WPS8527 Policy Research Working Paper 8527 Characterizing Business Cycles in Small Economies Viktoria Hnatkovska Friederike Koehler-Geib Macroeconomics, Trade and Investment Global Practice July 2018 Policy Research Working Paper 8527 Abstract This paper aims to document a set of stylized facts charac- more volatile trade balance and current account, have more terizing business cycle dynamics in smaller economies. The procyclical exports, and thus less countercyclical trade bal- paper uses a large sample of countries spanning 1960–2014 ance; (iv) have more volatile government consumption and to show that country size is a significant factor affecting more procyclical public revenues and fiscal balance; and (v) countries’ volatility, comovement with gross domestic possess more procyclical inflation. The effects of country product and real interest rate, and persistence. Specifically, size remain robust even after we control for the level of analysis finds that smaller countries (i) tend to have more economic and institutional development, the presence of volatile gross domestic product; (ii) have more volatile, fiscal rule(s) and fixed exchange rates, and the commodity less procyclical, and less persistent investment; (iii) exhibit exporting status. This paper is a product of the Macroeconomics, Trade and Investment Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/research. The authors may be contacted at Viktoriya.Hnatkovska@ubc.ca or fkoehler@worldbank.org. The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent. Produced by the Research Support Team Characterizing Business Cycles in Small Economies* Viktoria Hnatkovska† and Friederike Koehler-Geib‡ Keywords: small states, volatility, business cycles, fiscal rule JEL Classification: E30, O11, O54 * This paper benefitted from useful comments from Carlos Vegh, Edgardo Favaro, Cesar Calderon, Norbert Fiess, Klaus Schmidt-Hebbel, Raimundo Soto, Emilia Skrok, Jan Gaska, Elena Ianchovichina, and participants at the Authors’ Workshop for the World Bank’s Regional Study for Latin America and the Caribbean on Fiscal Rules. The authors acknowledge financial support from the Office of the Regional Chief Economist for Latin America and the Caribbean. † University of British Columbia, 253-6000 Iona Dr., Vancouver, BC V6T1L4, Canada, Viktoriya.Hnatkovska@ubc.ca. ‡ Lead Economist and Program Leader, Central America Department, The World Bank, 1818 H Street Washington, DC 20433 USA; fkoehler@worldbank.org. 1. Introduction Economic volatility has become an undeniable reality for countries around the world. Developing countries have been particularly susceptible to large and frequent changes in the internal and external economic conditions. This is troubling since greater volatility is frequently associated with lower growth (Hnatkovska and Loayza, 2005) and higher inequality (Breen and Garcia- Penalosa, 2005). These effects are likely to be even more pronounced in smaller economies partially due to their less diversified production and trade structure coupled with greater trade openness. This combination makes it particularly difficult for these countries to absorb and smooth out the effects of terms of trade shocks, fluctuations in international interest rates, and environmental disturbances. As a result, these countries are more likely to exhibit higher vulnerability to external and internal shocks, and greater volatility of the key macroeconomic aggregates such as output, consumption, investment, current account, etc. The relationship between country size and its economic performance has received renewed interest with the “new growth literature”. With its focus on increasing returns to scale, this literature has emphasized the positive relationship between country size and economic growth. Empirical works, however, failed to find a significant association between the two variables. A few empirical studies, such as Easterly and Kraay (2013) as well as Lederman and Lesniak (2016), however, do identify common features of smaller economies. In particular they find that small economies are more concentrated in terms of their value added, their export basket, their export destinations, that they are more open than larger economies, and that they have more volatile growth patterns. These features are highly relevant for the design of economic policies in those countries. A topic that has been understudied in the literature so far is the relationship between economic size and the business cycle characteristics of small economies. This relationship is at least as important for policy design as the performance characteristics mentioned above and this paper intends to contribute to filling this gap. The purpose of this study is to provide a comprehensive evaluation of the relationship between country size and its business cycles characteristics. Specifically, we aim to contrast the volatility, cyclicality and persistence of the key macroeconomic aggregates in small economies with those in larger economies. Our benchmark approach focuses on the properties of the cyclical component of various series obtained using Hodrick-Prescott decomposition. We explore several definitions of size -- based on population, labor force and geography.1 There are various reasons for why size may matter for business cycle fluctuations. First, smaller countries tend to have larger governments. Then, if government policy is a source of uncertainty and shocks, smaller countries will have more volatile economies. Second, smaller countries are less able to insure imperfectly correlated shocks across their different regions and jurisdictions, as well as sectors ad industries, and therefore may experience more pronounced business cycles.                                                              1  We also studied employment as a measure of size and found that results remain robust. Due to the scarcity of employment data for many countries, we focus on population, labor force and land area in the paper which allows for the broadest country coverage. 2   Third, smaller countries have lower capacity to build redistributive schemes across their regions and jurisdictions, reducing the ability of these countries to insure against regional shocks through fiscal transfers. Fourth, smaller countries have less diversified production and exports, which makes them more susceptible to domestic and external shocks. Fifth, smaller countries tend to rely more on fixed exchange rate policy. Sixth, smaller countries are more prone to weather shocks and natural disasters. All these channels indicate that business cycles are likely to be more pronounced in smaller economies. We find strong empirical support for this intuition. Our analysis yields the following key results:  Countries with smaller population have more volatile GDP and GNI. This is likely due to both larger and more volatile shocks facing small countries and their inability to insure them due to market imperfections and frictions.  Smaller countries also have investment that is more volatile, less procyclical and less persistent. These properties of investment are likely the outcome of larger shocks to investment in small economies, as well as lack of scale economies in the private sector in small countries.  We also find that trade balance and current account are more volatile in small economies.2 Trade balance is also less countercyclical in these countries, primarily driven by more procyclical exports. Higher volatility likely reflects greater trade openness of small economies and their greater vulnerability to external conditions and natural disasters, while higher cyclicality is likely driven by a more concentrated production structure and exports.  Small countries also feature higher fiscal volatility (government consumption volatility), and more procyclical fiscal balance, driven by more procyclical public revenues.3 Higher fiscal volatility is likely a reflection of expenditure responses to domestic shocks in small countries, such as weather and natural disaster shocks. Higher revenue cyclicality is likely due to greater reliance of these economies on trade taxes, and further narrowing of the tax base through income tax holidays and “tax havens” for multinational activity.  Inflation is more procyclical and less persistent in small economies, likely indicating the prevalence of demand-side shocks in these economies.  Inspired by the literature emphasizing the importance of interest rate shocks in developing countries, we also explore the cyclicality of key macroeconomic aggregates with the real interest rate. We find that smaller countries tend to have more negative correlation between GDP and real interest rates, however, the difference is not statistically significant. The only significant effect of country size that we find is the stronger correlation between terms of trade and real interest rate in smaller countries, likely indicating the importance of endogenous risk premium in small countries.                                                              2  Or results also indicate that smaller countries feature less persistent current account, which together with higher volatility of current account in these countries suggest large and volatile shocks to current account (i.e. weather and natural disasters shocks, terms of trade shocks, investment shocks, etc.).  3  We also find that government consumption is less procyclical with GDP while government investment is more procyclical with GDP in small economies. However, the differences are not statistically significant.  3   These results are broadly confirmed when country size is measured by labor force and land area. Given the importance of the level of development for business cycles characteristics reported in the literature (for instance, Neumeyer and Perri, 2005; Aguiar and Gopinath, 2007; Calderón and Fuentes, 2007, and others) we investigate to what extent our results for country size are driven by differences in the level of development between small and large economies. We find that controlling for the level of development, country size remains a significant factor affecting business cycle volatilities. Interestingly, we also show that controlling for country size, developing countries have significantly higher macroeconomic volatilities compared to developed economies. These results are consistent with the existing studies that focus on the properties of business cycles in developing countries. Turning to correlations with GDP, we show a similar result: controlling for the level of development, it is still the case that the cyclicality of a number of macro aggregates varies with country size. We also find that, conditional on country size, developing countries tend to have less procyclical aggregate investment, consumption, imports, and inflation; and less countercyclical trade balance.4 Interestingly, we find that the cyclicality of real interest rate with GDP is not affected by the level of development when country size is controlled for. On the fiscal side, we show that controlling for country size, fiscal balance and public revenues are less procyclical, while public expenditures are more procyclical with GDP in developing countries. Lastly, we look at the persistence of various macroeconomic aggregates and their correlations with the real interest rate. We find that practically all effects of country size on these business cycle moments survive even after controlling for the level of development. Overall, these results suggest that country size exerts a significant effect on business cycles dynamics and that this effect exists above and beyond the level of development effect that it potentially confounds. To ensure that our results are not driven by other country characteristics we introduce additional controls into our regressions of business cycle moments on size and level of development. Specifically, we add the level of institutional development which is proxied by the International Country Risk Guide (ICRG) index; a dummy variable for commodity exporting countries; a dummy variable for countries with fixed exchange rate regime; a dummy variable for the presence of fiscal rule(s); and a set of regional dummies.5 We find that the effects of country size remain mostly unchanged even after controlling for these additional country characteristics. These results confirm the importance of country size for characterizing business cycle dynamics. Finally, given our larger interest in the role of fiscal rules in the economic stabilization of small economies, we compare the business cycles characteristics of countries that have adopted various                                                              4  The lower countercyclicality of trade balance with GDP in developing countries may seem surprising in light of the results in Aguiar and Gopinath (2007). We confirm their finding of more countercyclical trade balance in the sample of 13 emerging market economies used in their analysis, and show that their findings do not extend to a larger sample of developing countries used in our study. 5 These are relevant characteristics because smaller countries are more likely to adopt a fixed exchange rate regime, are slightly more likely to be commodity exporters, and are less likely to adopt fiscal rules.  4   types of fiscal rules and non-adopters. We find that volatilities of almost all variables are lower for countries with fiscal rules in place. However, after controlling for country size and other country characteristics, the difference remains highly statistically significant for inflation only. Interestingly, this result masks significant differences in business cycle characteristics of countries with different types of fiscal rules. For instance, we show that lower volatility result was driven by countries with revenue rules. We then subject our findings to a series of robustness checks. First, we contrast the length and amplitude of business cycles in small and large countries. For this purpose, we apply the Harding and Pagan (2002) business cycles dating algorithm to quarterly GDP series in 39 developed and 30 developing countries.6 We show that the amplitude of expansions is the same in small and large countries, while contractions are significantly more pronounced in small countries. This confirms our findings of greater GDP volatility in small countries. We also find that the duration of expansions is shorter in small countries, compared to large economies. At the same time, the duration of contractions is comparable in the two groups of countries. These findings indicate potential differences in the duration of business cycles between large and small countries. Therefore, we revisit our business cycles analysis by applying a lower smoothing parameter in the Hodrick-Prescott decomposition of the series in small countries. We find our results to be robust to this amended decomposition. Second, we use Baxter and King (1995) band pass filter to decompose the series into trend and cyclical components. The results are robust to this alternative decomposition. Third, we explore the sensitivity of our results with respect to alternative definitions of fixed exchange rate regime, and to the duration of fiscal rules used by different countries. Again, our results go through practically unchanged. To sum up, we believe our results put forward a novel country characteristic – size (as measured by population or labor force or land area) – that exerts a significant influence on its business cycle properties. The prevalence of larger and more volatile shocks, higher macroeconomic volatility, lower cyclicality of investment, and strong comovement of public revenues, fiscal balance and exports with GDP constitute important vulnerabilities faced by small economies. They motivate several recommendations for policy in these countries. First, we argue that countercyclical expenditure rule or fiscal rule that forces these economies to save for the “rainy day” during good times will help to alleviate the vulnerabilities faced by small economies by cushioning them in the face of weather, terms of trade, or world demand shocks, and by stabilizing tax base and investment. Second, we argue that balanced budget rule may not have the desired effects in small economies as it would require strongly procyclical public expenditures in order to match higher cyclicality of public revenues. Third, in order to stabilize the tax base, small economies may want to rethink tax breaks for multinationals; and instead subsidize domestic investment, especially for small                                                              6 These are all the countries for which we could find quarterly real GDP series with at least 30 quarters of non- missing observations. 5   firms who likely face lack of scale economies in investment (for instance, by subsidizing the fixed cost). The rest of the paper is organized as follows. Section 2 provides a review of the relevant literature and discusses why country size may matter for business cycle dynamics. Section 3 describes the data and methodology used in the analysis. Section 4 contains a discussion of the results. Section 5 provides robustness evaluations. Section 6 summarizes the results and discusses their policy implications. Section 7 concludes. Additional results and robustness evaluations are presented in the Appendix. 2. Context and Literature Review Our work is related to a large literature studying business cycle fluctuations in different countries. Most of this literature has primarily focused on contrasting the business cycle characteristics of industrial and emerging market economies. For developed countries, the set of stylized facts describing business cycles is found to be quite robust to country samples and time periods and is well-documented in the literature (see Kydland and Prescott, 1990; Backus and Kehoe, 1992; Backus, et al. 1995; and many others). These empirical regularities include: (i) Output and consumption have similar volatility, while investment is 2-3 times as volatile as output. Government expenditures are significantly less volatile than output; (ii) Consumption, investment and employment are procyclical with output; (iii) Government expenditures are generally acyclical or weakly countercyclical; (iv) Net exports to GDP are countercyclical; and (v) Output exhibits significant persistence. Similar analysis for developing countries has been somewhat more limited and less conclusive. For instance, Agenor et al. (2000) document key features of macroeconomic fluctuations in 12 developing middle income countries. They show that output volatility, while varies significantly across countries, is much higher on average in these countries than in developed economies. They also find substantial persistence in output fluctuations in developing countries. In terms of fiscal policy, they show that government expenditures are countercyclical. Terms of trade appear to be strongly positively correlated with output fluctuations. The authors interpret their findings as suggesting that supply-side shocks are important drivers of business cycles in developing countries. The works that followed revisited and challenged some of these findings. For instance, Rand and Tarp (2002) use a sample of 15 developing countries at a quarterly frequency to show that the duration of business cycles is shorter in developing countries than in developed economies. Then, using annual data for the same countries and a Hodrick-Prescott filter with smoothing parameter around 1 (indicating shorter cycles in developing countries) they show that GDP volatility is larger in developing countries than in the OECD economies, although the difference is small (around 15- 20%). They also find that consumption is more volatile than output and that this result is true both for private and public consumption. At the same time, investment volatility in developing countries is in line with that for developed economies, in their study. For trade-related indicators such as imports, exports, terms of trade and the real effective exchange rate, they find no significant differences in volatility between developing and developed countries. When it comes to the 6   cyclical properties of macroeconomic aggregates, Rand and Tarp (2002) show that the correlation of consumption (private and public) and investment with GDP in their sample of developing countries is significant, positive, and in line with the same correlations in developed economies. Public expenditures and output are significantly positively correlated in six developing countries in their sample, and in general, the authors do not find clear evidence of a countercyclical role of fiscal policy in their data. Lastly, they show that imports are strongly procyclical, especially in Latin America, while exports do not exhibit a robust relationship with output. Calderón and Fuentes (2007) and Male (2010) challenged the findings in Rand and Tarp (2002) of the shorter duration of business cycles in developing countries. While the previous studies have relied predominantly on Hodrick-Prescott filter or Band-Pass filter to remove the trend component of the macroeconomic aggregates, Calderón and Fuentes (2007) used a methodology in Harding and Pagan (2002) to identify the business cycle component of the variables. Then, using a sample of twelve Latin American, eight East Asian and Pacific and three other emerging economies, they show that the duration of contractions is similar in developed and developing countries, but the duration of expansions is shorter in developing countries, on average. They also show that the amplitude of contractions and expansions is larger in developing economies than in developed countries. Moreover, they find that the output losses associated with contraction are significantly larger in developing countries. More recently, a few systematic regularities common to developing countries began to emerge. Neumeyer and Perri (2005), using a sample of 5 emerging market economies and 5 developed countries show that emerging economies business cycles are more volatile, their real interest rates are countercyclical and lead the cycle, their consumption is more volatile than output, and their net exports are strongly countercyclical, relative to developed economies. They propose a model of small open economy with interest rate shocks and financial frictions to rationalize the findings in the data. In their framework, shocks to the interest rate are driven by two components: the international interest rate and the country risk-premium. They show that changes in country spreads are important drivers of business cycles in developing countries. Uribe and Yue (2006) extend this work by empirically estimating and adding endogenous country risk-premium into the model, thus allowing for interactions between world interest rate, country spreads, and emerging- market fundamentals. Aguiar and Gopinath (2007) revisit the evidence for 13 developed and 13 developing countries and document several striking differences between their business cycles: (i) the trade balance is strongly countercyclical for emerging markets as compared to developed economies; (ii) consumption is 40 percent more volatile than income for emerging markets, while the ratio is slightly below one for developed markets; and (iii) income growth and net exports are twice as volatile in emerging markets as in developed economies. They argue that a neoclassical growth model featuring shocks to trend growth can match these stylized facts. Male (2010) using a larger sample of 32 developing countries documents that output, consumption and investment of developing countries are significantly more volatile than the corresponding variables in developed economies. For instance, output volatility in developing countries is double that in developed economies. She also finds that consumption is about 30% more volatile than 7   output, while investment is 3-4 times as volatile as output in developing countries. Both variables are highly procyclical, and of similar degree as observed in developed countries. These results line up well with Neumeyer and Perri (2005), Uribe and Yue (2006) and Aguiar and Gopinath (2007). Unlike the previous studies, however, Male (2010) also finds that government revenues and expenditures exhibit significant volatility in developing countries: they are significantly more volatile than in developed countries and are 4 times more volatile than output. Moreover, she finds evidence of a countercyclical fiscal policy in developing countries. Male (2010) also documents that real interest rates in her sample of developing countries are less volatile than in developed economies and are weakly procyclical in Africa, Asia and Eastern Europe, but are countercyclical in Latin America. These results are in contrast the findings in Neumeyer and Perri (2005), Lubik and Teo (2005), Uribe and Yue (2006). On the trade margin, Male (2010) shows that exports and imports are strongly procyclical in developing countries, although no systematic relationship emerges with trade balance. Moreover, terms of trade are strongly procyclical for the majority of developing countries in her sample. These results are generally in accord with Agenor et al. (2000). Lastly, she finds that output fluctuations in emerging markets are quite persistent, however, the magnitude of this persistence is found to be somewhat smaller than in developed economies. Thus, while some common features in business cycle characteristics of developing countries emerge in the literature, a few important disagreements still remain. Namely, while the literature generally agrees than business cycles in developing countries are more volatile than in developed economies, the disagreements persist about some of the cyclical properties of the macroeconomic aggregates. This is especially the case for the cyclicality of trade balance and real interest rates. The level of development is just one of the many country’s characteristics that may affect its business cycle dynamics. In this study we are interested in learning whether country size may exert an independent influence on country’s cyclical fluctuations. There are numerous reasons for why country size may matter:  Smaller countries lack scale economies in the public sector. As a result, the cost of public goods in per capita terms is higher in smaller (less populous) countries, leading them to have larger governments (see, for instance, Alesina and Wacziarg (1998) who showed that the share of government spending over GDP is decreasing in population). If government is a source of macroeconomic uncertainty, then it is likely that smaller countries will have more volatile business cycles.7 Furthermore, with government consumption expenditures (and public sector wage bill, in particular) taking up a larger share of GDP in small economies, the cyclicality of government consumption in small economies will likely be reduced. The cyclicality of public investment, on the other hand, is likely amplified to accommodate more rigid public consumption.                                                              7 In addition, smaller countries may experience higher volatility of government spending because they are less able to insure against idiosyncratic shocks, and because they have a smaller pool of taxpayers to spread the cost of financing government spending. Confirming this intuition, we find that smaller countries tend to have more volatile government spending. A similar result is documented in Furceri and Poplawski-Ribeiro (2008). 8    Smaller countries lack scale economies in the private sector, leading to a more concentrated production structure and exports (see for example, Lederman and Maloney (2012), Lederman, Pienknagura and Rojas (2015), and Pinies, Wacker and Varma (2015)).8 Indeed, in our data set, exports of small economies (based on 1.5 million population threshold) are concentrated in services, with the share of the latter in total exports equal to 46% as opposed to just 23% in large countries. Moreover, a substantial fraction of service exports in small economies is derived from tourism. This lowers risk-sharing opportunities across sectors and regions through factor reallocation, thus increasing the exposure of small economies to domestic and external shocks, and amplifying their business cycle fluctuations. Lack of scale economies in the private sector also likely affects private investment by making it lumpy and more volatile, as well as reducing its cyclicality with GDP.  Smaller economies are more open to trade. This influences both volatility and cyclical dynamics of macro variables in these countries. For instance, Di Giovanni and Levchenko (2012) show how country size impacts on aggregate volatility through the trade channel in the data and in a model of heterogeneous firms. They argue that when the distribution of firm sizes is fat-tailed, idiosyncratic shocks to large firms can generate aggregate fluctuations (see also Delli Gatti et al. 2005; Gabaix 2011). Since smaller countries have fewer firms they will also experience higher aggregate volatility. Trade openness also affects the cyclical properties of macro aggregates. With exports being a larger component of GDP in small economies, its cyclicality with GDP is likely to be higher in these countries. In addition, small states tend to rely more on trade taxes, both due to greater trade openness, as well as prevalence of income tax holidays, “tax havens” for multinational activity, and other incentives in some regions. This narrows their tax base and leads to more procyclical tax base and public revenues in small economies.  Larger countries are better able to hedge imperfectly correlated shocks across their different regions and jurisdictions. In the environment of imperfect international financial markets, where countries cannot fully self-insure, this implies that smaller countries will have more pronounced business cycles. Indeed, using intranational data for the US and Canada, Imbs (2004) show that bilateral risk sharing tends to be associated with low output correlations.  Larger countries have greater capacity to build redistributive schemes across regions/jurisdictions, which allows them to better insure against shocks and thus reduce the impact of these shocks on the economies. Such transfers may take place through changes in regional tax payments or explicit transfers in response to temporary or permanent shocks to relative regional GDP. There is a large literature in public finance measuring the extent of fiscal transfers across regions/jurisdictions within countries in response to regional income differentials (see, for instance, Boadway and Shah (2009)). Hagen (2007) and Poghosyan, Senhadji, and Cottarelli                                                              8  The literature has discussed various channels through which country size may limit specialization and lead to a greater market size. For instance, Romer (1986), Lucas (1988), and others have argued that greater scale allows countries to benefit from positive externalities in the transmission of knowledge and human capital accumulation. Aghion and Howitt (1998) and Aghion et al. (2002) emphasized the idea that greater scale creates incentives for product competition and thus higher growth.  9   (2015) summarize the empirical literature on the size of interregional transfers across the OECD countries; Sachs and Sala-i-Martin (1992) provide estimates for the US; Bayoumi and Masson (1995) for Canada; and Obstfeld and Peri (1998) for Italy. They all find evidence of non-negligible within-country fiscal risk sharing.  Small economies are more prone to weather shocks and natural disasters, which create potential disruptions in production and exports, and add to macro volatility in these economies.  A number of small economies around the world have adopted fixed exchange rates regimes rendering their monetary policy subordinate to the goal of exchange rate stability.9 As a result, the burden of macroeconomic stabilization falls entirely on the fiscal policy in these countries. With a limited number of stabilization instruments, smaller economies may experience more volatile business cycles.  There are also benefits of being small. These include lower administrative and congestion costs (Alesina and Spolaore, 2003); and more importantly, lower heterogeneity of preferences of different individuals within a country (Olson, 1982). In the data, population heterogeneity has been documented to be inversely related to measures of economic performance, economic freedom, and quality of government (Easterly and Levine (1997), La Porta et al. (1999), Alesina et al. (2003)). This factor likely has a stabilizing effect on small economies. The arguments laid out above suggest that, depending on which effects of size dominate, smaller countries may be faced with more or less pronounced business cycles relative to larger economies. Cyclicality of investment, trade and fiscal variables also likely differs in small economies. In this paper we provide a detailed characterization of the relationship between country size and its business cycles. To isolate the effects of size it is important to control for other country characteristics that may affect the relationship between country size and its business cycle dynamics. First, in the data country size and country level of development are correlated. Indeed, we find that developing countries tend to be larger than developed economies in terms of their population, labor force, and land area. Given this empirical fact and based on the insights of the literature studying business cycle dynamics in developed and developing countries, it is important to control for the level of development when evaluating the effects of country size on business cycles dynamics. We consider controls for the level of economic development, as captured by the World Bank income classification variable; and the level of institutional development, as captured by the composite risk index from the International Country Risk Guide. Second, as noted above, quite a few of the small economies have adopted currency pegs in an attempt to reach price stability or improve external competitiveness. So we also control for the presence of the fixed exchange rate regime in a country. Against the backdrop of minimal monetary policy, it became paramount for these countries to introduce sustainable fiscal policies. Working                                                              9 For instance, the Organization of Eastern Caribbean States (OECS) uses a common currency among its members and fixes the value of this currency to the US dollar. 10   towards the goal of more predictable and credible fiscal policy, a number of countries have adopted constraints on their fiscal policies in the form of one or several types of fiscal rules that impose numerical limits on budgetary aggregates (see, for example, Kopits and Symansky (1998) and (2001), IMF (2012), as well as Wyplosz (2005) and (2012)). The imposition of such rules may spill over onto the country’s business cycles through several channels.  Fiscal rules may limit the ability of the government to respond to business cycles shocks and smooth out their effects on the economy. This will tend to amplify macroeconomic volatility.  By imposing limits on fiscal policy, fiscal rules lower the stock of debt that the government may accumulate, as well as make fiscal policy more predictable, thus reducing the incidence of fiscal policy shocks on the economy. This channel will tend to reduce macroeconomic volatility. Therefore, the net effect of fiscal rules adoption depends on which of the two channels dominates. We investigate this question empirically, by comparing the business cycles dynamics of fiscal rule adopters and non-adopters; as well as by controlling for the potential effects of fiscal rules presence when evaluating the effects of country size on its business cycles characteristics. Lastly, we also control for commodity exporting status since commodity exporting countries are more prone to external shocks such as weather and terms of trade. 3. Data Description and Methodology Data A common feature of the studies discussed above is that they rely on relatively small samples of developing countries in their analysis. To a large extent, this is due to limited availability of quarterly data. This produces a trade-off between the country coverage of the analysis and the usage of quarterly versus annual data. Annual data for the key macroeconomic aggregates is available for almost all countries and thus allows for the broadest possible sample coverage. In fact, for most very small countries, which are of particular interest to us, quarterly data are not available at all, leaving us no choice but to use annual data. Moreover, many macroeconomic variables now have long time-series coverage at annual frequency going back to the 1960s, which gives us sufficiently long time series for reliable statistical inference. On top of that, annual data are available for a large spectrum of macroeconomic variables, which allows us to examine various dimensions of business cycle fluctuations. Our data come from several sources. Most of the macroeconomic variables and variables reflecting country size (population, labor force, employment, geographic area, etc.) are taken from the World Development Indicators (WDI) database of the World Bank. This data set covers the period of 1960-2014 at annual frequency. Most aggregate quantities that we use are measured in constant 2005 US dollars.10 The data on most fiscal variables, such as government revenues, expenditures, and net lending/borrowing are from the International Monetary Fund’s World Economic Outlook (WEO)                                                              10 The business cycle moments remain unchanged when variables are measured in constant local currency units since the two denominations differ by a constant factor. 11   database and covers the period of 1980-2014 at annual frequency. This data are in national currency and we convert it into real terms using the GDP deflator. Next, to control for the potential effects of governance, political, economic and financial risk, and political conditions on the business cycles characteristics, we also use the International Country Risk Guide (ICRG) database. This data covers the period going back to 1984. Lastly, to assess the effects of fiscal rules on business cycles dynamics we rely on the International Monetary Fund’s Fiscal Rules database which contains information on the type of fiscal rule in place, year of implementation, monitoring and enforcement procedures used. This data set is at annual frequency and covers 1985-2014 period. To have the broadest coverage possible, in our analysis we consider all countries and all variables for which we have at least 30 years of annual data. We also exclude countries that are non-sovereign states. This gives us a sample with a maximum of 138 countries (for GDP) and a minimum of 20 countries (for government investment). Measures of size We begin by characterizing measures of size we use in our analysis. We consider three key variables – population, labor force and geographic area.11 For each variable we compute the average value over the sample period of 1960-2014 in each country. Using average values for population and labor force, rather than the end of period values, has the advantage of allowing to capture longer histories of size dynamics. This becomes especially relevant when using thresholds to separate countries into different size groups. For instance, several small countries in our data set have transitioned by 2014 out of the small group after being in it for most of the period. Using average size allows to account for such transitions and allocate these countries into the small size group. The distributions of average values of size variables across countries are presented in Figure 1. Given our interest in the Latin America and Caribbean (LAC) region, we also show where LAC countries fit within those distributions. Figure 1. Distributions of country size 30 30 20 15 20 20 Frequency Frequency Frequency 10 10 10 5 0 0 0 10 15 20 0 5 10 15 20 10 12 14 16 18 20 all countries LAC all countries LAC all countries LAC (a) (log) average population (b) (log) average land area (c) (log) average labor force                                                              11 We also used total employment and found the results to be robust. The disadvantage of using employment as a measure of size is that employment data are available only for 30 countries in our sample. 12   Among all countries, the median country size in terms of land area is 100,00 sq. km; in terms of population – 4.151 million inhabitants; and in terms of labor force it is about 3 million. We use population as our benchmark variable for size, while land area and labor force are used in the robustness evaluations. Note that LAC countries are quite spread out along the size distributions, with a slight overrepresentation in the left tail of the distribution. This is driven by the small Caribbean economies. We consider two key thresholds to separate countries into small and not small. First, we define a country to be small if its population is below the threshold of 1.5 million people. This threshold is common in the literature and has been used by the IMF (Small States Report, 2000; Macroeconomic Issues in Small States, 2013, etc.) and the World Bank to define small states. We contrast the characteristics of these countries with those above the threshold of 1.5 million, to which we refer as “large” countries. With this threshold we have 51 countries in the small group and 141 countries in the large group. In the robustness exercises we also define smallness based on labor force using a threshold of 1 million people; or on land area with a threshold of 20,000 sq. km. In both cases 41 countries fall into the small group. We also consider alternative population thresholds of 1 million and 2 million to define small countries since these have also been used in the existing literature. For instance, Easterly and Kraay (2000) adopt a threshold of 1 million population, while Favaro (2008) used a higher threshold of 2 million people. In these cases, the small group contains 44 countries with 1 million threshold, and 57 countries with 2 million threshold. These results are reported in Appendix B. Second, we define a country to be small if its average size (measured by population, land area or labor force) is below the median. A large country is the one whose size (measured by population, land area or labor force) is above or equal to the median. This threshold gives us a more conservative measure of smallness. To understand how country size varies between developed and developing countries, we re-plot the size distributions above, but now conditioning on the developmental status. Specifically, we combine countries classified by the World Bank as low income and middle income countries into a “developing” countries group, while high income OECD and non-OECD countries are combined into a “developed” countries group. Figure 2 plots these conditional distributions. Figure 2. Distributions of country size by development level 13   .25 .3 .3 .2 .2 .2 .15 Density Density Density .1 .1 .1 .05 0 0 0 10 12 14 16 18 20 0 5 10 15 20 10 12 14 16 18 20 developed developing developed developing developed developing (a) (log) average (b) (log) average land area (c) (log) average labor population force It is easy to see that developed countries tend to be smaller in terms of land area that they occupy, as the land size distribution of these countries on panel (b) of Figure 2 is shifted to the left relative to the same distribution for developing countries. For instance, the smallest developed (high income) country by land area in our data is Monaco, while the largest is the Russian Federation. In the developing country group, the smallest country is Tuvalu, while the largest is China. In the same spirit, developing countries tend to be larger than developed countries in terms of their population (panel (a) of Figure 2) and labor force (panel (c) of Figure 2). Thus, while the association between the country developmental status and its size exists, the relationship between the two is far from perfect. Business cycles decomposition methodologies The key methodological aspect of the study is to perform the decomposition of the macroeconomic variables into their trend and cyclical components. We employ several approaches to accomplish this. One is a non-parametric approach due to Bry and Boschan (1971) and Harding and Pagan (2002, 2006), the second is Hodrick and Prescott (1997) (HP) decomposition, and the third is Baxter and King (1995) band-pass (BP) filter decomposition. The non-parametric procedure of Bry and Boschan (1971) and Harding and Pagan (2002, 2006) consists of a formal algorithm for dating business cycles by determining the turning points of the series, thus partitioning it into expansions and contractions. Bry and Boschan (1971) original algorithm applies to monthly data, while Harding and Pagan (2002, 2006) adapt it to quarterly data. The algorithm requires that each complete cycle has two phases (expansion and contraction) and they alternate; that the phases are at least 2 quarters long, and complete cycles are at least 5 quarters long. Following Harding and Pagan (2002) we also assume that the turning point is a local optimum relative to 2 quarters of data on either side. We apply this decomposition to quarterly (log) GDP series for 39 developed and 30 developing countries (see Hnatkovska and Koehler-Geib, 2016 for detailed data description).12 We then characterize the                                                              12 These, essentially, are all the countries for which we could find quarterly real GDP series. 14   resulting business cycles by the duration of expansions and contractions and their amplitude. Amplitude measures the cumulative growth of GDP during an expansion and contraction. Duration of an expansion is defined as the length (in quarters) between a trough and a peak; while duration of a contraction is the length between a peak and a trough. Next we compare the properties of expansions and contractions in small and large countries. As noted above, we define a country to be small if its population is less than 4.151 million people. Large countries have population greater or equal to 4.151 million people. Under this classification, our quarterly data set contains 22 small countries and 47 large countries.13 Table 1 shows the mean and standard deviation for durations and amplitudes of expansions and contractions, separately for small and large countries in our data set. Table 1. Characteristics of expansions and contractions, by country size Duration Amplitude (in quarters) Small Obs Mean Std. Dev. Mean Std. Dev. (pop<4.151mil) expansion 22 17.62 10.00 0.29 0.21 contraction 22 4.30 2.26 -0.07 0.06 Large (pop>=4.151mil) expansion 47 23.87 11.63 0.29 0.16 contraction 46 4.38 2.71 -0.05 0.05 Two key features differentiate business cycles in small and large countries. First, the average duration of expansions is shorter in small countries (at 17.6 quarters) relative to large countries (at 23.9 quarters) and the difference is statistically significant at 5% significance level. The average duration of contractions is comparable in small and large countries, equal to about 4 quarters. Second, contractions are more pronounced in small countries, with the average cumulative drop in GDP equal to 7% in small countries, as opposed to 5% in large countries. In contrast, the amplitude of the expansions is the same in the two groups of countries, equal to 29%. We interpret these results as providing mixed evidence on the differences in business cycles between small and large countries – by some measures, the business cycles are similar in the two groups, by others -- they are distinct. These results for small versus large countries echo the findings in the literature comparing developed and developing countries business cycles. For instance, using Bry and Boschan (1971) procedure to determine the turning points in GDP series for 15 developing countries, Rand and Tarp (2002) argued that the average length of the business cycle for these countries is only between 7 and 18 quarters, or 4.5 years. Other studies, using                                                              13 We do not use the 1.5 million population threshold to define small states as this gives a very small sub-sample of small countries in the quarterly data set.  15   different dating procedures show that there is no significant difference in the duration of business cycles between developed and developing countries (see Male, 2010 among others). Yet, others show more mixed evidence. For instance, Calderón and Fuentes (2007) find that on some dimensions, such as the duration of contractions, developed and developing countries are similar, while on others, such as duration of expansions, they differ, with developing countries experiencing shorter expansions, on average. With these results in mind, we turn to the HP filter to decompose the series into a cyclical and trend components. To apply the HP filter, a choice of the smoothing parameter must be made. A default choice of the smoothing parameter for annual data used in the literature is 100. However, our findings from the Harding and Pagan procedure suggest that small countries business cycles may be somewhat shorter than the business cycles in large economies, which requires using a lower value for the smoothing parameter. We choose to start with the default value of the smoothing parameter equal to 100 for annual series, as our benchmark. This choice also facilitates the comparison of our results with the existing studies that rely on the HP filter to characterize business cycles in developed and developing countries. Then we consider a lower smoothing parameter for small economies in the robustness analysis, which is discussed in appendix D. In the main text we focus on the results obtained with the HP filter, while the robustness evaluations using the BP filter are presented in appendix D. After having obtained the cyclical components of the key macroeconomic variables such as gross domestic product (GDP), gross national income (GNI), private and government consumption and investment, employment, current account, trade balance, terms of trade, real interest rates, fiscal balance, public revenues and expenditures, etc., we characterize their volatility, persistence and the patterns of cyclicality with GDP and real interest rate. This analysis provides us with a set of stylized facts about the business cycles of large versus small, developed versus developing countries, and those with and without fiscal rules in place. 4. Results Next, we turn to the business cycle statistics for our sample of countries. We are interested in characterizing the volatility of key macroeconomic aggregates, such as output, income, and employment, components of aggregate demand, external variables, and variables capturing the stance of fiscal and monetary policy; the cyclicality of these variables with output and interest rate; as well as their persistence. Trade balance, current account and fiscal balance are computed as a share of GDP. Interest rate is real lending rate computed as the difference between the lending rate and the consumer price index (CPI) inflation rate. All series (except trade balance, current account, fiscal balance, terms of trade and real interest rate) are log-transformed. To obtain the cyclical components of the variables, they are Hodrick-Prescott (HP) filtered with the smoothing parameter of 100. We also considered a lower smoothing parameter of 6.25 as advocated by Ravn and Uhlig (2002) and 16   found the results on the differences between large and small countries to remain robust. In fact, as long as the same smoothing parameter is applied to both groups of countries, the effects of size on business cycle statistics go through. After having computed the cyclical components of our series, we calculate their standard deviation, autocorrelation coefficient, and comovement with the cyclical component of GDP, and real interest rate. We begin by presenting the results for volatilities. Volatilities Table 2 summarizes the average values of percentage standard deviation of various aggregates for the groups of small and large economies, as well as the difference between them, when population is used to define country size. Appendix A discusses volatility patterns when size is measured by labor force and land area. The standard deviation of investment, employment, consumption, exports, imports, public revenues and expenditures are all reported relative to the standard deviation of GDP. As is commonly observed in the business cycles literature, aggregate investment is the most volatile variable among the expenditure components of GDP, with the relative volatility equal to around 4 on average. This number is comparable to that found in other studies. Private and government investment are more volatile than the aggregate, with the volatility of private investment equal to around 6 times that of GDP in small countries and 5 times that of GDP in large economies. The volatility of public investment is even higher at about 7 times that of GDP in both groups of economies. Public expenditures and revenues are more volatile than GDP by about a factor of 2 in both groups of countries. Note that the data on these series is missing for a large set of countries in our sample, so much so that our subsample of small countries with population below 1.5 million only contains one country. Therefore, in our comparisons for these variables we focus on the definition of smallness based on the median. Government consumption also exhibits higher volatility than GDP by a factor of about 1.9-2 in small economies; and 1.7-1.8 in large economies. Interestingly, private consumption is more volatile than GDP both in large and small economies. Both exports and imports also exhibit more volatility than GDP in both groups of countries. Table 2. Volatilities of key macro aggregates, by population % std dev <1.5m ≥1.5m diff