value of welfare index is the standard error of these simulated index ( ŷ ch ) based on the predicted values and r estimates. Lao PDR 2015 Census-Based Poverty Map – June 2016 29 Photo by Stanislas Fradelizi / World Bank, 2011 30 Lao PDR 2015 Census-Based Poverty Map – June 2016 Appendix 2: Databases and Lao PDR Administrative Layers The construction of such monetary poverty households” and therefore did not take maps is very demanding in terms of data. into account individuals living in collective The minimal requirement is a household households (e.g. hostels, boarding schools survey having an expenditure module and or penitentiaries) in order to have a Census a population and housing Census. If it is not database consistent with the LECS-5 survey already available, a profile of monetary poverty sample. Therefore, our poverty map is based on must be constructed from the survey. The 6,280,000 individuals grouped into 1,198,000 household-level welfare index and the poverty households. line from such a poverty profile could be used to construct the poverty maps. Apart from LECS-5 Survey household-level information, community level characteristics are also useful in the The Lao Expenditure and Consumption construction of a poverty map, as differences in Surveys (LECS) are national survey that geography, ethnicity, access to markets, public collect expenditure data at household level. services and infrastructure, and other aspects The one conducted in 2012/13, it is the most of public policy can all lead to substantial appropriate in terms of timing and also differences in the standard of living, whether collected information similar to that in the defined in monetary terms or not. In the case of Census questionnaire. LECS-5 covers a sample Lao PDR, some of that information is available. of 8,196 households with around 43,500 individuals. Non-monetary indicators are computed directly from the Census database, without The welfare index used in our regression models any complex statistical procedures. (per-capita expenditure) is the same as the one used in the latest poverty profile based on Census the LECS-5 database (Pimhidzai et al., 2014). Using the same household-level welfare index The latest Population and Housing Census and the associated poverty lines ensures full was conducted in 2015. The questionnaire is consistency between the poverty profile and the relatively detailed but contains no information new poverty map. It also makes it possible to on either household incomes or household test whether the predicted poverty indicators expenditures. At the individual level, it covers match those found in the poverty profile at demography, education, economic activities the strata level, the lowest statistically robust and durable good ownership. At the household level achievable in LECS-5. level, dwelling characteristics are covered. The Census database covers all individuals. However, we limited our analyses to “regular Lao PDR 2015 Census-Based Poverty Map – June 2016 31 Administrative Layers having a total of 183,000 individuals in 2015. As discussed previously, we need a minimal The administrative structure of Lao PDR is number of households per administrative simple. The top tier is composed of 18 provinces unit in order to compute statistically robust that are broken-down into 148 districts. Those monetary poverty indicators and in the case districts are composed of 1,282 kumbans and of Lao PDR, almost all districts yield robust 8,500 villages. In the largest cities, villages poverty estimates. However, computation of should be seen as neighbourhoods. Table 2 poverty estimates at kumban and village levels presents some descriptive statistics on the size gave results that we deemed not robust enough of these different administrative levels. The to be used. The very small of population of districts vary a lot in terms of population, from many kumbans and most villages yield poverty Longcheng, with only 6579 people residing in figures that are not as precise as we would like. 1,354 households, to Xaythany, a district of Vientiane, with more than 38,800 households Table 2: Descriptive Statistics on the Lao PDR Administrative Structure Administrative Unit # of Units Number of Households Median Minimum Maximum Province 18 52,526 13,908 166,344 District 148 6,457 1,354 38,825 Kumban 1,282 684 44 8,204 Village 8,500 100 5 1,743 Source: Authors’ calculation based on the 2015 Census 32 Lao PDR 2015 Census-Based Poverty Map – June 2016 Appendix 3: Monetary Poverty Methodology in Practice In Appendix 1, we describe in detail the predicted welfare figures will be consistent methodology behind computation of monetary with the survey-based poverty profile7. As poverty from a theoretical perspective, while noted above, that comparison exercise was the second appendix presents the required done at strata level. The survey’s two-stage datasets. The current appendix shows how the sample design was taken into account in the theoretical methodology is applied in practice. computation of the standard errors. In order to maximise the accuracy of the poverty Stage 2: Survey-based estimates we estimate econometric models for regressions each of the three regions of Lao PDR (Northern, Central and Southern) broken down into urban Appendix 4 presents the strata-specific and rural areas, with Vientiane Capital being a regression (Ordinary Least Squares) results separate strata. A household level expenditure based on the 2012/13 LECS-5 survey. The model has been developed for each of these ultimate choice of independent variables strata using explanatory variables which are was based on a backward stepwise selection common to both the LECS-5 and the Census. model. A check of the results confirmed The procedure can be split into three separate that all the coefficients have the expected stages: sign. As previously indicated, these models are not for discussion. They are exclusively Stage 1: Aligning the data prediction models, not determinants of poverty models that can be analysed in terms The first task was to make sure the variables of causal relationships. In the models used deemed common to both the Census and the for the poverty map we were only concerned survey really measure the same characteristics. with the predictive power of the regressors In the first instance, we compared the questions without regard, for example, to endogenous and modalities in both questionnaires to variables. We also ran a series of regressions identify potential variables. We then compared using the base model residuals as dependent the means of these (dichotomised) variables variables. These results – not shown here – are and tested whether they were equal using a used in the last stage in order to correct for 95% confidence interval. Restricting ourselves heteroskedasticity8. to these variables should ensure that our 7. We also deleted or redefined dichotomic variables less than 0.03 or more than 0.97 to avoid serious multicollinearity problems in our econometric models. 8. As described in the methodology section and Appendix 1, two statistical problems are likely to violate Ordinary Least Squares assumptions. Spatial autocorrelation (expenditure from households within a same cluster are surely correlated, i.e. there are location effects) is minimized by incorporating into the regressions the means of some key Enumeration Area variables. Heteroskedasticity (error terms are not constant across observations) is corrected by modelling the error terms. Correcting for these two problems yields unbiased estimates. See Elbers et al. (2002, 2003) and Mistiaen et al. (2002) for more details. Lao PDR 2015 Census-Based Poverty Map – June 2016 33 Table 3: Poverty Rates based on LECS-5 (actual) and 2015 Census (predicted), by region Poverty Headcount Poverty Gap Index Poverty Severity Index (P0) (P1) (P2) LECS-5 Census LECS-5 Census LECS-5 Census (Actual) (Predicted) (Actual) (Predicted) (Actual) (Predicted) Vientiane 5.9 8.5 1.5 2.0 1.5 0.7 (1.3) (1.2) (0.3) (0.4) (0.3) (0.2) North Urban 8.9 11.2 1.7 2.4 1.7 0.8 (1.8) (1.6) (0.4) (0.5) (0.4) (0.2) Central Urban 12.9 14.8 3.1 3.3 3.1 1.1 (2.7) (1.8) (0.9) (0.5) (0.9) (0.2) South Urban 16.2 19.8 3.5 5.4 3.5 2.1 (4.5) (2.6) (1.5) (1.0) (1.5) (0.5) North Rural 29.9 30.1 6.9 6.7 6.9 2.2 (2.6) (1.4) (0.9) (0.5) (0.9) (0.2) Central Rural 26.9 30.8 6.0 7.2 6.0 2.5 (2.7) (1.3) (0.8) (0.5) (0.8) (0.2) South Rural 32.1 33.9 8.4 9.4 8.4 3.7 (3.7) (1.9) (1.3) (0.7) (1.3) (0.4) Sources: Authors’ calculation based on 2012/13 LECS-5 and 2015 Census Note: Robust standard errors are in parentheses. The R2s of the different regional regressions necessarily yields a lower R2. Second, a large fall between 0.21 and 0.50. Although the number of potential correlates are simply Vientiane regression has a quite low R at 0.21,2 not observable using survey questionnaires. the remaining OLS regressions yield R [0.34- 2 Third, some good predictors were discarded 0.50] that are relatively large for survey-based during the first stage since their distributions cross-section regressions and can be very (mean and standard error) did not appear to be favourably compared with results from poverty identical. And finally, many indicators do not maps constructed in Asia or Africa. While these take into account the quality of the correlates. coefficients look “credible”, it is important to Not accounting for the wide variation in quality note that the models are purely predictive in of the different observable correlates makes the statistical sense and should not be viewed many of the potential correlates useless in as determinants of welfare or poverty. For terms of predictive power. these regressions, the R s were mainly bounded 2 by four important factors. First, in many areas households are rather homogeneous in terms of observable characteristics even if consumption varies significantly. That 34 Lao PDR 2015 Census-Based Poverty Map – June 2016 Stage 3: Welfare indicators9 declines as the number of households in the different administrative units falls. While Based on the results from the previous stage, we expect district-level poverty estimates to we applied the estimated parameters10 to the be precise enough it is legitimate to be more Census data to compute a series of poverty skeptical about sub-district estimates. indicators: the headcount ratio (P0), the poverty gap index (P1) and the poverty severity How low can we go? index (P2). Table 3 presents estimated poverty figures for each strata and compares them In order to pass an “objective” judgement on with actual figures from the latest survey- the precision of these estimates we computed based poverty profiles. For each strata and coefficients of variation for the three top poverty indicator, the equality of LECS-5- administrative levels (province, district and based and Census-based indicators cannot kumban) and then compared them with an be rejected (using a 95% confidence interval)11. arbitrary but commonly-used benchmark. The difference between the LECS-5-based and Figure 2 presents the headcount incidence Census-based headcount ratio is minimal in all coefficients of variation of province-, district- cases. Although Census-based poverty figures and kumban-level estimates and compares can only be compared with the ones provided by them to a 0.2 benchmark. The lower curve the LECS-5 survey at the strata level, equality (represented by xs) in Figure 2 clearly shows of these poverty figures provides an excellent that our province-level headcount poverty test of the reliability of the methodology used estimates do rather well while the accuracy here. of district-level estimates fare very well in most cases except in a few districts for which After having established the reliability of the the coefficient of variation is above the 0.2 different predictive models, we estimated benchmark. However, the results for the 1282 poverty figures for the three disaggregated kumbans clearly show very high coefficients of levels described in Table 2: province and district. variation for most kumbans which pose a real Before presenting the actual results we need to problem of reliability. Given that single reason determine whether they are precise enough to we decided to not present kumban estimates be useful. As discussed in the methodological and even less village ones. Figure 3 plots section, the precision of the poverty estimates these coefficients of variation against poverty 9. Computation of the welfare indicator has been greatly simplified thanks to PovMap 2.0, a computer program especially written to implement the methodology used here. We used the latest version developed by Zhao and Lanjouw (2012). 10. Apart from regression models explaining the household welfare level, we also estimated a model for the heteroskedasticity in the household component of the error. We also estimated the parametric distributions of both error terms for the simulations. See the methodological Appendix for further details. 11. It is worth noting that the standard errors of the mean of the Census-based figures are systematically lower than the ones calculated from LECS-5. Lao PDR 2015 Census-Based Poverty Map – June 2016 35 headcount for each district, the lowest level for of the relevant geographical areas is acceptable which we are presenting results. It shows that and suitable for targeting purposes. Actually amongst the districts with higher coefficients they are among the least poor districts and of variation all have a poverty headcount level therefore much less likely to be targeted by any well below the national level (24.8%). Since one poverty alleviation program. It is clear that of the main applications of the poverty map our poverty estimates at disaggregated levels would be to target the poorest provinces and would provide policy-makers with good guides. districts areas we believe that level of precision Figure 2: Poverty Headcount Accuracy, by administrative level Sources: Authors’ calculation based on 2012/13 LECS-5 and 2015 Census 36 Lao PDR 2015 Census-Based Poverty Map – June 2016 Figure 3: Poverty Headcount and Coefficients of Variation, by District Sources: Authors’ calculation based on 2012/13 LECS-5 and 2015 Census Lao PDR 2015 Census-Based Poverty Map – June 2016 37 Photo by Bart Verweij / World Bank, 2014 38 Lao PDR 2015 Census-Based Poverty Map – June 2016 Appendix 4: Survey-Based Regression Models Strata 1: Vientiane Capital Number of observation 763 R-square 0.215 Variable Coef. Std.Err. t-ratio Intercept 13.5194 0.1121 120.57 Has a computer (0/1) 0.3041 0.0542 5.61 Uses wood as cooking fuel (0/1) -0.1210 0.0521 -2.32 Number of elderly individuals -0.2559 0.1149 -2.23 Floor in ceramic (0/1) 0.2313 0.0467 4.95 Head has upper sec. education (0/1) 0.1384 0.0487 2.84 Household Size (in log) -0.3448 0.0602 -5.73 Has a motorcycle (0/1) -0.1767 0.0866 -2.04 Has a phone (0/1) 0.1115 0.0483 2.31 Spouse has vocational training (0/1) 0.2430 0.0866 2.81 Strata 2: Urban Northern Region Number of observation 655 R-square 0.405 Variable Coef. Std.Err. t-ratio Intercept 13.8648 0.1097 126.41 Has a car (0/1) 0.3064 0.0511 5.99 Uses wood as cooking fuel (0/1) -0.2068 0.0536 -3.86 North Midland Ecological Zone (0/1) 0.2032 0.0444 4.57 Number of elderly individuals -0.0678 0.0345 -1.96 Has a fridge (0/1) 0.1607 0.0502 3.20 Head is Khmer (0/1) -0.1587 0.0605 -2.63 Head has some primary education (0/1) -0.1140 0.0566 -2.01 Household Size (in log) -0.6282 0.0525 -11.97 Has a phone (0/1) 0.1068 0.0399 2.68 Reside in Xayaboury Province (0/1) -0.2002 0.0433 -4.62 Spouse is self-employed in agriculture (0/1) -0.1478 0.0418 -3.53 Has a TV (0/1) 0.1641 0.0750 2.18 Lao PDR 2015 Census-Based Poverty Map – June 2016 39 Strata 3: Urban Central Region Number of observation 701 R-square 0.370 Variable Coef. Std.Err. t-ratio Intercept 13.7450 0.1430 96.13 North Lowland Ecological Zone (0/1) -0.1450 0.0565 -2.57 Floor in concrete (0/1) -0.2246 0.0524 -4.29 Floor in other material (0/1) -0.5920 0.1268 -4.67 Floor in wood (0/1) -0.4472 0.0815 -5.49 Age of head squared 0.00002 0.00001 2.57 Head has tertiary education (0/1) 0.3190 0.0870 3.67 Head is self-employed in agriculture (0/1) -0.1124 0.0471 -2.39 Head has vocational training (0/1) 0.2761 0.0668 4.13 Household Size (in log) -0.5645 0.0589 -9.58 Number of prime-age male 0.0840 0.0274 3.07 Has a motorcycle (0/1) 0.2930 0.0779 3.76 Reside in province (0/1)12_1 -0.1416 0.0578 -2.45 Spouse has upper secondary education (0/1) 0.1704 0.0746 2.29 Spouse has vocational training (0/1) 0.2501 0.0892 2.80 Village has a primary school (0/1) -0.1870 0.0662 -2.83 Wall is in brick (0/1) -0.1613 0.0708 -2.28 Strata 4: Urban Southern Region Number of observation 335 R-square 0.501 Variable Coef. Std.Err. t-ratio Intercept 13.8173 0.1410 97.97 Number of boys aged 7-14 -0.0799 0.0387 -2.06 Has a car (0/1) 0.2486 0.0661 3.76 Household Size (in log) -0.6412 0.0725 -8.84 Reside in Attapeu Province (0/1) 0.3771 0.0731 5.16 Spouse works in public sector (0/1) 0.2336 0.0794 2.94 Village has a market (0/1) -0.3519 0.0587 -5.99 Village has a primary school (0/1) 0.1721 0.0759 2.27 Has wall in other material (0/1) -0.1521 0.0564 -2.69 Has a washing machine (0/1) 0.3446 0.0626 5.50 40 Lao PDR 2015 Census-Based Poverty Map – June 2016 Strata 5: Rural Northern Region Number of observation 2424 R-square 0.343 Variable Coef. Std.Err. t-ratio Intercept 12.7232 0.1029 123.65 Has a bicycle (0/1) 0.1075 0.0241 4.46 Has a boat (0/1) 0.2168 0.0399 5.43 Number of boys aged 7-14 -0.0297 0.0131 -2.27 Has a car (0/1) 0.2723 0.0383 7.10 North Lowland Ecological Zone (0/1) -0.0944 0.0208 -4.54 Age of head 0.0201 0.0044 4.56 Age of head squared -0.0002 0.0000 -4.13 Head is Lao (0/1) 0.1565 0.0238 6.57 Head has an other ethnic groups (0/1) 0.1475 0.0257 5.73 Head is literate (0/1) 0.0675 0.0246 2.75 Head has lower secondary education (0/1) 0.0847 0.0258 3.28 Head has at least upper secondary education (0/1) 0.1448 0.0530 2.73 Number of kids aged 0-6 -0.0308 0.0118 -2.60 Household Size (in log) -0.4854 0.0310 -15.65 Reside in Huaphanh Province (0/1) -0.1457 0.0252 -5.76 Roof is in zinc (0/1) 0.0645 0.0188 3.43 Village has a market (0/1) 0.1515 0.0484 3.13 Strata 6: Rural Central Region Number of observation 1960 R-square 0.412 Variable Coef. Std.Err. t-ratio Intercept 12.7232 0.0706 183.96 Has a car (0/1) 0.3795 0.0341 11.12 Uses wood as cooking fuel (0/1) -0.0656 0.0261 -2.51 North Lowland Ecological Zone (0/1) 0.0757 0.0307 2.46 Vientiane Plain Ecological Zone (0/1) 0.1615 0.0382 4.23 Number of elderly individual -0.0661 0.0220 -3.00 Has a fridge (0/1) 0.1045 0.0238 4.39 Number of girls aged 7-14 -0.0427 0.0149 -2.87 Age of head squared 3.38e-005 9.46e-006 3.58 Head has an other ethnic groups (0/1) 0.1454 0.0368 3.95 Head has upper secondary education (0/1) 0.0790 0.0389 2.03 Head has vocational training (0/1) 0.1886 0.0519 3.63 Household Size (in log) -0.5055 0.0285 -17.73 Travel time to nearest district capital -0.0003 9.8e-005 -3.16 Has a motorcycle (0/1) 0.1644 0.0267 6.16 Spouse is literate (0/1) 0.1100 0.0227 4.84 Village has road access (0/1) 0.1825 0.0414 4.41 Wall is in “other” material (0/1) -0.0673 0.0259 -2.60 Lao PDR 2015 Census-Based Poverty Map – June 2016 41 Strata 7: Rural Southern Region Number of observation 1358 R-square 0.485 Variable Coef. Std.Err. t-ratio Intercept 13.4594 0.0846 159.13 Has a bicycle (0/1) 0.0675 0.0369 1.83 Has a car (0/1) 0.3617 0.0629 5.75 Village elevation (avg. in meters) -0.0025 0.0004 -5.79 Village elevation (min. in meters) 0.0029 0.0005 6.35 Floor in ceramic (0/1) 0.1715 0.0704 2.44 Floor in concrete (0/1) 0.1690 0.0477 3.54 Head work in public sector (0/1) 0.1695 0.0644 2.63 Head has no education (0/1) -0.1911 0.0421 -4.54 Head has some primary education (0/1) -0.0901 0.0389 -2.32 Head has upper secondary education (0/1) 0.1532 0.0653 2.35 Number of kids aged 0-6 -0.0454 0.0191 -2.38 Household Size (in log) -0.7240 0.0522 -13.87 Number of prime-age male 0.0740 0.0203 3.64 Has a motorcycle (0/1) 0.1454 0.0373 3.90 Reside in Saravane Province (0/1) -0.2864 0.0318 -9.01 Has a roof in zinc (0/1) 0.0981 0.0472 2.08 Has improved sanitation facility (0/1) 0.1432 0.0357 4.02 Village has water supply (0/1) 0.1280 0.0507 2.52 Lao PDR 2015 Census-Based Poverty Map – June 2016 43 Appendix 5: Administrative Unit Labels 44 Lao PDR 2015 Census-Based Poverty Map – June 2016 # Name # Name # Name # Name Vientiane Capital Oudomxay Province Huaphanh Province Xiengkhuang Province 101 Chanthabuly 401 Xay 701 Xamneua 904 Khoune 102 Sikhottabong 402 La 702 Xiengkhor 905 Morkmay 103 Xaysetha 403 Namor 703 Huim 906 Phoukoud 104 Sisattanak 404 Nga 704 Viengxay 907 Phaxay 105 Naxaithong 405 Beng 705 Huameuang Vientiane Province 106 Xaythany 406 Hoon 706 Xamtay 1001 Phonhong 107 Hadxaifong 407 Pakbeng 707 Sopbao 1002 Thoulakhom 108 Sangthong 708 Add Bokeo Province 1003 Keo oudom 109 Mayparkngum 709 Kuane 501 Huoixai 1004 Kasy 710 Sone Phongsaly Province 502 Tonpheung 1005 Vangvieng 201 Phongsaly 503 Meung Xayabury Province 1006 Feuang 202 May 504 Pha oudom 801 Xayabury 1007 Xanakharm 203 Khua 505 Paktha 802 Khop 1008 Mad 204 Samphanh 803 Hongsa 1009 Viengkham Luang Prabang Province 205 Boon neua 804 Ngeun 1010 Hinherb 601 Luangprabang 206 Nhot ou 805 Xienghone 1013 Meun 602 Xieng ngeun 207 Boontai 806 Phiang 603 Nan Borikhamxay Province 807 Parklai Luang Namtha Province 604 Park ou 1101 Pakxane 808 Kenethao 301 Namtha 605 Nambak 1102 Thaphabath 809 Botene 302 Sing 606 Ngoi 1103 Pakkading 810 Thongmyxay 303 Long 607 Pak xeng 1104 Bolikhanh 811 Xaysathan 304 Viengphoukha 608 Phonxay 1105 Khamkeuth 305 Nalae 609 Chomphet Xiengkhuang Province 1106 Viengthong 610 Viengkham 901 Pek 1107 Xaychamphone 611 Phoukhoune 902 Kham 612 Phonthong 903 Nonghed Lao PDR 2015 Census-Based Poverty Map – June 2016 45 # Name # Name # Name Khammuane Province Saravane Province Attapeu Province 1201 Thakhek 1401 Saravane 1701 Xaysetha 1202 Mahaxay 1402 Ta oi 1702 Samakkhixay 1203 Nongbok 1403 Toomlarn 1703 Sanamxay 1204 Hinboon 1404 Lakhonepheng 1704 Sanxay 1205 Nhommalath 1405 Vapy 1705 Phouvong 1206 Bualapha 1406 Khongxedone # Name 1207 Nakai 1407 Lao ngarm Saysomboune Province 1208 Xebangfay 1408 Samuoi 1801 Anouvong 1209 Xaybuathong 1802 Thathom Sekong Province 1210 Khounkham 1803 Longcheng 1501 Lamarm Savannakhet Province 1502 Kaleum 1804 Home 1301 Kaysone Phomvihane 1503 Dakcheung 1805 Longsane 1302 Outhoomphone 1504 Thateng 1303 Atsaphangthong Champasack Province 1304 Phine 1601 Pakse 1305 Sepone 1602 Sanasomboon 1306 Nong 1603 Bachiangchaleunsook 1307 Thapangthong 1604 Paksxong 1308 Songkhone 1605 Pathoomphone 1309 Champhone 1606 Phonthong 1310 Xonbuly 1607 Champasack 1311 Xaybuly 1608 Sukhuma 1312 Vilabuly 1609 Moonlapamok 1313 Atsaphone 1610 Khong 1314 Xayphoothong 1315 Phalanxay 46 Lao PDR 2015 Census-Based Poverty Map – June 2016 Appendix 6: Monetary and Non-Monetary Maps at Different Administrative Levels Map 3: Poverty Gap Index (P1) A. Province Phongsaly ! . Luang Namtha . ! Muang Xay . ! Xamneua Huay Xay ! . . ! Luang Prabang . ! Phonsavan . ! ! . Xayabury Xaisomboun . ! Phonhong ! . Pakxanh ! . VIENTIANE . ! Thakhek ! . Savannakhet . ! ! .Saravane Sekong . ! Pakxe . ! Attapeu Depth of poverty (P1) [%] . ! 0 0 <4 5 -7 0 -1 -2 -1 >2 4 7 15 10 Sources: Authors’ calculation based on 2012/13 LECS-5 and 2015 Lao PDR Census Lao PDR 2015 Census-Based Poverty Map – June 2016 47 B. District Phongsaly ! . Luang Namtha . ! Muang Xay . ! Xamneua Huay Xay . ! . ! Luang Prabang . ! Phonsavan . ! . ! Xayabury Xaisomboun . ! Phonhong ! . Pakxanh . ! VIENTIANE . ! Thakhek . ! Savannakhet . ! ! .Saravane Sekong . ! Pakxe . ! Attapeu Depth of poverty (P1) [%] . ! 0 0 0 <4 5 -7 -2 -1 >2 -1 4 15 7 10 Sources: Authors’ calculation based on 2012/13 LECS-5 and 2015 Lao PDR Census 48 Lao PDR 2015 Census-Based Poverty Map – June 2016 Map 4: Youth Literacy Rate, 15-24 Age Group [3] (in %) A. Province Source: Authors’ calculation based on the 2015 Lao PDR Census Lao PDR 2015 Census-Based Poverty Map – June 2016 49 B. District Source: Authors’ calculation based on the 2015 Lao PDR Census 50 Lao PDR 2015 Census-Based Poverty Map – June 2016 Map 5: Literacy Rate, 25-64 Age Group [4] (in %) A. Province Source: Authors’ calculation based on the 2015 Lao PDR Census Lao PDR 2015 Census-Based Poverty Map – June 2016 51 B. District Source: Authors’ calculation based on the 2015 Lao PDR Census 52 Lao PDR 2015 Census-Based Poverty Map – June 2016 Map 6: Net School Enrolment in Primary [5] (in %) A. Province Source: Authors’ calculation based on the 2015 Lao PDR Census Lao PDR 2015 Census-Based Poverty Map – June 2016 53 B. District Source: Authors’ calculation based on the 2015 Lao PDR Census 54 Lao PDR 2015 Census-Based Poverty Map – June 2016 Map 7: Net School Enrolment in Lower Secondary [6] (in %) A. Province Source: Authors’ calculation based on the 2015 Lao PDR Census Lao PDR 2015 Census-Based Poverty Map – June 2016 55 B. District Source: Authors’ calculation based on the 2015 Lao PDR Census 56 Lao PDR 2015 Census-Based Poverty Map – June 2016 Map 8: Net School Enrolment in Upper Secondary [7] (in %) A. Province Source: Authors’ calculation based on the 2015 Lao PDR Census Lao PDR 2015 Census-Based Poverty Map – June 2016 57 B. District Source: Authors’ calculation based on the 2015 Lao PDR Census 58 Lao PDR 2015 Census-Based Poverty Map – June 2016 Map 9: Gross School Enrolment in Primary [8] (in %) A. Province Source: Authors’ calculation based on the 2015 Lao PDR Census Lao PDR 2015 Census-Based Poverty Map – June 2016 59 B. District Source: Authors’ calculation based on the 2015 Lao PDR Census 60 Lao PDR 2015 Census-Based Poverty Map – June 2016 Map 10: Gross School Enrolment in Lower Secondary [9] (in %) A. Province Source: Authors’ calculation based on the 2015 Lao PDR Census Lao PDR 2015 Census-Based Poverty Map – June 2016 61 B. District Source: Authors’ calculation based on the 2015 Lao PDR Census 62 Lao PDR 2015 Census-Based Poverty Map – June 2016 Map 11: Gross School Enrolment in Upper Secondary [10] (in %) A. Province Source: Authors’ calculation based on the 2015 Lao PDR Census Lao PDR 2015 Census-Based Poverty Map – June 2016 63 B. District Source: Authors’ calculation based on the 2015 Lao PDR Census 64 Lao PDR 2015 Census-Based Poverty Map – June 2016 Map 12: Girl-to-Boy Ratio at Primary [11], Lower Secondary [12] and Upper Secondary [13] School A. Province Source: Authors’ calculation based on the 2015 Lao PDR Census Lao PDR 2015 Census-Based Poverty Map – June 2016 65 B. District Source: Authors’ calculation based on the 2015 Lao PDR Census 66 Lao PDR 2015 Census-Based Poverty Map – June 2016 Map 13: Proportion [14] and number [15] of out-of-school 6-11 year-old children (in %) A. Province Source: Authors’ calculation based on the 2015 Lao PDR Census Lao PDR 2015 Census-Based Poverty Map – June 2016 67 B. District Source: Authors’ calculation based on the 2015 Lao PDR Census 68 Lao PDR 2015 Census-Based Poverty Map – June 2016 Map 14: Proportion [16] and number [17] of out-of-school 12-18 year-old children (in %) A. Province Source: Authors’ calculation based on the 2015 Lao PDR Census Lao PDR 2015 Census-Based Poverty Map – June 2016 69 B. District Source: Authors’ calculation based on the 2015 Lao PDR Census 70 Lao PDR 2015 Census-Based Poverty Map – June 2016 Map 15: Employment rate for the 15-64 age group [18] (in %) A. Province Source: Authors’ calculation based on the 2015 Lao PDR Census Lao PDR 2015 Census-Based Poverty Map – June 2016 71 B. District Source: Authors’ calculation based on the 2015 Lao PDR Census 72 Lao PDR 2015 Census-Based Poverty Map – June 2016 Map 16: Self-employment Rate for the 15-64 Age Group [19] (in %) A. Province Source: Authors’ calculation based on the 2015 Lao PDR Census Lao PDR 2015 Census-Based Poverty Map – June 2016 73 B. District Source: Authors’ calculation based on the 2015 Lao PDR Census 74 Lao PDR 2015 Census-Based Poverty Map – June 2016 Map 17: Unemployment Rate for the 15-24 Age Group [20] (in %) A. Province Source: Authors’ calculation based on the 2015 Lao PDR Census Lao PDR 2015 Census-Based Poverty Map – June 2016 75 B. District Source: Authors’ calculation based on the 2015 Lao PDR Census 76 Lao PDR 2015 Census-Based Poverty Map – June 2016 Map 18: Unemployment Rate for the 25-64 Age Group [21] (in %) A. Province Source: Authors’ calculation based on the 2015 Lao PDR Census Lao PDR 2015 Census-Based Poverty Map – June 2016 77 B. District Source: Authors’ calculation based on the 2015 Lao PDR Census 78 Lao PDR 2015 Census-Based Poverty Map – June 2016 Map 19: Percentage of non-agricultural wage earner workers in total employment [22] (in %) A. Province Source: Authors’ calculation based on the 2015 Lao PDR Census Lao PDR 2015 Census-Based Poverty Map – June 2016 79 B. District Source: Authors’ calculation based on the 2015 Lao PDR Census 80 Lao PDR 2015 Census-Based Poverty Map – June 2016 Map 20: Percentage of non-agricultural own-account workers in total employment [23] (in %) A. Province Source: Authors’ calculation based on the 2015 Lao PDR Census Lao PDR 2015 Census-Based Poverty Map – June 2016 81 B. District Source: Authors’ calculation based on the 2015 Lao PDR Census 82 Lao PDR 2015 Census-Based Poverty Map – June 2016 Map 21: Demographic Dependency Rate [24] & Share of Women in Wage Employment in the Non-Agricultural Sector [25] A. Province Source: Authors’ calculation based on the 2015 Lao PDR Census Lao PDR 2015 Census-Based Poverty Map – June 2016 83 B. District Source: Authors’ calculation based on the 2015 Lao PDR Census 84 Lao PDR 2015 Census-Based Poverty Map – June 2016 Map 22: Proportion of married 17 year-old girls [26] (in %) A. Province Source: Authors’ calculation based on the 2015 Lao PDR Census Lao PDR 2015 Census-Based Poverty Map – June 2016 85 Map 23: Proportion of Population Using Improved Sanitation [27], Improved Drinking Water [28] or Not Using Wood for Cooking [29] A. Province Source: Authors’ calculation based on the 2015 Lao PDR Census 86 Lao PDR 2015 Census-Based Poverty Map – June 2016 B. District Source: Authors’ calculation based on the 2015 Lao PDR Census Lao PDR 2015 Census-Based Poverty Map – June 2016 87 Map 24: Proportion of Population Having Electricity [30] or a Telephone [31] A. Province Source: Authors’ calculation based on the 2015 Lao PDR Census 88 Lao PDR 2015 Census-Based Poverty Map – June 2016 B. District Source: Authors’ calculation based on the 2015 Lao PDR Census Lao PDR 2015 Census-Based Poverty Map – June 2016 89 Appendix 7: Correlation Matrix between the different Poverty Indicators [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] [22] [23] [24] [25] [26] [27] [28] [29] [30] [31] [1] 1.00 [2] 0.97 1.00 [3] -0.52 -0.51 1.00 [4] -0.57 -0.52 0.91 1.00 [5] -0.37 -0.39 0.81 0.65 1.00 [6] -0.65 -0.63 0.75 0.72 0.72 1.00 [7] -0.61 -0.55 0.56 0.61 0.46 0.81 1.00 [8] 0.29 0.21 0.24 -0.03 0.51 -0.05 -0.14 1.00 [9] -0.56 -0.55 0.72 0.65 0.71 0.98 0.80 0.06 1.00 [10] -0.64 -0.56 0.53 0.62 0.41 0.76 0.98 -0.22 0.73 1.00 [11] -0.31 -0.31 0.54 0.44 0.43 0.28 0.14 0.21 0.26 0.14 1.00 [12] -0.51 -0.53 0.42 0.51 0.17 0.32 0.24 -0.22 0.23 0.28 0.36 1.00 [13] -0.45 -0.43 0.19 0.34 -0.02 0.17 0.27 -0.29 0.10 0.31 0.05 0.63 1.00 [14] 0.49 0.49 -0.87 -0.76 -0.97 -0.80 -0.56 -0.34 -0.78 -0.52 -0.46 -0.27 -0.09 1.00 [15] 0.28 0.28 -0.49 -0.30 -0.60 -0.70 -0.68 -0.41 -0.80 -0.59 -0.17 0.09 0.15 0.57 1.00 [16] 0.33 0.33 -0.53 -0.34 -0.64 -0.51 -0.27 -0.33 -0.51 -0.21 -0.29 0.05 0.17 0.63 0.52 1.00 [17] 0.07 0.08 -0.03 0.16 -0.20 -0.24 -0.15 -0.23 -0.31 -0.08 -0.02 0.37 0.39 0.15 0.58 0.74 1.00 [18] 0.32 0.29 -0.29 -0.30 -0.24 -0.53 -0.80 -0.01 -0.59 -0.79 0.02 -0.03 -0.12 0.29 0.65 0.01 0.11 1.00 [19] 0.54 0.43 -0.35 -0.46 -0.18 -0.46 -0.78 0.29 -0.43 -0.86 -0.10 -0.25 -0.33 0.28 0.35 0.04 -0.05 0.75 1.00 [20] -0.43 -0.38 0.29 0.35 0.22 0.54 0.77 -0.15 0.56 0.77 -0.02 0.09 0.20 -0.29 -0.53 -0.03 -0.08 -0.87 -0.72 1.00 [21] -0.42 -0.36 0.22 0.31 0.09 0.40 0.68 -0.24 0.40 0.72 -0.03 0.18 0.28 -0.18 -0.35 0.14 0.09 -0.84 -0.79 0.89 1.00 [22] -0.53 -0.42 0.35 0.46 0.18 0.47 0.79 -0.27 0.43 0.86 0.10 0.24 0.33 -0.29 -0.36 -0.04 0.04 -0.76 -1.00 0.73 0.79 1.00 [23] -0.55 -0.45 0.33 0.44 0.20 0.45 0.74 -0.23 0.42 0.81 0.08 0.26 0.32 -0.29 -0.34 -0.01 0.06 -0.75 -0.90 0.74 0.84 0.90 1.00 [24] 0.72 0.67 -0.52 -0.71 -0.28 -0.56 -0.59 0.41 -0.44 -0.66 -0.25 -0.61 -0.60 0.44 0.01 0.11 -0.27 0.27 0.58 -0.35 -0.40 -0.58 -0.56 1.00 [25] -0.20 -0.20 0.09 0.30 -0.03 -0.01 0.09 -0.30 -0.11 0.14 0.04 0.45 0.55 -0.06 0.43 0.19 0.52 0.12 -0.21 -0.01 0.06 0.20 0.14 -0.55 1.00 [26] 0.48 0.45 -0.51 -0.59 -0.35 -0.52 -0.67 0.05 -0.49 -0.67 -0.29 -0.41 -0.48 0.45 0.32 0.05 -0.23 0.48 0.57 -0.49 -0.46 -0.58 -0.54 0.60 -0.38 1.00 [27] -0.68 -0.65 0.73 0.72 0.64 0.85 0.67 -0.11 0.81 0.66 0.29 0.33 0.15 -0.74 -0.50 -0.49 -0.17 -0.40 -0.45 0.43 0.37 0.44 0.44 -0.64 0.04 -0.37 1.00 [28] -0.47 -0.44 0.41 0.30 0.48 0.60 0.54 0.07 0.62 0.51 0.11 -0.03 -0.05 -0.49 -0.58 -0.46 -0.38 -0.41 -0.38 0.38 0.29 0.38 0.36 -0.31 -0.16 -0.20 0.65 1.00 [29] -0.36 -0.27 0.31 0.51 0.10 0.18 0.34 -0.30 0.08 0.43 0.15 0.43 0.42 -0.20 0.19 0.14 0.49 -0.25 -0.56 0.26 0.42 0.56 0.51 -0.62 0.53 -0.47 0.27 -0.01 1.00 [30] -0.65 -0.63 0.58 0.67 0.38 0.62 0.51 -0.24 0.55 0.51 0.33 0.58 0.38 -0.50 -0.14 -0.19 0.20 -0.23 -0.38 0.33 0.30 0.37 0.37 -0.72 0.31 -0.45 0.70 0.29 0.44 1.00 [31] -0.64 -0.62 0.64 0.69 0.54 0.75 0.62 -0.13 0.71 0.59 0.23 0.36 0.27 -0.63 -0.32 -0.30 0.09 -0.33 -0.37 0.35 0.29 0.37 0.36 -0.63 0.21 -0.44 0.73 0.43 0.34 0.76 1.00 Source: Authors’ calculation based on the 2015 Lao PDR Census Note: The indexed columns and rows correspond to the indicator numbers in Table 1 Photo by Remy Rossi / World Bank, 2013 Lao PDR 2015 Census-Based Poverty Map – June 2016 91 Appendix 8: Monetary Poverty Indices, by Province and District Poverty Poverty Poverty Gap Severity Number Administrative Headcount Index Index of Poor Code Structure Population (P0) (P1) (P2) Individuals 100 Vientiane Capital 771,974 8.5 2.0 0.7 65,695 (1.2) (0.4) (0.2) 101 Chanthabuly 65,218 5.0 1.1 0.4 3,241 (1.3) (0.4) (0.1) 102 Sikhottabong 115,094 7.4 1.6 0.6 8,528 (1.4) (0.4) (0.2) 103 Xaysetha 106,966 6.5 1.4 0.5 6,963 (1.2) (0.3) (0.1) 104 Sisattanak 58,318 5.8 1.3 0.4 3,353 (1.2) (0.3) (0.1) 105 Naxaithong 71,504 10.5 2.4 0.9 7,506 (1.9) (0.6) (0.2) 106 Xaythany 183,358 9.4 2.2 0.8 17,291 (1.6) (0.5) (0.2) 107 Hadxaifong 94,597 9.6 2.2 0.8 9,081 (1.5) (0.4) (0.2) 108 Sangthong 28,916 12.2 3.0 1.1 3,518 (2.3) (0.7) (0.3) 109 Mayparkngum 48,003 12.9 3.2 1.2 6,192 (2.3) (0.8) (0.4) 200 Phongsaly 171,426 22.7 4.9 1.6 38,894 (2.1) (0.6) (0.2) 201 Phongsaly 21,361 17.5 3.9 1.4 3,739 (2.7) (0.8) (0.3) 202 May 26,145 28.8 6.4 2.1 7,523 (2.7) (0.8) (0.4) 203 Khua 25,629 24.3 5.2 1.7 6,236 (2.8) (0.8) (0.3) 204 Samphanh 22,981 27.6 6.3 2.1 6,341 (3.4) (1.1) (0.5) 205 Boonneua 21,383 17.6 3.5 1.1 3,761 (3.1) (0.8) (0.3) 206 Nhotou 30,525 21.1 4.4 1.4 6,437 (2.5) (0.7) (0.3) 207 Boontai 23,402 20.7 4.3 1.4 4,854 (3.0) (0.8) (0.3) 92 Lao PDR 2015 Census-Based Poverty Map – June 2016 Poverty Poverty Poverty Gap Severity Number Administrative Headcount Index Index of Poor Code Structure Population (P0) (P1) (P2) Individuals 300 Luangnamtha 168,434 21.1 4.6 1.5 35,524 (2.2) (0.7) (0.3) 301 Namtha 51,835 16.2 3.6 1.2 8,411 (2.8) (0.8) (0.3) 302 Sing 38,044 18.3 3.8 1.2 6,944 (2.8) (0.8) (0.3) 303 Long 33,521 23.8 5.1 1.6 7,978 (3.3) (0.9) (0.4) 304 Viengphoukha 23,162 26.3 6.1 2.1 6,093 (3.5) (1.1) (0.5) 305 Nalae 21,872 27.9 6.2 2.0 6,095 (3.0) (0.9) (0.4) 400 Oudomxay 295,813 25.5 5.7 1.9 75,327 (1.9) (0.6) (0.2) 401 Xay 75,214 17.7 3.8 1.2 13,305 (2.3) (0.6) (0.2) 402 La 16,506 22.8 4.7 1.5 3,763 (3.3) (0.9) (0.3) 403 Namor 37,352 26.1 5.7 1.8 9,750 (3.2) (1.0) (0.4) 404 Nga 29,965 30.6 7.0 2.3 9,168 (3.0) (0.9) (0.4) 405 Beng 36,544 21.4 4.5 1.4 7,828 (3.0) (0.9) (0.4) 406 Hoon 71,537 28.8 6.4 2.1 20,571 (2.8) (0.8) (0.3) 407 Pakbeng 28,695 38.1 9.2 3.2 10,937 (3.7) (1.2) (0.5) 500 Bokeo 171,585 25.5 5.9 2.0 43,738 (2.0) (0.7) (0.3) 501 Huoixai 67,411 21.7 4.9 1.6 14,633 (2.4) (0.8) (0.3) 502 Tonpheung 32,410 19.1 4.3 1.5 6,197 (3.0) (0.9) (0.4) 503 Meung 14,005 28.1 7.1 2.6 3,935 (4.7) (1.8) (0.9) 504 Phaoudom 39,569 34.2 8.1 2.8 13,545 (3.3) (1.1) (0.5) 505 Paktha 18,190 29.8 7.1 2.5 5,427 (3.9) (1.3) (0.6) Lao PDR 2015 Census-Based Poverty Map – June 2016 93 Poverty Poverty Poverty Gap Severity Number Administrative Headcount Index Index of Poor Code Structure Population (P0) (P1) (P2) Individuals 600 Luangprabang 418,000 22.9 4.9 1.6 95,575 (1.7) (0.5) (0.2) 601 Luangprabang 82,541 11.5 2.3 0.7 9,532 (2.0) (0.5) (0.2) 602 Xiengngeun 31,689 22.7 4.8 1.5 7,198 (3.2) (0.9) (0.3) 603 Nan 27,992 16.3 3.3 1.0 4,566 (2.5) (0.7) (0.3) 604 Parkou 25,509 21.2 4.3 1.3 5,401 (2.7) (0.8) (0.3) 605 Nambak 67,113 24.1 5.2 1.7 16,191 (3.1) (0.9) (0.4) 606 Ngoi 29,546 27.0 5.8 1.9 7,973 (2.4) (0.7) (0.3) 607 Pakxeng 22,024 30.2 6.7 2.2 6,647 (2.9) (0.9) (0.4) 608 Phonxay 31,802 30.5 6.8 2.2 9,695 (3.5) (1.0) (0.4) 609 Chomphet 29,927 26.5 5.9 1.9 7,943 (2.9) (0.9) (0.4) 610 Viengkham 28,441 30.5 6.8 2.2 8,664 (2.9) (0.9) (0.4) 611 Phoukhoune 22,735 26.7 5.7 1.8 6,061 (3.9) (1.1) (0.5) 612 Phonthong 18,681 30.5 7.2 2.5 5,696 (3.6) (1.1) (0.5) 700 Huaphanh 285,450 37.0 8.5 2.8 105,680 (3.7) (1.2) (0.5) 701 Xamneua 54,960 30.8 7.0 2.3 16,902 (3.7) (1.2) (0.5) 702 Xiengkhor 25,666 38.0 8.5 2.8 9,758 (4.9) (1.5) (0.6) 703 Huim 12,118 29.3 5.9 1.8 3,545 (5.0) (1.4) (0.5) 704 Viengxay 31,298 27.7 5.5 1.7 8,658 (4.2) (1.1) (0.4) 705 Huameuang 32,234 45.6 11.0 3.8 14,711 (5.3) (1.9) (0.8) 706 Xamtay 36,696 39.5 9.2 3.1 14,512 (4.8) (1.6) (0.7) 94 Lao PDR 2015 Census-Based Poverty Map – June 2016 Poverty Poverty Poverty Gap Severity Number Administrative Headcount Index Index of Poor Code Structure Population (P0) (P1) (P2) Individuals 707 Sopbao 25,326 36.7 8.1 2.6 9,300 (4.3) (1.4) (0.6) 708 Add 26,872 38.8 8.8 2.9 10,435 (4.8) (1.6) (0.6) 709 Kuane 24,525 45.2 10.9 3.7 11,093 (5.3) (1.9) (0.8) 710 Sone 15,755 42.8 10.3 3.5 6,749 (6.1) (2.2) (0.9) 800 Xayaboury 368,267 20.2 4.5 1.5 74,325 (2.1) (0.7) (0.3) 801 Xayabury 70,109 21.8 5.1 1.8 15,312 (3.2) (1.0) (0.5) 802 Khop 19,773 22.1 4.9 1.7 4,362 (3.6) (1.1) (0.5) 803 Hongsa 26,524 21.1 5.0 1.7 5,584 (3.9) (1.2) (0.5) 804 Ngeun 17,028 23.2 5.4 1.9 3,957 (4.7) (1.5) (0.7) 805 Xienghone 31,863 20.8 4.7 1.6 6,632 (3.3) (1.0) (0.4) 806 Phiang 55,947 23.5 5.6 2.0 13,158 (4.2) (1.3) (0.6) 807 Parklai 66,563 16.0 3.3 1.0 10,663 (2.8) (0.8) (0.3) 808 Kenethao 39,708 15.4 3.1 1.0 6,112 (3.0) (0.8) (0.3) 809 Botene 17,217 13.2 2.6 0.8 2,268 (3.3) (0.8) (0.3) 810 Thongmyxay 8,509 11.3 2.1 0.6 961 (3.7) (0.9) (0.3) 811 Xaysathan 15,026 35.4 8.3 2.8 5,323 (5.1) (1.7) (0.7) 900 Xienkhuang 238,766 28.2 7.2 2.7 67,336 (2.7) (0.9) (0.4) 901 Pek 71,321 13.6 2.8 0.9 9,720 (2.5) (0.7) (0.2) 902 Kham 47,256 31.2 7.8 2.8 14,749 (3.1) (1.0) (0.5) 903 Nonghed 37,406 41.5 13.2 5.9 15,525 (4.3) (1.8) (1.1) Lao PDR 2015 Census-Based Poverty Map – June 2016 95 Poverty Poverty Poverty Gap Severity Number Administrative Headcount Index Index of Poor Code Structure Population (P0) (P1) (P2) Individuals 904 Khoune 32,574 31.0 7.3 2.5 10,088 (4.2) (1.4) (0.6) 905 Morkmay 14,061 42.3 11.2 4.4 5,942 (7.6) (2.9) (1.4) 906 Phoukoud 24,873 35.3 8.8 3.2 8,779 (4.0) (1.5) (0.7) 907 Phaxay 11,275 22.5 4.7 1.5 2,534 (4.4) (1.3) (0.5) 1000 Vientiane Province 406,810 16.5 3.5 1.1 67,298 (2.2) (0.6) (0.3) 1001 Phonhong 62,307 9.9 1.9 0.6 6,198 (2.7) (0.7) (0.2) 1002 Thoulakhom 51,369 9.5 1.8 0.5 4,903 (2.9) (0.7) (0.2) 1003 Keooudom 16,678 9.5 1.8 0.5 1,589 (2.8) (0.6) (0.2) 1004 Kasy 35,993 24.2 5.2 1.6 8,715 (4.1) (1.3) (0.5) 1005 Vangvieng 53,488 16.8 3.4 1.1 8,981 (3.4) (0.9) (0.3) 1006 Feuang 41,062 21.1 4.4 1.4 8,683 (5.2) (1.5) (0.6) 1007 Xanakharm 39,712 11.3 2.1 0.6 4,496 (2.9) (0.8) (0.3) 1008 Mad 20,820 21.9 4.5 1.4 4,561 (4.7) (1.3) (0.5) 1009 viengkham 17,012 6.7 1.2 0.4 1,136 (2.2) (0.5) (0.2) 1010 Hinherb 28,598 17.1 3.4 1.0 4,889 (3.1) (0.8) (0.3) 1013 Meun 39,771 33.0 8.3 3.0 13,135 (6.9) (2.7) (1.3) 1100 Borikhamxay 264,135 20.7 4.8 1.6 54,781 (2.1) (0.7) (0.3) 1101 Pakxane 43,161 8.0 1.5 0.4 3,435 (2.2) (0.5) (0.2) 1102 Thaphabath 24,351 8.6 1.6 0.4 2,099 (2.8) (0.6) (0.2) 1103 Pakkading 49,474 18.9 3.8 1.1 9,330 (3.5) (0.9) (0.3) 96 Lao PDR 2015 Census-Based Poverty Map – June 2016 Poverty Poverty Poverty Gap Severity Number Administrative Headcount Index Index of Poor Code Structure Population (P0) (P1) (P2) Individuals 1104 Bolikhanh 45,960 22.6 4.9 1.6 10,399 (4.7) (1.5) (0.6) 1105 Khamkeuth 61,879 21.5 4.4 1.4 13,279 (3.1) (0.9) (0.4) 1106 Viengthong 28,587 32.7 8.6 3.3 9,351 (5.8) (2.1) (1.0) 1107 Xaychamphone 10,723 64.2 21.3 9.2 6,887 (7.4) (4.2) (2.4) 1200 Khammuane 383,202 27.1 6.2 2.1 103,978 (1.8) (0.6) (0.3) 1201 Thakhek 87,261 17.2 3.4 1.0 15,041 (2.3) (0.6) (0.2) 1202 Mahaxay 35,643 27.0 5.7 1.8 9,610 (3.3) (1.0) (0.4) 1203 Nongbok 46,967 22.4 4.6 1.4 10,536 (3.2) (0.9) (0.4) 1204 Hinboon 49,465 23.3 5.0 1.6 11,517 (2.6) (0.7) (0.3) 1205 Nhommalath 32,003 27.7 6.2 2.0 8,859 (3.3) (1.1) (0.5) 1206 Bualapha 31,206 43.7 11.1 3.9 13,635 (3.7) (1.5) (0.7) 1207 Nakai 25,050 42.6 12.6 5.1 10,678 (5.3) (2.5) (1.4) 1208 Xebangfay 28,198 28.9 6.4 2.0 8,162 (4.4) (1.3) (0.5) 1209 Xaybuathong 25,796 39.2 8.9 2.9 10,106 (4.5) (1.6) (0.6) 1210 Khounkham 21,613 27.0 6.1 2.0 5,831 (5.0) (1.4) (0.6) 1300 Savanakhet 943,357 32.0 7.5 2.5 302,264 (1.8) (0.6) (0.3) 1301 KaysonePhomvihane 118,366 13.4 2.7 0.8 15,913 (2.6) (0.7) (0.2) 1302 Outhoomphone 87,437 28.0 6.3 2.1 24,445 (3.0) (0.9) (0.4) 1303 Atsaphangthong 44,746 34.6 7.9 2.6 15,498 (3.6) (1.2) (0.5) 1304 Phine 64,184 42.4 11.0 3.9 27,206 (2.9) (1.2) (0.6) Lao PDR 2015 Census-Based Poverty Map – June 2016 97 Poverty Poverty Poverty Gap Severity Number Administrative Headcount Index Index of Poor Code Structure Population (P0) (P1) (P2) Individuals 1305 Sepone 53,891 42.2 10.4 3.6 22,739 (3.4) (1.3) (0.6) 1306 Nong 28,432 54.0 13.8 4.8 15,347 (4.1) (1.6) (0.8) 1307 Thapangthong 40,119 40.6 10.1 3.6 16,281 (3.1) (1.2) (0.6) 1308 Songkhone 98,731 25.1 5.3 1.7 24,806 (3.0) (0.8) (0.3) 1309 Champhone 107,882 30.2 6.6 2.1 32,564 (2.6) (0.8) (0.3) 1310 Xonbuly 59,725 49.5 13.1 4.8 29,546 (3.5) (1.4) (0.7) 1311 Xaybuly 58,696 28.0 6.0 1.9 16,439 (3.1) (0.9) (0.4) 1312 Vilabuly 37,481 32.1 7.1 2.3 12,041 (3.5) (1.1) (0.5) 1313 Atsaphone 58,836 42.0 10.1 3.5 24,715 (3.0) (1.2) (0.6) 1314 Xayphoothong 45,723 17.1 3.4 1.0 7,838 (3.5) (0.9) (0.3) 1315 Phalanxay 39,108 43.2 10.7 3.7 16,882 (4.1) (1.5) (0.6) 1400 Saravane 390,465 48.2 14.6 6.1 188,354 (3.4) (1.5) (0.7) 1401 Saravane 98,145 50.3 15.3 6.3 49,348 (3.7) (1.6) (0.9) 1402 Ta oi 30,724 64.3 21.9 9.8 19,756 (4.7) (2.5) (1.5) 1403 Toomlarn 28,605 73.1 27.9 13.5 20,920 (4.4) (2.9) (1.9) 1404 Lakhonepheng 46,997 38.4 10.4 4.0 18,059 (4.1) (1.5) (0.7) 1405 Vapy 37,102 42.9 11.7 4.4 15,925 (4.6) (1.7) (0.8) 1406 Khongxedone 62,275 41.5 11.6 4.5 25,849 (4.4) (1.7) (0.8) 1407 Lao ngarm 70,941 42.6 11.9 4.6 30,235 (4.1) (1.6) (0.8) 1408 Samuoi 15,676 52.8 16.5 7.0 8,269 (4.5) (2.1) (1.2) 98 Lao PDR 2015 Census-Based Poverty Map – June 2016 Poverty Poverty Poverty Gap Severity Number Administrative Headcount Index Index of Poor Code Structure Population (P0) (P1) (P2) Individuals 1500 Sekong 109,872 31.4 9.3 3.9 34,469 (3.5) (1.4) (0.7) 1501 Lamarm 33,773 28.0 8.0 3.2 9,455 (3.5) (1.4) (0.7) 1502 Kaleum 15,741 46.4 14.8 6.6 7,310 (4.9) (2.3) (1.4) 1503 Dakcheung 22,043 35.4 11.9 5.7 7,807 (5.5) (2.4) (1.5) 1504 Thateng 38,315 25.8 6.6 2.4 9,895 (4.3) (1.5) (0.7) 1600 Champasack 676,856 22.8 5.6 2.1 154,054 (2.6) (0.9) (0.4) 1601 Pakse 71,741 14.9 3.8 1.4 10,693 (2.5) (0.8) (0.4) 1602 Sanasomboon 67,902 22.5 5.5 2.0 15,299 (3.5) (1.1) (0.5) 1603 Bachiangchaleunsook 55,313 24.1 6.1 2.2 13,321 (3.5) (1.2) (0.6) 1604 Paksxong 78,792 15.5 3.9 1.5 12,213 (2.9) (0.9) (0.4) 1605 Pathoomphone 60,359 24.1 5.9 2.2 14,540 (3.2) (1.1) (0.5) 1606 Phonthong 92,957 23.1 5.7 2.1 21,498 (3.4) (1.2) (0.5) 1607 Champasack 62,235 26.6 6.9 2.6 16,579 (3.8) (1.4) (0.6) 1608 Sukhuma 56,514 26.5 6.4 2.2 14,959 (4.0) (1.3) (0.5) 1609 Moonlapamok 38,490 27.1 6.6 2.4 10,415 (4.3) (1.4) (0.6) 1610 Khong 92,553 26.5 6.4 2.3 24,566 (3.8) (1.2) (0.5) 1700 Attapeu 135,813 18.9 4.6 1.6 25,652 (2.6) (0.8) (0.3) 1701 Xaysetha 32,839 12.9 2.8 0.9 4,250 (3.6) (1.0) (0.4) 1702 Samakkhixay 34,528 13.4 3.1 1.1 4,616 (2.8) (0.9) (0.4) 1703 Sanamxay 33,399 26.8 6.6 2.3 8,964 (4.3) (1.4) (0.6) Lao PDR 2015 Census-Based Poverty Map – June 2016 99 1704 Sanxay 21,267 22.5 6.1 2.3 4,788 (4.2) (1.4) (0.7) 1705 Phouvong 13,780 22.0 5.2 1.8 3,032 (4.6) (1.4) (0.6) 1800 Xaysomboune 79,452 27.8 6.3 2.1 22,048 (4.7) (1.5) (0.6) 1801 Anouvong 20,966 23.2 5.1 1.7 4,861 (6.8) (2.1) (0.9) 1802 Thathom 19,007 25.8 5.5 1.8 4,913 (5.4) (1.7) (0.7) 1803 Longcheng 6,579 27.8 6.5 2.2 1,828 (6.7) (2.2) (0.9) 1804 Home 10,499 35.2 9.0 3.3 3,690 (9.8) (3.6) (1.6) 1805 Longsane 22,401 30.2 6.8 2.3 6,756 (7.3) (2.2) (0.9) Source: Authors’ calculations based on the 2012/13 LECS-5 and 2015 Lao PDR Census Note 1: Robust standard errors are in parentheses. Note 2: The provinces are shown in bold, while the associated districts are listed below their respective province. 100 Lao PDR 2015 Census-Based Poverty Map – June 2016 Appendix 9: Non-Monetary Indicators (Education), by Province and District Girl/Boy Ratio – Lower Girl/Boy Ratio – Upper Literacy Rate –15-25 year- old [3] Literacy Rate – 15-64 year- old [4] Net School Enrolment Rate – Primary [5] Net School Enrolment Rate – Lower Sec. [6] Net School Enrolment Rate – Upper Sec. [7] Net School Enrolment Rate – Primary [8] Net School Enrolment Rate – Lower Sec. [9] Net School Enrolment Rate – Upper Sec. [10] Girl/Boy Ratio – Primary [11] Secondary [12] Secondary [13] Proportion of Out-of-School 6-11 year-old Children [14] Proportion of Out-of-School 12-18 year-old Children [15] Number of Out-of-School 6-11 year-old Children [16] Number of Out-of-School 12-18 year-old Children [17] Code Province/District 100 Vientiane Capital 99.1 97.6 80.5 55.3 43.9 93.8 66.0 83.8 0.94 1.00 0.99 13.4 27.6 9,689 25,198 101 Chanthabuly 99.6 99.2 80.0 58.2 56.0 93.6 70.9 108.0 0.97 0.97 0.99 12.9 19.8 673 1,434 102 Sikhottabong 99.4 98.8 84.9 58.6 45.3 99.4 70.0 85.0 0.94 0.99 1.08 9.1 23.1 950 3,054 103 Xaysetha 99.3 98.9 73.9 52.4 49.8 86.4 62.3 94.2 0.95 1.02 0.94 19.3 28.2 1,815 3,477 104 Sisattanak 99.6 99.3 78.9 59.3 57.9 91.2 70.9 115.3 0.95 1.02 0.99 15.5 22.7 729 1,446 105 Naxaithong 99.0 96.9 84.9 56.2 32.2 96.7 66.3 56.2 0.93 0.99 0.98 10.3 31.3 769 2,654 106 Xaythany 98.7 95.8 77.6 53.5 44.2 91.6 64.9 89.6 0.91 0.99 0.95 15.7 28.5 2,844 6,557 107 Hadxaifong 99.1 98.2 80.9 53.6 41.5 93.3 63.6 75.1 0.92 0.99 1.07 12.6 29.6 1,073 3,101 108 Sangthong 98.1 94.2 83.6 51.3 20.0 98.7 60.1 31.4 0.98 0.99 0.88 10.7 36.6 349 1,422 109 Mayparkngum 98.7 95.8 86.8 57.6 23.9 99.5 66.1 39.1 0.93 0.99 0.99 9.3 32.5 487 2,053 200 Phongsaly 77.4 57.1 66.9 26.4 10.9 98.0 34.4 15.7 0.87 0.89 1.04 30.6 44.2 7,735 11,483 201 Phongsaly 76.2 65.3 62.6 30.2 16.7 86.8 38.8 29.2 0.88 0.99 1.07 33.8 41.8 989 1,215 202 May 87.8 63.6 75.1 23.7 8.9 118.2 35.0 11.2 0.89 0.71 1.07 24.2 37.5 997 1,639 203 Khua 87.4 67.9 70.5 27.1 9.8 108.9 34.7 13.9 0.87 0.98 1.38 26.1 35.7 980 1,339 204 Samphanh 73.6 55.7 59.2 17.1 9.7 94.2 23.8 13.5 0.88 0.70 0.81 39.1 43.4 1,559 1,501 205 Boonneua 75.6 57.3 71.3 36.0 13.6 92.3 44.5 19.1 0.88 0.94 0.91 23.3 46.8 665 1,457 206 Nhotou 65.7 41.5 63.6 24.7 8.2 84.5 31.4 11.2 0.83 0.92 1.07 35.1 59.7 1,479 2,868 207 Boontai 76.5 51.8 66.1 28.8 12.9 97.4 35.7 17.7 0.87 0.97 1.04 31.2 41.3 1,066 1,464 Lao PDR 2015 Census-Based Poverty Map – June 2016 101 Girl/Boy Ratio – Lower Girl/Boy Ratio – Upper Literacy Rate –15-25 year- old [3] Literacy Rate – 15-64 year- old [4] Net School Enrolment Rate – Primary [5] Net School Enrolment Rate – Lower Sec. [6] Net School Enrolment Rate – Upper Sec. [7] Net School Enrolment Rate – Primary [8] Net School Enrolment Rate – Lower Sec. [9] Net School Enrolment Rate – Upper Sec. [10] Girl/Boy Ratio – Primary [11] Secondary [12] Secondary [13] Proportion of Out-of-School 6-11 year-old Children [14] Proportion of Out-of-School 12-18 year-old Children [15] Number of Out-of-School 6-11 year-old Children [16] Number of Out-of-School 12-18 year-old Children [17] Code Province/District 300 Luangnamtha 82.5 58.5 72.2 37.9 18.7 98.3 48.5 28.4 0.92 0.88 0.89 25.6 36.7 6,120 9,278 301 Namtha 90.7 76.8 75.3 49.6 32.7 96.0 62.2 53.6 0.91 0.94 1.00 19.8 29.2 1,254 2,248 302 Sing 81.3 54.0 76.3 37.8 11.1 103.9 47.8 16.0 0.93 0.90 0.75 21.5 38.3 1,135 2,122 303 Long 65.2 30.6 64.0 18.6 6.9 96.1 24.5 9.1 0.89 0.68 0.75 36.2 50.5 1,887 2,614 304 Viengphoukha 80.7 53.6 68.3 41.4 18.0 94.1 56.1 24.4 0.89 0.88 0.80 29.6 32.7 1,102 1,215 305 Nalae 94.1 66.0 76.6 37.6 17.7 101.9 47.7 24.1 0.98 0.83 0.69 21.8 34.3 742 1,079 400 Oudomxay 87.5 66.5 74.7 38.0 18.4 104.5 51.1 27.5 0.94 0.92 0.86 22.6 33.9 9,995 16,672 401 Xay 93.5 78.6 78.7 47.6 27.2 103.1 63.4 43.8 0.98 0.97 0.88 17.7 29.8 1,817 3,620 402 La 78.5 56.7 66.1 35.5 18.9 86.8 44.2 26.2 0.83 0.97 1.08 31.6 45.7 674 1,147 403 Namor 86.8 61.5 80.2 32.2 13.5 111.9 43.1 19.8 0.94 0.89 0.76 17.6 37.3 1,010 2,244 404 Nga 83.9 58.5 70.6 23.6 9.2 108.0 34.7 13.2 0.94 0.99 0.88 27.3 37.4 1,313 1,762 405 Beng 93.6 78.6 78.1 53.2 22.8 100.1 67.3 31.8 0.94 0.92 0.89 15.8 28.5 788 1,784 406 Hoon 84.1 58.8 73.3 35.8 15.9 106.1 48.7 22.4 0.95 0.87 0.80 25.1 34.0 2,837 4,289 407 Pakbeng 81.5 55.5 67.5 23.6 10.5 104.0 36.1 15.3 0.93 0.88 0.72 31.3 37.7 1,556 1,826 500 Bokeo 86.0 67.0 72.6 37.1 16.7 98.2 49.5 26.2 0.95 0.91 0.79 24.5 37.3 6,053 9,378 501 Huoixai 90.7 77.6 73.4 43.1 25.1 98.3 58.0 40.3 0.93 0.89 0.82 23.1 32.2 2,058 3,303 502 Tonpheung 85.4 70.3 62.8 36.3 11.2 79.5 45.7 19.8 0.95 0.97 0.84 32.3 50.4 1,164 2,019 503 Meung 68.5 39.4 67.6 29.3 10.3 91.3 37.9 15.8 0.93 0.84 0.56 31.0 40.2 769 788 504 Phaoudom 83.9 57.3 75.9 30.7 10.9 108.2 43.0 14.6 0.97 0.95 0.76 22.3 36.4 1,505 2,283 505 Paktha 84.4 60.3 78.6 37.1 10.4 103.5 47.3 15.1 0.95 0.90 0.64 19.2 37.1 557 985 600 Luangprabang 93.9 79.8 81.9 45.4 22.9 108.9 57.4 37.5 0.94 0.89 0.74 15.2 29.4 8,945 19,383 601 Luangprabang 98.2 94.4 78.2 52.7 40.2 96.3 64.9 77.7 0.92 0.97 0.79 16.9 27.9 1,440 2,907 602 Xiengngeun 94.6 79.6 83.6 45.8 21.3 115.1 56.4 32.9 0.94 0.90 0.62 13.9 28.2 595 1,521 102 Lao PDR 2015 Census-Based Poverty Map – June 2016 Girl/Boy Ratio – Lower Girl/Boy Ratio – Upper Literacy Rate –15-25 year- old [3] Literacy Rate – 15-64 year- old [4] Net School Enrolment Rate – Primary [5] Net School Enrolment Rate – Lower Sec. [6] Net School Enrolment Rate – Upper Sec. [7] Net School Enrolment Rate – Primary [8] Net School Enrolment Rate – Lower Sec. [9] Net School Enrolment Rate – Upper Sec. [10] Girl/Boy Ratio – Primary [11] Secondary [12] Secondary [13] Proportion of Out-of-School 6-11 year-old Children [14] Proportion of Out-of-School 12-18 year-old Children [15] Number of Out-of-School 6-11 year-old Children [16] Number of Out-of-School 12-18 year-old Children [17] Code Province/District 603 Nan 95.0 81.0 81.4 48.9 21.7 104.6 59.5 33.2 0.96 0.94 0.80 14.1 30.5 509 1,344 604 Parkou 92.2 76.5 79.5 39.3 18.8 106.2 48.1 32.6 0.90 0.87 0.81 18.5 35.2 636 1,280 605 Nambak 89.5 71.6 79.5 46.2 20.7 106.0 57.7 30.9 0.93 0.96 0.86 17.7 32.8 1,573 3,664 606 Ngoi 94.0 77.3 82.4 40.7 15.0 114.2 52.5 21.6 0.99 0.85 0.61 15.2 29.4 668 1,379 607 Pakxeng 94.1 76.6 85.0 42.7 15.7 119.0 57.2 21.7 0.93 0.87 0.66 12.9 25.1 482 1,005 608 Phonxay 93.5 67.7 85.5 41.1 16.0 114.3 53.2 21.8 0.98 0.88 0.65 12.2 26.2 717 1,344 609 Chomphet 94.2 82.8 82.1 41.4 18.5 106.9 51.7 29.9 0.96 0.92 0.77 15.6 36.8 660 1,757 610 Viengkham 95.0 80.3 87.6 47.2 21.3 118.3 59.4 29.9 0.93 0.79 0.57 9.8 23.9 471 1,252 611 Phoukhoune 96.2 75.9 86.0 53.0 21.2 112.7 71.6 28.3 0.97 0.83 0.58 10.7 21.7 409 899 612 Phonthong 82.8 60.0 75.7 31.1 8.4 104.8 41.4 12.3 0.94 0.70 0.54 23.3 36.0 785 1,031 700 Huaphanh 92.4 78.5 78.3 43.2 25.1 115.1 61.2 34.5 0.92 0.84 0.72 19.5 24.1 8,229 13,000 701 Xamneua 92.9 82.9 79.0 47.9 30.4 107.6 64.6 45.1 0.92 0.84 0.82 17.5 24.5 1,347 2,410 702 Xiengkhor 90.8 76.7 75.3 35.7 22.5 121.8 56.2 28.2 0.89 0.75 0.80 23.8 26.4 798 1,225 703 Huim 96.9 81.3 85.4 60.6 32.3 112.2 77.9 39.6 1.02 0.98 0.89 12.3 17.5 218 383 704 Viengxay 96.4 88.2 80.5 54.9 36.6 113.5 72.0 48.9 0.94 0.91 0.74 15.6 19.7 573 1,176 705 Huameuang 94.8 79.5 83.5 35.4 17.0 124.3 48.8 24.4 0.93 0.91 0.71 15.5 28.0 821 1,737 706 Xamtay 94.4 78.1 81.3 40.1 22.1 124.9 61.2 30.9 0.98 0.82 0.55 17.7 19.8 1,081 1,475 707 Sopbao 87.8 76.9 75.6 44.4 27.3 108.6 63.8 35.8 0.83 0.84 0.63 22.8 27.0 767 1,246 708 Add 88.0 73.9 75.7 39.7 21.8 117.7 60.2 29.6 0.86 0.77 0.75 21.8 24.4 833 1,246 709 Kuane 89.1 64.5 75.1 35.0 13.8 112.8 53.4 20.3 0.91 0.73 0.57 23.5 26.8 1,076 1,264 710 Sone 92.2 71.0 68.3 44.1 24.4 99.5 60.4 30.8 0.95 0.87 0.78 27.4 26.0 715 838 800 Xayaboury 97.8 92.9 77.4 46.7 18.0 92.0 55.3 30.4 0.95 0.97 0.91 16.5 40.8 6,961 20,179 801 Xayabury 98.0 94.4 75.2 45.8 23.1 89.1 54.3 38.8 0.94 0.92 0.95 19.0 40.9 1,572 4,058 Lao PDR 2015 Census-Based Poverty Map – June 2016 103 Girl/Boy Ratio – Lower Girl/Boy Ratio – Upper Literacy Rate –15-25 year- old [3] Literacy Rate – 15-64 year- old [4] Net School Enrolment Rate – Primary [5] Net School Enrolment Rate – Lower Sec. [6] Net School Enrolment Rate – Upper Sec. [7] Net School Enrolment Rate – Primary [8] Net School Enrolment Rate – Lower Sec. [9] Net School Enrolment Rate – Upper Sec. [10] Girl/Boy Ratio – Primary [11] Secondary [12] Secondary [13] Proportion of Out-of-School 6-11 year-old Children [14] Proportion of Out-of-School 12-18 year-old Children [15] Number of Out-of-School 6-11 year-old Children [16] Number of Out-of-School 12-18 year-old Children [17] Code Province/District 802 Khop 98.6 91.7 79.5 44.6 13.9 99.5 53.8 24.3 1.01 1.00 0.70 16.5 37.6 378 979 803 Hongsa 97.2 89.4 68.2 45.9 16.4 79.8 57.4 29.1 0.96 0.91 0.70 24.3 44.4 782 1,655 804 Ngeun 97.3 88.7 80.6 48.3 13.5 99.7 54.5 22.4 1.01 1.03 0.98 16.7 36.8 343 837 805 Xienghone 98.0 88.8 77.9 42.1 11.5 93.0 49.8 20.2 0.94 1.01 0.82 17.2 45.9 648 1,958 806 Phiang 98.0 94.6 78.9 47.9 17.2 92.5 57.7 31.1 0.95 0.97 0.96 13.8 40.1 938 3,194 807 Parklai 99.0 96.8 81.1 49.6 20.0 94.8 57.3 31.5 0.90 0.98 0.98 12.9 40.5 909 3,568 808 Kenethao 98.5 94.6 78.3 52.5 18.5 89.3 61.5 31.3 0.94 0.96 1.04 14.0 38.9 529 1,783 809 Botene 99.0 97.9 69.2 57.3 27.0 79.8 64.0 42.6 0.95 1.26 0.79 23.5 32.3 339 559 810 Thongmyxay 99.0 94.8 87.2 71.2 34.6 92.1 82.5 59.4 1.01 1.04 0.90 3.9 17.9 31 176 811 Xaysathan 86.9 66.4 76.8 19.2 3.5 105.2 25.6 6.3 0.99 0.68 0.56 18.9 54.0 492 1,412 900 Xienkhuang 96.8 87.2 83.3 52.9 30.2 107.1 68.1 47.5 0.91 0.86 0.86 13.0 23.0 4,500 9,351 901 Pek 98.4 92.4 83.4 60.1 40.8 99.5 75.1 72.0 0.91 0.94 0.96 11.4 19.0 972 2,007 902 Kham 96.6 86.7 82.5 52.8 30.6 107.2 67.1 43.9 0.91 0.90 0.91 13.8 24.2 922 2,008 903 Nonghed 97.7 84.8 84.5 45.2 18.2 117.4 62.9 25.6 0.91 0.81 0.67 13.5 24.4 886 1,825 904 Khoune 95.0 82.8 81.8 50.2 25.4 105.2 64.4 39.5 0.88 0.78 0.74 14.4 27.4 719 1,562 905 Morkmay 88.4 65.2 83.4 46.4 16.1 112.0 61.2 25.1 0.91 0.80 0.52 14.5 22.3 402 589 906 Phoukoud 98.0 90.9 83.7 53.7 31.6 107.2 69.6 45.0 0.95 0.82 0.85 11.7 23.3 399 992 907 Phaxay 95.3 86.1 85.3 61.6 33.5 101.5 74.6 46.5 0.89 0.89 0.73 12.0 21.1 200 368 1000 Vientiane Pro 96.6 90.4 79.5 53.6 26.8 95.9 65.5 44.3 0.94 0.92 0.79 14.7 30.3 7,499 18,129 1001 Phonhong 97.6 93.6 80.3 58.4 34.2 91.3 71.4 58.0 0.91 0.97 0.88 11.1 26.2 796 2,197 1002 Thoulakhom 97.2 92.7 73.6 54.4 32.0 87.0 65.1 55.3 0.90 0.97 0.86 19.1 32.2 1,060 2,137 1003 Keooudom 98.8 96.4 80.6 58.1 37.9 91.9 68.6 69.2 1.05 0.94 0.97 10.9 26.4 178 569 1004 Kasy 95.1 81.7 79.7 52.0 19.1 97.6 62.3 29.7 1.00 0.93 0.73 16.3 32.1 903 1,818 104 Lao PDR 2015 Census-Based Poverty Map – June 2016 Girl/Boy Ratio – Lower Girl/Boy Ratio – Upper Literacy Rate –15-25 year- old [3] Literacy Rate – 15-64 year- old [4] Net School Enrolment Rate – Primary [5] Net School Enrolment Rate – Lower Sec. [6] Net School Enrolment Rate – Upper Sec. [7] Net School Enrolment Rate – Primary [8] Net School Enrolment Rate – Lower Sec. [9] Net School Enrolment Rate – Upper Sec. [10] Girl/Boy Ratio – Primary [11] Secondary [12] Secondary [13] Proportion of Out-of-School 6-11 year-old Children [14] Proportion of Out-of-School 12-18 year-old Children [15] Number of Out-of-School 6-11 year-old Children [16] Number of Out-of-School 12-18 year-old Children [17] Code Province/District 1005 Vangvieng 96.9 88.6 80.7 60.3 31.4 98.5 76.0 50.0 0.91 0.90 0.76 12.9 22.7 875 1,877 1006 Feuang 97.0 89.5 77.9 52.3 24.0 95.1 65.8 38.7 0.96 0.83 0.68 15.8 31.6 887 2,107 1007 Xanakharm 97.5 95.3 84.2 51.4 13.0 95.5 59.2 25.8 0.94 1.04 0.88 11.2 39.9 496 2,011 1008 Mad 95.1 87.6 84.1 46.7 22.0 107.7 57.1 33.1 0.96 0.87 0.62 9.8 31.0 282 1,074 1009 viengkham 99.4 97.7 80.5 59.5 59.4 88.9 68.4 101.5 0.95 0.92 0.84 12.6 19.2 205 408 1010 Hinherb 98.0 92.2 78.2 51.1 25.0 102.0 63.2 36.8 0.90 0.92 0.82 18.7 29.3 687 1,351 1013 Meun 92.3 78.1 78.4 44.4 13.6 99.6 56.8 20.6 0.95 0.85 0.55 18.0 38.1 1,130 2,580 1100 Borikhamxay 95.6 88.0 80.0 47.0 20.3 101.3 57.9 32.1 0.94 0.92 0.86 15.4 35.1 5,526 15,048 1101 Pakxane 98.8 97.3 77.2 56.9 38.0 88.0 66.8 65.2 1.01 0.93 1.05 14.7 29.3 656 1,720 1102 Thaphabath 99.4 98.4 84.0 61.1 23.7 92.0 72.0 40.8 0.98 1.01 0.87 8.7 32.1 233 980 1103 Pakkading 98.6 94.7 80.8 45.3 15.6 96.7 53.9 23.0 0.96 0.90 0.76 14.8 45.9 886 3,453 1104 Bolikhanh 93.7 85.3 78.0 46.8 19.2 96.4 58.2 31.8 0.88 0.90 0.68 15.9 35.7 1,107 2,745 1105 Khamkeuth 94.8 79.3 81.2 47.9 19.1 110.0 61.2 28.2 0.94 0.96 0.90 15.6 30.6 1,403 3,666 1106 Viengthong 89.1 71.3 77.7 32.9 12.7 106.7 42.0 18.6 0.92 0.84 0.79 20.2 39.5 961 1,940 1107 Xaychamphone 91.8 75.8 84.9 32.8 10.2 121.9 44.5 13.5 0.94 0.73 0.49 14.1 28.9 280 544 1200 Khammuane 93.8 83.5 73.5 36.1 16.0 101.6 44.7 25.7 0.93 1.00 0.97 21.9 42.4 10,714 27,277 1201 Thakhek 96.5 91.8 68.5 44.4 26.5 87.8 55.1 45.8 0.89 1.03 1.10 22.7 38.8 2,091 5,363 1202 Mahaxay 91.8 71.9 80.8 31.3 11.0 113.8 38.9 16.9 0.97 1.09 0.89 15.7 44.8 791 2,991 1203 Nongbok 98.2 92.7 72.4 48.2 17.6 82.9 56.9 30.4 0.87 0.96 0.98 19.1 46.0 889 3,245 1204 Hinboon 96.6 87.4 80.7 35.1 12.4 107.1 42.9 19.1 0.91 1.00 0.76 15.9 45.9 911 3,297 1205 Nhommalath 86.2 67.8 70.5 30.0 11.7 108.6 38.6 15.9 1.04 1.02 0.83 27.4 40.9 1,263 2,362 1206 Bualapha 92.8 75.7 63.4 25.4 7.4 96.8 32.2 10.3 0.89 0.99 0.80 35.7 44.7 1,907 2,492 1207 Nakai 85.9 65.9 68.9 23.6 8.0 115.7 30.1 11.6 0.90 0.97 0.87 29.9 40.9 1,120 1,949 Lao PDR 2015 Census-Based Poverty Map – June 2016 105 Girl/Boy Ratio – Lower Girl/Boy Ratio – Upper Literacy Rate –15-25 year- old [3] Literacy Rate – 15-64 year- old [4] Net School Enrolment Rate – Primary [5] Net School Enrolment Rate – Lower Sec. [6] Net School Enrolment Rate – Upper Sec. [7] Net School Enrolment Rate – Primary [8] Net School Enrolment Rate – Lower Sec. [9] Net School Enrolment Rate – Upper Sec. [10] Girl/Boy Ratio – Primary [11] Secondary [12] Secondary [13] Proportion of Out-of-School 6-11 year-old Children [14] Proportion of Out-of-School 12-18 year-old Children [15] Number of Out-of-School 6-11 year-old Children [16] Number of Out-of-School 12-18 year-old Children [17] Code Province/District 1208 Xebangfay 90.6 82.3 72.0 39.6 18.6 90.6 47.7 29.9 0.99 0.98 1.07 20.4 45.2 726 2,181 1209 Xaybuathong 91.4 75.7 83.3 31.1 9.4 113.9 39.1 12.5 0.98 0.87 0.60 14.1 42.2 619 2,015 1210 Khounkham 97.2 91.9 82.1 39.4 18.3 119.7 50.1 26.1 0.91 1.00 0.96 15.3 35.1 397 1,382 1300 Savanakhet 85.5 77.1 68.3 33.3 15.0 94.4 42.6 24.3 0.92 1.01 1.04 28.4 46.4 34,029 68,823 1301 KaysonePhomvihane 98.3 95.9 74.1 52.4 37.4 89.9 65.9 70.5 0.95 1.00 1.17 18.5 32.8 1,996 5,082 1302 Outhoomphone 90.5 81.1 68.3 34.4 13.3 98.3 44.1 20.1 0.96 1.06 0.99 27.3 46.6 2,663 6,596 1303 Atsaphangthong 87.5 75.4 75.5 40.3 19.4 102.3 52.2 29.9 0.96 1.05 1.06 19.9 39.9 1,123 3,050 1304 Phine 57.4 47.6 53.1 17.3 6.2 75.7 22.2 9.6 0.90 0.92 0.84 45.5 62.3 4,688 6,232 1305 Sepone 57.6 40.2 51.6 16.7 8.7 78.9 23.0 12.1 0.80 0.90 0.87 47.6 50.4 4,489 3,945 1306 Nong 43.5 25.5 48.6 8.3 3.6 79.4 14.1 5.5 0.68 0.67 0.61 51.1 52.5 2,694 2,114 1307 Thapangthong 72.5 59.7 65.9 17.6 4.9 93.5 23.3 7.1 0.88 0.90 1.04 32.7 59.6 2,097 4,171 1308 Songkhone 98.5 95.2 79.7 34.0 10.5 100.6 41.2 17.3 0.94 1.07 1.04 16.5 54.0 1,771 7,654 1309 Champhone 94.8 87.2 77.8 41.4 13.6 105.3 52.5 21.3 0.94 1.02 1.07 17.8 41.9 2,130 7,538 1310 Xonbuly 75.8 64.0 67.4 27.1 9.8 98.8 35.5 13.8 0.95 0.99 0.95 30.3 49.0 2,715 5,320 1311 Xaybuly 95.7 87.2 77.9 40.3 15.4 101.5 49.4 23.1 0.92 1.12 1.00 17.1 44.1 1,108 4,058 1312 Vilabuly 78.1 59.0 66.9 30.5 11.1 102.9 41.9 14.6 0.91 0.94 0.78 31.7 36.0 1,783 2,190 1313 Atsaphone 87.6 73.0 74.6 36.9 15.9 104.4 47.6 21.7 0.94 1.04 0.91 22.1 41.3 1,848 4,453 1314 Xayphoothong 98.5 93.2 81.2 50.2 17.6 98.5 61.3 28.4 1.00 0.99 0.97 12.8 39.0 563 2,483 1315 Phalanxay 69.5 57.8 57.4 17.9 6.2 86.1 25.7 9.5 0.92 1.00 0.79 41.2 57.6 2,361 3,937 1400 Saravane 86.7 77.5 69.4 25.7 10.4 99.4 33.2 15.9 0.92 0.94 0.90 27.6 50.6 15,311 33,738 1401 Saravane 84.1 76.7 63.7 26.4 12.9 95.8 34.8 20.5 0.94 0.98 0.98 32.6 50.4 4,357 8,952 1402 Ta oi 67.5 45.4 60.3 11.5 3.4 96.5 18.8 5.1 0.83 0.64 0.33 39.8 46.0 2,319 2,258 1403 Toomlarn 57.0 43.4 52.0 12.8 4.1 80.8 19.3 6.1 0.77 0.45 0.54 46.0 59.5 2,418 3,092 106 Lao PDR 2015 Census-Based Poverty Map – June 2016 Girl/Boy Ratio – Lower Girl/Boy Ratio – Upper Literacy Rate –15-25 year- old [3] Literacy Rate – 15-64 year- old [4] Net School Enrolment Rate – Primary [5] Net School Enrolment Rate – Lower Sec. [6] Net School Enrolment Rate – Upper Sec. [7] Net School Enrolment Rate – Primary [8] Net School Enrolment Rate – Lower Sec. [9] Net School Enrolment Rate – Upper Sec. [10] Girl/Boy Ratio – Primary [11] Secondary [12] Secondary [13] Proportion of Out-of-School 6-11 year-old Children [14] Proportion of Out-of-School 12-18 year-old Children [15] Number of Out-of-School 6-11 year-old Children [16] Number of Out-of-School 12-18 year-old Children [17] Code Province/District 1404 Lakhonepheng 96.3 91.6 75.7 27.5 7.7 99.1 33.6 11.6 0.96 0.87 0.64 19.8 59.2 1,064 4,265 1405 Vapy 95.0 87.8 76.0 35.8 14.7 99.7 43.5 22.0 0.97 0.96 0.99 18.5 47.5 854 2,985 1406 Khongxedone 94.5 89.7 75.2 32.3 14.2 98.3 39.1 21.8 0.94 1.01 0.92 21.2 51.3 1,539 4,897 1407 Lao ngarm 92.1 81.5 79.7 26.2 9.4 111.3 32.7 13.3 0.97 1.15 0.99 18.2 49.8 1,935 6,574 1408 Samuoi 75.1 42.1 71.2 20.5 5.1 114.2 33.5 8.3 0.87 0.75 0.85 26.9 27.9 825 715 1500 Sekong 90.9 72.3 71.3 31.4 15.9 107.5 46.1 23.4 0.97 0.90 0.92 26.7 31.2 4,965 5,960 1501 Lamarm 92.7 80.6 74.6 47.2 27.6 98.6 64.5 42.3 0.93 0.86 0.96 21.8 27.8 1,101 1,560 1502 Kaleum 83.5 61.9 66.8 8.8 4.1 112.0 18.0 5.7 0.97 0.71 0.52 31.7 35.1 963 874 1503 Dakcheung 92.6 72.2 69.2 22.1 10.9 110.8 37.3 14.8 0.98 0.88 0.83 31.1 28.3 1,319 1,041 1504 Thateng 91.0 68.3 72.3 32.2 12.7 110.2 46.5 17.9 0.98 0.99 0.93 25.1 33.8 1,582 2,485 1600 Champasack 94.9 91.2 77.0 34.9 18.1 100.4 41.6 30.3 0.94 0.98 0.92 18.7 47.5 15,062 51,842 1601 Pakse 99.1 98.1 85.7 55.1 46.9 101.9 65.8 84.6 0.89 0.97 0.97 7.6 24.1 529 2,378 1602 Sanasomboon 92.2 87.0 67.9 32.3 16.3 90.0 39.3 27.6 1.01 1.04 0.92 26.2 53.2 1,869 5,677 1603 Bachiangchaleunsook 92.2 86.9 72.1 30.9 17.5 99.3 38.1 29.4 0.96 0.98 0.90 23.8 48.5 1,657 4,672 1604 Paksxong 91.4 84.6 76.3 35.8 17.5 106.8 44.6 27.2 0.95 1.03 0.99 21.0 40.0 2,254 5,531 1605 Pathoomphone 93.7 88.2 73.6 30.6 12.2 97.5 36.3 18.5 0.95 1.00 0.98 22.2 52.7 1,642 5,244 1606 Phonthong 98.2 96.3 79.5 36.3 17.0 96.1 42.6 28.2 0.94 0.96 0.86 16.2 52.5 1,543 6,947 1607 Champasack 96.3 93.3 82.1 33.1 14.6 107.1 38.2 24.4 0.88 1.01 0.89 14.1 50.8 978 5,265 1608 Sukhuma 92.0 86.4 73.8 28.8 9.9 95.4 33.1 15.2 0.91 0.97 0.75 21.6 56.4 1,632 5,432 1609 Moonlapamok 93.9 88.1 79.2 30.0 8.0 104.6 34.8 12.3 0.96 0.90 0.84 18.4 52.9 947 3,422 1610 Khong 97.4 94.8 79.2 34.4 14.7 103.2 40.7 25.2 0.97 0.95 0.94 16.5 46.9 2,011 7,274 1700 Attapeu 87.6 76.2 70.1 31.3 14.9 106.2 41.6 22.1 0.95 0.96 0.86 27.6 37.6 5,369 8,816 1701 Xaysetha 81.7 71.4 68.2 31.3 13.8 107.8 39.9 20.3 0.93 1.04 0.81 30.5 41.5 1,226 2,453 Lao PDR 2015 Census-Based Poverty Map – June 2016 107 Girl/Boy Ratio – Lower Girl/Boy Ratio – Upper Literacy Rate –15-25 year- old [3] Literacy Rate – 15-64 year- old [4] Net School Enrolment Rate – Primary [5] Net School Enrolment Rate – Lower Sec. [6] Net School Enrolment Rate – Upper Sec. [7] Net School Enrolment Rate – Primary [8] Net School Enrolment Rate – Lower Sec. [9] Net School Enrolment Rate – Upper Sec. [10] Girl/Boy Ratio – Primary [11] Secondary [12] Secondary [13] Proportion of Out-of-School 6-11 year-old Children [14] Proportion of Out-of-School 12-18 year-old Children [15] Number of Out-of-School 6-11 year-old Children [16] Number of Out-of-School 12-18 year-old Children [17] Code Province/District 1702 Samakkhixay 95.5 90.2 79.3 47.6 27.5 107.6 60.6 43.1 0.93 0.93 0.94 16.8 26.7 754 1,543 1703 Sanamxay 92.2 77.3 75.6 27.4 10.3 116.3 38.0 13.5 0.96 0.99 0.84 23.7 37.1 1,229 2,194 1704 Sanxay 84.5 64.3 58.7 20.2 8.1 92.5 29.0 11.8 0.96 0.89 0.59 36.2 43.7 1,343 1,538 1705 Phouvong 75.7 64.2 59.9 18.5 6.7 99.5 28.6 10.0 0.97 0.86 0.79 39.9 46.8 817 1,088 1800 Xaysomboune 93.7 74.4 80.9 52.2 24.3 105.5 65.5 33.9 0.91 0.89 0.68 16.8 23.6 2,148 3,309 1801 Anouvong 94.3 74.4 84.4 53.1 27.4 111.6 68.0 37.7 0.99 0.93 0.64 13.1 17.9 459 656 1802 Thathom 94.9 80.4 82.5 49.5 24.0 109.7 60.6 34.4 0.87 0.82 0.76 15.6 27.8 434 978 1803 Longcheng 91.2 73.3 78.7 36.9 8.9 107.1 47.6 11.7 0.94 0.76 0.65 20.4 30.9 222 291 1804 Home 91.3 62.6 78.0 56.6 24.9 99.9 70.7 31.8 0.84 0.79 0.46 20.0 21.9 369 424 1805 Longsane 93.6 74.1 78.6 55.3 25.2 98.8 69.6 36.1 0.88 0.98 0.76 18.5 24.3 664 960 Source: Authors’ calculations based on 2015 Lao PDR Census Note: The provinces are shown in bold, while the associated districts are listed below their respective province. 108 Lao PDR 2015 Census-Based Poverty Map – June 2016 Appendix 10: Non-Monetary Indicators (Others), by Province and District Employment Rate [18] Self-employment [19] Youth Unemployment Rate [20] Unemployment Rate [21] Proportion of Non-Agric. Wage Earner [22] Proportion of Non-Agric. Own-Account Worker [22] Dependency Rate [24] Female in Wage Emp. Non Agric. [25] Proportion of Married 17-year-old Girls Improved Sanitation [27] Improved Water Source [28] Not Using Firewood [29] Using Electricity [30] Have a Phone [31] Code Province/District 100 Vientiane Capital 68.8 53.4 9.9 2.7 46.2 27.6 29.0 38.6 8.2 97.6 97.2 70.9 98.3 98.2 101 Chanthabuly 64.4 40.5 9.9 2.2 59.4 40.2 25.2 41.1 2.8 98.3 98.7 93.1 97.4 98.5 102 Sikhottabong 64.8 45.6 13.1 3.6 54.0 41.8 28.0 39.3 4.4 98.5 98.4 78.2 98.7 98.7 103 Xaysetha 63.9 40.2 13.1 3.1 59.5 32.2 27.1 39.5 6.8 97.8 97.9 86.9 98.0 98.1 104 Sisattanak 60.8 33.6 15.2 3.4 65.9 33.4 25.8 41.4 3.2 96.9 97.8 93.7 97.1 97.7 105 Naxaithong 76.4 60.5 7.3 2.3 39.0 24.6 31.7 34.7 12.0 97.8 97.4 44.2 98.9 98.4 106 Xaythany 66.1 52.5 11.5 3.2 46.8 23.5 30.4 37.4 8.7 97.0 96.6 51.9 98.3 98.3 107 Hadxaifong 72.7 56.3 9.1 2.4 43.2 24.0 28.0 37.1 10.8 98.1 98.3 88.0 98.8 98.0 108 Sangthong 89.9 91.9 1.2 0.3 7.5 4.7 33.6 33.4 20.7 97.6 90.3 25.3 98.7 97.6 109 Mayparkngum 86.9 89.4 1.6 0.5 10.1 8.6 34.0 36.0 14.9 95.6 94.3 65.5 98.8 97.5 200 Phongsaly 87.0 90.6 1.8 0.5 9.1 5.1 40.9 42.0 24.8 40.6 80.7 2.7 57.6 84.3 201 Phongsaly 87.2 77.1 2.7 0.5 22.7 8.6 40.1 45.3 13.8 40.0 81.6 9.8 54.4 76.4 202 May 85.5 92.2 2.1 0.5 7.7 3.4 42.3 32.7 22.1 36.7 76.3 1.1 34.0 83.6 203 Khua 86.0 92.4 2.4 0.7 7.4 7.9 39.9 36.5 19.2 46.7 88.3 1.1 66.5 86.1 204 Samphanh 87.5 92.6 1.2 0.2 7.3 3.8 45.7 34.9 26.0 21.8 80.8 0.9 46.3 81.2 205 Boonneua 86.3 88.4 3.7 0.5 11.1 4.8 39.1 46.9 34.1 47.2 89.0 5.3 77.8 88.4 206 Nhotou 89.4 95.2 0.5 0.6 4.5 3.7 38.3 45.2 31.9 47.8 70.1 1.0 56.3 88.2 207 Boontai 86.7 93.6 1.1 0.3 6.3 4.3 41.5 46.6 23.7 41.8 82.6 1.3 71.4 84.5 Lao PDR 2015 Census-Based Poverty Map – June 2016 109 Employment Rate [18] Self-employment [19] Youth Unemployment Rate [20] Unemployment Rate [21] Proportion of Non-Agric. Wage Earner [22] Proportion of Non-Agric. Own-Account Worker [22] Dependency Rate [24] Female in Wage Emp. Non Agric. [25] Proportion of Married 17-year-old Girls Improved Sanitation [27] Improved Water Source [28] Not Using Firewood [29] Using Electricity [30] Have a Phone [31] Code Province/District 300 Luangnamtha 85.1 88.8 2.9 0.7 10.4 6.7 38.8 35.9 19.8 70.4 94.7 2.7 86.5 89.9 301 Namtha 80.4 80.7 7.5 1.1 19.1 9.2 36.2 38.2 17.1 87.5 97.1 4.8 90.9 94.2 302 Sing 86.3 91.2 1.3 0.8 6.3 7.0 38.3 33.9 22.2 75.7 93.7 3.5 91.5 90.9 303 Long 91.6 95.0 0.2 0.1 4.9 3.9 40.9 31.5 33.2 44.3 96.0 1.2 80.6 89.9 304 Viengphoukha 83.3 90.9 1.3 0.3 8.7 4.7 41.1 31.1 13.1 67.3 88.2 1.0 83.2 82.8 305 Nalae 87.0 91.8 2.9 0.4 7.9 6.7 39.9 35.0 12.6 64.5 95.2 0.8 79.9 85.8 400 Oudomxay 82.4 90.1 3.4 0.9 9.5 6.6 40.3 31.5 20.9 59.0 86.3 2.9 71.7 86.4 401 Xay 76.7 81.8 6.8 1.7 17.8 13.1 37.6 33.8 16.9 76.8 92.1 7.3 83.7 92.4 402 La 85.7 91.4 2.5 0.5 8.5 3.3 37.1 30.9 24.3 62.1 92.3 2.6 75.0 93.1 403 Namor 85.7 94.0 2.2 0.4 5.9 4.5 40.8 28.1 26.7 57.7 85.9 1.1 71.5 88.4 404 Nga 84.7 93.9 1.7 0.5 5.9 4.4 43.6 32.0 23.0 44.4 88.8 0.7 58.3 80.9 405 Beng 83.9 92.2 2.5 0.7 6.6 3.8 38.0 31.7 17.8 66.2 80.4 1.2 88.0 89.2 406 Hoon 84.0 92.9 2.8 0.6 6.9 4.6 41.8 27.5 23.1 50.6 85.0 1.5 66.1 83.0 407 Pakbeng 83.8 92.2 2.8 1.1 7.3 6.2 43.9 29.9 19.0 39.9 75.9 2.4 45.4 75.2 500 Bokeo 83.3 84.7 3.9 1.2 13.0 9.0 38.8 35.1 24.3 80.4 91.6 8.9 90.2 87.8 501 Huoixai 77.5 80.2 8.2 2.0 18.7 14.5 37.4 33.2 17.5 86.2 92.6 11.5 96.7 93.0 502 Tonpheung 87.4 74.9 2.6 1.2 17.1 7.6 33.8 39.2 36.2 89.5 94.0 17.6 95.8 88.1 503 Meung 88.7 92.6 1.2 0.4 7.0 3.7 42.6 34.5 36.7 65.7 94.5 3.0 93.4 84.9 504 Phaoudom 86.5 94.7 1.0 0.5 5.0 4.5 43.1 32.7 23.2 69.8 85.7 2.5 73.8 79.3 505 Paktha 87.1 93.7 1.0 0.2 6.0 5.6 40.9 36.2 28.1 77.2 94.8 2.3 89.2 88.7 600 Luangprabang 80.6 85.6 4.5 1.1 14.2 12.9 39.5 36.1 19.6 69.8 91.8 4.9 72.6 89.7 601 Luangprabang 72.0 60.7 11.7 2.6 38.8 35.8 32.4 39.0 13.3 89.7 96.4 17.4 97.4 97.2 602 Xiengngeun 82.1 88.7 3.2 0.8 10.9 10.0 39.6 36.2 16.7 77.2 96.6 2.9 92.5 92.7 110 Lao PDR 2015 Census-Based Poverty Map – June 2016 Employment Rate [18] Self-employment [19] Youth Unemployment Rate [20] Unemployment Rate [21] Proportion of Non-Agric. Wage Earner [22] Proportion of Non-Agric. Own-Account Worker [22] Dependency Rate [24] Female in Wage Emp. Non Agric. [25] Proportion of Married 17-year-old Girls Improved Sanitation [27] Improved Water Source [28] Not Using Firewood [29] Using Electricity [30] Have a Phone [31] Code Province/District 603 Nan 85.7 90.7 1.2 0.3 9.1 6.3 36.4 34.2 13.8 83.9 94.9 3.2 82.3 92.0 604 Parkou 84.8 91.1 5.2 1.4 8.7 10.6 39.0 36.4 27.0 72.8 95.0 1.0 79.9 87.6 605 Nambak 83.3 92.8 3.0 0.6 7.1 6.9 38.7 30.5 20.5 74.0 90.0 1.7 80.9 92.2 606 Ngoi 82.1 93.3 4.0 0.9 6.6 7.2 41.5 32.5 23.0 52.9 88.6 2.6 67.5 86.1 607 Pakxeng 82.1 93.3 1.6 0.3 6.5 7.0 42.9 32.9 16.0 54.2 94.9 0.8 50.5 81.6 608 Phonxay 83.8 93.1 3.8 0.6 6.7 5.3 46.2 27.6 26.4 69.8 89.0 0.5 47.6 81.2 609 Chomphet 85.4 90.5 2.0 0.6 9.4 7.8 39.2 37.0 24.5 51.0 88.8 2.4 64.7 85.8 610 Viengkham 79.3 92.3 4.6 0.9 7.5 6.3 43.7 31.4 16.4 47.3 88.6 0.7 34.7 84.6 611 Phoukhoune 77.9 88.1 5.3 0.6 11.7 7.8 45.9 27.4 20.8 61.4 96.7 2.2 66.4 92.1 612 Phonthong 87.0 93.5 0.6 0.2 6.3 4.0 46.9 29.4 29.6 47.8 70.1 1.0 29.5 82.4 700 Huaphanh 77.7 90.5 4.3 0.7 9.4 5.3 41.4 33.4 21.3 71.9 93.8 2.0 79.2 93.6 701 Xamneua 75.5 81.7 7.8 1.0 18.2 11.0 40.0 35.9 21.4 69.3 95.5 5.9 82.0 96.0 702 Xiengkhor 78.3 92.2 4.4 0.6 7.6 2.1 38.7 33.4 27.3 78.7 96.5 0.9 87.2 95.3 703 Huim 76.7 86.5 11.4 1.2 13.2 6.0 38.8 32.0 10.8 69.3 99.7 1.3 95.9 91.4 704 Viengxay 76.7 90.2 4.5 0.6 9.6 5.3 37.3 35.8 12.8 84.6 96.7 1.2 84.4 95.3 705 Huameuang 82.3 94.6 2.5 0.3 5.3 4.1 43.4 29.4 23.0 74.4 99.7 0.6 66.4 91.0 706 Xamtay 76.2 93.0 3.2 0.8 6.9 6.3 44.1 29.1 22.9 65.1 94.4 2.0 77.5 95.2 707 Sopbao 78.6 93.5 2.7 0.3 6.5 3.0 39.7 34.4 20.8 79.1 88.4 1.3 90.6 94.4 708 Add 77.9 93.0 3.0 0.4 6.8 2.4 40.1 33.8 20.9 84.5 93.1 1.0 78.3 93.4 709 Kuane 79.6 94.1 1.8 0.4 5.8 2.3 47.7 24.9 27.4 47.5 92.6 0.4 64.1 87.7 710 Sone 77.8 93.0 2.3 0.8 6.9 2.5 44.8 29.4 21.1 62.9 72.2 0.6 70.6 90.3 800 Xayaboury 87.1 88.1 1.5 0.4 11.6 6.5 34.0 33.1 24.5 89.7 86.7 10.7 90.1 93.0 801 Xayabury 82.3 78.3 2.1 0.7 21.5 11.2 34.5 33.6 21.7 88.1 88.9 6.2 89.9 94.7 Lao PDR 2015 Census-Based Poverty Map – June 2016 111 Employment Rate [18] Self-employment [19] Youth Unemployment Rate [20] Unemployment Rate [21] Proportion of Non-Agric. Wage Earner [22] Proportion of Non-Agric. Own-Account Worker [22] Dependency Rate [24] Female in Wage Emp. Non Agric. [25] Proportion of Married 17-year-old Girls Improved Sanitation [27] Improved Water Source [28] Not Using Firewood [29] Using Electricity [30] Have a Phone [31] Code Province/District 802 Khop 85.8 92.8 2.8 0.7 7.1 5.3 34.0 25.2 40.4 91.8 97.1 3.2 96.7 95.8 803 Hongsa 85.6 79.9 2.7 0.9 19.6 8.6 34.5 31.4 25.6 83.6 96.2 4.1 83.4 92.8 804 Ngeun 89.8 89.7 0.8 0.2 10.3 10.2 36.0 32.1 29.8 94.4 96.3 2.7 83.3 93.2 805 Xienghone 89.2 91.1 1.4 0.5 8.8 3.4 33.5 35.1 30.9 92.8 96.1 1.6 84.1 90.2 806 Phiang 88.4 92.2 1.6 0.5 7.5 4.2 35.4 34.4 24.1 83.1 82.9 2.5 95.0 94.1 807 Parklai 87.6 90.7 0.9 0.3 9.1 6.7 32.6 31.9 20.8 96.4 76.8 15.9 93.4 93.9 808 Kenethao 89.7 93.1 0.5 0.1 6.4 3.7 31.4 33.9 23.8 97.6 76.1 18.9 98.6 96.0 809 Botene 89.0 86.0 2.1 0.3 13.7 7.8 31.4 35.3 23.4 96.7 88.0 71.2 98.1 98.2 810 Thongmyxay 87.2 86.0 1.5 0.3 13.7 3.9 30.1 33.5 18.1 97.4 88.4 8.4 98.8 97.7 811 Xaysathan 91.6 94.5 0.9 0.5 5.4 2.2 41.4 35.0 21.0 53.7 99.2 0.5 45.9 63.5 900 Xienkhuang 78.6 86.0 6.3 1.1 13.8 9.6 41.3 34.5 18.2 81.5 91.0 3.5 86.0 96.0 901 Pek 74.9 73.8 12.0 2.1 25.9 19.9 36.9 35.2 13.0 94.1 92.4 8.5 96.5 98.5 902 Kham 80.5 92.7 4.1 0.7 7.1 6.7 39.8 40.9 17.8 80.2 91.2 1.5 89.2 95.5 903 Nonghed 79.6 92.9 1.7 0.4 7.1 3.6 47.5 26.5 24.9 55.4 90.8 1.3 74.2 91.8 904 Khoune 79.3 90.5 7.2 0.9 9.3 7.0 42.8 32.6 24.1 80.5 95.8 2.1 86.3 96.8 905 Morkmay 81.6 88.2 1.4 0.6 11.7 4.2 50.5 25.7 21.9 84.7 96.3 0.5 42.0 94.1 906 Phoukoud 81.3 91.4 4.3 0.6 8.6 2.6 39.1 36.4 13.8 84.3 74.7 0.8 88.8 95.7 907 Phaxay 82.0 87.6 7.2 0.8 12.3 3.7 42.8 33.6 13.5 85.5 97.8 0.7 94.1 96.3 1000 Vientiane Pro 79.3 84.2 6.8 1.3 15.5 11.5 36.6 33.7 17.0 91.9 90.0 9.5 98.1 96.7 1001 Phonhong 76.3 73.5 9.8 1.9 26.1 21.4 35.0 33.2 15.1 98.1 97.2 16.9 98.8 98.8 1002 Thoulakhom 79.8 79.9 5.6 1.2 19.5 12.6 33.4 40.9 13.9 94.0 92.4 14.2 97.7 97.2 1003 Keooudom 74.7 66.0 9.5 1.8 33.6 25.2 32.2 37.2 4.2 98.7 94.0 13.0 98.2 98.5 1004 Kasy 85.0 93.4 3.2 0.4 6.3 3.9 40.7 27.8 17.7 72.9 88.6 1.7 98.3 92.5 112 Lao PDR 2015 Census-Based Poverty Map – June 2016 Employment Rate [18] Self-employment [19] Youth Unemployment Rate [20] Unemployment Rate [21] Proportion of Non-Agric. Wage Earner [22] Proportion of Non-Agric. Own-Account Worker [22] Dependency Rate [24] Female in Wage Emp. Non Agric. [25] Proportion of Married 17-year-old Girls Improved Sanitation [27] Improved Water Source [28] Not Using Firewood [29] Using Electricity [30] Have a Phone [31] Code Province/District 1005 Vangvieng 67.7 76.4 17.4 2.8 23.4 21.8 37.9 27.0 12.2 95.6 93.4 11.9 98.6 97.4 1006 Feuang 81.8 91.8 10.5 1.3 7.7 5.6 38.3 29.5 11.9 90.6 78.4 1.8 98.4 97.4 1007 Xanakharm 90.7 95.0 0.6 0.2 5.0 4.6 33.0 37.1 27.1 96.4 88.1 14.7 98.0 96.7 1008 Mad 72.9 92.2 4.9 0.6 7.6 3.6 37.5 28.9 21.5 86.7 90.4 1.5 97.1 94.6 1009 viengkham 71.8 62.5 15.8 2.4 37.2 14.8 30.9 40.1 6.0 98.9 98.4 18.0 99.1 98.5 1010 Hinherb 84.3 89.8 2.0 0.4 10.0 6.6 37.1 25.5 13.2 89.0 94.1 2.8 97.8 95.1 1013 Meun 85.0 95.4 2.0 0.7 4.2 4.4 43.4 30.1 34.8 88.0 77.7 2.5 97.0 95.9 1100 Borikhamxay 82.0 88.4 5.0 1.0 11.3 10.2 38.6 33.5 21.1 91.9 89.7 22.6 92.9 94.6 1101 Pakxane 78.4 73.8 4.9 1.0 25.9 16.2 32.4 35.3 9.1 98.3 96.6 60.7 98.1 97.9 1102 Thaphabath 85.8 88.0 3.7 0.6 11.3 8.5 34.1 36.3 15.6 99.1 94.8 43.1 99.2 98.3 1103 Pakkading 87.3 95.1 3.2 1.0 4.6 8.3 35.3 35.6 17.2 95.1 80.6 19.9 98.7 97.2 1104 Bolikhanh 82.1 89.6 4.2 1.0 10.1 7.7 41.7 31.6 22.5 88.5 86.1 8.1 95.7 95.4 1105 Khamkeuth 76.4 91.0 10.0 1.6 8.9 13.3 40.7 31.0 23.6 91.4 90.3 13.9 97.9 96.7 1106 Viengthong 85.7 91.8 2.0 0.5 7.9 5.5 44.4 27.3 31.5 80.1 91.5 2.3 79.7 90.1 1107 Xaychamphone 84.7 90.4 0.9 0.3 9.5 4.2 47.3 30.2 33.6 85.5 99.4 0.4 25.9 56.2 1200 Khammuane 83.5 87.8 3.3 1.1 11.7 9.7 37.0 37.3 18.6 65.5 72.2 24.1 89.7 87.4 1201 Thakhek 72.8 74.7 9.8 2.8 24.5 20.5 32.2 37.4 12.1 83.4 83.4 50.1 97.7 94.3 1202 Mahaxay 87.1 90.4 1.1 0.3 9.3 5.1 39.4 30.2 22.0 61.3 61.9 16.7 95.2 87.9 1203 Nongbok 89.5 91.3 1.0 0.3 8.0 4.7 31.2 46.0 15.8 92.6 86.6 22.1 98.0 95.9 1204 Hinboon 86.4 87.4 3.7 1.1 12.1 9.2 35.6 43.2 19.3 72.2 72.5 29.0 97.6 91.6 1205 Nhommalath 85.9 90.3 1.6 0.5 9.3 6.9 40.6 31.9 14.0 34.8 66.4 16.0 95.1 82.7 1206 Bualapha 88.6 94.6 0.5 0.2 5.2 5.2 45.6 30.3 26.3 37.5 51.3 2.9 61.1 67.1 1207 Nakai 85.8 94.5 1.6 0.5 5.5 11.5 42.0 31.6 33.2 48.4 69.1 11.7 70.6 65.3 Lao PDR 2015 Census-Based Poverty Map – June 2016 113 Employment Rate [18] Self-employment [19] Youth Unemployment Rate [20] Unemployment Rate [21] Proportion of Non-Agric. Wage Earner [22] Proportion of Non-Agric. Own-Account Worker [22] Dependency Rate [24] Female in Wage Emp. Non Agric. [25] Proportion of Married 17-year-old Girls Improved Sanitation [27] Improved Water Source [28] Not Using Firewood [29] Using Electricity [30] Have a Phone [31] Code Province/District 1208 Xebangfay 86.1 92.7 1.5 0.5 6.7 7.0 37.3 38.7 18.4 55.4 80.5 19.4 85.6 89.3 1209 Xaybuathong 86.8 93.9 1.9 0.3 6.0 5.6 43.5 30.9 26.0 47.6 44.7 7.5 82.7 84.8 1210 Khounkham 83.8 92.2 2.7 0.8 7.4 6.1 36.4 30.6 14.8 66.7 76.6 7.2 82.4 93.4 1300 Savanakhet 81.6 87.3 3.4 1.2 12.2 8.3 36.4 41.7 17.5 57.7 73.3 41.4 80.4 87.5 1301 KaysonePhomvihane 66.5 61.8 12.6 3.9 37.9 29.8 28.3 39.7 9.6 92.7 97.0 87.2 97.7 96.4 1302 Outhoomphone 84.3 84.3 2.9 0.9 15.1 12.4 33.8 41.5 14.0 64.7 78.4 61.9 94.7 92.0 1303 Atsaphangthong 84.2 89.6 1.8 0.7 10.1 5.1 36.8 40.0 13.1 57.2 65.4 39.0 88.7 87.8 1304 Phine 79.9 93.5 3.7 1.5 6.2 8.0 43.4 36.6 26.3 34.7 66.8 30.5 57.1 79.4 1305 Sepone 77.6 92.8 9.2 2.1 6.8 7.1 47.4 33.2 32.9 25.2 63.6 11.2 59.2 62.4 1306 Nong 82.9 94.0 3.9 1.0 5.7 3.6 47.8 29.0 40.0 8.7 64.5 3.9 35.9 61.4 1307 Thapangthong 85.9 94.9 3.1 0.8 4.7 3.8 42.4 43.3 32.9 22.6 52.2 24.8 50.0 85.2 1308 Songkhone 87.7 94.5 0.9 0.4 5.3 5.5 32.6 44.7 19.8 77.2 81.5 80.7 91.5 94.5 1309 Champhone 83.3 86.6 1.0 0.3 13.2 4.6 33.1 50.4 9.9 65.1 74.7 26.6 94.2 92.5 1310 Xonbuly 86.4 94.5 1.0 0.5 5.3 3.4 40.0 48.3 14.2 29.7 42.7 5.0 63.3 83.9 1311 Xaybuly 88.8 85.3 0.9 0.5 11.2 4.4 33.8 45.3 18.2 75.7 84.1 18.4 97.0 92.3 1312 Vilabuly 81.0 87.7 4.1 1.6 12.2 4.4 41.9 29.7 23.1 55.9 64.9 13.4 75.0 86.0 1313 Atsaphone 80.2 94.4 4.0 1.3 5.4 2.8 39.9 38.2 16.2 36.0 58.4 7.5 55.8 85.8 1314 Xayphoothong 82.1 94.3 4.0 0.9 5.6 2.5 29.8 46.2 16.0 95.3 93.5 91.1 98.8 96.5 1315 Phalanxay 89.3 91.3 1.4 0.6 8.4 2.6 40.3 40.9 17.4 27.9 63.6 16.1 72.5 79.1 1400 Saravane 88.4 90.4 1.0 0.4 9.2 4.5 40.4 43.7 21.0 34.9 70.2 31.2 76.7 85.4 1401 Saravane 84.6 89.0 2.1 0.6 10.8 5.4 39.1 37.5 14.8 29.4 73.8 31.5 77.3 87.2 1402 Ta oi 88.1 95.1 1.2 0.3 4.7 2.8 49.2 31.7 37.1 12.3 62.9 4.5 34.7 73.5 1403 Toomlarn 90.4 95.9 0.6 0.3 3.9 2.6 47.1 26.6 29.4 3.6 66.2 3.7 42.7 84.1 114 Lao PDR 2015 Census-Based Poverty Map – June 2016 Employment Rate [18] Self-employment [19] Youth Unemployment Rate [20] Unemployment Rate [21] Proportion of Non-Agric. Wage Earner [22] Proportion of Non-Agric. Own-Account Worker [22] Dependency Rate [24] Female in Wage Emp. Non Agric. [25] Proportion of Married 17-year-old Girls Improved Sanitation [27] Improved Water Source [28] Not Using Firewood [29] Using Electricity [30] Have a Phone [31] Code Province/District 1404 Lakhonepheng 91.6 91.7 0.7 0.4 7.9 5.2 35.4 46.9 21.2 57.3 57.9 77.9 92.2 89.3 1405 Vapy 88.2 90.9 0.9 0.4 8.9 4.2 37.7 48.0 15.9 45.2 66.0 37.2 92.8 89.6 1406 Khongxedone 89.9 83.4 0.4 0.2 16.3 4.8 36.3 53.4 22.8 61.9 72.8 48.3 95.9 92.0 1407 Lao ngarm 90.5 94.5 0.5 0.3 4.7 4.6 41.5 39.0 22.3 24.0 78.7 10.5 81.0 85.0 1408 Samuoi 82.7 88.8 2.2 0.5 11.0 2.0 51.1 26.0 22.0 20.1 67.6 4.1 37.6 54.3 1500 Sekong 78.9 84.2 6.3 1.9 15.5 6.2 45.5 30.6 22.1 56.4 82.5 17.2 76.7 83.8 1501 Lamarm 71.9 71.7 13.0 2.6 28.1 10.7 41.4 33.0 19.1 66.0 87.4 38.5 88.2 90.3 1502 Kaleum 86.8 89.7 1.0 0.2 10.0 2.9 51.5 19.4 27.9 32.7 78.4 4.5 37.8 72.7 1503 Dakcheung 83.2 86.9 3.7 0.9 12.9 2.6 50.7 27.0 29.0 30.7 70.0 2.6 52.0 75.6 1504 Thateng 80.3 91.0 4.7 2.4 8.5 5.6 43.8 32.0 19.1 72.6 86.9 12.1 96.7 87.2 1600 Champasack 85.7 84.8 2.1 0.9 14.8 8.6 36.5 40.5 15.0 65.8 76.0 65.7 93.7 93.9 1601 Pakse 67.1 53.4 12.8 3.9 46.3 42.2 30.4 34.9 7.5 94.6 97.0 90.9 97.3 98.1 1602 Sanasomboon 88.2 93.0 1.6 0.6 6.7 2.8 33.6 39.2 13.4 73.9 78.4 46.5 96.1 92.8 1603 Bachiangchaleunsook 83.0 67.1 1.9 0.7 32.3 14.1 37.4 39.9 13.5 56.2 81.1 33.6 95.7 92.0 1604 Paksxong 87.9 94.2 0.6 0.2 5.4 2.7 40.5 33.2 12.9 40.9 73.1 11.4 83.0 89.6 1605 Pathoomphone 87.3 91.1 1.8 0.6 8.7 4.8 37.5 39.6 18.5 66.2 73.0 73.0 93.7 93.9 1606 Phonthong 89.9 89.5 1.6 0.6 10.2 5.1 33.2 42.2 16.2 75.4 87.6 89.7 96.0 95.5 1607 Champasack 89.4 80.8 1.0 0.4 18.7 4.9 34.7 50.6 13.1 68.3 91.3 83.1 95.9 96.2 1608 Sukhuma 89.5 88.4 0.9 0.5 11.1 3.9 38.9 43.2 20.0 53.1 82.9 76.5 92.7 92.4 1609 Moonlapamok 89.3 84.3 0.7 0.5 15.1 6.3 40.5 45.5 22.9 57.9 63.3 81.8 92.4 93.1 1610 Khong 88.0 93.6 1.2 0.4 6.3 5.1 39.9 44.6 16.1 63.6 38.4 72.0 94.7 94.6 1700 Attapeu 83.5 87.5 3.6 1.0 12.2 9.1 40.6 32.2 22.6 50.3 73.8 17.5 78.8 85.1 1701 Xaysetha 86.2 91.9 2.1 0.5 7.6 8.1 36.5 32.2 23.6 53.2 76.8 19.0 82.7 88.0 Lao PDR 2015 Census-Based Poverty Map – June 2016 115 Employment Rate [18] Self-employment [19] Youth Unemployment Rate [20] Unemployment Rate [21] Proportion of Non-Agric. Wage Earner [22] Proportion of Non-Agric. Own-Account Worker [22] Dependency Rate [24] Female in Wage Emp. Non Agric. [25] Proportion of Married 17-year-old Girls Improved Sanitation [27] Improved Water Source [28] Not Using Firewood [29] Using Electricity [30] Have a Phone [31] Code Province/District 1702 Samakkhixay 76.5 72.9 9.5 2.0 26.9 13.2 36.9 33.6 13.2 62.1 88.1 34.8 94.3 90.5 1703 Sanamxay 85.7 93.6 2.4 0.7 6.3 5.6 43.5 32.5 25.3 45.1 61.5 10.4 68.0 83.5 1704 Sanxay 85.4 91.3 1.8 1.0 8.0 8.5 48.1 28.1 31.3 46.4 65.9 3.2 60.9 78.4 1705 Phouvong 87.7 91.9 0.4 0.4 8.0 10.5 40.6 25.9 25.2 32.7 72.5 9.3 83.9 79.2 1800 Xaysomboune 78.4 86.0 6.3 1.3 13.8 7.4 44.9 25.1 26.7 83.9 91.0 2.9 82.8 95.7 1801 Anouvong 76.4 75.8 4.0 1.1 24.1 10.6 46.4 24.1 25.2 90.2 97.8 4.6 96.5 97.1 1802 Thathom 82.0 91.0 6.1 1.2 8.9 4.8 40.3 34.8 21.0 81.9 93.7 1.6 61.6 94.7 1803 Longcheng 85.7 86.7 3.7 0.5 13.2 4.3 45.1 27.3 37.5 85.7 91.0 3.4 82.9 91.0 1804 Home 76.9 89.7 1.7 0.9 10.2 4.9 49.6 12.2 39.0 74.0 96.5 1.0 70.7 95.1 1805 Longsane 75.5 88.8 11.2 1.9 11.0 9.3 45.2 23.8 24.9 83.8 79.9 3.0 93.5 96.9 Source: Authors’ calculations based on 2015 Lao PDR Census Note: The provinces are shown in bold, while the associated districts are listed below their respective province.