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Vulnerability of HIPC countries to the Financial Crisis Daniel Ottolenghi, Chief Development Economist Bernard Ziller, Head of Development Policy Unit European Investment Bank Author: Markus Berndt ([email protected]) Washington, 8 July 2009 1 Impact of the financial crisis on EIB partner countries The global financial crisis 1000 Origin of the crisis in advanced economies but… J.P. M organ, EM BI Global, Composite , Inde x, All M aturitie s, Strippe d Spre ad, USD 800 > Heightened risk aversion Impact on HIPC countries through... 600 400 Financial market links: - Deleveraging and heightened risk aversion 200 0 01/01/07 01/07/07 01/01/08 01/07/08 01/01/09 108 107 106 forecast of October 2008 Output of advanced econom ies forecast of April 2009 (index 2005=100) > Global recession forecast 105 104 103 102 2007 250 230 210 190 170 150 130 110 90 70 50 2008 2009 Commodoty price indice s (2005 =100) Real economy links: - Global slowdown / recession → lower trade, → falling commodity prices → decline in remittances M e tals > Tumbling commodity prices 2007M11 → financing on international markets more difficult and costly → a reversal of short-term capital more likely Oil Indirect impact on - 2008M5 2008M11 bank credit risk/quality of loan portfolio government revenue and fiscal balance 2008M11 2 Analytical framework Domestic crisis risk: Potential for a global financial crisis leading to a surfacing of pre-existing weaknesses in the domestic financial system, measured by recent credit growth and credit to private sector Fiscal risk: Potential for fiscal strains due to the need of bailing out or providing stimulus, measured by fiscal deficit and debt service Higher risk Direct liquidity risk: Direct exposure of the banking system to the global financial markets, measured by shortterm liquid external assets over liquid external liabilities Capital/remittances outflow risk: Exposure to a reversal or drying out of volatile capital inflows, measured by dependence on portfolio inflows and remittances Export slump risk: Exposure to slowing of import demand from crisis-hit advanced economies, measured by dependence on exports to advanced economies Insufficient reserves risk: Potential for balance of payment crises due to insufficient initial reserves to smooth crisis related swings in the current account, measured by reserves coverage of imports 3 Risk categories 3 Risk categories: High: above empirically determined threshold Medium: above 50% of threshold High Medium Low Low: below 50% of threshold Threshold determined by optimizing the fit of probit regressions explaining - banking, - currency and - debt crises of a panel of 161 countries, 1970-2007 4 Estimated thresholds Dependent Vulnerabilities Explanatory variables variables Banking crisis Currency crisis Direct Domestic Liquid external assets over liabilities 0.805 Credit to private sector (% of GDP) 187 % Prior average credit growth 20.2% Reserves Reserves (months of imports) Exports Dependence on exports to adv. econ (% of GDP) 22.3 % Dependence on portfolio investments (% of GDP) 7.3 % Dependence on remittances (% of GDP) 7.6 % Prior government deficits (% of GDP) 3.6 % Prior debt service (% of exports) 9.2 % Flows Debt crisis Estimated Thresholds Fiscal 1.6 5 Results: HIPCs compared to all LICs HIPC countries as a group show a similar risk profile as all LICs in most dimensions including potentially vulnerable financial sectors due to excessive credit growth during the recent commodity price boom. However, HIPC countries tend to have more vulnerable fiscal and reserve positions than an average LIC. 6 Notes: Averages weighted by GDP. Afghanistan, Kyrgyz Republic, and Somalia not included. Results: Differences within HIPC Reserves are the lowest in the pre-decision point countries Decision point countries face greater external vulnerabilities than completion point countries 7 Results: country by country Completion point countries 1/3 8 Results: country by country Completion point countries 2/3 9 Results: country by country Completion point countries 3/3 Decision point countries 1/2 10 Results: country by country Decision point countries 2/2 Pre-decision point countries 1/1 11 Conclusion Impact of the crisis on HIPC countries – Direct external liquidity risk limited in most HIPC countries’ financial sectors – Reduction in remittances a concern in Latin American HIPCs but also in Senegal, Sierra Leone and Uganda – Impact of recession on exports expected to be high in Guyana, Honduras, Mauritania, Chad and the Republic of Congo. – Reserves are low in many of those HIPC countries that have not reached the completion point, yet. – The Fiscal positions are challenging in many HIPCs including those that have already reached the completion point – High risk of domestic vulnerabilities in commodity producers 12 Methodology: Mapping past risks and past crises Data source: IMF working paper by Laeven and Valebcia (2008) Banking crisis - Large number of defaults in corporate and financial sector - Large number of difficulties to repay contracts on time Currency crisis - Nominal depreciation or devaluation of at least 30% and 10% higher than the previous year’s depreciation or devaluation Debt crisis - Sovereign debt default Sovereign debt restructuring 13 Methodology: Target regressions to determine ‘optimal’ thresholds Dependent variables explained by* Banking crisis dummy = F ( Prior average credit growth, Credit to private sector, Liquid external assets over liabilities ) Currency crisis dummy = F ( Gross portfolio investments + Gross remittances, Exports to advanced economies, Reserve cover of imports ) Debt crisis dummy = F ( Prior government deficits, Debt service in % of exports ) 14 * Dummies of explanatory variables are used to explain the probability of a crisis starting in the next year. Crisis and two post-crisis observations are excluded. Methodology: Example: Searching for optimal thresholds to explain banking crises Banking crisis dummy = F ( Prior average credit growth, Credit to private sector, Liquid external assets over liabilities Credit growth dummy = 1 if credit growth > threshold_cg Credit to private dummy = 1 if credit to priv.dummy > threshold_cp Banking crisis = ) Liquidity dummy = 1 F ( Prior average credit growth, to private if Credit liquidity < sector, threshold_li Liquid external assets over liabilities ) Search function Iterative search to identify of those ‘optimal thresholds’ that maximize the fit of the target probit regression with the respective dummies 15 Methodology: Example: Searching for optimal thresholds to explain banking crises .01 0 -.01 -.02 .061 .062 .063 Marg. effect (right axis) .064 .02 .065 Threshold for explaining a banking crisis: (1) Avg. credit growth in last two years: 20.15 0 10 20 Threshold Pseudo R2 (left axis) 30 40 Marg. effect (right axis) 16 Methodology: Example: Searching for optimal thresholds to explain banking crises .02 .015 .01 .054 .056 .058 .06 Marg. effect (right axis) .062 .064 .025 Threshold for explaining a banking crisis: (2) Liquid external liabilities over assets: 124% 50 100 Threshold Pseudo R2 (left axis) 150 Marg. effect (right axis) 17 Methodology: Example: Searching for optimal thresholds to explain banking crises .1 .05 .06 0 .061 .062 .063 Marg. effect (right axis) .064 .065 .15 Threshold for explaining a banking crisis: (3) Credit to the private sector, % of GDP: 187 100 120 140 160 Threshold Pseudo R2 (left axis) 180 200 Marg. effect (right axis) 18 Methodology: Example: Regressions for optimal thresholds to explain banking crises Banking crisis regressions VARIABLES credgro_d liab_d cred_d credgro_2y liabcover_l1 cred_l1 real_growth Constant Pooled (1) banking 0.242 (0.158) 0.320*** (0.124) 1.422*** (0.549) 0.000631 (0.00332) 0.000170 (0.000166) -0.00291* (0.00167) -0.0499*** (0.00955) -1.749*** (0.0927) 2091 0.0741 Observations 2 Pseudo R Number of id Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1 (2) banking (3) banking (4) banking 0.255* (0.144) 0.330*** (0.109) 0.872* (0.454) 0.142 (0.139) 0.334*** (0.105) 0.863* (0.457) 0.187 (0.129) -0.0500*** (0.00929) -1.833*** (0.0769) 2122 0.0652 -1.956*** (0.0718) 2157 0.0218 (5) banking (6) banking 0.277*** (0.102) 0.891** (0.353) -0.0311*** (0.00640) -1.817*** (0.0517) 3092 0.0265 -0.0363*** (0.00780) -1.767*** (0.0664) 2269 0.0380 -0.0319*** (0.00585) -1.770*** (0.0458) 3310 0.0343 (7) banking dF / dx 0.0199 (0.0131) 0.0248*** (0.00919) 0.123 (0.106) -0.00328*** (0.000605) 2122 0.0652 Panel with random effects (9) (8) lnsig2u banking 0.255* (0.144) 0.330*** (0.109) 0.872* (0.454) -0.0500*** (0.00929) -1.833*** (0.0769) 2122 -14.79 (26.68) 2122 144 144 19 Methodology: Definition of fit Definition of the maximized Pseudo R2 (McFadden, 1973) ˆ ln L M Full 2 R 1 ln Lˆ M Intercept Mfull = Model with predictors Mintercept = Model without predictors L̂ = Estimated likelihood 20 Selected References Berg, Nadrew, Eduardo Borentzstein and Catherine Patillo « Assessing Early Warning Systems: How have they worked in practice?, IMF Working Paper, WP/04/52 Borio, Claudio (2003) “Towards a macroprudential framework for financial supervision and regulation?”, BIS Working Paper No 128 Duttagupta, Rupa and Paul Cashin (2008) “The Anatomy of Banking Crises”, IMF Working Paper, WP/08/93 Kaminssky, Graciela L., Saúl Lizondo, and Carmen M. Reinhart (1998) “Leading Indicators of Currency Crises”, IMF Staff Papares, Vol. 45, Issue 1 (march), pp.1-48 Kraay, Aart and Vikram Nehru (2004) “When is External Debt Sustainable?”, World Bank Policy Research Paper 3200 Laeven, Luc and Fabian Valencia (2008) “Systemic Banking Crises: A New Database”, IMF Working Paper, WP/08/224 21 Backup Countries in panel 1970-2007: Albania, Algeria, Angola, Argentina, Armenia, Australia, Austria, Azerbaijan, Bangladesh, Barbados, Belarus, Belgium, Belize, Benin, Bolivia, Bosnia and Herzegovina, Botswana, Brazil, Brunei, Bulgaria, Burkina Faso, Burundi, Cambodia , Cameroon, Canada, Cape Verde, Cayman Islands , Central African Rep., Chad, Chile, China, P.R., Colombia, Comoros , Congo, Dem. Rep. of, Congo, Rep. of, Costa Rica, Côte d’Ivoire, Croatia, Czech Republic, Denmark, Djibouti, Dominica, Dominican Republic, Ecuador, Egypt, El Salvador, Equatorial Guinea, Eritrea, Estonia, Ethiopia , Fiji , Finland, France, Gabon, Gambia, The, Georgia, Germany, Ghana, Gibraltar , Greece, Grenada, Guatemala, Guinea, Guinea-Bissau, Guyana , Haiti , Honduras, China, P.R.: Hong Kong, Hungary, Iceland, India, Indonesia, Iran, I.R. of, Ireland, Israel, Italy, Jamaica, Japan, Jordan, Kazakhstan , Kenya, Korea, Kuwait, Kyrgyz Republic , Lao People’s Dem. Rep., Latvia, Lebanon, Lesotho, Liberia, Libya , Lithuania, Luxemburg, Macedonia, Madagascar, Malawi, Malaysia, Maldives , Mali, Mauritania, Mauritius, Mexico, Moldova , Mongolia , Morocco, Mozambique, Myanmar, Namibia , Nepal, Netherlands, New Zealand, Nicaragua, Niger, Nigeria, Norway, Pakistan, Panama, Papua New Guinea, Paraguay, Peru, Philippines, Poland, Portugal, Romania, Russia, Rwanda, São Tome and Principe, Saudi Arabia, Senegal, Serbia, Republic of, Sierra Leone, Singapore, Slovak Republic, Slovenia, South Africa, Spain, Sri Lanka, Sudan, Suriname, Swaziland, Sweden, Syrian Arab Republic, Switzerland, Tajikistan, Tanzania, Thailand, Togo, Trinidad and Tobago, Tunisia, Turkey, Turkmenistan, Uganda, Ukraine, United Kingdom, United States, Uruguay, Uzbekistan, Venezuela, Vietnam, Yemen, Zambia, Zimbabwe 22