Report No. 50158-ECA Europe and Central Asia The Crisis Hits Home Stress Testing Households in Europe and Central Asia September 17, 2009 Office of the Chief Economist and Poverty Reduction and Economic Management Unit Europe and Central Asia Region Document of the World Bank TABLE OF CONTENTS Acknowledgements ............................................................................................................ 7 Abstract ..................................................................................................................... 9 Executive Summary ......................................................................................................... 11 OBJECTIVES OF THE STUDY .......................................................................................... 11 MAINFINDINGS ............................................................................................................. 13 CHAPTER 1 MACROECONOMIC S H O C K S ........................................................... 19 A. INTRODUCTION ...................................................................................................... 19 B. MACRO SHOCKS AND HOUSEHOLD WELFARE: FRAMEWORK.......... .... 19 c. EXTERNAL SHOCKS AND TRANSMISSION CHANNELS .......................................... 20 D. CONTEXT: MACROECONOMIC STRENGTHS AND VULNERABILITIES .................. 23 E. SHOCKS T O HOUSEHOLD WELFARE .................................................................... 28 CHAPTER 2 H O U S E H O L D V U L N E R A B I L I T I E S ................................................... 37 A . INTRODUCTION ...................................................................................................... 37 B. CONTEXT: POVERTY VULNERABILITYI THE PRE-CRISISPERIOD ........... AND N 38 c. SHOCKS TO HOUSEHOLD WELFARE: EMPIRICAL STRATEGY............... 39 D. HOUSEHOLDS AND CREDIT MARKET SHOCKS..................................................... 40 E. HOUSEHOLDS AND EXTERNAL PRICE SHOCKS .................................................... 53 F. HOUSEHOLDS AND INCOME SHOCKS .................................................................... 60 CHAPTER 3 COPING WITH THE C R I S I S................................................................ 67 A. INTRODUCTION...................................................................................................... 67 B. HOUSEHOLD RESPONSES: LESSONS ECA EXPERIENCE............................^^ FROM c. CONTEXT: POLICY RESPONSE, GOVERNMENT RESOURCESAND CONSTRAINTS69 D. IMMEDIATE POLICYRESPONSES: SOME ILLUSTRATIONS ................................... 71 E. LONGER-TERM POLICY RESPONSES .................................................................... 7~ Appendix Tables .............................................................................................................. 79 References ................................................................................................................... 87 L i s t o f Boxes . B o x 1 Definition o f E U - S I L C Variables Used in the Analysis .................. 45 . B o x 2 Stress Testing Household Indebtedness ............................................................. 48 3 . Box 3 EU-SILC and HBS Data on Household Debt: Comparisons with Other Sources...................................................................................................................... 51 . Box 4 Public Works Programs in ECA ........................................................................ 76 List o f Figures Figure 11Macroeconomic Shocks and Household Welfare: . 20 ...................................... Figure 1.2 Global Growth and Trade Slowdown 21 ......................................................... Figure 1.3 Export and Import Growth .......................................................................... 21 Figure 1.4 Gross Capital Flows ...................................................................................... 22 Figure 1.5 Contraction in BIS Creditor Bank Foreign Claims 22 ................................... Figure 1.6 Commodity Price Developments .................................................................. 23 Figure 1.7 Sharp Contractions in Industrial Production 29 ............................................. Figure 1.8 Rising Unemployment Rates ....................................................................... $29 Figure 1.9 Sharp Deceleration in Formal Remittance Inflows 30 .................................... Figure 1.10 Growth in Remittance Inflows ................................................................... 30 Figure 11 Growth Around Recent Crisis Periods: 1997-1998 and 2008-2009 .1 31 ........ Figure 1.12 "Credit-less Growth" .................................................................................. 32 Figure 1.13 Local Currency Depreciations ................................................................... 33 Figure 1.14 International Food and Energy Price Movements and Local Currency Equivalent Indices ................................................................................................... 34 Figure 1.15 CPI Food Price Sub-indices: Selected Countries 34 .................................... Figure 1.16 Local Currency Equity Market Declines Across ECA 35 .............. Figure 1.17 Housing Price in Selected ECA Countries 35 ................................................ Figure 2.1 Household Debt ............................................................................................. 41 Figure 2.2 Growth in Mortgage Debt ............................................................................ 41 Figure 2.3 The Composition o f Household Debt ........................................................... 42 Figure 2.4 Latvia Household Loan Delinquency Rates and Unemployment Rate 42 .... Figure 2.5 Foreign Currency DenominatedLoans 2008 43 .............................................. Figure 2.6 Foreign Currency DenominatedLoans in Ukraine 2008 43 ............. Figure 2.7 Mortgage Loans with Adjustable Interest Rates 2006 44 ............................... Figure 2.8 Household Debt by Income Quintile ............................................................ 46 Figure 2.9 Household Income Used For Debt Repayments 46 ......................................... Figure 2.10 Stress Testing Household Indebtedness: Selected EU-SILC Data 50 ......... Figure 2.11 Stress Testing Household Indebtedness: Selected HBS Data 51 .................. Figure 2.12 Energy Intensity and Food Consumption 1970s-2000s 53 .............. Figure 2.13 Food and Fuel Share ................................................................................... 54 Figure 2.14 Food and Fuel Imports 2006 ...................................................................... 54 Figure 2.15 Food Shares o f Consumption ..................................................................... 55 Figure 2.16 UtilitylEnergy Shares o f Consumption 56 ..................................................... Figure 2.17 Kyrgyz Republic: Net Food Consumers and Net Food Producers 59 ......... Figure 2.18 Kyrgyz Republic: Estimated Poverty Impact of the Food Crisis 59 ........... Figure 2.19 Albania: Welfare Impact ............................................................................ 60 Figure 2.20 Tajikistan: Welfare Impact ........................................................................ 60 Figure 2.21 The Impact of the Crisis on Poverty and Vulnerability 63 ............. Figure 2.22 The Impact of the Crisis on Poverty and Vulnerability 64 ............. Figure 3.1 General Government Balances in ECA 2007 and 2009 70 ............... 4 List o f Appendix Tables . Appendix Table 1 Interest Rate Shock and Borrowers at Risk ................. 79 . Appendix Table 2 Economic Shocks and Borrowers at Risk ..................................... 79 . Appendix Table 3 Economic Shocks and Borrowers at Risk ..................................... 80 . Appendix Table 4 Food Share o f Consumption ........................................................... 81 . Appendix Table 5 Utilitymnergy Share o f Consumption ........................................... 82 . Appendix Table 6 The Welfare Impact o f a 10 Percent Food Price Increase ...........83 . Appendix Table 7 The Welfare Impact o f a 10 Percent Fuel Price Increase ............84 . Appendix Table 8 Summary Data: GDP Growth and Poverty Simulations ............85 List o f Appendix Figures . Appendix Figure 1 The Impact o f the Crisis on Poverty and Vulnerability .............85 . Appendix Figure 2 FinancialMargins in Selected Countries .................................... 86 5 6 ACKNOWLEDGEMENTS This report was prepared by a core team led by Erwin R. Tiongson and including (in alphabetical . order) Anna I Gueorguieva, Victoria Levin, Kalanidhi Subbarao, Naotaka Sugawara, Victor Sulla, and Ashley Taylor. The report received generous financial support from the E C A Office o f the Chief Economist. This report was undertaken under the guidance o f Indermit Gill (Chief Economist), Luca Barbone (Sector Director), Asad Alam (former Sector Manager, currently ECCU3 Country Director) and Benu Bidani (Sector Manager). The report draws heavily from several background notes and papers including those prepared by Victoria Levin (lessons from previous E C A crises) and Kalanidhi Subbarao (public works programs). It also draws from an ongoing research project conducted by members o f the team together with Thorsten Beck and Katie Kibuuka on household indebtedness in Europe and the CIS. The research project i s financed by the DECRG Research Support Budget (RF-P115252- RESE-BBRSB). Kechen Chen conducted an initial analysis o f the Kazakhstan H B S data in July and August 2008. The team received valuable comments and suggestions at the Concept Note, Decision Draft, and other stages o f the preparation process from Peer Reviewers and numerous colleagues. These include (in alphabetical order): Mohamed Ihsan Ajwad, Emanuele Baldacci (IMF), Lawrence Bouton, R. Sudharshan Canagarajah, Sanjeev Gupta (IMF), Ardo Hansson, Jesko S. Hentschel, Valerie Herzberg, Christos Kostopoulos, Kathy Lindert, Pradeep Mitra, Fernando Montes-Negret, Pierella Paci, Stefan0 Paternostro, Bryce Quillin, Sophie Sirtaine, and Marijn Verhoeven. Paloma Anos Casero provided many useful suggestions during the early stages o f this study. Salman Zaidi offered generous advice at various stages o f the preparation process. M. Willem van Eeghen provided valuable guidance in preparing the final version o f this report. A number of individuals generously shared the results o f their ongoing empirical analyses and/or their data, including (in alphabetical order): Carlo Azzarri (DECRG), Diiniel Ho116 (Magyar Nemzeti Bank), Kotaro Ishi (IMF), Alejandro Izquierdo (IADB), Sarosh Sattar (ECSPE), Emil Tesliuc (HDNSP), Marijn Verhoeven (PRMPS), Olga Vybornaia (ECSPE), and Albert0 Zezza (FAO). This report also draws from many o f the ideas first discussed at the World Bank Workshop on Macro Risks and Micro Responses (held in Washington, D C on February 15, 2008). The team i s grateful to the workshop participants, including presenters from the European Bank for Reconstruction and Development, the European Central Bank, the International Monetary Fund, the Center for Strategic Research (Moscow), the National Bank o f Poland, and the Economic and Financial Risk Unit o f the World Economic Forum. 8 ABSTRACT The crisis threatens the welfare o f about 160 million people in the Europe and Central Asia (ECA) region who are poor or are just above the poverty line. Using pre-crisis household data along with aggregate macroeconomic outturns to simulate the impact o f the crisis on households-transmitted via credit market shocks, price shocks, and income shocks-this report finds that adverse effects are widespread and that poor and non-poor households alike are vulnerable. By 2010, for the region as a whole, some 11 million more people will likely be in poverty and over 23 million more people will find themselves just above the poverty line because o f the crisis. The aggregate results mask the heterogeneity o f impact within countries, including the concentration o f the poverty impact in selected economic sectors. Meanwhile, stress tests on household indebtedness in selected countries suggest that ongoing macroeconomic shocks will expand the pool o f households unable to service their debt, many o f them from among the ranks o f relatively richer households. In fact, already there are rising household loan delinquency rates. Finally, there i s evidence that the food and fuel crisis i s not over and a new round o f price increases, via currency adjustments, will have substantial effects on net consumers. Lessons from last year's food crisis suggest that the poor are the worst hit, as many o f the poor in Albania, Kyrgyz Republic, and Tajikistan, for example, are net food consumers, with limited access to agricultural assets and inputs. The resilience o f households to macroeconomic shocks ultimately depends upon the economy's institutional readiness, the flexibility o f the economic policy regime, and the ability o f the population to adjust. However, compared with previous crises, the scope for households to engage in their traditional coping strategies may be more limited. Fiscal policy responses in the short-term are also constrained by rapidly falling revenues. Governments in E C A have to make difficult choices over what spending items to protect and what items to cut, social protection programs to reform and scale-up, and new interventions to mitigate the impact o f the crisis. 9 10 EXECUTIVE SUMMARY 1. The Europe and Central Asia (ECA) region has been hit by a crisis on multiple fronts. Countries in E C A are facing major, interrelated, external macro-financial shocks. The first i s the global growth slowdown leading to falling export market demand. In addition, the prospects for inflows o f remittances to low-income countries have been downgraded as economic activity in migrant host countries has declined. The second i s the financial deleveraging by major banks and other financial institutions in developed economies, which has markedly reduced the availability, and increased the cost, o f external finance across public, corporate and financial sectors. The third i s the recent commodity price changes, which have involved a reversal o f much o f the commodiv price boom o f 2007 and 2008. As a result, countries whose exports are focused on commodities have suffered adverse terms o f trade pressures, in addition to the quantity shock to export demand. Across countries in the region, unemployment levels have risen while economic activities have collapsed. 2. The crisis risks reversing the region's recent gains and exposes ECA to significant adverse economic and social impacts. Over the recovery period following the 1998 Russian crisis through 2006, over 50 million people moved out o f poverty in the region. Poverty fell throughout all the sub-regions o f ECA, with the middle-income countries o f the Commonwealth o f Independent States (CIS) experiencing the largest declines in poverty. Poverty reduction in E C A has been driven largely by growth in mean incomes and rising real wages among the working poor. However, the rapidly deteriorating global economic environment i s eroding the region's substantial recent gains, and i s threatening the welfare o f about 160 million people- close to 40 million people who are poor and about 120 million people who are just above the poverty line. OBJECTIVES OF THE STUDY 3. The objective o f the study i s to understand the impact o f these macroeconomic shocks on household well-being. In particular, it seeks to understand the key macroeconomic shocks confronted by the region and the impact o f such shocks o n household welfare, including the effect on household income flows, consumption levels, and liabilities. It will also assess possible strategies to cope with the crisis and manage the adverse social impact. 4. The report examines household vulnerabilities along three main transmission channels. Figure 1 represents a stylized diagram for understanding the impact o f macroeconomic shocks to date on household welfare. It reflects a summary o f the emerging conceptual and empirical understanding o f the social effects o f macroeconomic crises experienced in various parts o f the world over the last three decades. In brief, the diagram focuses on three main channels through which major macroeconomic shocks-such as the regional growth slowdown or the credit crunch-are transmitted to household welfare. These are the income and employment o f members o f the household; the relative prices o f goods and services they purchase; and their access to finance (including the cost o f credit and the burden o f servicing debt). 11 Figure 1: Macroeconomic Shocks and Household Welfare: Stylized Transmission Channels Income and Macro Shock Access to Credit Market) 5. The diagram i s stylized and abstracts from several important elements. It i s simplified and ignores second-round effects, the consequences o f multiple shocks, and does not indicate how the social effects are distributed. Neither does the diagram take into account the role of wealth effects as a transmission channel of the crisis to households, for example, via changes in the prices o f property, the value o f equity holdings (directly or in pension funds) or indeed expectations o f future labor income. Changes in wealth may directly lead to adjustment in the consumption behavior o f households or indirectly through the role o f certain assets, such as property, as collateral that affects a household's ability to access credit. The heterogeneous asset positions o f households mean that such wealth changes will lead to redistributions within the household sector, for example, between those long or short in a particular asset. Unfortunately, lack o f data on household wealth levels, and composition, precludes detailed stress testing o f such wealth effects. However, the build-up o f mortgage indebtedness detailed in the report provides some, indirect, insight into the growing exposure o f households' asset positions to property holdings. The above diagram also does not address the role o f government policy (including fiscal and monetary) and social assistance (though social assistance may be thought o f as a source o f income). Government policy can, in fact, either mitigate shocks or exacerbate them, depending on'how they are formulated and implemented. A further transmission channel o f the real and financial impacts of the crisis through to household welfare, though not explicitly addressed, i s via pension provision. The nature and magnitude o f the effects o f the crisis via this channel depend crucially on the structure o f the pension system, in particular the mix between pay-as- you-go (PAYG), funded and voluntary pension systems. 6. The report analyzes household vulnerabilities by examining credit markets, external prices (food and fuel), and income shocks to date and by assessing their impact on hopsehold welfare. Because actual household survey data over the crisis period will typically not be available for some time to come, we use the most recent pre-crisis household data along with aggregate macroeconomic outturns to simulate the impact on households of key economic shocks already taking place. The impact on household well-being i s quantified as the change in the household debt service burden, the fall in real income, or movements into poverty, as appropriate. The report presents regional overviews along with cross-country comparisons and contrasts. I t also presents selected country examples, depending on data availability and relevant economic developments, to illustrate the incidence and distribution o f specific vulnerabilities within countries. 12 7. The microeconomic simulation in the report draws on a large, cross-country database o f household surveys. The report brings together for the first time comparable cross-country data on household indebtedness for a large group o f E C A countries using the EU Survey o f Income and Living Conditions (EU-SILC) and Household Budget Surveys (HBS). The report also highlights newly updated information on household consumption from the E C A Household Data Archives. Comparisons with Western Europe and other advanced economies are also used to inform the analysis when relevant data are available. A NN S N I I MI FDG 8. The results o f the analysis suggest that the adverse effects o f the crisis on households- via credit market shocks, food/fuel price shocks, and income shocks-are widespread. Both poor households and non-poor households are vulnerable depending on the economic shock, the specific transmission channel, and on selected household characteristics. Credit Market Shocks 9. The rapid rise in household Household Debt in ECA 2008 indebtedness-in the new EU member states (In percent o f GDP) as well as in some Western Balkan 6o countries, such as Albania and Serbia, and 50 40 CIS countries such as Ukrainehas exposed 30 households to a number o f credit market 2o shocks. There i s no doubt that household debt 10 holding has improved the lives o f many, 0 allowing them to smooth consumption and share risks, purchase durables and invest in housing stock. At the same time, the nature o f household debt in E C A i s such that households 10. Within countries, household indebtedness i s more common than previously understood. Mortgage loans, in particular, have grown rapidly in recent years among poorer and middle-income households in a number o f EUlO countries. Both poor households and non-poor households are exposed to the risks o f unsustainable debt service burdens. 11. The results o f stress tests on household The Share o f Vulnerable Households indebtedness in selected countries suggest Beforeand AAeran UnemploymentShock (In percento f indebtedhouseholds) that ongoing macroeconomic shocks may After the Shock 0 Before the Shock significantly expand the pool o f households 40 ~-~______.______ ____ ___I_~ ___-_- , that will be unable to meet debt service obligations. Interest rate shocks in Estonia, Lithuania and Hungary, for example, increase the share o f vulnerable households or borrowers at risk (in percent o f all indebted households) by up to 20 percentage points, depending on the magnitude and severity o f the shock. Unemployment and exchange rate shocks also expand the share o f vulnerable households (out o f all indebted households) by several percentage points. Many o f those household borrowers at risk o f unsustainable debt burdens are 13 from the richer income quintiles. Although the shares o f indebted households and households at risk in the ECA region s t i l l lag behind those o f richer countries, the aggregate effects o f rising debt service burdens are already being seen in rising household loan delinquency rates, as unemployment has increased. External Price Shocks 12. The food and fuel crisis may not be over. Food and fuel prices have abated worldwide because o f the worsening global financial crisis, the economic recession or slowdown in many countries across regions and, as a result, global demand for commodities has fallen. In addition, increased agriculture production activity led to a bountiful 2008 harvest and eased global commodity shortages. However, international commodity price levels have not returned to pre- 2007 levels. Specialists have also pointed to longer-term challenges in global food production that are yet to be addressed. In addition, falling currencies in some EUlO countries are resulting in a new round o f price increases, depending on the share o f imported food and fuel in local consumption and the degree o f pass-through o f exchange rate changes in domestic prices. Finally, in a number o f countries such as Belarus, Moldova, and Ukraine, the utility reform program remains largely incomplete. As a result, for reasons o f economic efficiency or fiscal consolidation, a number o f countries will have adjust their tariffs to cost-recovery levels in the coming years. Kyrgyz Republic 13. There i s significant heterogeneity Poverty and the Food Price Crisis within countries in the welfare impact o f commodity price shocks. The net effect o f a mBefore the Cnsis I A f t e r the Crisis _ - -- I _ food price shock depends on whether households are net producers or net consumers 2 20 d . o f food, it depends on their intensity o f food 4 c 15 consumption and the availability o f cheaper 10 substitutes, and it depends on their livelihood e, g 5 strategies, access to agriculture assets and 0 inputs and their ability to take advantage o f N e t Consumers Net Producers profitable opportunities in agriculture. These multiple considerations suggest that, at least in principle, the poor are not necessarily the hardest hit. However, the food share o f total household consumption typically falls with income; in some o f the low-income countries in the region, the food share o f consumption among the poor i s 70-80 percent. Moreover, in reality, the poor are the worst hit, as many o f the poor in Albania, Kyrgyz Republic, and Tajikistan, for example, are also observed to be net consumers, with limited access to agricultural assets and inputs. Income Shocks The Poor and Vulnerable Population 2007-2010 (Using the $5-a-day measure o f poverty) 14. Poverty will rise. Simulations suggest that by 2010, there will be 11 million more +Pre-crisisprojection +Latestprojection people in poverty and over 23 million more 170 I people will find themselves just above ECA's international poverty line, relative to baseline pre-crisis projections. The growth in poverty would represent a fifth o f the E C A population who moved out o f poverty between 1998 and 2006. This i s not surprising given that poverty ."- . 2007 2008 2009 2010 14 in E C A i s shallow, characterized by large numbers o f individuals susceptible to falling into poverty even with modest falls in average income. Alternatively, one could think o f them as the recent-poor, with tenuous links to the labor market, little precautionary savings, and who are likely to have benefited from recent credit and construction booms. 15. The magnitude o f the poverty impact varies by sub-regions. The middle-income CIS countries, on average, have seen the largest and most significant downward revisions to their GDP growth projections. As a result, and by construction, they are also seeing the largest percentage point increases in the projected poverty headcount. They are followed closely by the low-income CIS. 16. The aggregate results mask the heterogeneity of impact within countries, including the concentration of the poverty impact in selected economic sectors. Country studies recently completed suggest that for economic shocks transmitted primarily through the labor market, poverty will rise especially among households that have been dependent on remittance inflows and those previously employed in booming construction sectors where economic activity i s now projected to decline sharply. 17. The results o f the analysis are indicative o f how vulnerabilities are distributed across countries and, within countries, across broad types o f households. In some ways, the estimated effects may be understated because they capture only some o f the first-round effects. On the other hand, general equilibrium effects will either dampen or worsen some o f these effects. 18. The second-order effects on human capital accumulation and social capital will be significant. Lessons from the region's own experiences suggest that transitory shocks' long-term toll on human capital has been substantial because families curbed their education and health investments in response to a banking or exchange rate crisis. Crises may lead to increased social unrest, criminal activity and human trafficking, disrupt communal and ethnic relations, or bring down fragile governments and fledgling democracies. Coping with the Crisis 19. Compared to previous crises, the scope for households to engage in their traditional coping strategies may be more limited. During previous crises, households found secondary employment, relied on transfers from friends and families, or left for work abroad to augment family income. Because o f the global nature o f the crisis, and because macroeconomic shocks are hitting households on multiple fronts, many o f these coping strategies are n o longer viable. For the poorest households, subsistence farming may s t i l l be feasible, though evidence from the recent food price shock suggests that many o f the poorest households do not have access to agricultural assets and inputs. For some, transitions into informal sector employment may be possible, though for many households, earnings from informal sector activity will be insufficient t o offset the poverty impact o f the crisis. Policy Responses 20. Fiscal policy responses in the short-term are constrained by rapidly falling revenues. Substantial government deficits are currently projected for the region. It would be essential to determine the overall fiscal adjustment warranted for macroeconomic stability and debt sustainability, taking into account initial conditions and the likely impact o f the crisis o n public finances. Economies that experienced strong initial fiscal and external positions are likely to 15 have more room for expansionary fiscal policy and can afford a fiscal stimulus package, while those with weaker initial positions may require substantial fiscal adjustment. Where there are no new official or alternative sources o f financing and little scope exists to mobilize revenues, some countries will likely resort to across-the-board cuts in spending. Although social safety nets will be among those items likely to be cut as revenues fall, protecting these programs-and possibly expanding some o f them, where some reallocation o f resources i s possible-will be an important element in the response to the crisis. 2 1. Inappropriate policy responses to economic shocks may have welfare consequences far larger than the welfare losses resulting directly from the shocks themselves. In 2007-08, some countries imposed trade restrictions and price controls in response to rising food prices. Such policies redistribute income away from rural food producers (who tend to be poorer) to urban consumers (who tend to be richer). The net social impact may be even larger when considering the impact o f such policies on production incentives and the likely spillover impacts o f restrictive trade policies on neighboring countries, thus exacerbating regional welfare consequences. 22. The region's social assistance systems vary in size and targeting performance and not every program can and should be scaled up. In addition, some o f these programs will have to be cut as revenues fall. The response to the crisis will vary across countries and may include, among other things, expanding some well-performing programs and reforming relatively less effective interventions. Some o f those who will fall into poverty because o f the crisis-the "new poor"-may not be easily reached by existing social protection programs. For example, returning migrants do not qualify for unemployment insurance. 23. The ECA region should consider new instruments o f social protection. Social safety nets in E C A need to be strengthened to handle the challenges o f global and domestic risks. The experiences o f other countries suggest that programs such as workfare and public works programs can be appropriate instruments for protecting the vulnerable from immediate as well as longer- term (second-round) consequences o f transitory shocks on non-income dimensions o f welfare, including human capital accumulation. There are a few, albeit limited, country experiences with workfare in ECA-in Bulgaria, Poland, the Slovak Republic, and Slovenia. Some insights from these country experiences can inform the broader application o f workfare in E C A so that they can be efficient instruments for social risk mitigation while minimizing displacement effects. 24. The prioritization o f labor-intensive public investments could be an important response to the crisis while creating the conditions for medium-term growth. Such a strategy can create employment opportunities, as in workfare and public works programs, while creating the infrastructure that supports economic recovery and economic growth in the medium-term. Longer-Term Policy Responses 25. Over the longer term, there are various measures for limiting the risks borne by households as financial markets deepen. On the demand-side, promoting financial literacy may help households to understand the risks they expose themselves to because o f their consumption, employment, or borrowing choices. In addition, a whole host o f macro-financial policies, such as prudential norms as adopted by some EUlO countries to limit foreign currency exposures o f households, can be used in combination to help mitigate the potential risks associated with increased exposures o f households to credit and financial markets. 16 26. I t i s important that policy responses do not conflict with the key longer-term reform agenda. For example, authorities should guard against reversal o f efforts to lower quasi-fiscal deficits in the energy sector, which i s an ongoing challenge in many E C A countries, and they should maintain an open and transparent trading regime. Some countries in E C A adopted restrictive trade and price controls in response to the food price increases in 2007 but many o f them have now been reversed. 27. Diversified sources of economic growth will be critical in helping dampen ECA countries' vulnerability to macroeconomic shocks. In some countries in ECA, recent growth performance has been underpinned by economic activity concentrated in a few sectors, such as the housing or construction sector, or income flows from some dominant source, such as migrant labor. 28. Monitoring systems are important. Guaranteeing that statistical monitoring systems are in place and that relevant household data are collected regularly and made available for analysis are important measures for ensuring that household vulnerabilities to a range o f potential shocks are understood in a timely manner and that those households at risk can be reached by a country's social protection system. 29. The resilience o f households to macroeconomic shocks ultimately depends upon the economy's institutional readiness, the flexibility of the economic policy regime, and the ability of the population to adjust. Policy and institutional preparedness i s essential so that countries can manage the adverse social impacts o f macroeconomic shocks. This requires ex ante analysis o f risks, a good understanding o f their possible transmission channels if triggered, and their possible impacts on households; developing approaches that ensure that the state does not intervene excessively in terms o f detrimental longer-term distortions to incentives or fiscal sustainability; and having a comprehensive social safety net system that provides far countercyclical and scalable interventions. 17 18 CHAPTER 1 MACROECONOMIC SHOCKS A. INTRODUCTION 1.1 The Europe and Central Asia (ECA) region has been hit by a crisis on multiple fronts. The first i s the global growth slowdown leading to falling export market demand. In addition, the prospects for inflows o f remittances to low-income countries have been downgraded as economic activity in migrant host countries has declined. The second i s the financial deleveraging by major banks and other financial institutions in developed economies, which has markedly reduced the availability, and increased the cost, o f external finance across public, corporate and financial sectors. The third i s the recent commodity price changes, which have involved a reversal o f much o f the commodity price boom o f 2007 and 2008. 1.2 This chapter examines how the external shocks arising from the global economic crisis can be transmitted through to macro shocks affecting the welfare of households, via their income, access to credit, wealth and relative prices o f food and fuel. Section B first introduces a simple stylized framework o f the transmission channels, which provides the structure for the subsequent discussion. Section C examines the external shocks and their transmission channels to countries within the region. The nature, and extent, o f the transmission o f these shocks through to households depends crucially on an economy's macroeconomic strengths and vulnerabilities, such as the degree o f international integration, the strength o f sectoral balance sheets and domestic policy stance, which are discussed in Section D. Finally, Section E outlines the main resulting macro shocks to household welfare, the micro implications o f which are analyzed in subsequent chapters. B. MACRO WELFARE: FRAMEWORK SHOCKS AND HOUSEHOLD 1.3 Major macroeconomic shocks are transmitted through to household welfare via various mechanisms of which this report focuses on three main channels. Figure 1.1 represents a highly stylized diagram for understanding the impact o f macroeconomic shocks on household welfare. It reflects a summary o f the emerging conceptual and empirical understanding o f the social effects o f macroeconomic crises experienced in various parts o f the world over the last three decades. The main channels considered are the income and employment o f members of the household; the relative prices o f goods and services they purchase; and their access to financial market (including the cost o f credit and the burden o f servicing debt). As discussed below, in the current context the shocks to household welfare via these channels have arisen primarily due to the impact o f external shocks, for example to global income, credit conditions and commodity prices, whose effects depend crucially on the domestic economy's macro strengths and vulnerabilities. 19 Figure 1.1 Macroeconomic Shocks and Household Welfare: Stylized Transmission Channels Income and Employment (Labor Market) t Macro Relative Prices (Product Market) Shock 5 Access to Credit (Financial L Market) 1.4 The diagram i s stylized and abstracts from a few important elements. I t ignores second-round effects (such as on human capital accumulation, access to social services, and disruptions to communal ties), the consequences o f jointly occurring crises, and, as drafted, does not indicate how the social effects are distributed (along geographic, occupational, sectoral, gender, or income lines), though all these will be considered in varying degrees below. Neither does the diagram take into account the role o f wealth effects as a transmission channel o f the crisis to households, for example via changes in the prices o f property, the value o f equity holdings (directly or in pension funds) or indeed expectations o f future labor income. Changes in wealth may directly lead to adjustment in the consumption behavior o f individual households or may do so indirectly via the role o f certain assets, such as property, as collateral that affects their ability to access credit. The heterogeneous asset positions o f households mean that such wealth changes are likely to lead to redistributions within the household sector, for example between those long or short in a particular asset. Unfortunately, lack o f data on household wealth levels, and composition, precludes detailed stress testing o f such wealth effects. However, the build-up o f mortgage indebtedness detailed in the report provides some, indirect, insight into the growing exposure of households' asset positions to property holdings. The above diagram also does not address the role o f government policy (including fiscal and monetary) and social assistance (though social assistance may be thought o f as a source o f income). Government policies can, in fact, either mitigate shocks or exacerbate them, depending on how they are formulated and implemented. c. SHOCKS AND TRANSMISSION EXTERNAL CHANNELS' Global Income 1.5 Since 2006, the growth o f the major developed economy countries, and world export demand, has weakened as the global credit crisis, which began in the summer of 2007, unfolded. The IMF's April 2009 World Economic Outlook projected a contraction in world growth o f 1.3 percent in 2009 with growth recovering to 1.9 percent in 2010 (Figure 1.2). These For a discussion o f the origins of these shocks, and their global implications, see, for example, IMF WE0 (October 2008, April 2009), IMF Global Financial Stability Report (October 2008, April 2009) and, for a particular focus on commodity price movements see the World Bank Global Economic Prospects (2009). 20 shocks to global income may be transmitted to countries within the region via trade flows and remittances. Demand for exports from the region has fallen sharply, with the GDP o f advanced economies projected to contract by 3.8 percent in 2009. At the same time, the credit crunch i s also impeding the ability to finance export trade credits. As a result, the World Bank's 2009 Global Economic Prospects predicts that world trade will decline in 2009 for the first time since 1982 (with the IMF April 2009 WE0 projecting an 11 percent contraction in the volume o f world trade in goods and services in 2009). The impact o f these trends on trade for E C A countries has resulted in a precipitous drop in export and import values (Figure 1.3). As discussed in more detail later, remittances have already fallen sharply in some countries and prospects for 2009 inflows o f remittances to developing countries have been downgraded as economic activity in migrant host countries has declined. For many countries in ECA, particularly those in the f0rme.r Soviet Union, this reflects the impact of the slowdown in Russia, and the valuation effects o f the nominal depreciation o f the ruble, i.e. a second-round regional shock, rather than being directly due to the slow-down in developed markets. Figure 1.2 Global Growth and Trade Figure 1.3 Export and Import Growth Slowdown (In percent) (In percent) Growthyear-on-year, percent Annual real growth, percent 50 40 30 20 10 0 -10 -ECAExports -20 ---ECAImports -30 -World Exports -40 -5n _I World US EU World trade Jan-03 Jan-05 Jan-07 Jan-09 GDP GDP GDP volume Source: IMF WE0 October 2008 and April Source: WB DECPG and staff calculations. 2009. Note: Change in U S dollar seasonally adjusted Note: 2009 and 2010 are projections. values. Trade defined as volume o f goods and services. Global Credit Conditions 1.6 As the financial crisis deepened from September 2008, mounting concerns over liquidity risk, asset quality and counterparty credit risk and enhanced risk aversion have resulted in significant deleveraging and attempts to reduce portfolio risk by financial institutions. This has affected not only the ability of financial institutions and corporates in developed economies to obtain financing but also led to a retrenchment o f the international exposures o f banks and, for many countries, a sharp reduction in their ability to access international finance. Gross capital flows to emerging and developing economies have fallen significantly (Figure 1.4). The contraction, which has been across asset classes, has been particularly marked for E C A (whose share o f such flows fell from around 40 percent in 2007 and 2008 to just over 20 percent in H 1 2009). In terms o f international banking exposures, after peaking at end-March 2008, the consolidated foreign claims o f BIS creditor banks, in real terms, 21 on OECD economies f e l l by around 20 percent to end-March 2009 (Figure 1S ) . Real BIS creditor banks' foreign claims on emerging economies generally peaked at end-June 2008 and by end- March 2009 had fallen by 17 percent for E C A compared with around 12.5 percent for Latin American and the Caribbean and East Asia and Pacific. Figure 1.4 Gross Capital Flows Figure 1.5 Contraction in BIS Creditor to Emerging and Developing Economies Bank Foreign Claims (In billions o f U S dollars) (InQ1 2009 prices) -Europe & Central Asia -High-income OECD excluding ECA East Asia& Pacific ---Latin America& Caribbean I50 10s 100 8 1 :: ; : l 50 0 4Q I 1; 60 4 Dec-06 Jun-07 Dec-07 Jun-08 Dec-08 Source: DECPG. Source: BIS, IMF International Financial Statistics and staff calculations, Note: U S dollar values deflated by U S CPI. 2009 Q1 data are preliminary estimates. 1.6 Regional equity and exchange rates came under pressure during late 2008 as foreign investors drew back funds from the region, and concerns over the domestic impact o f the financial crisis mounted. Despite somewhat o f a reversal in recent months, the downturn in financial markets in ECA since early 2008, and since September 2008 in particular, has been widespread and deep across asset classes and countries. These declines unwound a large part o f the gains made in equity and sovereign bond valuations during the asset price run-up o f preceding years (in which the average dollar value o f the M S C I Emerging Europe equity index increased by over seven times from October 2001 to December 2007). The reduced demand for emerging market assets also contributed to marked local currency nominal depreciations as discussed in detail below. Secondary market credit spreads also increased substantially. The JP Morgan EMBIG EmergingEurope sovereign spread increased from 275 basis points on 1 September 2008 to over 900 basis points in late October. Having declined t o 740 basis points by end-2008, the spread continued to narrow through 2009, with the average monthly spread reaching around 400 basis points in July 2009. Similarly, the cost o f credit default protection via credit default swaps (CDS) and external corporate funding rates increased sharply. For example, the JP Morgan C E M B I external corporate spread for emerging Europe (covering Kazakhstan, Russia and Ukraine) increased from 530 basis points to 1560 basis points at end-2008 before declining to an n average of around 730 basis points in July 2009. I addition to the falls in bond and equity markets, interbank markets exhibited rising spreads in October and November reflecting international funding pressures and domestic liquidity concerns. 22 Global Commodity Prices I Figure 1.6 Commodity Price 1.7 The global growth slowdown has I Developments contributed to a sharp easing in global food, -Oil price spot, US$per barrel fuel and other commodity prices since mid- * Food price index (June 2007=100) 2008. Although making projections i s Energy price index (June2007=100) particularly difficult given the current macro- Steel products price index (June 2007=100) financial uncertainty, the June 2009 World Bank Global Development Finance forecasts a 43 200 175 +,f.-. + . 1 S percent fall in the U dollar o i l price in 2009 relative to 2008, with a rise o f 13 percent in 2010. Non-oil commodity prices are projected to fall by 30 percent in 2009 with a further 2 percent decline in 2010. In recent months, there has been some recovery in some commodity prices, such as o i l (Figure 1.6). Clearly, the overall impact o f these price movements on a 25 - country's external payment position i s dependent 0 8 upon their net consumption mix and respective Jun-07 Dec-07 Jun-08 Dec-08 Jun-09 export and import price elasticities. Countries whose exports are focused on commodities have Source: WJ3 DECPG and staff calculations. thus suffered adverse terms o f trade pressures, in Note: Oil price i s a simple average of Brent, addition to the quantity shock to export demand. West Texas Intermediateand Dubai crude oil For example, while the weakening o i l price has prices. had material implications on external and fiscal positions in Russia and Kazakhstan, the downturn in steel prices adversely affected the external outlook for countries such as Ukraine with the rapid fall in fertilizer prices having similar impact in economies such as Belarus. D. CONTEXT: MACROECONOMIC STRENGTHS AND VULNERABILITIES 1.8 The impact on a country's economic outlook of the above external shocks depends upon its potential exposure, which can be mapped through different stages of the transmission mechanism. The first i s the extent o f international integration o f the country via trade and financial channels (including remittances). The second i s the structure and health o f sectoral balance sheets, for example in terms o f external financing requirements, currency and maturity mismatches. The third stage i s the ability o f policymakers to mitigate the impact o f the shock through the policy stance in terms o f monetary policy, exchange rate flexibility and, linked to the strength o f public sector balance sheets, the current fiscal stance and the ability to use fiscal policy measures to absorb the impact o f the global shocks. International Integration 1.9 The increasing international integration of countries in ECA over the past decade via trade, income and capital flows has enabled countries to benefit from the growth and financing o f partners but also provides increasing channels through which global and regional shocks are transmitted to domestic economies. Over the past decade, the ratio o f the total U dollar value o f merchandise trade (exports plus imports) o f countries in E C A to their S GDP has increased from around 45 percent in 1998 to 57 percent in 2007. This follows the general growth in global trade over this period. However, there are marked variations in the level o f trade openness across sub-regions in ECA. For example, over this period the merchandise 23 trade for the new EU member states in Central Europe and the Baltics (the EU8) rose from 70 percent to 107 percent while for middle income CIS the ratio was broadly flat over this period. 1.1,O I n addition to the variation in the level of trade openness within the region, there are considerable differences in the patterns of trade partners and major trading products across sub-regions, as.would be expected from gravity-type models of trade flows. The importance o f the EU as an export market, and hence the exposure o f countries to the contraction in demand from the EU as a result o f the crisis, i s particularly marked in the EU members o f ECA, south-east Europe and Turkey. The extent o f intra-regional trade linkages within E C A i s particularly high between the middle- and lower-income CIS countries. In terms o f major product categories, the exports o f these two groups o f countries are highly concentrated in petroleum and petroleum products (around 44 and 53 percent o f total exports in 2007 respectively) whose international prices have dropped for their mid-2008 highs. Iron and steel export earnings in the former sub-region and Southeastern Europe are also vulnerable to the commodity price and activity downturns (accounting for just under 10 percent o f exports in both cases). Trade patterns in the EU8 are strongly intra-industry and particularly focused on consumer durables including products such as road vehicles (around 15 percent o f exports and 10 percent o f imports) and electrical and telecoms equipment which again are subject to strong demand shocks as consumption falls in partner regions. 1.1 1 Net capital flows to the region doubled as a proportion of GDP from 2002 to 2007, financing consumption and investment while increasing the impact of any sudden stops to such flows. From a level o f around 4 percent o f GDP in 2002-2004, net capital flows to E C A increased to around 8 percent o f GDP in 2007 buoyed by factors including the global search-for- yield, the EU accession process and FDI related to commodity investments. This broad pattern o f growth in relative flows was present across sub-regions. The mean level o f net capital flows to GDP across countries reached over 15 percent in Southeastern Europe and over 10 percent in the EU 8. Although the mean level f e l l in low-income CIS countries this reflected net capital outflows from Azerbaijan. 1.12 Increased cross-border lending and foreign bank ownership have both contributed to the sharp rise in international banking claims on ECA. The level o f gross international assets o f BIS creditor banks in ECA, on a locational basis, rose from around 13 percent o f GDP at end-2004 to 21 percent o f GDP at end-2007. There are considerable variations across sub- regions with the CIS countries having net claims on BIS creditor banks for most o f the period from 2003. In contrast, the net assets o f BIS creditor banks on the Baltics reached over 70 percent o f GDP in early 2008 (up from 30 percent in mid-2005) with levels o f around 40 percent o f GDP on the EU5 and Southeastern Europe. These figures compare to net assets o f BIS creditor banks on the five Asian crisis countries (Indonesia, Korea, Malaysia, Philippines and Thailand) o f ' around 20 percent o f GDP in mid-2007. 1.13 The rise in consolidated foreign claims o f BIS creditor banks (Le. netting out intra- group exposures) in recent years has been particularly marked in ECA's EU member states and Southeastern Europe, increasing the potential for two-way spillovers between local and Western-European banking systems. Foreign claims on ECA, which include international claims (i.e. cross-border claims plus local claims o f foreign affiliates in foreign currency) and local claims o f foreign affiliates in local currency, peaked at around 45 percent o f GDP at end June-2008, up from around 30 percent in the two years from June-2008, before falling to around 35 percent o f GDP by end-2008. In 2008, foreign claims on the Baltic countries peaked at almost 140 percent o f GDP, Southeastern Europe at over 100 percent and the EU5 (the Czech Republic, Hungary, Poland, Slovak Republic and Slovenia) at over 80 percent o f GDP. M u c h o f this 24 increase has been due to the growth in local claims o f western European foreign affiliates. The level o f foreign claims to GDP on the EU8 and Southeastern European countries at end-2008 remain considerably higher than the averages for OECD countries and indeed that observed for the Asian-crisis countries at end-1997. International claims tend to be concentrated on the non- bank private sector and banking sectors rather than the public sector with the share o f short-term international claims relatively high in Turkey and the middle-income CIS countries. The geographic patterns o f banking sector inter-linkages via foreign claims have evolved in a different manner across sub-regions. While all regions have seen a relative reduction in the share o f German banks in their foreign claims, Swedish banks are the primary foreign claim creditor in the Baltics and the share o f Austrian claims has risen in the Central European new member states o f the EU, the middle-income CIS and Southeastern Europe. 1.14 Remittance inflows have grown rapidly over the past five years and for lower- income economies in ECA outweigh the intra- and extra-regional financial inter-linkages via private capital flows. The dollar value o f remittance inflows to E C A grew at an annualized growth rate o f around 37 percent between 2003 and 2007 versus around 19 percent per annum for developing countries as a whole. O f those countries with high inflows o f remittances relative to GDP, annualized growth rates o f remittance inflows o f 32 percent were seen for Moldova, 66 percent for Azerbaijan, 74 percent for the Kyrgyz Republic and 84 percent for Tajikistan. In such countries, the level o f external financial inflows from remittances far exceeds that o f capitzil inflows, exposing countries to reductions in employment and wages in migrant host countries more than direct exposures to developments in international financial markets. For example, in Tajikistan and Moldova in 2007 it i s estimated that remittance inflows to GDP were around 46 percent and 34 percent respectively compared with net capital inflows o f around 10 percent o f GDP. 1.15 For many countries, particularly in the lower-income CIS, the exposures to recent external shocks come particularly via their second-round regional impact, for example ip terms o f remittances and trade flows with Russia. For ECA's EU member states and Southeastern Europe, financial, particularly banking, and trade integration developments highlighted the increasing interdependences with economic developments in Western Europe and global financial conditions. However, the patterns o f trade and importance o f remittances for lower-income CIS focus attention on the potential for intra-regional spillovers arising from developments in Russia. For example, exports to Russia accounted for around 35 percent o f Belarus' exports in 2007 (or roughly 20 percent o f GDP) and around a quarter o f the exports o f Kyrgyz Republic, Moldova, Ukraine and Uzbekistan. Similarly, in 2007 flows from Russia accounted for almost all the remittance inflows for the highly remittance-dependent economies of Kyrgyz Republic and Tajikistan and over half the remittances to Moldova. As Russia's economy grew strongly between 2003 and 2007 (with annual GDP growth in the range o f 6.4 to 8 percent), these inter-linkages led to strong positive spillovers to partner countries. The flipside i s the exposure o f these countries to any downturn in Russia (with the World Bank's June 2009 Russian Economic Report forecasting a real GDP contraction o f 7.9 percent in 2009 with growth o f 2.5 percent in 20 10). Balance Sheet Strengths and Weaknesses 1.16 The composition and strengths o f domestic sectoral balance sheets are crucial determinants o f the impact on the economy of external shocks transmitted via the various international inter-linkages discussed above. O f particular interest in E C A have been the interrelated developments in household and financial sector balance sheets over the past five 25 years relating to increasing household indebtedness and their exposures to currency and interest rate shocks. 1.17 Household indebtedness has grown rapidly in many ECA countries. Between 2002 and 2007, for example, household debt relative to GDP grew at an annual average rate of 37 percent in the newer member countries o f the EU, while rising only by 7 percent in the older EU member countries. In the new EU members household debt now represents a little over a quarter o f GDP, although remains below the 65 percent level in older EU members. Household indebtedness also has been growing rapidly in a number o f countries in the CIS countries and the Western Balkans. The rising trends in household indebtedness, and the associated risks and benefits, are analyzed in more detail in Chapter 2. 1.18 The growth in household indebtedness follows the rapid expansion in credit to the private sector more generally.* Buoyant housing markets, favorable macroeconomic and financial conditions and the increasing availability o f a broad range o f mortgage instruments have underpinned it. For the new EU member countries, it has also been suggested that the convergence in living standards toward the EU average has helped accelerate credit gr~wth.~ Over this same period, household financial assets also grew rapidly, though not at the same pace as household indebtedness. As a result, the net financial assets relative to GDP o f the household sector have fallen in many countries in the past few years; although on a per capita basis net financial assets have generally risen since 2000 with some decline in recent years due to the pace o f accumulation o f liabilities. To the extent that the rises in household liabilities are associated with mortgages they are likely to be matched by greater property assets although unfortunately data on the overall balance sheet positions o f the household sector, including both financial and non-financial assets such as property, are not available. 1.19 The rise in the gross financial positions o f the household sector, and their changing composition, has brought both benefits and introduced new sectoral vulnerabilities. As household financial positions have grown, there has been a shift towards housing loans or mortgages on the liability side o f the balance sheet and an increasing share o f equities and , pension and mutual funds on the asset side. On the one h ~ drising indebtedness reflects the benefits o f financial sector development, allowing households to smooth their consumption over time and acquire home ownership without significant savings. Changes in the asset side o f the balance sheet brought increasing diversification and exposure to higher yielding asset classes than the traditional deposits and currency. On the other hand, these developments bring the potential for greater exposures o f households' net financial positions to currency, asset pricing and interest rate risks. (This will be discussed in greater depth in the next Chapter.) If the respective risks are not hedged and they subsequently materialize, they may lead to deteriorations in households' ability to service their debt obligations. This in turn can adversely affect the health o f financial sector balance sheets with second-round implications for households in terms o f the availability and cost o f credit. 1.20 Banking sector balance sheets in ECA have expanded rapidly in the past five years, particularly in the Baltics and middleincome CIS countries, funded increasingly by external parent groups and wholesale markets. Credit growth has covered both the household sector and non-bank private corporate sector. As a result, the mean private credit to GDP o f *See also World Bank (2009), "In Focus: Domestic Credit Developments" EUlO Regular Economic Report, February. See OECD (2006). 26 countries in E C A roughly doubled from 2003 to 40 percent in 2007 (with the median ratio rising from 19 to 33 percent). In the Baltics, the mean level o f private credit to GDP tripled over this period to 71 percent with the means for the middle- and low-income CIS groupings doubling to around 40 and 18 percent respectively. These levels compare to means o f 120 percent, 48 percent and 33 percent for OECD countries, middle-income and low-income developing country sub- samples respectively. 1.21 Average bank credit-to-deposit ratios had reached around 120 percent in ECA by 2007 leading to concern over funding and liquidity risks. The growth in credit to GDP in general through 2002 to 2007 has been associated with rising credit-to-deposit ratios, i.e. increased reliance on non-deposit funding sources. However, both trends have been particularly marked in countries within ECA. Some o f these non-deposit funds reflect increased access to parental funding sources, as the trend towards increased foreign ownership o f banking sectors in E C A has continued in recent years, or in the case o f many o f ECA's EU member states stabilized at high levels. Foreign operations have been attracted by relatively high returns within E C A in comparison to developed banking markets, at least up to 2007. Some o f the major parent banks in the region themselves also appeared vulnerable to liquidity and funding risks (for example with net loans to consumer and short-term funding as o f end-2007 in the range o f 100 to 150 percent). The high level o f intra-regional linkages through the set o f major parent banks raised concerns over the impact o f group liquidity problems on local banking systems and the related regulatory coordination issues. 1.22 Although the banking system-level picture going into late 2008 from standard asset quality and capital adequacy indicators revealed only a limited number o f weaker outliers, such lagged aggregate indicators may not provide an accurate picture o f the current health of banking sectors. For example, N P L ratios may be relatively low due to the recent rapid expansion o f credit more than offsetting reclassification o f loans as problematic. In addition, ' rising interest rates on their own can cause a deterioration o f capital adequacy ratios in a mark-to- market environment. Furthermore, a more general weakening o f asset quality may increase solvency concerns in less robust banking sectors, rather than the proximate liquidity concerns o f late 2008. 1.23 As i s well known, many o f the economies in ECA, particularly in the Baltics and central Europe, entered 2008 with substantial current account deficits. Much o f the funding for these has come from the international bank flows that are projected to decline markedly in 2009. Even those countries more reliant on FDI financing are likely to face increasing difficulties in funding given the general downturn in growth prospects in the region and corporate sector difficulties in developed economies. In some o f the cases o f previous notable reversals current account deficits, for example in the Asian crisis, adjustment via the trade balance was possible due to a relatively supportive external environment which unfortunately i s not the case for the current deficits in the E C A region. Policy Stance ' 1.24 The ability of policy measures to either support domestic balance sheets in the face of external shocks o r mitigate the transmission of these shocks to the household sector i s constrained by initial conditions in terms of fiscal space, exchange rate arrangements and inflationary outlook. Indeed the nature o f the balance sheet strengths and weaknesses also guides the potential policy responses to the external shocks. For example, a relatively weak banking sector with high levels o f foreign liabilities may limit the overall impact o f exchange rate depreciation on economic activity given the scope for adverse balance sheet effects to offset, or 27 outweigh, any positive benefits in external trade positions. Such considerations may caution against significant exchange rate loosening. 1.25 On the fiscal side, the ability o f economies to use government spending to address the adverse income shock i s generally constrained (or non-existent) in the presence o f large and harder to finance current account deficits. In some cases, it may also be limited through debt sustainability concerns arising from structural deficits and possible contingent liabilities arising from banking sector recapitalizations. Although o i l exporters, such as Russia and Kazakhstan, entered this period with stronger external and fiscal reserves than other E C A countries, their scope to employ these funds has become more limited in the face o f falling o i l prices. W h i l e reduced demand and lower commodity prices have reduced overheating pressures in certain countries, inflationary concerns remain in a number o f countries during the pass- through o f exchange rate depreciation. In other countries, the presence o f fixed exchange rate regimes limits the usage o f monetary policy to respond to external shocks. Political considerations, o f course, add a further complexity to these policy trade-offs. E. WELFARE SHOCKS T O HOUSEHOLD 1.26 Depending on the strengths and weaknesses in macro vulnerabilities, and policy responses, the global shocks may result in a range of shocks to household consumption and welfare. The next chapters examine the potential impact o f shocks to household income via credit market shocks, external prices (food and fuel) and income shocks. The macro context o f each o f these shocks i s outlined below, in addition to a brief discussion o f the potential for wealth effects, which, as mentioned above, are not, included in the subsequent microanalysis for data availability reasons. Income Shocks 1.27 Shocks to household income arising from the economic crisis may arise through a variety o f channels and, depending on the household, may be viewed as temporary or permanent. First, labor income may fall due to the loss o f employment or falling real wages for those who remain in work. Second, declining remittance inflows are another channel through which household income may fall. Finally, changes in social protection policies as a result o f the crisis may also affect household incomes. 1.28 While the exposures to external shocks and strengths of initial balance sheets and policy stances varies across countries, there has been a broad-based reduction in real activity in ECA as a result of the global economic and financial crisis. After turning negative in July 2008, the 3 month on 3 month growth in industrial production in E C A contracted at an increasingly rapid rate from October 2008, reaching around -40 percent on an annualized rate in January 2009. The severity o f this downturn has exceeded even the contraction in the OECD countries. The scale o f the real slowdown i s also evident in the magnitude o f the GDP contractions in 2009. For example, Ukraine suffered a 20 percent year-on-year real GDP contraction in Q1 2009 with contractions in the Baltics in the range o f 12 to 19 percent in Q 1 and 17 to 23 percent in 4 2 (according to preliminary estimates). 28 Figure 1.7 Sharp Contractions in Industrial Figure 1.8 Rising Unemployment Rates Production (In percent) (Percent change) Percent change 3 monthon A Kazakhstan -RussianFederation 3 month, seasonally Ukraine -Baltics (mean) adjustedannualizedrate 30 1 I - EU5 (mean) e Turkey Percent 20 IO 0 -10 -20 -30 -40 -50 ' ` II 2 - o ! Jan-07 Jul-07 Jan-08 Jul-08 Jan-09 Jan-07 Jul-07 Jan-08 Jul-08 Jan-09 Source: WB DECPG. Source: UN Economic Commission for Europe, Turkish Statistical Institute, the Agency o f Statistics of the Republic o f Kazakhstan. Noies: Unemploymentrates based on labor force surveys. Break in Turkey series methodology at January 2008. 1.29 As real activity has fallen, there i s also increasing evidence of the transmission o f the crisis through t o rising unemployment numbers and declining real wage growth. Unemployment rates have been gradually increasing since mid-2008. The Baltic countries, where Latvia and Estonia experienced GDP contractions in 2008, have shown the earliest and particularly steep rises in unemployment but rates have also started to show an upward trend in many other countries across the region. Real wage growth has also turned downward in a number o f countries. For example, real wages in Ukraine fell by 12 percent year-on-year in Q 1 2009 compared with growth of around 13 percent in Q l 2008. 1.30 Remittance inflows have also taken a sharp downturn, tracking developments in the major sources o f funds, in particular Russia and the EU. Slower global and regional growth lowers demand for migrant workers from ECA. For example, growth in the Russian constructioh sector, an important source o f employment for regional migrants, has decelerated sharply. As credit conditions tighten further, construction sector activity i s likely to continue to decline. Indeed, formal remittance outflows from Russia to CIS countries contracted by 3 1 percent year- on-year in U dollar terms in 2009 Q 1 compared with growth o f 12 percent in Q4 2008. This S S compares to depreciation o f the average ruble to U dollar exchange rate o f 29 percent year-on- year in Q 1 and 10 percent in Q4. Formal remittance inflows, in U S dollars, for Tajikistan fell 36 percent year-on-year in the first five months o f 2009 with inflows to Georgia and Moldova also down 21 percent and 32 percent year-on-year respectively in the first half o f 2009, tracking declines in Russian construction activity. After annual growth o f around 37 percent per year from 2004 through 2007, the growth in the nominal dollar value o f inward remittances to the region i s estimated by the World Bank to have declined to around 12 percent in 2008 with a contraction o f 15-17 percent forecast for 2009. This i s roughly double the projected baseline contraction for total remittances to developing countries and compares to a contraction o f 16 percent in 1999 during the Russian crisis period. These effects will be particularly felt in selected countries in 29 Southeastern Europe and the l o w income CIS where remittances are the largest source o f external finance and constitute large portions o f GDP. Figure 1.9 Sharp Deceleration in Formal I - Figure 1.10 Growth in Remittance Inflows : Remittance Inflows S (Nominal U Dollar) , Growth in 3 -Georgia monthmoving -Tajikistan Annual growth, percent average, percent year-on-year - -Moldova 0 Russianconstmction(US%) 50% I + Russianconstruction(roub1es) \ DCA 100% 7 I 40% Forecasts for 2009 and 2010: 75% 30% - Base solid line Low - dashed 50% 20% 25% 10% economies - 0% 0% a\* -10% -20% 2005 2006 2007 2008e 2009f 2010f Jan-06 Jul-06 Jan-07 JuI-07 Ja11-08 JuI-08 Jan-09 Jd-09 Source: National authorities, IMF International Financial Statistics, Datastream and staff calculations. Notes: Remittances are from money transfer data. Russian constructioni s the value o f works performed in current prices and i s converted from Russian rubles into U dollars at the average exchange rate of period. S Source: WB DECPG Migration and Development Brief, 13 July 2009. 1.3 1 Looking forward, the likely magnitude and timing o f these adverse income shocks i s dependent upon the growth outlook for the region. This has been subject to continual, and significant, downgrades from October 2008. As forecasts have been downgraded, so the , uncertainty around them (as reflected in the variation in the forecasts o f contributors) has increased. Official growth projections on the IMF and World Bank have been continually revised since October in response to the changing national and global economic conditions. The IMF's April 2009 WE0 forecasts are for a contraction o f over 10 percent in the Baltics in 2009, around 6 percent in the middle-income CIS countries and 5 percent in Turkey. Combined with contractions o f around 2 to 3 percent forecast for Southeastern Europe and the Central European new member states and some positive growth in the low-income CIS the overall contraction in GDP in E C A in 2009 i s forecast to be just over 4 percent with a recovery to 1 percent growth in 2010. O f particular interest, in terms o f the potential drivers o f economic recovery, i s the global nature o f the downturn with the contraction in developed economies limiting the scope for export- led recoveries, as pursued, for example, in the Asian crisis countries. 30 Figure 1.11 G r o w t h A r o u n d Recent Crisis Periods: 1997-1998 and 2008-2009 + Advancedeconomies + Advanced economies - AsianCrisis5 - AsianCrisis 5 -Middle-income CIS Real GDP growth, -Middle-income CIS Real GDP growth, -- -Turkey EU5 . percent -Turkey percent .*.*Baltics 1995 1996 1997 1998 1999 2000 2001 2006 2007 2008 2009 2010 2011 2012 Source: IMF WE0 (April 2009) database and staff calculations. Note: Regional averages are weighted using country shares in global PPP GDP. 1.32 The quality o f economic recovery also matters. In addition to substantial uncertainty regarding the duration and severity o f the crisis, it i s unclear whether economic growth-if and when the recovery begins-will necessarily translate fully into growth in household consumption. In part, the poverty impact o f economic recovery depends on whether renewed growth i s accompanied by, for example, commensurate increases in wage, employment expansion, and the renewed availability o f credit for households and enterprises. Some recent research, the implications o f which are yet to be fully explored, suggest substantial heterogeneity in countries' experience o f the resumption o f economic growth following a systemic financial crisis. 1.33 I n the recovery period following the 1998 Russia crisis, some ECA countries experienced what has come t o be k n o w n as "jobless growth." In part, this may have been due to rapid wage increases that outstripped productivity gains, thus constraining j o b creation and squeezing profits in the process. N o t surprisingly, poverty has been least responsive in countries where employment creation has been limited and where jobless men and women account for a significant share o f the poor.4 Along with modest economic growth and stalled poverty reduction (in some cases, rising poverty), these countries have also experienced rising inequality. See also World Bank (2004 and 2005). More formally, the (total) elasticity o f the poverty headcount with respect to growth in average per capita consumption has been about -1.3 in these countries, compared with -3.4 in the Middle Income CIS countries. 31 Figure 1.12 "Credit-less Growth" in Emerging Markets and in the U.S. Great Depression Emerging Markets S U Great Depression 108 1 10 1 115 110 105 -- 105 1 105 - 100 100 - 100 lo* 9s - 1 85 ' 98 4 195 t-2 t-1 t t+l t+2 I -GDP - - Credit 1 Source: Calvo, Izquierdo and Talvi (2006a). 1.34 The experience of systemic financial crises in emerging markets-including a number of ECA countries-also suggest the possibility o f economic recovery without credit. The first set o f results from recent pioneering research, in what has been incorporated into the international finance lexicon as "credit-less growth" indicate that economic output may recover without any measurable recovery in domestic or external credit5 These studies have also documented comparable developments in the US. following the Great Depression. Researchers speculate that this phenomenon may be driven in part by enterprises postponing their investment projects or, where investments have been observed t o increase, by financing n e w investment projects out o f earnings or funds from informal credit sources. Because these types o f economic recovery have just been recently documented, the household welfare implications o f such experiences have not yet been explored. One possibility would be that private consumption may grow more slowly (compared with consumption growth following other types o f recession), as households restore their overleveraged balance sheets and increase their precautionary savings6 1.35 I t i s not clear whether the ECA region i s likely to experience such "credit-less growth" when the region recovers. I t has been suggested that credit-less growth was made possible in the past in countries such as Argentina mostly because o f rapid export growth. A s mentioned, a major difference with the emerging market crises o f the late 1980s i s the global nature o f the crisis, which effectively rules out an export-led recovery heavily reliant o n growth in developed m a r k e t ~ . ~ See Calvo, Izquierdo and Talvi (2006a and 2006b). Among the ECA countries in their sample are the Russian Federation, Slovenia, and Ukraine. See also IMF (2009a). See Ghosh et al. (2009). 32 Credit Market Shocks 1.36 Funding pressures and rising credit risks Figure 1.13 Local Currency within domestic banking sectors have resulted in a Depreciations general tightening of domestic credit conditions for (In U S dollars per local currency) households and the private sector more generally, Foreign **-Hungary(versus euro) On the quantity side, many countries in ECA have seen currency per local currency -Poland (versus euro) a rapid deceleration in the expansion o f domestic credit (1 Jan - S -Kazakhstan(versus U dollar) reflecting the drying up of external funding and 2Oo8=1o0) -Ukraine(versusUS dollar) concerns over potential credit risks. In some countries, such as Ukraine, the level o f nominal private credit 110 outstanding has remained flat or declined in the first half 100 o f 2009, with real credit now declining. On the cost o f 90 financing, the wide variety o f household interest rates, 80 by currency and maturity, makes it difficult to provide a comprehensive assessment o f changes in lending rates. 70 However, focusing on the rates on euro housing loans 60 there was a gradual rise in rates through 2008. Since 50 J I October/November, the euro rates have dropped off, as Jan-08 May-08 Sep-08 Jan-09 May-09 policy rate and quantitative easing have been adopted, Source: Datastream and staff and also likely demand has dropped. However, o f calculations. course, these euro rates do not reflect the burden o f mortgage repayments in local currency, which has increased markedly with the depreciations during the fall o f 2008. Ukraine's average U S dollar exchange rate in July 2009 remained depreciated by 40 percent compared with i t s level at the beginning o f September 2008 with Poland and Hungary depreciating by 22 percent and 13 percent respectively against the euro over the same period. Some countries, such as Belarus and Kazakhstan, have undertaken step devaluations o f their currencies (although the fixed exchange rate regimes in countries such as the Baltics and Bulgaria have remained firm). External Price Shocks 1.37 Food and fuel prices rose sharply in many ECA countries in 2007 and through the first three quarters o f 2008. Between 2006 and 2008, global food and fuel inflation doubled. The rapid increase in food prices was underpinned by significant droughts in various parts o f the world including in some countries in the ECA region, shifts toward bio-fuel production, declining inventories and tight commodity market conditions, and rising demand in emerging markets. Over this same period, energy prices reached record highs. A number o f countries in the region were particularly hard hit, including Kazakhstan, the Kyrgyz Republic, and Tajikistan. In many o f the CIS countries, inflation rose close to 20 percent in 2008. 1.38 As discussed above, as the global financial crisis has worsened, food and fuel prices have abated worldwide. In large part, this has been driven by the worsening global financial crisis, the economic recession in many countries across different regions and the economic slowdown, more generally, and, as a result, falling global demand for commodities. In addition, the increased agriculture production activity, following soaring food prices and higher returns to agricultural activity, led to a bountiful 2008 harvest, easing global commodity shortages. 1.39 For many countries in ECA, however, there are reasons t o believe that the impact of the adverse impact o f the food and fuel crisis on households may not be over. The rationale for this view can be split into near- and medium-term factors. In the near-term, the significant 33 depreciations o f local currencies as detailed above serve as offsetting factors against the decline in the U S dollar international prices (see Figure 1.14). In addition, some have expressed concern that inflation risks may persist with the continuing pass-through o f recent food and fuel price increases, due to lags in shipping and distribution.8 There i s also some indication that falling global commodity prices have not translated into lower retail food prices locally in these economies, in part because hedge contracts may have previously locked in higher price^.^ In addition, while price levels may have come down, they could s t i l l be at levels substantially higher than their pre-2007 or pre-2008 levels. The marked fall in international food prices in U S dollar terms from late 2008 has not been reflected in a number o f food price CPI sub-indices (Figure 1.15). Indeed, these sub-indices have continued to rise over this period in a number o f countries. Figure 1.14 International Food and Energy Figure 1.15 CPI Food Price Sub-indices: Price Movements and Local Currency Selected Countries Equivalent Indices (Jan 2007=100) (Jan 2007=100) Food price index International food price index -Median local currency value o f food price index (shaded Baltics(average) areasare IOthto 90thpercentilerange) Index(Jan *****HungW % & :; - -Foodpriceindex(US$) 2007=100) -Turkey 190 , 2oo 175 1 1 Energy price index Jan-07 Jul-07 Jan-08 Jul-08 Jan-09 Jul-09 -Median local currency value of energy price index (shaded Index(Jan areasare IOthto 90thpercentilerange) 2007=100) 250 ., - -Energy priceindex(US$) ,-. 1 50 1 Jan-07 Jul-07 Jan-08 Jul-08 Jan-09 Source: Eurostat, State Statistics Committee o f Ukraine, DECPG. W 3 DECPG and staff calculations. E Notes: U dollar indices converted into local currency value using monthly average exchange rates. S 1.40 I n some CIS countries, there are also prospects for further rounds o f external energy price shocks in the near-term as Russia moves towards full market pricing for its * IMF (2008b, 2008~). "Rising Food Prices Hit Eastern Europe," The Wall Street Journal, March 12. 34 energy exports. The price o f imported natural gas faced by consumers in Moldova, for example, i s still below European market prices and i s expected to converge to European levels in the near future. In Ukraine, some have argued that energy networks have been historically underfunded and energy tariffs will have to rise to ensure these networks' financial viability." In the Western Balkans, increasing tariffs to cost-recovery levels will be an important component o f electricity sector reform. 1.41 As the global recession worsens, it may undercut both public and private investments in the agriculture sector thus curbing agricultural production. The results o f some simulations conducted at International Food Policy Research Institute (IFPFU) suggest that a global economic recession that depresses agricultural investment can be associated with cereal prices that are 30 percent higher over the longer term than in the absence o f a recession." Figure 1.16 Local Currency Equity Market Figure 1.17 Housing Price in Selected ECA Declines Across ECA Countries Index (1 Jan 2008=100) 2005 Q2 E 2006 Q2 02007 Q2 Growth year-on-year, percent 02008Q2 EZOOSQ4 80 40 - -60 9" L 0 Dark gray shading indicates interquartile range for ECA countnes, light gray the 10th to 90th percentile range 0 .&--7--1--1 ~?^- "--" --- Jan-08 Apr-08 JuI-08 Oct-08 Jan-09 Apr-09 Jul-09 Source: Bloomberg, Datastream and staff Source: Knight Frank Global House Price Index, calculations. various issues. Wealth Shocks 1.42 Households who were long in equities and property o r short in foreign currency, were particularly exposed to the shocks to hit their net worth position over the past six months. For example, the median fall in local equity indices from 1 January 2008 through to their July 2009 average levels was 60 percent, with a 40 percent median fall alone over the two months from 1 September 2008. These compare with falls o f 38 percent and 25 percent respectively for the MSCI developed equities index in local currencies. As discussed above, households' financial assets in the form o f mutual fund and pension fund holdings have increased in recent years in many countries in ECA, along with their holdings o f residential property. However, it i s unclear to what extent the reduction in asset values through the downturn in asset prices (or increase in the local currency value o f liabilities denominated in foreign currencies) has, or will, lead to a significant wealth effect on consumption. There have also been major changes in the path o f 10 Fankhauser, et al. (2008). Under the ongoing IMF-supported program, energy tariff increases in Ukraine are expected to be phased-in (IMF, 2009~). Von Braun (2008). 35 house prices in recent years in many E C A countries, as in developed markets. For example, in Estonia and Latvia house prices f e l l in 2008 Q4 by around 16 percent and 36 percent year-on-year respectively compared with growth rates reaching roughly 20 percent and 60 percent in 2007 Q 1. Such price changes lead to redistributions o f wealth between those long or short in housing stocks. These can then affect the distribution o f consumption via direct wealth effects and via the impacts o f changing collateral values on credit constraints. Indeed, household level analysis in the UK has found the largest elasticity o f consumption with res ect to housing prices in older IP homeowners with an insignificant elasticity for younger renters. 1.43 A further transmission channel o f the real and financial impacts o f the crisis through to household welfare i s via pension provision. The nature and magnitude o f the effects o f the crisis via this channel depend crucially on the structure o f the pension system, in particular the mix between pay-as-you-go (PAYG), funded and voluntary pension system^.'^ For example, the main transmission channel for public P A Y G systems i s via the impact o f the crisis on contributions, through rising unemployment and potentially reduced wage growth. Funded pension systems are exposed to declining asset values (particularly affecting those individuals reaching retirement age during the crisis). Voluntary pensions may also suffer strong adverse effects via this channel, particularly via the wider equity exposures o f defined contribution funds, or through the impact o f declining corporate health on the defined benefit schemes. 1.44 Almost all countries in ECA, except for Kosovo and Kazakhstan, have some form of PAYG system, helping mitigate the direct pension impact o f the crisis. However, the ability o f countries to absorb rising pension deficits as a result o f falling contributions i s dependent upon their fiscal space. Indeed, in some countries that have been particularly affected by the crisis, revisions to state pension provision may form part o f the fiscal adjustment. In Latvia, for example, significant pension cuts have been recently proposed. 1.45 Those countries, which adopted fully-funded defined-contribution schemes as an integral part of their mandatory pension schemes, appear most directly vulnerable to the crisis. This group includes thirteen countries in ECA, mainly EU members but also Croatia, Macedonia, KOSOVO, Kazakhstan and Russia. However, in these countries the near-term implications o f the fall in asset prices for households in aggregate may be limited for a number o f reasons. First, with the exception o f Kosovo and Kazakhstan, where 100 percent o f contributions are in the funded pillar, these countries place a heavy weight on public provision (with 6.7 percent to 35 percent o f contributions in the funded pillar). Second, in the near-term relatively few workers are retiring with direct exposure to such second-tier benefits (although clearly there may be a greater future impact if asset prices remain depressed in the medium-term). Looking forward, from a political economy perspective, the fall in the value o f funded pillar pensions because o f the crisis may also have implications for the appetite for future reforms or calls for changes in the current structure o f pension provision. l2Campbell and Cocco (2007). l3This and the next paragraphs draw heavily from World Bank (2009h). 36 CHAPTER 2 HOUSEHOLD VULNERABILITIES A. INTRODUCTION 2.1 This Chapter examines household vulnerabilities by analyzing how macro shocks discussed in Chapter 1, namely (i)credit market shocks, (ii)external price (food and fuel) shocks, and (iii)income shocks, impact on their well-being. It treats each o f these shocks separately and quantifies how the crisis i s likely affecting the welfare o f households, on average, and, whenever possible and drawing from country-specific examples and illustrations, how such welfare effects may be distributed across households. 2.2 The results reported in this Chapter suggest that household vulnerability in ECA i s widespread. There are adverse effects on both poor households and non-poor households depending on the macroeconomic shock, the specific transmission channel, and on selected household characteristics. In brief, this Chapter finds the following: f The ongoing macroeconomic shocks will significantly expand the pool o households that are unable to service their debt. Interest rate shocks in Estonia, Lithuania and Hungary, for example, can increase the share o f vulnerable households or borrowers at risk (in percent o f all indebted households) by up to 20 percentage points, depending on the magnitude and severity o f the shock. Household indebtedness has risen rapidly in ECA countries among both poor and non-poor households. The nature o f household debt in ECA i s such that many households have likely exposed themselves to various types o f risks, including exchange rate and interest rate risks, with few opportunities for hedging. a f Thefood and fuel crisis may not be over and a new round o price increases will have substantial effects on household weyare. International commodity price levels have not returned to pre-2007 levels and falling currencies in some E C A countries are resulting in a new round o f price increases, depending on the share o f imported food and fuel in local consumption and the degree o f pass-through o f exchange rate changes in domestic prices. The net effect o f a food price shock depends on whether households are net producers or net consumers o f food, it depends on their intensity o f food consumption and the availability o f cheaper substitutes, and it depends on their livelihood strategies, access to agriculture assets and inputs and their ability to take advantage o f profitable opportunities in agriculture. These multiple considerations suggest that, at least in principle, the poor are not necessarily the hardest hit. However, the food share o f total household consumption typically falls with income and, in reality, the poor are also likely to be the worst hit, as many o f the poor in Albania, Kyrgyz Republic, and Tajikistan, for example, are also observed to be net consumers, with limited access to agriculture assets and inputs. Poverty will rise. The region now risks a major reversal o f its gains in the years of economic recovery following the 1998 Russian crisis. By 2010, about 11 million more people could fall into poverty and an additional 24 million people could find themselves vulnerable, or just above ECA's international poverty line, over the next two years. The regional simulations mask the heterogeneity o f impact within countries, including the 37 likely concentration o f the poverty impact in selected economic sectors. Country studies recently completed suggest that for economic shocks transmitted primarily through the labor market, poverty will rise especially among households that have been dependent on remittance inflows and those previously employed in booming construction sectors where economic activity i s now projected to decline sharply. 2.3 The rest o f the Chapter i s organized as follows: Section B sets out the context for the analysis in terms o f the trends in poverty reduction and vulnerability prior to the crisis. Section C discusses the empirical strategy, the scope and objectives, and the key limitations o f the analysis. Section D presents the results o f the analysis o f household indebtedness and the likely impact o f credit market shocks on the household debt service burden in selected countries. Section E analyzes recent trends in food and fuel prices, patterns o f food and fuel consumption among households in the region, and the likely impact on households o f a new round o f food and fuel prices increases. Section F assesses the impact o f the regional recession and in particular, the effect on household welfare o f falling incomes in the region. B. CONTEXT: POVERTY AND VULNERABILITY IN THE PRE-CRISIS PERIOD 2.4 Over the recovery period following the 1998 Russian crisis through 2006, some 50 million people moved out of poverty in the region.14 Poverty f e l l throughout all the sub- regions o f E C A led by the middle-income countries o f the Commonwealth o f Independent States (CIS), which experienced the largest declines in poverty, particularly in Russia where the share o f the poor and vulnerable has declined sharply in percent o f the population. 2.5 Poverty reduction in ECA has been driven largely by growth in average income. In particular, growth in mean income i s calculated to have contributed close 90 percent o f the overall reduction in poverty experienced by the region. A modest improvement in the distribution o f income has also helped reduce poverty. The labor market has provided an important channel for poverty reduction in the region, largely through rising real wages among the working poor. In contrast, j o b creation has generally not been an important factor for reducing poverty. For a number o f countries, the index o f employment has been flat in recent years. 2.6 Notwithstanding the rapid decreases in poverty, millions o f people still remain poor or are just above the poverty line. More than two-thirds o f the poor live in the middle-income countries of the region, including Kazakhstan, Poland, Romania, Russia, and Turkey. N o t surprisingly, low-income countries in ECA have higher rates o f poverty and vulnerability compared to other countries in the region, but as a group, they account for less than a quarter o f the region's poor population. 2.7 The growth slowdown will have significant adverse consequences for the region, given its poverty and vulnerability profile. Most o f the poor in the E C A region are working adults and children. Together, they represent about two-thirds o f the poor population across countries in the region, with the working poor accounting for anywhere from about a quarter (e.g., Turkey) to close to half (middle-income CIS) o f the poor population. The working poor represent a group that i s directly exposed to the fall in income and declining employment prospects projected throughout the region. In addition, because many o f those currently employed I4 This section draws heavily fiom the work o f Alam and Sulla (2009). Their analysis i s based on the same internationally comparable consumption aggregates and poverty and vulnerability lines used in this Chapter 38 have just moved out o f poverty, they are just above the poverty line and highly susceptible to modest falls in mean income and economic activity. c. SHOCKS TO HOUSEHOLD WELFARE: EMPIRICALSTRATEGY 2..8 The rest o f this Chapter examines household vulnerabilities using micro data by examining the potential impact of credit market, shocks external price (food and fuel) shocks, and income shocks on household welfare. The impact on household welfare i s defined as the change in the household debt service burden, the fall in real income, or movements into poverty, as appropriate. The report presents regional overviews and simulations along with cross- country comparisons and contrasts. It also presents selected country examples, depending on data availability and relevant economic developments, to illustrate the incidence and distribution o f specific vulnerabilities within countries. 2.9 The novel microeconomic analysis in the report draws on a large, cross-country database of household surveys. We use the most recent pre-crisis household data along with aggregate macroeconomic outturns to simulate the impact on households o f key economic shocks already taking place. The report brings together for the first time comparable cross-country data on household indebtedness for a large group o f E C A countries using the EU Survey o f Income and Living Conditions (EU-SILC) and Household Budget Surveys (HBS). The report also highlights newly updated information on household consumption from the E C A Household Data Archives. Comparisons with Western Europe and other advanced economies are also used to inform the analysis when relevant data are available. Important Caveats 2.10 The analysis i s not exhaustive. First, the choice o f emphasis has been guided in large part by the policy issues o f the day when the project was first designed. Thus, for example, it i s an analysis o f food and fuel' price shocks, instead o f rising prices o f other household consumptioh items, reflecting the widespread concern over the food and fuel crisis. It i s an analysis o f household indebtedness and the welfare consequences o f rising debt burdens-rather than, for example, the analysis o f the welfare effects o f the continuing lack o f access to credit among certain households-given the policy interest in the new vulnerabilities created by the credit boom through 2007-2008 in many countries in ECA. Second, the country examples and analyses have also been selective, depending on data availability and the relative country exposure and risk. This i s a primary reason why the potential impact on household welfare o f wealth changes associated with the crisis, for example related to property and equity price falls, i s not analyzed. , 2.1 1 The analysis i s not predictive. The GDP growth projections alone, on which many o f the simulations here are predicated, were updated at least three times during the course of the preparation o f this report. The frequency o f updates reflects the substantial uncertainty regarding the severity and duration o f the crisis and, by extension, its impact on households. In addition, the actual poverty impact can be mitigated by private responses to the crisis and by various household coping strategies. This study i s unable to account for the interactions between channels, the behavioral changes (including coping strategies to mitigate the crisis, discussed in the final Chapter), and the net higher-order effects. Policy responses, meanwhile, can either mitigate or exacerbate some o f these consequences. 2.12 The results are not additive. The analyses o f changes in household welfare in response to three types o f shocks are treated as parallel exercises. First, the shocks have not been analyzed 39 within a common general equilibrium framework. Second, the choice o f country examples and illustrations vary across shocks, depending on data availability and the relevant country risk. More generally, the data are drawn from two different household data sources. Finally, there are methodological differences in the way vulnerability was evaluated, consistent with the respective, existing literature. With household indebtedness for example, the impact o f the shocks are assessed relative to indicative debt burden "thresholds" (payments in percent o f income). With respect to the fall in income, the predicted household consumption levels are compared to an international poverty line. However, the real impacts in each country may very well be multi- channeled and cumulative. Countries in Eastern Europe for example, have to deal with financial sector shocks, labor market shocks, as well as product market shocks transmitted through currency declines. For a number o f reasons, however, we treat these impacts independently and using partial equilibrium analysis. 2.13 The aim, then, is to provide a broad overview of household vulnerabilities confronted by the region. It seeks to assess how such vulnerabilities are distributed across countries and, within countries, across broad types o f households. Some o f the estimated effects may be understated, as they capture only some o f the first-round effects. On the other hand, general equilibrium effects will either dampen or worsen some o f these effects. 2.14 This report i s also cognizant o f many ongoing, decentralized efforts throughout the region to simulate the household welfare consequences o f the crisis. Such efforts are able to model these effects and interactions more fully using richer, more comprehensive country- specific data. This report does not substitute for those efforts-some o f whose preliminary results are also reported and referenced below-but instead provides a complementary regional overview. D. HOUSEHOLDS AND CREDIT M R E SHOCKS AKT Background 2.15 Household debt now represents a little over a quarter o f GDP in the EU10. Though nontrivial, this level i s lower than the debt level in most of the older EU member countries, which on average i s about 65 percent o f GDP. Within the EU10, however, there i s significant variation in aggregate household debt holdings, both in their level and composition. Estonia i s at the higher end o f the distribution by magnitude, with household debt representing close to half o f GDP. Household debt in percent o f GDP in the CIS and other ECA countries, in turn, lags behind the EU10, on average. Ukraine i s an exception, with household indebtedness comparable to that o f the EU10 average. 40 Figure 2.1 Household Debt Figure 2.2 Growth in Mortgage Debt Selected ECA Countries 2008 Selected ECA Countries 2007 (In percent o f GDP; end-period) (In percent) - ~ 140 7 __ _ _ - - _ _ IO0 120 40 0 I 00 30 o 0 80 20 0 0 60 10 0 0 40 00 0 20 OW EUlO(incl Croatia) Source: European Central Bank; National Central Source: European Mortgage Federation. Banks; IMF; and UniCredit. 2.16 As household financial positions have grown, there has been a shift towards housing loans o r mortgages on the liability side o f the balance sheet and an increasing share of equities and pension and mutual funds on the asset side. For many o f the countries in E C A rising mortgage and housing loans have accounted for much o f the growth in household liabilities and now, for example, account for around 40 percent o f total household liabilities in Bulgaria, Croatia and Hungary and up to 60 percent in the Czech Republic. However, for some notable exceptions, such as Romania and Bulgaria, consumer credit remains the primary form o f household loans. Elsewhere, such as in the CIS, housing loans are a much smaller share o f all household loans compared to the EUIO. Mortgage debt has increased multiple times over the period 2002-2007 both in per capita terms and relative to disposable income. Some have suggested that government initiatives, such as construction or mortgage-related subsidy and tax schemes, have contributed to this growth. The growth in mortgages can also be viewed in terms o f longer-term convergence towards the financial norms o f Western Europe. Indeed, as would be expected, the most rapid annualized growth over the period 2002 to 2007 was seen in those economies with relative low initial levels o f mortgages per capita. At 2007, housing loans accounted for close to 60 percent o f all household loans. Mortgage debt in Serbia, for example, grew at an astonishing rate o f 96 percent in 2007 while growing by 86 percent in Albania. In Russia, the Central Bank reports that mortgage lending grew by a factor o f 2.6 in 2007.'' CIS mortgage lending also grew very sharply. l5Central Bank o f the Russian Federation (2008). 41 Figure 2.3 The Composition o f Household Debt EU10 2008 (end period) Selected Countries 2008 (end period) (In percent o f total) (In percent o f total) BCannumerCredit BHouiingIaans OOthorloans BiHousingLnan Bother Bulaana Czech Republic Russia .`' . Estonia Poland Romania Slovak Rcpublic Ukraine Slovenia 0% 20% 40% 60% 80% 100% 0% 20% 40% 60% 80% 100% Source: European Central Bank. Source: National Central Banks. 2.17 The welfare consequences of rising household indebtedness in the ECA region can be significant. Rising indebtedness reflects the benefits o f financial sector development, allowing households to smooth their consumption over time and acquire home ownership without significant savings. In fact, there exists a growing literature on the welfare impact o f credit constraints among households, particularly in a downturn when households are unable to meet their consumption needs.I6 On the other Figure 2.4 Latvia Household Loan Delinquency hand, rapidly growing household Rates and UnemploymentRate indebtedness and the exposure o f the financial sector to vulnerable households Shareofhouseholdloansoverdueby31-90 days Share o f householdloansoverdue91-1 80 days (or borrowers at risk) may have important -Shareofhouseholdloansoverdueover 180 days consequences for financial stability. At the -Latvia Unemploymentrate(seasonallyadjusted) 18% same time, the welfare and distributional I 16% implications for households themselves 14% can be large, particularly in a worsening 12% 10% macroeconomic environment. 8% 6% 2.18 Some characteristics of 4% 2% household debt in ECA expose these 0% households to a number of Q3 Q4 Q1 4 2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 4 2 4 3 4 4 Q1 4 2 macroeconomic shocks. Given these 2005 2006 2007 2008 2009 characteristics, household debt service burdens may increase in a difficult Source: Eurostat and the Financial and Capital Market Commission. Latvia. macroeconomic environment, and this, in turn may lead to higher default and l6 This problem has been modeled as a problem of nter-temporal consumption smoothing under a stochastic income process. Using this fiamework, some papers (Kang and Sawada, 2008; Sawada, Nawata, iand I, Lee, 2007) estimate the welfare costs o f a credit crunch. For example, over the period of the Korean "twin" crises o f 1997-1998, the marginal utility loss due to the credit crunch was found to be higher among lower-incomehouseholds, ranging from 29.3 percent for the bottom quartile to 14.2 percent for the richest quartile. In Japan in 1998, the marginal utility loss ranged from 10.3 to 2.4 percent for the bottom and top income quartiles, respectively. 42 delinquency rates. These in turn adversely affect the health o f financial sector balance sheets with second-round implications for households in terms o f the availability and cost o f credit. Already, rising household loan delinquency ratios are being observed in some countries, as unemployment rates have risen. 2.19 First, a large share of household debt i s denominated in foreign currencies or i s indexed to foreign currencies, which has exposed households to recent exchange rate depreciations to the extent that the currency composition of their assets, particularly their labor income flows, leaves them unhedged. Where foreign currency loans became popular in recent years, borrowers were typically obtaining loans in Euros and Swiss francs, attracted to relatively lower nominal interest rates compared to loans denominated in local c ~ r r e n c y . 'On the ~ banks' side, at the height o f the expansion in household credit, there appeared little interest in reducing their exposure to foreign currency-denominated loans because default rates were l o w and because o f the ease o f access, at the time, to foreign currency funding via wholesale markets or via Western European parent banks. Among households borrowing in foreign currency, however, there also seemed little awareness o f their exposure to currency risks although in some countries a high share o f foreign currency deposits provide some hedging o f the currency risk. These developments in the EUlO mirror recent trends elsewhere, particularly in the middle- income CIS countries, where households also obtained loans denominated in U S dollars and other foreign currencies. In Serbia, few o f the household loans are explicitly foreign currency- denominated. However, up to 8 1 percent appear to be foreign currency-indexed.'8 Figure 2.5 Foreign Currency Denominated Figure 2.6 Foreign Currency Denominated Loans 2008 Loans in Ukraine 2008 (In percent o f bank loans to households) (In percent o f total, by currency) 900 1 Hryvnia B U S dollar I Euro IRussianruble a other 80 0 100 0 70 0 60 0 80 0 50 0 40 0 60 0 30 0 20 0 40 0 10 0 00 20 0 00 Consumercredit Housingloans Other Source: MNB and other National Central Banks. Source: National Bank of Ukraine and staff calculations. 2.20 There are again substantial variations in the foreign currency exposures o f household debt across countries. The Baltics and Ukraine are at the higher end o f this distribution, with foreign currency-denominated loans accounting for over 80 percent o f bank loans to households in Estonia and Latvia; the Czech and Slovak Republics are at the lower end, with little or no foreign currency-denominated household debt. Some have suggested that a few l7Rosenberg and Tirpsik (2008) suggest that EU membership promotes borrowing in foreign currency indirectly, such as through capital account liberalization that then facilitates access to foreign funds. In addition, they also observe that EU membership seems associated with greater private sector confidence in the stability o f the exchange rate and the eventual adoption of the euro. '* National Bank of Serbia (2008). 43 national policies may explain some o f these differences across countries-such as more restricted eligibility requirements in 2004 for housing subsidies in Hungary (which then prompted households to substitute toward less expensive foreign currency loans) or regulatory measures to limit borrowing foreign currency in the Czech R e p ~ b l i c . ' ~ 2.21 Second, in some EUlO countries, mortgages with variable (adjustable) interest rates account for the largest share of lending, exposing households to interest rate shocks. In these countries, such variable interest rate mortgage debt represented over three-quarters o f all mortgage debt, at least until recently, using available data. Households are vulnerable in a financial downturn, in the event that banks pass on a higher cost o f credit to them. However, as shown in other countries' experiences, this may be mitigated to the extent that interest rate adjustments may be capped, as i s the case, for example, in Denmark. Figure 2.7 Mortgage Loans with Adjustable Interest Rates 2006 (In percent o f all housing loans) 0 20 40 60 80 100 Source: IMF; OECD; and National Central Banks. 2.22 Increasing mortgage indebtedness has exposed a rising share o f households to the recent changes in house price trends in many o f the EUlO countries. For example, in Estonia and Latvia house prices f e l l in 2008 Q4 by around 16 percent and 36 percent year-on-year respectively compared with growth rates o f around 20 percent and 60 percent in 2007 Q I . Such price changes lead to redistributions o f wealth between those long or short in housing stocks. These can then affect the distribution o f consumption via direct wealth effects and via the impacts o f changing collateral values on credit constraints. Indeed, household level analysis in the UK has found the largest elasticity o f consumption with respect to housing prices in older homeowners with an insignificant elasticity for younger renters2' Household Vulnerability: Regional Overview 2.23 Microeconomic data can be a critical source o f information on household indebtedness. Current assessments o f the credit risks faced by the banking sector have been largely based on macroeconomic data. In general, little i s known about household indebtedness based on household level data in the EU10. The debt profile could vary across household income 19 See Rosenberg and TirpAk (2008) for a brief survey of some of these policies. But the results o f their analysis suggest that the observed cross-country differences i s in large part explained by interest rate differentials. 20 Campbell and Cocco (2007). 44 groups and by type o f loan, such as mortgage and non-mortgage. In principle, such microeconomic data and profiles allow for a closer monitoring o f risks associated with selected household groups. Where household borrowing i s limited, indicators based on average household indebtedness for all households as a whole mask the likely concentration o f borrowing among selected households. 2.24 This section draws information from the databases o f the EU-Statistics on Income and Living Conditions (EU-SILC), an annual household survey anchored in the European Statistical System that was first initiated in 2003, with the new EU member countries undertaking their first surveys in 2005. Data are typically made available to the general public two years after the survey, so that we currently have data through 2007 and data for both older and newer EU members for 2005-2007. Among other variables, the EU-SILC collects information on the incidence o f mortgage debt holding, interest payments, arrears on mortgage interest payments, disposable income, and others. The analysis o f EU-SILC data i s supplemented with the analysis o f a few other E C A countries with relevant variables in their Household Budget Surveys (HBS). For these countries, there i s information on total household debt, including mortgage debt and other household loans, and on total debt service (including interest payment and principal payment) in contrast to the EU-SILC data, which has information on interest payment alone. 2.25 There are a few notable patterns in the household survey data, suggesting likely adverse welfare consequences during an economic downturn. These include patterns o f household debt holdings, including among those that are more vulnerable or less able to service their debt in a difficult economic environment. 2.26 First, debt holdings rise with household income level but are spread across income quintiles, including the poorer households. In the Czech Republic, for example, over a third o f households in the poorest quintile hold some debt, rising to about 55 percent o f households in the richest quintile. In addition, on average among EUlO countries, the share o f mortgage holders across age groups first increases and then decreases with age, a pattern that i s broadly consistent 45 with the l i f e cycle theory o f consumer behavior. Taken together, these suggest that when macroeconomic shocks increase the financial burden due to mortgage debt i t i s the poorest households and the youngest households with weaker ties to the labor market who are among those most likely to suffer adverse shocks, in the absence o f a savings buffer. The shocks can be channeled through income shocks, exchange rate shocks (if the mortgage i s in foreign currency), or interest rate shocks (in case o f variable-interest mortgages). If the mortgage payments represent a considerable share o f a household's disposable income, a rising debt burden may curtail the household's ability to protect i t s welfare. Figure 2.8 Household Debt by Income Quintile Selected EU10 Countries 2007 Other E C A Countries 2006 or 2007 (In percent o f households) (In percent o f households) 70 70 60 60 SO 50 40 40 30 30 20 20 IO 10 0 0 Czech Ellonin Hungvry Lithusnia Latvia Poland Slovuk Slovenin Rcpublio Rcpublic Georgia Kazakhstan Turkey Ukraine Source: EU-SILC and staff calculations. Source: HBS and staff calculations. 2.27 Second, in some countries debt service i s a significant share o f income, particularly among the poor. In Hungary, for example, data from the EU-SILC suggest that mortgage interest payments among the poor represent over 10 percent o f their income. In Latvia, the share increases to almost 15 percent. If anything, these estimates o f the debt service burden may be understated. A recent, independent survey for UniCredit Group indicates that for about 30 percent o f all households, total household debt repayment cover more than a fifth o f the household budget. Another 20 percent o f households allocate 10-20 percent o f their household budget to debt repayments. Figure 2.9 Household Income Used F o r Debt Repayments (In percent o f all households) I S% a f H H budgel m6 10% 0 II lS%U 16 20%m21-30%B>30%.Don tKnaw Bulgans Czech Repuhltc Hww Palwd Rolllw,* Sloval Republic Slovrnla 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Source: UniCredit Group. Note: The graph should be read as follows: The bars represent shares of the household population. The colors represent the percentage of household budget spent on debt service. In Slovenia, for example, 10 46 percent of households spend 1 to 5 percent of their budgets on debt service. Another 15 percent of households allocate 6 to 10 percent o f their budgets for debt service. 2.28 Third, in some countries, mortgage interest payments are a significant share o f income among the youngest and oldest workers. In Hungary, the youngest workers (age 25 and younger) allocate over a tenth o f their disposable household income on mortgage interest payments. Slovak workers in the youngest group also spend almost 10 percent o f their income to pay mortgage interest. In Lithuania, interest payments as a share o f disposable income are the smallest in the youngest workers and then rise with age, reaching close to 6 percent o f income among those aged 55 or older. In the meanwhile, in Latvia, mortgage interest payments occupy a large share o f household income across all age groups from the youngest to oldest, which is, in most cases, over 10 percent o f disposable income. Large debt service ratios are also observed among those employed in economic sectors that have experienced some o f the sharpest downturns in recent months (such as in construction). Stress Testing Household Indebtedness: Country Illustrations Introduction 2.29 Stress tests of household debt using microeconomic data are rare, but the results of existing tests suggest considerable welfare consequences. A recent stress test in Hungary suggests that a simultaneous fall in employment and an interest rate shock would increase "risky loans" by 8-12 percentage points. Though the banking sector i s found to be resilient to these shocks, the default risk i s concentrated among the poor households. A stress test in Poland suggests that unemployment shocks (compared to interest rate or exchange rate shocks) have the highest impact on probability o f default. Modest increases in unemployment can increase the share o f loans in default by over 5 percentage points.2' 2.30 We run similar analyses of mortgage debt on a few selected countries, using EU- SILC data, and of total household debt, using H B S data. The choice o f countries has been guided by data availability and the degree o f exposure to interest rate, exchange rate, and unemployment rate shocks. The magnitude o f the hypothetical shocks have been driven by actual changes in recent months-such as the doubling o f unemployment rates in some EUlO countries-and are thus greater in magnitude than what has been previously assumed by the few stress tests that exist. We also simulated uniform shocks across countries-e.g., 25 percent exchange rate depreciations-as explained more fully in B o x 2. 2.31 For two o f the countries analyzed, the fixed exchange rate regime, the authorities' commitment to the peg, and the credibility of this regime protects households from the adverse effects o f exchange rate adjustments. Some institutions have been examining the merits o f alternative exchange rate regimes and they argue that a regime change would lead to adverse social consequences.22The results o the simulations here should be seen in a similar f light, as evidence o the likely weuare costs o abandoning the peg. f f 21 Zochowski and Zajqczkowski (2007 and 2008). 22 See, for example, the discussions on Latvia summarized in IMF (2009e). 47 23 See for example Ho116 (2007), Zochowski and Zajqczkowski (2008), Johansson and Persson (2006), and others. 24 The financial margin i s calculated as M, = DZ, - BLC, - DSE, where i=household; M, = margin o f the i'th household; DZ, = disposable income o f the i'th household; BLC, = basic living costs (defined by country) o f the i'th household; and DSE, = debt service expenditure o f the i'th household. See also Johansson and Pefsson (2006) and Vatne (2006). Nationally-defined minimum consumption expenditures, minimum consumption baskets, or poverty lines have been typically used to proxy basic living expenses. 25 See M a y and Tudela (2005) on how this threshold interest payment level i s determined. It may be argued that a 20 percent threshold seems overly restrictive because other stress testing exercises have used a 30 percent threshold instead (e.g., Karasulu, 2008; Beer and Schurz, 2007; ECB, 2007). However, those exercises were based on comprehensive data on household debt (including mortgage debt, consumer loans, and other household debt) and household debt service (covering both interest payments and principal repayments). In the case o f SILC data, we have information on mortgage interest payments, thus requiring the relevant interest payment threshold. Nonetheless, we also use a 30 percent threshold as a sensitivity test. 26 This refers to the analysis o f EU-SILC data, which are for 2007 and thus the two-year period for these EU countries captures the recorded increase in unemployment rates between 2007 and 2009. In the case o f HBS data, which are for CIS and other countries and refer to older years (e.g., 2006), we use a longer time horizon (e.g., 5-year period) to capture historical increases (rather than decreases) in unemployment rates. 48 Recalculating fhe share o vulnerable households. As h ~ u s e ~ o are subjected t o a shock--e.g., as f ~ds a member o f the household becomes `'unemploye~' and ceases to receive any income from w o r d ' t h e shock then results in the decrease in total household income and the household's ability to repay debt. In the case o f an interest rate shock or an exchange rate shock, the size o f debt (or interest) payment grows accordingly. In all cases, the debt service burden is recalculated and then compared to the relevaat threshold. The share o f vulnerable households &en 27 The procedure i s carried out in Stata using the rbinomial routine. 28 I t i s assumed that the ratio of unemployment rates within each subgroup i s constant before and after the unemployment shock. For example, if the rural unemployment rate i s double that o f urban unemployment, the ratio i s kept constant after the new "unemployed" are selected. 29 Neither can we estimate a probability model for taking on loans with variable interest rate, as the relevant information does not exist in the household survey. 30 Ho116 (2007), for example, simulates a 5-percentage point interest rate shock in Hungary. 3 1 I t should be pointed out that only those who were previously employed are subjected to the shock. Unemployed individuals as well as unpaid family workers and agricultural workers and farmers producing for their own consumption are excluded. 49 Results 2.32 The results o f the analysis of EU-SILC data suggest that current macroeconomic shocks can significantly expand the pool of households that are unable to service their debt. A severe 5-percentage point interest rate shock in Estonia, Lithuania and Hungary, for example, can increase the share o f vulnerable households or borrowers at risk by up to 20 percentage points, depending on the magnitude and severity o f the shock (Figure 2.10). A less restrictive threshold-that is, interest payment representing 30 percent o f disposable income-yields smaller welfare effects from interest rate shocks compared to this first set o f estimates, but they are still large. In particular, the share o f borrowers at risk can expand by 7-12 percentage points in our sample o f countries. A more modest interest rate hike-3 percentage points-using a 30 percent threshold yields much lower, but s t i l l nontrivial adverse consequences for household well-being. Borrowers at risks increase by 4 t o 7 percentage points o f a l l indebted households. The results are in Appendix Table 1, Appendix Table 2, and Appendix Table 3. 2.33 Unemployment shocks also expand the share of vulnerable households by several percentage points. The results hold, regardless o f whether the unemployment shock follows a probability assignment o r a random assignment, although a random assignment generally leads t o higher welfare costs. Figure 2.10 Stress Testing Household Indebtedness: Selected EU-SILC Data (Vulnerable households or borrowers at risks as a share o f indebted households) Unemployment Shock Interest Rate Shock Exchange Rate Shock Before BAfter Before .After Before .After 35 1 30 30 25 30 20 20 20 15 10 10 10 5 0 0 0 Estonia Hungary Lithuania Estonia Hungary Lithuania Estonia Hungary Lithuania Source: EU-SILC data and staff calculations. Note: The simulated shocks are a IO-percentagepoint increase in unemployment rates, a 5-percentage point increase in interest rate shocks, and 25 percent depreciation in exchange rates. This refers to mortgage debt only. Vulnerable households are identified using a 20 percent interest payment threshold. See main text and Box 2. 2.34 I n the countries analyzed, interest rate shocks have the largest impact on household vulnerability. In part, this i s due to the assumed magnitude o f the shock. It i s also driven by the degree o f initial exposure. I particular, while only some indebted households will be hit by an n unemployment shock, all indebted households with variable interest rates will see increasing debt burdens from an interest rate hike. 2.35 The analysis o f H B S data assuming comparable unemplo ment and exchange rate shocks suggest a far more limited impact on household welfare. n I Belarus, Kazakhstan, ' Serbia, and Ukraine, exchange rate shocks increase, on average, the share o f borrowers at risk by less than 1 percentage point. Unemployment rate shocks, on the other hand, were found t o 32 At the time these stress tests were conduct, the study team was unaware o f publicly available aggregate data on the share o f household loans with variable interest rates. 50 increase vulnerable households by up to 5-6 percentage points, depending on the magnitude o f the shock and depending on whether the shocks are distributed randomly or according to a probability assignment. Figure 2.1 1 Stress Testing Household Indebtedness: Selected H B S Data (Vulnerable households or borrowers at risks as a share o f indebted households) Unemployment Shock Exchange Rate Shock Before WARer 4 1 I I j 30 20 30 10 10 0 0 Belarus Kazakhstan Serbia Ukraine Belarus Kazakhstan Serbia Ukraine ~ Source: HBS data and staff calculations. Note: The simulated shocks are a IO-percentage point increase in unemployment rates and a 25 percent depreciation in exchange rates Vulnerable households are identified based on the "financial margin" measure. See main text and Box 2. 2.36 These two sets of estimates-one for SILC and one for HBS-are not comparable. As previously discussed, one i s based on mortgage debt information and the other i s on total household debt. The two methodologies employed for identifying borrowers at risks-the use o f a threshold level o f interest payment burden in the case o f SILC data and the use o f financial margins in the case o f H B S data, which i s a less restrictive measure o f vulnerability-preclude a meaningful comparison o f the two sets of outcomes. Nonetheless, some of the differences in the relative magnitudes may be driven in part by the differences in average debt burdens in these countries. In many o f the countries with H B S data, the share o f borrowers at risk i s small, the average loan size i s small, and the debt burdens are s t i l l sufficiently far from critical thresholds. Box 3. EU-SILC and ebt: Co This Chapter USCS household debt data drawn froni EU-SILC and IlBS data for those ECA cotintries for which the relevant data are available. Some caution is warranted iu the interpretation ofthese household survey data. as they are not primarily designed to collect information on household liabilities. The focus o f the SILC survey is not access to financial services or financing constraints, but rather social exclusion and income poverty. Because these are survev data, the volunie of household loans and mortgages may not necessahly eonespond fuily to a SILC data have been analyzed, household debt?3 More important, the c a l c u l a ~used in this Chapter are i~~~ sources o f macroeconomic and microeconotnic information. 33 See, for example, Beer and Schurz (2007). 51 rative Jinanciul nturgins u ~ consi.srtmt wit1 e ample, between 7001 and 2008, the econom! lational Rank's h i l e t i n ot' Banking Statistics :alculations o f financial margins. the share o steadily between 9001 and 2008 (Appendi! Lobtained by the team indicates that the shari hit the country in late 2007. of'household debt holding docummted hert ?bf dti/ri. In Lithuania, for example, surnrnar: ieholds with housing loarts rises tvith iiicome L s o f debt holding by income and by age ii m tent with those o f Western Europe and othe The Share o f IndebtedHouseholds: EU-SILC and ECB Data mSILC .ECB 80 d i s ~ ~ b while~ o ~ e r l a n is s the higher end, ~ ~ Nen ~ at 40 Nonetheless, in some countries there are 30 zn signij?cand dipereme8 iir the estimated levels o f IO h ~ ~i n s e ~ ~ ~ can be lseen~from the Figure. d ~ as ~ ~ ~ s e ~ n Greece Italy Ireland Portugal Spain France Netherlands nces in the estimated debt senice LC data for ECA countries can be compared with those o f other studies. Deb1Serriee.SILCand Unicredit Data For example, the debt service numbers calculated B>PS./rafHH budget m6-10% 011.155. 016.20% m21.30% ~ 0 0 % by the Bank o f Slovakia, particularfy for the poorest s higher than those reported clear what is driving the s from the EU-SXLC for the same s. In part, it could reflect the ~ e ~ e ~ i o ~ a t i n ~ financial conditions captured by household UniCredit's more recent data collection efforts. They may also be explained by differences in survey design, though information on UniCredit's survey design is not readily available, The results o f the stress tests in this Chapter could then be possibly a lower bound, 34 See, for example, OECD (2006) and ECB (2009). 52 E. AND EXTERNAL HOUSEHOLDS PRICE SHOCKS Economic and Welfare Impact: Main Transmission Channels 2.37 The economic and welfare impact of rising commodity prices depends o n the intensity o f use. One possible index i s "energy intensity", which i s measured as energy consumption per unit o f real GDP. Country averages over the last four decades indicate that energy intensity in advanced economies has fallen and both emerging and developing countries are now substantially more energy-intensive in relative terms.35 Similarly, food consumption is significantly higher in both emerging and developing countries compared to advanced economies. Their food consumption levels (in percent o f household consumption) are almost three times those o f advanced economies. Figure 2.12 Energy Intensity and Food Consumption 1970s-2000s Energy Intensity Food Consumption (In metric tons o f o i l equivalent per million o f (In percent o f household consumption) GDP - -2007 purchasing-powerparity__ __ __ in -- - -- - - - _- --_ - dollars) _- __ - - - - __ __ - -- - __ - - I 1970s 0 1 9 8 0 s 01990s 0 2 0 0 0 s m l 9 7 0 s 0 1 9 8 0 s 01990s M2OOOs 350 , I 45 , 300 250 40 * 35 - 200 150 I 100 50 0 - Advancedeconomies Emerging economies Developingeconomies Advancedeconomies Emerging economies Developingeconomies Source: IMF (2008a). 2.38 Where the price shock i s transmitted through falling currencies, the economic consequence depends on whether a country i s a net commodity importer. With respect to net food importing, some recent work based on an indicative threshold for vulnerability suggest that a few countries in E C A may be vulnerable. 2.39 Soaring domestic food and fuel prices-whether due t o increasing global commodity food prices o r through falling currencies-affects the national headline inflation based o n these commodities' share in a country's CPI. The relative importance o f these commodities varies across countries, though some comparisons are hampered by the differences in the definition o f what constitutes "food" (e.g., including or excluding beverage, tobacco, and others) and "fuel" (e.g., including gasoline, household utilities, and others). 2.40 Notwithstanding these measurement issues, these commodities typically account f o r a large share o f th e consumption basket, particularly in poorer countries. Food represents about 10 percent o f the consumption basket in richer countries, while representing up to 80 ~~ 35 IMF (2008a). 53 percent o f the consumption basket in the world's poorest countries. Fuel accounts for a much smaller share, although this does not capture the secondary dimensions, that is, the use o f fuel as input into the production o f other items in the consumption basket. Evidence in some countries suggests that taken all together, both the primary and secondary use of fuel could account for about double i t s typical share o f the consumption basket.36 Figure 2.13 Food and Fuel Share Figure 2.14 Food and Fuel Imports 2006 of the CPI Basket (In percent o f GDP) (In percent) BFud .Food 0 Food 0 Fuel AtlIlellla 25 Bulgana Croatia CzcchRepublic G W p Hungary Kyrgyz Republlc Lithuania t Poland I Romanla Ukrdsnc I Middle Income CIS _-- I -T _ _ * ~ 1 7 EUlO (tCroatm) Low Income CIS Mrddle Wcstcm 00 100 200 300 400 500 600 I Income CIS Balkans Source: Habermeier, et al. (2009); and IMF (2008b). 2.4 1 These aggregate economic effects hide some o f the likely distributional consequences o f commodity price shocks within countries. First, within a given country, the food share in the CPI consumption basket may understate the relative weight o f food consumption among poorer households. Second, the poverty and social consequences may vary depending on the geographic location of the household and depending on whether households are net food buyers or net food sellers. I t may also matter whether they rely exclusively on food purchases for food consumption and if they do, whether they have access to cheaper substitutes. The rural poor are thought to be more self-sufficient, able to produce food for own-consumption, compared to the urban poor. With respect to energy consumption, the poor are also thought to have access to less expensive sources o f energy (though they are probably dirtier sources and pose both environmental and health risks). 2.42 The indirect effects can also be large. Fuel price increases can have a direct poverty effect, through the household consumption o f energy. The indirect effects on other products consumed by the households -using f u e l as an intermediate input---can also be substantial. Shidies o f non-ECA countries suggest that f u e l price increases can have net effects that are progressive (and thus have much larger welfare consequences for urban and richer households compared to poorer, rural households) mainly through their indirect effects.37The indirect effects through income can also be substantial. For households with members who are wage-employed in the agriculture sector, the increase in earnings may partially offset the welfare consequences o f rising food prices. 36 Coady, et al. (2006). 37 Coady, et a]. (2006). 54 2.43 Policy responses, in turn, may mute the effects o f global commodity price shocks on domestic prices, though they may incur large fiscal costs o r redistribute income regressively. Governments may prevent a less-than-full pass through o f higher prices to consumers, through lower fuel taxes o f higher subsidies. Some countries use trade policy to address external price shocks. In 2008, for example, many countries enacted more restrictive food trade policy-such as through quantitative export restrictions and taxes on selected commodities-with the stated objective o f protecting food security and curbng price increases. Though this may dampen overall price increases, the policy redistributes income away from net food sellers to net food buyers. Where net food sellers are mostly poorer, agricultural households, the policy impact can be regressive. Regional Overview 2.44 T h e rise in food and fuel prices through 2008 has had adverse economic effects o n countries in the region. For oil-importing countries, increases in energy prices led t o widening trade imbalances and escalating inflationary pressure^.^' Higher energy prices also led to higher unit costs, which are perceived to undermine competitiveness unless accompanied by productivity enhancements. The poverty impact o f further increases in food and fuel prices depends, as previously stated, on their relative importance in the consumption basket o f households. Such shares o f total consumption are observed to vary across countries, geographic locations and by household income, among other dimensions. 2.45 This section draws f r o m the ECA Household Data Archives to assess household welfare consequences in case o f a new round o f price shocks. The figures below, for example, report the share o f food and energy in total consumption by household quintiles in selected E C A countries (Figure 2.15 and Figure 2.16). There are a few notable observations: F i g u r e 2.15 Food Shares o f Consumption (In percent o f total consumption; by quintiles o f household consumption) EUlO (incl. Croatia) L o w Income CIS ElQl mQ2 OQ3 OQ4 8 Q 5 B P I SQZ 0 Q 3 OQ4 8 Q 5 80 70 60 50 40 30 20 IO n Bulgma Croatia Estonia Hungq Latvia Lithuania Poland Source: Staff calculations 38 There are o f course offsetting developments that are difficult to quantify in net terms. Rising oil prices through late 2008 bolstered the GDP growth o f o i l exporting countries such as Russia to about 7.3 percent on average in 2007. I n turn, the growing demand fiom the region's o i l exporting countries has increased exports among smaller oil-importing countries. 55 Middle Income CIS Western Balkans an 70 60 60 so 50 40 40 30 30 20 20 in in 0 n Source: Staff calculations. 2.46 First, as expected, richer countries have lower food shares. For example, food represents about a third o f total consumption among the new EU member countries, on average. Among low-income CIS countries, food accounts for close to two-thirds o f total consumption. In fact, across sub-regional groups, the average share o f food consumption tracks the level of development fairly well. There are o f course some exceptions. Ukraine, for example, which ranks as a middle-income count has food shares that are more or less comparable with some o f the low-income CIS countries. % 2.47 Second, within countries, there are substantial variations across geographic space and by household income (Appendix Tables 4 and 5). In Moldova, for example, the food share o f rural household consumption i s close to 50 percent; among urban households, it i s about a third. I Poland, food accounts for about 50 percent o f consumption among households in the n lowest quintile; among households in the lowest quintile, the food share o f consumption i s a little more than a fifth. Figure 2.16 UtilityiEnergy Shares o f Consumption (In percent o f total consumption; by quintiles o f household consumption) EU L o w Income CIS 30 25 20 15 in 5 n Source: Staff calculations 39 This was previously noted in World Bank (2005) as well. See the report's data and methodology appendix. 56 Middle Income CIS Western Balkans PIQl mQ2 UQ3 UQ4 BQS B Q l 8 4 2 UQ3 DQ4 BQS 30 30 25 25 20 20 15 IS 10 10 5 5 0 0 Source: Staff calculations. 2.48 Third, the energy shares o f consumption do not reflect clear patterns along country, income o r geographic lines. In part, this may be due to the use o f an imperfect proxy for energy share o f consumption. Using the comparable consumption aggregates from the ECA Household Data Archives, the consumption component that comes closest to energy i s the "utility" share o f household consumption, consisting o f expenditures on electricity, heat, gas, water and sewerage. In addition, the state or quality o f infrastructure matters as well. Where there i s insufficient utility infrastructure, many households may not be connected to central sources o f energy. In fact, in many countries, the utility shares o f consumption among urban households are somewhat higher compared to those o f rural households. Furthermore, the expenditure shares could reflect non- payment or payment arrears. They could also possibly reflect access to less expensive sources o f fuel and energy. 2.49 Aggregate energy shares o f consumption also likely mask important variations across energy sources. Connection rates, intensity o f consumption, and payment behavior, among others are likely to vary across various energy sources, such as central heat, electricity, natural gas, and other sources o f fuel. In Moldova, for example, households connected to central heating units are mostly urban households. In contrast, there i s almost universal electricity c~nnection.~' 2.50 Some patterns in the utility shares o f consumption may also reflect country-specific policies on utility tariffs, which can be lower than or equal to the relevant cost-recovery levels depending on whether utility reform programs have been completed. In fact, in countries known for energy tariffs that have not been completely adjusted to full cost-recovery, the utility shares o f consumption are relatively low. The utility shares o f consumption in Belarus and Ukraine, for example, are about half or even a third o f utility shares among some o f the new EU member states. 2.5 1 An analysis conducted by the World Bank in the middle o f the crisis, suggested that the welfare impacts o f last year's food and fuel price increases were possibly very large. The study found that for some E C A countries, a 5 percent relative increase in food prices could worsen by poverty rates by up to 3 percentage points.41 40 Baclajanschi, et al. (2006). 41 Alam, et al. (2008a and 2008b). 57 2.52 One simple numerical exercise for assessing the welfare impact o f illustrative food (or energy price) increases would be to calculate the fall in real income associated with these increases. This follows previous studies o f fuel and food price increases, including selected E C A The calculations are made using two plausible scenarios. One scenario assumes no substitution while another scenario allows for a limited degree o f substitution. The distribution o f such welfare effects across all households can then be analyzed. 2.53 Previous studies thus essentially calculate two indexes o f price ~hange.4~ index, One the Laspeyres price index, assumes that consumption quantities in the baseline period are fixed. I t does not allow for substitution toward cheaper alternatives. The other price index, the geometric price index, allows for some degree o f substitution. An alternative way to interpret these calculations would be as compensations needed to ensure that the household are as well o f f as they were prior to the price change or that household utility i s kept constant. In the case o f the Laspeyres index, this i s consistent with the items and quantities o f consumption remaining unchanged, with underlying preferences characterized by a Leontief utility function (that is, no substitution). In the case o f the geometric index o f relative price change, it reflects Cobb-Douglas preferences and allows for substitution away from relatively more expensive goods but keeping household utility constant. 2.54 The welfare effects are of course proportional to the budget share of food consumption, by construction. The results are in the Appendix (Appendix Tables 6 and 7). Across all countries in the region, the poor bear a greater burden o f the welfare impact o f a food price increase. The differences along geographic lines are also clear: rural households are hit harder compared to urban households. With respect to a 10 percent fuel price increase, the distributional consequences are less clear. In many countries, urban households and the more affluent households bear a greater burden o f the welfare impact; t h i s however i s not true everywhere. Where there i s some possibility o f substitution, the welfare impact i s smaller; this i s true for both food, and fuel price increases. Country Illustrations 2.55 Within countries, there i s likely to be substantial heterogeneity in the welfare impact o f a price shock. The regional simulations above ignore a number o f household specificities that determine the net poverty impact o f food or energy price increases. As previously stated, the welfare impact o f rising food price depends, in part, on whether households are net buyers or net sellers o f food. The unfavorable consequences o f rising prices can also be offset by rising real transfers or real wage increases. This section illustrates some o f these dimensions drawing from countries where the food or fuel price increases that have taken place are among the sharpest in the region. 42 See, e.g., Baclajanschi, et al. (2006); Freund and Wallich (1997); and Coady, et al. (2006). 43 The Laspeyres index i s also known as an arithmetic mean index, calculated as the s u m o f weighted prices in time t+l, retaining base period consumption shares. The second i s a geometric index o f relative price change (RG) using the base period consumption shares as weights:: RG =n , (Pt+l,,/ PL1)W where Pt+l,, and P,, are the prices o f the i'th consumption items in the new and base time periods, respectively, and W i s , the share of the i'th consumption item in total consumption. See also Pollak (1989), Gupta, et aZ (2000), . US. Bureau o f Labor Statistics (1997) and the Technical Appendix in Baclajanschi, et al. (2006). 58 2.56 I n the Kyrgyz Republic, for example, the food price increases are estimated to have had substantial welfare effects on net consumers.44Although the share o f food in total consumption falls with income (and i s thus highest among the poor, as we saw from the regional overview in the previous section), the share o f net food consumers generally rises with income. However, net consumers s t i l l represent the majority o f households in the poorest quintile. More generally, for the country as a whole, 53 percent o f the population lives in households characterized as net food consumers. O f these net producers, 35 percent are poor. As a result, about 19 percent o f the population are both net food consumers as well as living in poverty, and were estimated to have been hurt the most by the food price increases in 2007. Figure 2.17 Kyrgyz Republic: Net Food Figure 2.18 Kyrgyz Republic: Estimated Consumers and Net Food Producers Poverty Impact of the Food Crisis (In percent o f households) (In percent o f the populations) aNet Consumers N t Producers e BNet Consumers . e Nt Producers O A l l 100 80 60 40 20 0 Wage +lo% Wage +20% I Wage +30% Q1 42 Q3 Q4 Q5 2006 2007 Source: Staff calculations. 2.57 At the same time, the welfare consequences of rising food prices were partially offset by rising wages in the Kyrgyz Republic. N o t surprisingly, the estimated net impact on absolute poverty (with the poverty headcount at 40 percent in 2006) was inconclusive. Extreme poverty, however, was estimated to increase by up to 8 percentage points (from 9 percent in 2006), depending on the degree o f wage increase. This percentage point increase i s equivalent to about 400 thousand people falling into extreme poverty because o f rising food prices. Urban poverty was also estimated to increase. This i s not surprising considering that about 30 percent o f all net consumers live in the capital. 44 This i s based on Sarosh Sattar's unpublished work and data, which she generously shared. Errors o f interpretation are the study team's own. 59 Figure 2.19 Albania: Welfare Impact Figure 2.20 Tajikistan: Welfare Impact by Livelihood by Livelihood (In percent; bubbles represent the size o f the (In percent; bubbles represent the size of the population affected) population affected) __ J 10 0.0 4 00 -10 - I -1 0 -20 - -2 0 -30 -4.0 ._ 1- ............................................... " 1 2 3 4 5 1 2 3 4 5 Expenditurequintiles Expenditure quintiles Source: Zezza, et. al. (2008). 2.58 I n Tajikistan and Albania, the net poverty impact i s mediated by access to agriculture inputs, assets, and livelihood strategies. In a recent study o f 11 countries, including Tajikistan and Albania, the authors found that the poorest households were likely to be hurt the most by food price shocks (Figure 2.19 and Figure 2.20).45 They did find some evidence that some o f the poor households manage to benefit from rising prices o f basic commodities, depending on whether these households have sufficient access to agriculture inputs, or assets such as land. 2.59 Despite the moderating effects of livelihood and assets, the poor were nonetheless found to be the most likely to have been hit hardest by the price shock. This was true for all countries, irrespective o f location within each country. This i s not completely surprising, as the poorest households also have the weakest access to agriculture inputs and assets. They also tend to be relatively less educated, with relatively lower productivity, and limited capability to take advantage o f profitable activities in agriculture. F. HOUSEHOLDS AND INCOME SHOCKS Data and Methodology 2.60 This section follows the methodology underpinning recent simulations o f the n poverty implicationso f economic growth projections?6I brief, this section uses country-level projections for GDP and private consumption through 2010. Following existing exercises, we first assume that changes in GDP or income will not be passed on fully to private consumption. The impact will depend on the relationship between private consumption growth and GDP growth in each country. Next, the projected growth in private consumption i s then used to predict per capita household consumption in each country, using the household survey data from the latest available year. Finally, the predicted household consumption i s compared to the relevant poverty line. 45 Zezza, et. al. (2008). The data were generously provided by the authors. 46 See, for example, World Bank (2009 and 2005). 60 2.61 The exercise yields two sets o f results: (i)poverty projections using the pre-crisis GDP and private consumption projections and (ii) poverty projections calculated f r o h more recent GDP and private consumption projections (released in January 2009 and April 2009). The difference between (i) (ii) be considered a measure of the poverty impact o f and can the global crisis. 2.62 This section uses household survey data and macroeconomic growth projections. Household survey data are drawn from the ECA Household Data Archives. We have survey data for 25 o f the 29 countries in the ECA region, representing 95 percent o f the region's total population. Economic growth projections are drawn from the I M F ' s World Economic Outlook (WEO) databa~e.~' Growth projections at the country level are available for the pre-crisis period (April 2008) and for April 2009. The January 2009 WE0 growth projections are available at the country level for some ECA countries (such as Russia); however, for most ECA countries, only sub-regional averages were made publicly available. These sub-regional averages were used to impute growth projections at the country level. Finally, we use historical data (covering the three years preceding the crisis) for each country to estimate the ratio between private consumption growth and GDP growth. On average, it i s equal to one but there i s some slight variation from country to country. (This assumption i s discussed more fully below.) The underlying country data are reported in Appendix Table 8. 2.63 This numerical exercise uses a poverty line of $PPP 2.50 per person per day and a povertyhulnerability line o f $PPP 5.00 per person per day. This follows the most recent round o f the International Comparison Program (ICP) on purchasing power parities (PPP). Although the World Bank recommends a new international poverty line of $PPPl.25 per person, the $PPP 2.50 and $PPP 5.00 poverty/vulnerability fines have been found to be more relevant for ECA, to take into account the higher cost-of-living associated with the region's colder climate and the conditions in many middle-income countries throughout the region.48In addition, this follows the 2005 regional study that adjusted the region's international poverty line(s) to reflect similar consideration^.^^ Important ~aveats" 2.64 These regional simulations are based on several strong assumptions, which are explained further below. Although these assumptions are defensible, there i s a large, inconclusive literature on, among other things, whether these assumptions hold on average, whether they hold linearly or non-linearly (depending on, for example, the level financial sector development), and whether these assumptions hold depending on whether it i s a "normal" period or a crisis period, and, during a crisis period, whether it i s a financial crisis or a different kind o f economic crisis. 2.65 These simulations ignore the distributional consequences of the crisis. The exercise assumes that the growth in per capita household consumption i s distribution neutral; that is, households in every part o f the income distribution are all affected uniformly by the average 47 Ideally, private consumption growth projections fiom the Global Economic Prospects (GEP) database would have been preferable. However, country-level projections were not readily available. The calculations in World Bank (2009) are based on the GEP database. 48 See also Alam and Sulla (2009). 49 World Bank (2005). '' This section draws in part fiom the caveats outlined in World Bank (2009). 61 growth or decline in consumption. On one hand, previous research suggests that there has been no change in inequality, on average, during economic contractions thus lending some support to this assumption. On the other hand, there may be disproportional effects on the poor depending on the relative exposure o f households to the economic shock. In fact, despite the zero change in inequality on average, substantial variations exist from country to country. 2.66 A review of ECA's experience with previous crises suggests that, in fact, certain types o f households tend to be more vulnerable during crisis periods.51 For example, an analysis o f vulnerability in Moldova reveals that the consumption o f larger households experienced larger drops after the Russian financial crisis; moreover, controlling for household size (among other individual and household characteristics), the number o f children in the household was associated with larger consumption losses. Similar results were found in an analysis o f Russian households over this same period: The more children are present in a household, the greater this household's poverty risk and the lower i t s ability to smooth consumption. In addition, households with higher initial incomes and more assets were found to be better able to protect their welfare during and after a macroeconomic shock, in large part due to their broader menu options o f coping with the shock, such by drawing from their savings or asset liquidation. 2.67 The exercise does not assume a unitary ass-through from GDP growth to private consumption growth as the economy contracts. "These simulations are based on the estimated ratio o f private consumption growth to GDP growth using non-crisis data at the country level, which may be higher or lower than one, depending on actual country outcomes. However, there i s no reason to think that this recent relationship will continue to hold over the crisis period. 2.68 A large literature has emerged on the relationship between consumption growth and GDP growth. In particular, the literature has explored what i s typically referred to as "excess private consumption volatility" (relative to GDP or income growth volatility) and i t s possible drivers, including financial i n t e r m e d i a t i ~ nThe literature postulates that financial deepening .~~ curbs consumption volatility, as financial markets promote risk sharing and allow households to smooth consumption. Some empirical studies have provided some supporting evidence, but they have also found this relationship to be nonlinear, requiring some sufficient level o f financial deepening before yieldin any measurable relationship between consumption smoothing and financial intermediation?' In addition, some recent studies o f the fall in consumption during financial crises suggest that financial intermediation may exacerbate the decline in consumption, as consumption becomes more sensitive to the availability o f bank credit.55 51 This and other references throughout the report to the welfare costs o f previous crisis in ECA are drawn from the comprehensive review of the literature conducted by Victoria Levin. 52 In fact, there are two underlying assumptions: (i) first concerns the relationship between GDP growth the and average per capita consumption and (ii) second concerns the relationship between the growth in the average per capita private consumption as measured in national accounts and the growth in per capita household consumption as measured in household surveys. The first (i) estimated as explained in the data is section and the second (ii) il assumes a f l pass-through. As discussed in World Bank (2009), the poverty impact may be overstated if the actual fall in household consumption i s less than the fall in national accounts-based private consumption. 53 See, for example, Bekaert, Harvey, and Lundblad (2006). " See, for example, Kose, Prasad, and Terrones (2003). In fact, up to a certain threshold, relative consumption volatility may rise with greater financial intermediation. " IMF (2009a). 62 2.69 The regional simulations based on GDP shocks abstract from the potential household income shocks arising from reduced remittances due to the impact of the crisis in migrant host countries. As highlighted in the previous Chapter, many countries in E C A are heavily dependent upon remittances as a source o f foreign finance at the macro level. At the household level, such inflows can be important sources o f funds for consumption expenditures, health and education, and investment. For example, in Tajikistan in 2007 around 60 percent o f the yearly consumption o f the median household was financed by remittances (World Bank 2009~). As outlined in the country studies detailed below, it i s thus important to tailor the specific income shocks to country characteristics. 2.70 These simulations also ignore the many nonmonetary and non-income dimension9 of poverty likely resulting from the crisis. As has been seen in previous crises, the social consequences of crises can be significant, as households cut back on their health care spending, pull children out o f school, and curb many other essential expenditure^.^^ Such social consequences may have immediate consequences, as well as longer-term implications for human capital formation, the intergenerational transmission of poverty, and the sustainability o f long- term economic growth. 2.71 The results presented below for the region as a whole should thus be interpreted with caution. They should be treated as illustrative, taking into account many o f the limitations o f the calculations behind them. In some cases, the poverty impact may be understated, such as in the event that consumption substantially lags behind GDP growth in 2010. In other cases, the poverty impact may be overstated, where there are opportunities for consumption-smoothing and offsetting income shocks. Regional Overview: Main Results Figure 2.21 The Impact o f the Crisis on Poverty and Vulnerability in the ECA Region (In Dercent o f the DoDulation) , * I 1 L SPPP2.5 a Day SPPP5.00 a Day Poverty and Vulnerability Projections 2007-2010 Poverty and Vulnerability Projections 2007-2010 10 1 I 36 I 34 - 32 - 30 - 4 .I I 28 - 26 - 25.0 24 - I 0 1 22 J 2007 2008 2009 2010 2007 . 2008 2009 2010 --Pre-Crisis Projection *January Projections -cPre-Crisis Projection +January Projections 'Latest Projections -Latest Proiections Source: Staff calculations. 2.72 The results suggest that poverty will rise. By 2010, the poverty headcount (using the $PPP 2.5 poverty line) for the region as a whole i s expected to be about 2.4 percentage points higher than it would have been, relative to baseline projections o f income or GDP growth (Figure j6 See also Dudwick, et al. (2003). 63 2.2 1). The share of the poor or vulnerable population also rises by 7.2 percentage points. In 2009, these shares rise by 1.6 and 5.9 percentage points, respectively. In absolute terms, an additional 11 million people will fall into poverty b 2010. An additional 23 million people will find thqmselves vulnerable because o f the crisis! In 2009, 7 million more people are in poverty and 28 million more are either poor or vulnerable. 2.73 Turkey and the middle-income CIS countries are driving the percentage-point increases in poverty and vulnerability, followed closely by the EUlO plus Croatia. Relative to baseline projections, the share o f the poor and vulnerable population rises by over 8 percentage points, on average, in these countries. The relative differences across sub-regions reflect the significant revisions to GDP growth projections (Figure 2.22). Many o f the middle-income CIS countries, for example, have experienced substantial downward revisions in their economic growth prospects between April 2008 and April 2009, with growth prospects switching from expansion to recession. Russia's 2009 growth projections, for example, f e l l from +6.8 to -6.5. n Ukraine's growth prospects in 2009 declined from +4.9 to -7.3. I contrast, a number o f low- income CIS countries s t i l l expect their economies to expand by modest amounts in 2009. These include Azerbaijan (+1 ,7), Georgia (+1 .O), Tajikistan (+1.4), and Uzbekistan (+4.9), though all their GDP growth numbers have been revised downwards as well. At the lowest end o f these adjustments i s Uzbekistan, with 2009 GDP growth numbers essentially unchanged from the pre- crisis period to April 2009. Figure 2.22 The Impact o f the Crisis on Poverty and Vulnerability in the ECA Region: Sub-Regional Results (In percent o f the population) EU Western Balkans SPPP 5.00 a Day SPPP 5.00 a Day Poverty and Vulnerability Projections 2007-2010 Poverty and Vulnerability Projections 2007-2010 35 30 j:i 21.3 22 25 15 7:O 10 , , , 5 0 2007 2008 2009 2010 -Baseline Projection *January 2009 Projections -Baseline Projection --January 2009 Projections +Latest Projections +Latest Projections ''This i s based on the estimatedtotal ECA population o f about 477 million, using UN Population data. 64 L o w Income CIS Middle Income CIS ~ ~ $PPP5.00 a Day SPPP5.00 a Day Poverty and Vulnerability Projections 2007-2010 Poverty and Vulnerability Projections 2007-2010 , 80 70 60 . f 20 , , , 15 20 10 10 5 0 0 2007 2008 2009 2010 2007 2008 2009 2010 --Baseline Projection --January 2009 Projections 1 --Baseline Projection ---January 2009 Projections , +Latest Projections +-Latest Proiections ; o w e : Staff calculations. Some Sensitivity Tests 2.74 The core simulations are based on the historical relationship between GDP growth and private consumption. We re-ran the simulations above to allow for a unitary pass-through from GDP growth to private consumption (and thus to household consumption). The key results are essentially unchanged-both for the region as a whole and for the sub-regions. Selected figures are presented in Appendix Figure 1. 2.75 The simulations were also re-calculated using the elasticity of poverty to rowth in consumption per capita calculated for ECA countries over the period 1998-2003. Because ti the period refers to the economic recovery period following the Russian crisis, the poverty elasticity estimates may not be appropriate. Nonetheless, the results are essentially unchanged. Country Illustrations 2.76 The regional overview masks the likely heterogeneity of impact within countries. This regional analysis should not be a substitute for country-specific poverty analysis. As previously discussed, the results o f the preceding numerical exercises ignore many country specificities and the likely concentration o f vulnerable households, depending on the nature o f the economic downturn. In addition, while some economies are s t i l l projected to grow by modest amounts, the welfare risks are not shared uniformly across all households. 2.77 Tajikistan i s a case in p0int.5~ While the country as a whole i s s t i l l projected to grow by a very modest amount through 2009, many households are vulnerable to falling demand for foreign labor in Russia and Kazakhstan. As mentioned in Chapter 1, the growth o f remittance outflows from Russia to CIS countries contracted in 2008 44, tracking the declines in Russian construction activity. The latest figures indicate that the dollar value o f recorded remittances to Tajikistan (via money transfers) f e l l 36 percent year-on-year in the first five months o f 2009, with similar contractions seen in the heavily remittance-dependent economies o f Georgia and Moldova. In Tajikistan the results o f simulating the impact o f up to a 50 percent fall in remittances suggests that the poverty headcount can rise by up to 7 percentage points, assuming 58 World Bank (2005). See Table 2.1. 59 World Bank (2009~). 65 households do not adjust (e.g., returning migrants do not find jobs in local labor markets), or by 3.5 percentage points, allowing for some adjustment on the part o f households. 2.7.8 I n Armenia6', the poverty headcount i s estimated to increase by over 5 percentage points between 2008 and 2010, primarily driven by shocks transmitted through labor market channels. Many will find themselves out o f work or earning substantially less than in previous years, particularly in sectors such as the construction and mining sectors. In addition, the impact on remittance-dependent households could be large. The results o f recent analysis suggest that the poverty headcount may rise from 18 percent to 27 percent in households that receive remittances from sources other than immediate family members (a peculiar feature o f household well-being in Armenia i s the large share o f remittances from non-immediate family members). 2.79 I n Bulgaria6',the economic slowdown and the fall in remittances i s estimated to lead to a 1.2 percentage point increase in poverty. Although more modest than the expected impact in other countries, the labor market i s again an important transmission channel, particularly among workers in the construction sector. Declining remittances underpin about a quarter o f the overall poverty increase, though a much larger share o f the rise in extreme poverty. 2.80 I n Russia6*,the results of recent simulations suggest that the poverty headcount in rural areas will likely rise by over 5 percentage points. The simulations suggest that in addition to rural households, households with children and pensioners are at the highest risk o f falling into poverty. The growth in unemployment levels will also drive increases in poverty. 6o World Bank (2009d). 61 World Bank (2009e). 62 World Bank (2009g). 66 CHAPTER 3 COPING WITH THE CRISIS A. INTRODUCTION 3.1 The resilience o f households to macroeconomic shocks ultimately depends upon the economy's institutional readiness, the flexibility o f the economic policy regime, and the ability of the population to adjust. Policy and institutional preparedness i s essential so that countries can manage the adverse social impacts o f macroeconomic shocks. This requires ex ante analysis o f risks, a good understanding o f their possible transmission channels if triggered, and their possible impacts on households; developing approaches that ensure that the state does not intervene excessively in terms o f detrimental longer-term distortions to incentives or fiscal sustainability; and having a comprehensive social safety net system that provides for countercyclical and scalable interventions. 3.2 This Chapter looks at how the impact of the various shocks arising from the crisis on household welfare may be offset by households' own coping strategies and by social safety net systems. It will also assess some key constraints in the policy response to the crisis, drawing from some recent analyses o f fiscal space and the availability o f fiscal resources and a recent assessment o f the performance o f social protection programs in ECA countries. Finally, it will provide examples o f possible policy responses to mitigate the impact o f the crisis, by type o f shock to households. The options for policy responses covered here are by no means exhaustive. They are discussed below mainly for illustrative purposes. B. RESPONSES: LESSONS ECA EXPERIENCE HOUSEHOLD FROM 3.3 Over the transition period, a growing literature has documented patterns o f self- insurance, informal insurance, and informal risk pooling in ECA. They have also chronicled household strategies for coping with economic shocks, including borrowing, migratiori, substitution o f consumption toward less expensive goods, and engaging in risky or illegal activities. Such strategies and risk mitigation mechanisms may be disproportionately concentrated among certain groups of households, depending on their region o f residence, income, and social capital. 3.4 Households in ECA have employed a variety o f coping strategies to smooth consumption during previous crisis periods. Some o f these strategies correspond to what i s referred to in the literature as "risk management".63 These include household members holding jobs with uncorrelated risks, either domestically or through migration of family members to foreign countries. Other strategies smooth consumption over time, such as dissaving, including ~~ 63 Alderman and Paxson (1 992). 67 asset liquidation, and borrowing where possible, and s t i l l other strategies share risks across households (inter-household private transfers). Generally, the empirical literature rejects the existence o f full consumption insurance, whereby temporary income fluctuations have no effect on consumption, but does provide some support to partial consumption smoothing, whereby consumption changes are smaller than income changes. This implies that, in general, households in the region were successful, albeit only partially, in protecting their welfare through crisis times by relying on a variety o f coping strategies as described in more detail below.64 3.5 Labor supply adjustments. In response to falling income due to the effects o f a macroeconomic shock, a household can increase i t s involvement in the labor market. Those already employed can increase their hours worked, or find secondary employment. Other members o f the household can transition out o f inactivity in order to supplement household income. Existing studies o f Bulgaria, Russia, and Turkey indicate that, in general, labor supply adjustments have not allowed households in the ECA region to preserve their pre-crisis welfare levels. The proportion o f households that found secondary employment i s small and the earnings were generally insufficient to compensate for the loss o f income from primary jobs. 3.6 Migration. As local employment opportunities decline, one option would be to relocate to a region with better labor market conditions. Labor migration can be internal or international, and it can involve either the whole household or only some o f i t s working-age members. The necessary conditions for the effectiveness o f this coping strategy are labor market flexibility and the ability and willingness o f workers to move to locations with jobs plus a host region likely to provide sufficient labor income gains to offset migration costs. In the years following the Russian crisis, for example, many Moldovans migrated abroad in search o f employment opportunities and better living conditions. Studies o f household behavior during the early transition period in Kazakhstan also found that migration responded almost immediately to movements in relative exchange rates and to systemic crises, such as the 1998 Russian financial crisis. However, wage differentials and differences in construction activity have been found to take a longer time in influencing migration patterns. A recent study o f Turkey found that rural-to-urban migration has been the most important informal coping strategy, leading to increased urbanization in all regions o f Turkey. The broad-based nature o f the ongoing downturn, affecting both traditional host and source countries, i s clearly an important determinant o f the effectiveness o f this coping strategy in the current economic environment. 3.7 Subsistence Farming. Households that have access to private land plots can use it to supplement their income by selling the home-produced goods or to augment their own consumption with such home production. Studies o f household behavior in Bulgaria, Russia, and Tutkey during previous crises observe that subsistence farming has often been employed by households to supplement their food consumption. However, it has also been found to be an ineffective coping strategy to address vulnerabilities in non-food consumption, or in lifting households out o f poverty. 3.8 Dissaving /Borrowing and Asset Liquidation. By saving a portion o f its income flow in good times and dissaving (or borrowing) in bad times, a household can minimize consumption variability in the presence o f income fluctuations. The same principle applies to the accumulation o f assets (such as housing, durables, production equipment) in good times and the sale o f such assets in bad times. Of course, the usefulness o f this strategy depends on households' access to credit markets and their ability to dispose o f their assets after a macroeconomic shock. For 64 The full set o f references i s available on request. 68 example, many households in Turkey turned to selling their assets during the 2001 crisis. About 20 percent of households reported selling assets and valuables. However, it has also been suggested that proceeds from such asset sales were meager due to insufficient demand for assets held by the poor. This i s similar to the phenomenon o f asset "fire-sales" in financial markets potentially yielding prices below fundamental values (and a wealth redistribution from net sellers to buyers). In addition, as highlighted in the discussion o f household indebtedness, household gross asset positions may be associated with financial liabilities such as mortgages, thus limiting the potential net gains from such sales (or even leading to potential net losses as in the case o f negative mortgage equity). 3.9 Private transfers. Besides turning to the government for assistance, households suffering from the impacts o f an economic shock can turn for help to friends and family. If the shock does not affect households equally-Le., more technically, if the idiosyncratic component o f the economic shock i s large compared to the covariate component-then households can reduce consumption volatility through inter-household transfers, flowing from less affected households to more affected households. In ECA, private transfers have been found to be an important buffer against household income and consumption volatility. However, macroeconomic crises decrease the likelihood that a household will be able to use this strategy effectively, since a widespread shock would, by definition, affect most people in that household's social network. Moreover, some marginalized groups, such as ethnic minorities, are often excluded from the informal support networks available to other households. 3.10 Compared to previous crises, the scope for households to engage in their traditional coping strategies may be more limited. During previous crises, households found secondary employment, relied on transfers from friends and families, or left for work abroad to augment family income. Because o f the global nature o f the crisis, and because macroeconomic shocks are hitting households on multiple fronts, these coping strategies may no longer be feasible; 3.11 F o r the poorest households, subsistence farming may be a viable strategy, though evidence from the recent food price shock suggests that many of the poorest households do not have access to agricultural assets and inputs. For some, transitions into informal sector employment may be possible though, for many households, earnings from informal sector activity will likely be insufficient to offset the poverty impact o f the crisis. c. CONTEXT: POLICY RESPONSE, GOVERNMENT RESOURCES AND CONSTRAINTS Overall Fiscal Envelope 3.12 The ability o f many governments in ECA to respond to the crisis-such as by increasing social transfers-is generally constrained by rising government deficits. Between 2007 and 2009, on average, deficits in percent o f GDP are projected to rise by about 3 percentage points. There are marked variations across countries, with Estonia, Montenegro, and Russia at the higher end o f this distribution, while Belarus, Hungary, and Georgia are at the lower end o f the distribution. Nonetheless, for many countries, fiscal policy responses to the crisis will likely be muted by rising deficits that have become much more difficult to finance. I t would be essential to first determine the overall fiscal adjustment warranted for macroeconomic stability and debt sustainability, taking into account initial conditions and the likely impact o f the crisis on public finances.65 Economies that experienced strong initial fiscal and external positions are likely to `'See World Bank (2008) for a more comprehensive discussion. 69 have more room for expansionary fiscal policy and can afford a fiscal stimulus package, while those with weaker initial positions may require substantial fiscal adjustment. Other features o f a country's macroeconomic policies are also important. For example, countries with fixed exchange rates will have to depend more on fiscal policy, rather than monetary policy, for adjustment. 3.13 A recent analysis in fact suggests that there are likely large shortfalls in education and health spending worldwide due to the growth slowdown.66ECA countries, as a group, will require the largest outlays, compared with other regions, to protect their planned expenditures in education and health services. Accounting for relative fiscal constraints, ECA i s in a better position. However, there i s s t i l l potentially a large shortfall in education and health spending among countries with little fiscal capacity and it i s not likely to be financed by donor resources. 3.14 Where there are no new official or alternative sources o f financing, or where there is little scope to mobilize revenues, some countries may resort to across-the-board cuts in public spending.67Although social safety nets will be among those items likely to be cut as revenues fall, protecting these programs-and possibly expanding some o f them, where some reallocation o f resources i s possible-will be an important element in the response to the crisis. Figure 3.1 General Government Balances in ECA 2007 and 2009 (In percent o f GDP) __ - _- - 1 60 40 20 00 -2 0 -4 0 -6 0 I EUlO (+Croatia) Low-income CIS I Middle Income CIS 1 Western Balkans Source: 1 F WE0 database (April 2009). M 3.15 The prioritization o f labor-using investment expenditures-either from countries' own budgets or from resources provided by donors-could be one option for addressing the labor market consequences of the crisis, while accounting for constrained fiscal resources. Such 66 World Bank (2009f). The calculations are based on the April 2009 WE0 and are consistent with other WEO-based calculations elsewhere in this report. 67 See, for example, Brownbridge and Canagarajah (2009). 70 investments could include rural roads projects or irrigation systems rehabilitation projects that can create short-term employment opportunities while creating the conditions for longer-term growth. Improving the efficiency o f public spending may also create some additional fiscal space. Existing Social Protection Systems6' 3.16 Countries in the region operate a combination of safety net programs. The programs are typically in the form of cash transfers with an emphasis on family allowances (such as child allowances), social pensions, heating and housing allowances, and targeted anti- poverty programs. Some countries in E C A are yet to reform a range o f categorical benefits and subsidies leftover from the pre-transition period. Across countries, multiple programs exist, leading to the fragmentation and duplication o f benefits. 3.17 The region's social protection systems currently vary in size and targeting performance across countries. The results o f comparing the targeting performance o f selected social assistance benefits across countries suggest that Lithuania, Ukraine, and Turkey are among the countries with the bulk o f social benefits reaching the poorest households. At the lower end are countries where only 40 percent o f the social benefits reach the poorest quintile. However, most countries in the region have at least one targeted safety net program that can possibly be scaled-up in response to the crisis. Expanding such programs can take place either by increasing the value o f benefits they provide or by expanding their coverage to reach those households s t i l l currently outside the system. However, in some countries, including Belarus, Bosnia, Hungary, Kazakhstan, Moldova and Russia, the targeting performance o f existing programs remains weak. 3.18 Depending on a country's initial conditions, the response to the crisis in terms o f social assistance may involve expanding some well-performing programs, reforming relatively less effective interventions or, alternatively, introducing new programs as appropriate. The experiences o f other countries suggest that programs such as conditional cash transfers (CCTsf", workfare schemes, and public works programs can be effective instruments for protecting the vulnerable from immediate as well as longer-term (second-round) consequences o f transitory shocks on non-income dimensions o f welfare, including human capital accumulation. D. POLICY RESPONSES: IMMEDIATE SOME ILLUSTRATIONS 3.19 This section provides illustrations o f potential policy responses and instruments for mitigating the poverty and social impact of the crisis. The examples are organized by type of shock to households. The treatment o f the topic i s not comprehensive and the options listed are by no means exhaustive. The options, are instead, discussed below for illustrative purposes. 3.20 Across various policy instruments and social protection programs, there are a number o f important considerations. The primary consideration would o f course be the appropriate role for the government-whether the government responds to the crisis through expenditure policy, tax policy, or through regulatory policy. Another important consideration This and subsequent paragraphs are drawn heavily from World Bank (2009h). The report provides an excellent, comprehensive review of the region's social protection system. 69 According to a recent report (World Bank 2008b), Turkey initiated a CCT program during the 2001 crisis and the program has been found to be effective. FYR Macedonia i s now in the process of developing a CCT, with a special focus on youth and infants. 71 would be the fiscal cost o f a program, the administrative ease in which it can be implemented, and the incentives it creates. It will also be important to consider whether a program should have universal coverage, or whether it should be narrowly targeted or self-targeted. As explained below, country-specific resources and institutions will drive the relative merits o f these instruments. Credit Market Shocks 3.21 I n countries where households are experiencing rising debt service burdens, governments may have to consider facilitating the restructuring o f household debt in default.70In many E C A countries where banks currently have limited capital buffers, bank responses to rising non-performing loans have focused on extending grace periods. However, without the certainty o f a rapid economic recovery, these restructuring strategies effectively postpone problems into the near future. This creates substantial risks o f under-provisioning and inadequate recognition o f losses and thus o f over-estimating bank solvency. 3.22 There i s a role for governments to provide incentives for proper debt restructuring. Defining the right framework i s challenging as it requires balancing competing pressures on banks, households and the government in a way that i s fiscally affordable, creates minimal market disruption, i s socially acceptable, and allows banks to remain solvent and able to resume lending in the medium-term. 3.23 A template for government-assisted household debt restructuring has been The proposed re~ently.~' authors advocate a restructuring program that reflects some essential features including simplicity and limited scope, as well as participation on a voluntary basis, among other features. They consider two general approaches, one involving the creation o f a legal and institutional framework that can underpin case-by-case debt restructuring. The other approach i s based on some form o f financial assistance by the government. 3.24 The estimated cost o f providing financial assistance to indebted households at risk o f default i s relatively modest, on average, though with variations across countries. Simple calculations can be made for the cost o f compensating indebted households who are subjected to an interest rate shock in Estonia, Hungary, and Lithuania and an exchange rate shock in Hungary and Ukraine. This i s based on the assumption that all households are fully compensated for the increase in the debt service burden resulting from the shock. In Estonia, Hungary, and Lithuania, the implied costs o f an interest rate shock are 0.44, 0.19, and 0.17 percent o f GDP, respectively, equivalent to about 29 percent, 6 percent, and 12 percent o f the social assistance budget, respectively. In Hungary and Ukraine, the compensation for an exchange rate shock i s 0.04 and 0.22 percent o f GDP, respectively, equivalent to about 2 and 15 percent o f the social assistance budget, r e ~ p e c t i v e l yIn general, these are relatively small sums, except in Estonia. The share o f .~~ indebted households in these countries that i s s t i l l not as large as those in more advanced economies likely drives this. 3.25 On the other hand, the fiscal cost o f assisting severely indebted households may be an underestimate for a number o f reasons. First, the SILC-based calculations (Estonia, 70 We thank Sophie Sirtaine for raising these points. 71 See Laeven and Laryea (2009). 72 If financial assistance i s provided only to the households in the lowest quintile, the cost o f providing assistance i s o f course substantially smaller. 72 Hungary, and Lithuania) include mortgage interest payments only, because SILC data only allows us to assess the rising cost o f mortgage debt service. Taking all o f household debt service costs together may then yield a much bigger sum. Second, the risk exposure varies by type o f household debt. In Hungary, in particular, we know from central bank data that the exchange rate exposure o f consumer loans i s much larger than the exchange rate exposure o f housing loans (60 percent versus 84 percent at the end o f 2008). The SILC and Ukraine data are for 2007 and our calculations are based on households reporting themselves as indebted. Between 2007 and 2008, the pool o f indebted households may have expanded further. External Price Shocks 3.26 Increases in the domestic prices o f energy and food pose both short- and long-term , challenges for policy maker^?^ In the current environment, the short-run inflationary pass- through o f higher imported food and energy prices, including those due to exchange rate effects, may be offset by falling domestic demand as economic activity weakens. However, managing inflation using appropriate policy instruments remains important. The full pass-through o f price increases to consumers avoids introducing distortions into productive incentives, with support for vulnerable households to be provided by appropriate, well-targeted social assistance within the constraints imposed by a country's fiscal space. A country may also opt for a gradual phase-in o f energy tariff adjustments, where the price increases required by adjustment toward full cost recovery may be too steep. 3.27 The ECA region's previous experience with energy tariff adjustments suggests that direct transfers or tariff-based subsidies can play an important role in protecting poor household^.^^ There i s ongoing debate on the comparative merits o f direct transfers and tariff- based subsidies, such as a lifeline tariff or by charging a lower tariff for an initial minimum level o f energy consumption. Opponents o f lifeline tariffs suggest that they are expensive and, for the at least the initial block of, for example, electricity consumption, such lifeline tariffs subsidize both poor and non-poor consumers alike. However, supporters o f lifeline tariffs argue that where, poverty i s prevalent, where there i s close to universal access to network energy, and where social transfers are not well targeted, there i s a case to be made for tariff-based subsidies. 3.28 I t i s also important that policy responses do not conflict with the key longer-term reform agenda. For example, authorities should guard against reversal o f efforts to lower quasi- fiscal deficits in the energy sector, which i s an ongoing challenge in many E C A countries. It will also be critical to maintain an open and transparent trading regime. Although some countries within E C A adopted restrictive trade and price controls in response to the food price increases in 2007, many o f them have now been reversed. For example, Ukraine eliminated i t s export quotas * in June 2008 and Kazakhstan lifted i t s export ban in September 2008. At the same time, work needs to continue toward medium- to longer-term goals for improving the policy environment for agricultural productivity growth, improving energy efficiency, and strengthening social safety nets and other risk mitigation systems. Finally, communication to the public o f the policy choices adopted to address the impact o f higher energy and food prices, and the various trade-offs which are involved, may help build broader constituencies in support o f the adopted policies. 73 For a detailed discussion o f these issues, see Alam, et al. (2008a and 2008b). 74 See Lampietti, et al. (2007) and Lampietti (2004) for a more comprehensive discussion. 73 Income and Employment Shocks 3.29 The unemployment insurance system, the main tool for addressing rising unemployment may not be sufficient to mitigate the impact of the crisis. In fact, the unemployment insurance system itself may suffer from several limitations, including weak incentives for reducing welfare dependency or for job search. Benefit durations are long and can be expensive. Moreover, none o f the existing programs i s available for returning migrant workers, for example due to a lack o f work history necessary for unemployment insurance or lack o f permanent residence required for social assistance. This suggests that it may be worthwhile to consider alternative approaches to social protection. 3.30 M o r e generally, the global crisis will probably create "the new poor", or households that may be among those in higher income quintiles in the pre-crisis period but made poor by shocks to their income flows, liabilities, or consumption. These households will likely not be reached immediately by existing social protection programs. 3.31 Public works programs were an important component of the overall safety net package in Argentina, Mexico, Korea and Thailand during the so-called Tequila Crisis o f 1995 and the 1997 East Asia crisis. Public workfare programs generally played an important role in mitigating the negative effects o f the macroeconomic crises in these countries, though i t s relative role varied depending on the effects o f the crisis on the labor market. With the exception o f Mexico, income gains from public workfare programs were significant in these cases. For example, in Korea the main reason for launching a workfare program was the very sharp increase in unemployment, in both formal and informal sectors, because o f the crisis. The rate o f unemployment increased from about 2 percent prior to the crisis to 9.3 percent barely six months into the crisis. N o t surprisingly, public works in Korea played a dominant role in providing immediate short-term employment opportunities at low wages. In contrast, in Mexico the labor market impact o f the crisis was a dramatic fall in the real incomes o f workers, with relatively more limitedj o b losses. A cash income support program (Progresa) played a major role in social protection, with public works playing only a subsidiary role. 3.32 The ECA region's experience with workfare has been relatively limited. To date, simple, non-randomized evaluations are available for only four countries: Bulgaria, the Slovak Republic, Slovenia and Poland. 75 These countries' experiences with workfare are summarized in Box 4. 3.33 A broader use o f workfare in the region faces a number o f constraints. First, workers in most countries in the region have access to unemployment insurance. Second, unemployment rates are quite high in some countries even during non-crisis periods. Third, most unemployed are long-term unemployed, with some looking for jobs for over two years, in contrast to many developing countries. Fourth, a uniform application o f any policy across the region i s not feasible given tremendous diversity within the region in terms o f income, degree o f urbanization, dependence on agriculture or manufacturing, etc. Fifth, in many countries over a long period, there has been substantial emphasis on workers' rights; trade unions have been strong and ''The region's experience with workfare may be broader than these four evaluations may suggest. For example, during the 1998-2000 period, participation rates (as per cent of registered unemployed) in public works was about 15 percent in Bulgaria, 11 percent in Estonia, 27 percent in Hungary, 19 percent in Russia, 3.2 percent in Slovakia, 2.2 percent in Poland and 11.6 percent in Ukraine. Unfortunately, this rich experience has not been evaluated. 74 influential, and the attitude towards a downward adjustment o f wages has been generally hostile. By contrast, in more decentralized countries such as Argentina (and South Africa) there was less resistance to l o w wages, particularly when communities are fully informed about program goals. Sixth, the term "public works" i s often mistakenly associated with "forced labor". Indeed, in some countries the two terms have been used synonymously for years. N o t surprisingly, workfare programs are not viewed favorably in the region. Finally, at the implementation level, it i s common practice to use contractors. T h i s creates its own problems, and requires careful attention to the tendering process and even `greater attention to monitoring. 3.34 Given these constraints, what role can public works program play in ECA? With respect to the low-income countries in the region, public works program may have considerable merit. These countries have significant seasonal shortfalls in employment (during agricultural slack seasons). In addition, given very l o w yields o f main agricultural crops, productivity-enhancing works, including the construction o f rural infrastructure, have a role to play to promote agriculture productivity. Moreover, the design features o f public works programs can be modified and adjusted relatively easily to suit this class o f countries. 3.35 I n contrast, the introduction of public works programs in the lower middle and upper middle-income countries of the region requires more careful design and adjustment. For example, the central design feature o f programs-the wage rate-needs to be set carefully, so that the level i s higher than the unemployment benefit, but lower than the prevailing market wage rate. In order for the program to be attractive to skilled and semi-skilled labor, projects need to be carefully selected to accommodate labor o f varying skills, as was done, for example, in Korea. 3.36 The use of contractors to execute public works programs may pose a challenge, but there are suitable alternatives. In general, countries have followed two approaches: One option i s to avoid using contractors at all (for example in Korea and Argentina) and let local governments and communities implement the program instead. Alternatively, a program can use contractors under a regulatory framework, which has taken several forms. For example, governments could fix the share o f labor in each specific contract (say 30 percent wage cost in a road repair project) in the tendering process, and enforce it. Another option would be to provide a l i s t o f laborers in each locality that contractors could hire for any specific activity. Contractors provide a weekly report to the Government on the number and names o f persons worked on a specific project, and the Government will then transfer wages direct into the Bank accounts o f laborers. A third approach i s to provide appropriate incentives in the tendering process: ask contractors to specify the share o f labor cost in each project that they plan to execute, with the proviso that this would be one o f the selection criteria. The chosen bid can then be the one that promises to meet quality standards and promises to use the highest labor share in total cost. This needs to be enforced and monitored on a weekly or monthly basis. In all o f the above approaches, the government fixes the level o f the wage and contractors have to follow accordingly. Clearly, in any o f the above scenarios, contractors do not have the freedom to offer a wage that i s different from the one fixed by the government. 3.37 Another difficuIty could be market wages that are below the statutory minimum wage. Because governments cannot offer a wage less than the statutory minimum wage, this becomes a challenge. Argentina stated in i t s program document that what i s provided i s not a wage, technically, but compensation. However, contractors may refuse to offer a wage less than ' the minimum wage, even if the minimum wage were higher than the prevailing market wage. 3.38 Finally, contractors may bring in their own labor gangs to work on a project, instead o f using local labor. To avoid this scenario, the appropriate requirements need to be 75 specified clearly in the tender. In a depressed region with a high unemployment rate, contractors have to use available local labor, and only if such local labor i s unavailable are contractors legally allowed to bring in labor from outside a region. This i s not easy and tendering bids may be slower than otherwise. Clearly, if contractors are used, "self-selection" as a method o f targeting may not be feasible and so other approaches to targeting need to be explored. 3.39 I n sum, the following sequential decisions need to be taken: (a) Decide on whether a public works program i s the right option. If so, what i s the balance between public works and other programs already in place? (b) When public works i s chosen, decide on the specific design aspects critical for success for the chosen country. (c) Decide on the implementation modalities. (d) Finally, institute a credible monitoring and evaluation. Regardless o f which program i s chosen, post-crisis settings require that full attention be paid to selecting the right targeting instrument to reach the intended groups, explore possibilities for quickly scaling up the program throughout the country without compromising on the quality, and consider exit strategies right upfront before launching any program. 76 De Koning, Kotzeva, and Tzvetkov (2005). 77 Lubyova and van Ours (1999). 76 participationin the program, although a few workers (10 percent of the total) had a lower transition rate. In general, female workers, lower educated and older unemployed workers have had much greater difficulty in accessing regular jobs. The exit rate from PUJ jobs was quite high, mainly due to the positive effect of the retrainingprovided. Slovenia also introduced public works during 1992-96, in response to rising unemployment in the early 1990s. There was heavy reliance on public works, partly because of the limited success of other programs. The program consisted of creating jobs for the unemployed under the auspices of a public or a non-profit (NGO) organization. Projects were required to provide useful services or build infrastructure of use to communities. Jobs were for a period of one year. The objectives were to help workers maintain their workforce mchment and prevent the erosion o f their human capital. The contractors (selected via a tendering process) organized and carried out public works as well as provided mentoring and training as needed. In comparison with programs in Hungary and Poland, Slovenian public works attracted significant1 more educated participants and younger workers, and the program was more innovative. Ah assessmenty8 concluded that Slovenian public works participants immediately found a job upon completing the program. Poland implementedactive labor market programs (ALMP) consisting o f training and retraining, programs to enhance human capital, along with public works. A systematic evaluation of Polish ALMP showed training and retrainingperformed well, with the post-treatment employment rates o f both female and male participants observed to be higher than those who did not participate in the program. By contrast, the public works program suffered from major distortions, mainly because of "benefit churning" and lack of attention to proper calibration of various benefits (unemployment compensation) and wage levels. In addition, program officials felt male heads of households deserved sustained income support, which in turn adversely affected the functioning of the public works program." Some important lessons emerge fiom the Polish experience. First, greater emphasis should have been given to the training of the long-term unemployed while they were employed in public works. Second, the careful monitoring of employer behavior should have been incorporated into the program, to curb abuses of hiring cheap labor under the program, Third, distortions in the functioning of programs should have been minimized by carefully calibrating program benefits (wage levels) with other benefits such as unemployment compensation. E. POLICY LONGER-TERM RESPONSES 30. Over the longer term, there are various measures for limiting the risks borne by households as financial markets deepen. These include measures affecting both the demand- and supply-side o f household financial products. In terms o f the demand-side, promoting financial literacy may help households to understand the risks they expose themselves to because o f their consumption, employment, borrowing and asset portfolio choices. Addressing the supply- side dimension potentially incorporates a whole host o f macro-financial policy measures. 31. Detailed examination o f such measures i s not within the scope of this report, but in its discussion o f the generic policy implications of household credit growth in emerging market countries, the IMF highlighted five key policy areas that can help to limit related financial stability risks.80 These include prudent macroeconomic management to minimize the potential future likelihood o f interest rate, exchange rate and income shocks to households. The 78 M. Vodopivec (1 999). ''J. Kluve, H. Lehmann, and C.M. Schmidt (1999). IMF (2006b). 77 second set o f measures relates to the usage o f macro-prudential norms, for example on loan-to- value or debt service-to-income ratios. The third area concerns improvements to the overall legal environment and infrastructure, for example in sharing credit information, effective enforcement o f collateral etc. The fourth area relates to enhanced data availability on the risks in household credit portfolios both in aggregate and individually. Finally, as highlighted in the various trade- offs discussed throughout this report, authorities should recognize the potential impact on households o f traditional economic management policy measures, for example exchange rate and interest rate adjustments. 32. Many of these generic policy messages have clear resonance for countries within ECA. For example, while a number o f countries within the EUlO have taken measures to limit the extent o f foreign currency borrowing by households, a recent analysis found that they might have had only limited effects." In particular, the analysis finds that while such measures appeared to influence the extent o f foreign currency credit channeled through the domestic financial system they may have had the effect o f shifting borrowing towards nonresident financial institutions. This highlights the need to adopt a combination o f policies, both at the macro-financial and household level, to help mitigate the potential risks associated with increased household credit growth, for example relating to foreign currency or variable interest rate loans. The exact combination o f policy measures that i s appropriate to allow for the benefits o f household credit growth while limiting the potential associated risks will depend on country circumstances. 33. Diversified sources o f economic growth will also be critical in helping dampen ECA countries' vulnerability to macroeconomic shocks. In some ECA countries, recent growth performance has been underpinned by economic activity concentrated in a few sectors, such as the housing sector, or income flows from some dominant source, such as migrant labor. 34. Monitoring systems are important. Guaranteeing that statistical monitoring systems are in place and that relevant household data are collected regularly and made available for analyses are important measures for ensuring that household vulnerabilities are understood in a timely manner. Such monitoring systems can also help identify households at risk and ensure that they can be reached by a country's social protection system. The monitoring o f vulnerabilities could include risks in household credit portfolios, as discussed previously. 81 Rosenberg and TirpAk (2008). 78 APPENDIX TABLES Appendix Table 1. Interest Rate Shock and Borrowers at Risk (Percentage change in share o f borrowers at risk, in percent o f indebted households) Interest Rate Shock _ _____~ _ _ _ ~ ~ 20% Threshold 30% Threshold Historical 3 pp 5pp 6pp Historical 3 pp 5pp 6pp Estonia 16.80 11.06 17.95 22.35 12.02 6.76 12.45 13.61 (0.03) (0.03) (0.03) (0.04) (0.03) (0.02) (0.03) (0.03) Hungary 5.70 7.62 11.82 12.75 3.25 4.93 8.71 10.12 (0.04) (0.05) (0.06) (0.06) (0.03) (0.04) (0.05) (0.06) Lithuania 8.39 5.50 11.28 13.34 4.58 3.73 6.95 7.52 (0.06) (0.04) (0.06) (0.07) ' (0.04) (0.04) (0.04) (0.05) Note: Absolute errors in parenthesis. Source: Staff calculations. Appendix Table 2. Economic Shocks and Borrowers at Risk (Percentage change in share o f borrowers at risk in percent o f indebted households) Exchange Rate Shock Unemployment Rate Shock Probabilrty Assignment Random Assignment Historical 25% 35% Historical 1Opp 15 pp Historical 1Opp 15 pp Estonia ... 5.51 9.02 9.05 11.64 16.40 10.86 14.31 20.98 , ... (0.04) (0.05) (0.08) (0.09) (0.11) (0.10) (0.11) (0.13) Hwi3ry 5.40 3.72 6.10 3.31 12.04 17.42 3.30 12.37 18.03 (0.04) (0.03) (0.05) (0.04) (0.07) (0.08) (0.04) (0.07) (0.08) Lithuania ... 1.89 4.31 5.76 4.29 6.70 8.68 6.64 10.16 ... (0.05) (0.10) (0.14) (0.12) (0.15) (0.17) (0.15) (0.18) Note: Absolute errors m parenthesis. 20% threshold is used. Source: Staff calculations. 79 Appendix Table 3. Economic Shocks and Borrowers at Risk (Percentage change in share o f borrowers at risk in percent o f indebted households) Exchange Rate Shock Unemployment Rate Shock Probability Assignment Random Assignment Historical 25% 35% Historical 1Opp 15pp Historical 1Opp 15pp Belarus 0.12 0.11 0.19 0.21 2.68 3.81 0.26 3.47 5.39 (2008) (0.00) (0.00) (0.00) (0.00) (0.01) (0.01) (0.00) (0.02) (0.02) Kazakhstan 0.13 0.18 0.36 0.46 2.99 4.56 0.69 4.52 6.97 (2005) (0.00) (0.00) (0.00) (0.00) (0.01) (0.01) (0.00) (0.01) (0.01) Serbia, Rep. 0.05 0.05 0.05 0.65 2.36 3.70 0.77 2.82 4.43 (2oo8) (0.00) (0.00) (0.00) (0.01) (0.01) (0.02) (0.01) (0.01) (0.02) Ukraine 0.52 0.20 0.34 1.12 3.86 5.66 1.19 4.09 6.26 (2007) (0.00) (0.00) (0.00) (0.01) (0.01) (0.01) (0.01) (0.01) (0.02) Note: Absolute errors in parenthesis. Source: Staff calculations. 80 Appendix Table 4. Food Share of Consumption (In percent o f total consumption) Location Consumption Quintiles All Rural Urban Q1 42 43 44 Q5 , E U10 (including Croatia) Bulgaria 47 54 44 51 50 47 44 41 Croatia 25 28 22 32 27 25 22 18 Estonia 35 38 34 48 40 35 31 22 H W 28 31 26 36 31 28 25 18 Latvia 32 36 29 45 36 32 25 19 Littl& 41 51 37 57 47 41 36 26 Poland 36 41 32 49 40 35 31 23 . Low-Income CIS Armen$ 64 70 61 77 72 66 60 45 Azerbaijan 56 57 55 65 60 56 53 45 Georgia 70 80 61 78 74 73 68 57 KyrgyzRepublic 55 56 54 66 60 56 50 43 Moldova 42 48 33 56 49 42 37 25 Tajikistan 76 78 71 72 79 79 79 74 Uzbekistan 75 79 69 85 84 79 72 56 Middle Income CIS Belarus 32 34 30 35 33 32 30 27 KaZkhStan 46 52 42 55 50 47 43 35 Russia 42 51 38 56 49 43 36 24 Ukraine 57 65 53 66 61 57 54 47 Turkey Turkey 36 43 32 51 40 35 30 24 Western Balkans Albania 52 55 48 59 55 54 49 43 . Bosnia and Herzegovina 39 37 41 48 43 40 36 30 Macedonia, FYR 56 59 54 77 64 56 46 36 Montenegro 66 65 69 80 72 67 62 51 Serbia 40 43 37 50 43 39 36 31 Source: Staff calculations. 81 Appendix Table 5. UtilityEnergy Share of Consumption (In percent o f total consumption) Location Consumption Quintiles All Rural Urban Q1 42 43 44 Q5 EUlO (including Croatia) Bulgaria 19 18 20 26 20 18 17 16 Croatia 9 10 9 10 10 9 9 8 Estonia 17 13 20 18 20 19 16 15 Hungary 18 18 18 20 20 19 18 15 Lamia 12 9 14 17 14 12 10 8 Lithuan$ 13 10 15 13 15 15 13 11 Poland 20 17 22 18 20 20 21 21 Low-Income CIS Annenia 7 6 8 7 7 7 8 7 Azerbaijan 6 7 6 6 6 6 6 7 'Georgia 8 4 12 8 9 8 8 8 K r Republic yw 11 11 11 9 10 11 13 10 Moldova 14 13 16 12 13 14 14 17 Tajikistan 2 2 1 3 2 2 2 1 Uzbekistan 1 1 2 2 1 1 1 2 Middle Income CIS Belarus 8 8 8 8 8 8 8 7 Kazakhstan 10 10 10 11 11 10 10 9 Russia Ukraine 12 8 14 12 12 13 12 12 Turkey Turkey 12 11 12 10 12 12 13 12 Western Balkans Albania 12 11 14 12 12 12 12 14 Bosnia and Herzegovina 10 11 10 13 11 11 10 8 Macedonia, FYR 8 6 9 2 6 8 10 13 Montenegro 6 7 5 3 6 7 8 9 Serbia 13 11 14 12 13 13 13 12 Source: Staff calculations. 82 Appendix Table 6. The Welfare Impact of a 10 Percent Food Price Increase Laspeyres Price Index Geometric Price Index Location Consumption Quintiles Location Consumption Quintiles Rural Urban Q1 Q5 Rural Urban Q1 Q5 EUlO (including Croatia) Bulgaria 5.38 4.37 5.06 4.08 5.26 4.26 4.94 3.97 Croatia 2.80 2.22 3.25 1.81 2.70 2.14 3.14 1.74 Estonia 3.76 3.40 4.83 2.20 3.65 3.29 4.71 2.12 Hungary 3.10 2.58 3.61 1.81 3.00 2.49 3.50 1.74 Latvia 3.65 2.93 4.50 1.91 3.54 2.83 4.38 1.84 Lithuania 5.06 3.68 5.67 2.57 4.94 3.57 5.56 2.48 Poland 4.10 3.22 4.91 2.28 3.99 3.11 4.79 2.20 Low-Income CIS Amnia 6.98 6.11 7.65 4.49 6.88 6.00 7.57 4.37 Azerbaijan 5.69 5.47 6.48 4.52 5.57 5.35 6.37 4.40 Georgia 7.99 6.13 7.79 5.67 7.92 6.01 7.71 5.55 Kyrgyz Republic 5.59 5.37 6.61 4.32 5.47 5.25 6.51 4.21 Moldova 4.84 3.34 5.64 2.53 4.72 3.23 5.52 2.44 , Tajikistan 7.83 7.14 7.19 7.44 7.74 7.04 7.09 7.35 Uzbekistan 7.87 6.92 8.53 5.56 7.79 6.81 8.47 5.44 Middle Income CIS Belarus 3.40 3.04 3.54 2.70 3.29 2.94 3.44 2.61 Kazakhstan 5.17 4.18 5.46 3.53 5.05 4.07 5.35 3.42 Russia 5.07 3.82 5.61 2.37 4.95 3.71 5.49 2.29 Ukraine 6.54 5.33 6.62 4.73 6.43 5.21 6.51 4.61 Turkey Turkey 4.30 3.18 5.11 2.38 4.18 3.08 4.99 2.29 Western Balkans Albania 5.53 4.79 5.89 4.29 5.41 4.67 5.78 4.17 Bosnia and Herzegovina 3.67 4.14 4.76 3.05 3.56 4.02 4.65 2.95 Macedonia, FYR 5.94 5.38 7.69 3.57 5.82 5.26 7.60 3.46 Montenegro 6.47 6.88 7.99 5.06 6.36 6.77 7.91 4.95 Serbia 4.33 3.74 5.03 3.12 4.21 3.63 4.91 3.01 Source: Staff calculations. 83 Appendix Table 7. The Welfare Impact of a 10 Percent Fuel Price Increase ~ _ _ _ _ _ _ ~ ~ _ _ _ _ _ ~ ~ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ ~ ~ Laspeyres Pnce Index Geomtnc Pnce Index Location Consumption Qulntdes Location Consumption Qulntlles Rural Urban Q1 Q5 Rural Urban Q1 Q5 EUIO (including Croatia) Bulgaria 1.8 2.0 2.6 1.6 1.73 1.91 2.47 1.57 Croatia 1.0 0.9 1.0 0.8 0.93 0.85 0.99 0.75 Estonia 1.3 2.0 1.8 1.5 1.28 1.90 1.69 1.42 Hungary 1.8 1.8 2.0 1.5 1.75 1.78 1.90 1.46 Latvia 0.9 1.4 1.7 0.8 0.87 1.33 1.66 0.74 Lithuania 1.0 1.5 1.3 1.1 0.97 1.45 1.22 1.06 Poland 1.7 2.2 1.8 2.1 1.60 2.10 1.73 1.98 Amnia 0.6 0.8 0.7 0.7 0.55 0.77 0.68 0.64 Azerbaijan 0.7 0.6 0.6 0.7 0.63 0.59 0.57 0.65 Georgia 0.4 1.2 0.8 0.8 0.38 1.14 0.81 0.73 Kyrgyz Republic 1.1 1.1 0.9 1.0 1.01 1.06 0.86 0.96 Moldova 1.3 1.6 1.2 1.7 1.22 1.58 1.19 1.62 Tajikistan 0.2 0.1 0.3 0.1 0.21 0.13 0.29 0.14 Uzbekistan 0.1 0.2 0.2 0.2 0.10 0.21 0.15 0.19 Belarus 0.8 0.8 0.8 0.7 0.72 0.74 0.74 0.71 Karakhstan 1.0 1.0 1.1 0.9 0.97 0.97 1.05 0.85 Russia 0.0 0.0 0.0 0.0 Ukraine 0.8 1.4 1.2 1.2 0.80 1.37 1.16 1.18 Turkey 1.1 1.2 1.0 1.2 1.08 1.20 0.99 1.16 Albania 1.1 1.4 1.2 1.4 1.07 1.33 1.11 1.31 Bosnia and Hemgovina 1.1 1.0 1.3 0.8 1.07 0.95 1.25 0.75 Macedonia, FYR 0.6 0.9 0.2 1.3 0.59 0.82 0.18 1.22 Montenegro 0.7 0.5 0.3 0.9 0.66 0.51 0.28 0.85 Serbia 1.1 1.4 1.2 1.2 1.08 1.32 1.13 1.19 Source: Staff calculations 84 Appendix Table 8. Summary Data: GDP Growth and Poverty Simulations Baseline Poverty Estimated Growthm Per C a p h Heacount ' GDP GrowthProjection for 2009 Private Consumptionfor 2009 %PPP2.5 %PPP5.00 Baseline Apr 2009 Baseline Apr2009 Albania 15.0 60.0 5.6 -0.1 6.0 -0.1 Armenia 30.0 84.0 5.6 -7.1 4.9 -6.2 Azerbaijan 1.o 71.0 14.7 1.7 10.6 1.2 Bekrus 1.o 13.0 7.4 -3.4 6.9 -3.1 Bosnia and Hemgovina 1.3 8.0 4.6 -3.3 4.7 -3.3 Bulgaria 3.1 20.0 5.6 -1.3 5.9 -1.4 Croatia 0.0 2.0 4.0 -3.5 3.9 -3.5 Estonia 2.0 18.0 3.9 -10.1 4.0 - 10.3 Georgia 39.0 76.0 9.8 1.o 10.8 1.1 HwwY 0.0 7.0 2.7 -3.2 2.8 -3.3 - Kazakhstan 7.0 54.0 6.9 -2.1 7.3 -2.2 Kygy Republic 52.1 88.1 6.9 -2.1 7.0 -2.1 Kosovo 38.1 82.0 5.7 -2.0 5.8 -2.0 Latvia 1.0 12.0 0.8 -11.7 0.8 -11.9 Macedonia 10.0 37.1 4.7 -2.3 4.9 -2.4 Moldova 30.0 77.0 8.0 -3.4 10.1 -4.3 Montenegro 10.2 49.2 5.7 -2.0 5.8 -2.0 POW 2.0 20.0 4.7 -0.7 4.5 -0.7 Romania 7.0 45.0 5.1 -3.8 4.8 -3.6 I Russian Federation 3.0 20.0 6.8 -5.6 7.7 -6.3 Serbia 2.0 17.1 5.7 -2.0 5.4 -1.9 Tajkistan 56.0 89.0 6.4 1.4 6.8 1.5 Turkey 15.0 49.0 3.1 -6.1 3.0 -6.0 Ukraine 1.o 18.0 4.9 -7.3 6.0 -8.9 Uzbekistan 19.0 67.0 5.4 4.9 5.5 5.0 I Latest year for which data are available. Sources: ECA Regional HouseholdData Archives; IMF World Economic Outbok database; and staff calculations. Appendix Figure 1. The Impact o f the Crisis on Poverty and Vulnerability Allowing for full pass-through from GDP growth to private consumption growth - ~ ___.___II____-. ~ ~. (In percent o f tl t PWlatik!!! __.__-________ _ _ I. - ____ I_ S2.5 a Day Poverty Rates Projections 2007-2010 $5 a Day Poverty and Vulnerability Projections 2007-2010 36 I 34 - 32 30 - 28 - 14-1 26 - 25.3 24 - 22 ` I I 2007 2008 +F're-crisis projection -Latest projection 2009 2010 *January projection 2007 2008 -cF're-crisis projection +Latest projection 2009 2010 *January projection Source: Staff calculations. 85 Appendix Figure 2. Financial Margins in Selected Countries Evidence from HBS D a t a (In local currency and in percent of a l l households; by years) Household Vulnerability, Belarus Household Vulnerability Kazakhstan Cumulative distribution of household financial margins' Cumulative distribution of household economic margins' 100 100 90 90 60 80 70 70 80 60 50 50 40 40 30 30 20 20 10 10 (Thousands of Tenge) 0 0 (Mlllions of Ruble) -10 -5 0 5 10 15 20 25 30 ' B a d en subehlencc Wel budpl Household Vulnerability, Serbia Household Vulnerability, Ukraine r- Cumulative distribution of household ewnomic margins. Cumulative distribution of household ewnomic margins' I 100- 90 - 80- 70- 60 - ll 50- 40 - 30 - 20 20- 10 10 0 (Thousands of Hryvnia) -1000 0 1000 2000 3000 *rima on p v r h In. d S 5 W w w N d . y In Pm?i PllL. Source: Staff calculations. 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