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Vulnerability of HIPC countries Vulnerability of HIPC countries to the Financial Crisis to the Financial Crisis

Author: Markus Berndt (m.berndt@eib.org) Washington, 8 July 2009

Daniel Ottolenghi, Chief Development Daniel Ottolenghi, Chief Development EconomistEconomist

Bernard Ziller, Head of Development Policy UnitBernard Ziller, Head of Development Policy UnitEuropean Investment Bank

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Commodoty price indices (2005 =100)

507090

110130150170190210230250

2007M11 2008M5 2008M11 2008M11

Metals

Oil

102

103

104

105

106

107

108

2007 2008 2009

forecast of April 2009

forecast of October 2008Output of

advanced economies (index 2005=100)

J.P. Morgan, EMBI Global, Composite, Index, All Maturities, Stripped Spread, USD

0

200

400

600

800

1000

01/01/07 01/07/07 01/01/08 01/07/08 01/01/09

Impact of the financial crisis on EIB partner Impact of the financial crisis on EIB partner countriescountries

Origin of the crisis in advanced economies but…

Impact on HIPC countries through...

Financial market links:-Deleveraging and heightened risk aversion

→ financing on international markets more difficult and costly

→ a reversal of short-term capital more likely

Real economy links:-Global slowdown / recession

→ lower trade, → falling commodity prices→ decline in remittances

Indirect impact on- bank credit risk/quality of loan portfolio- government revenue and fiscal balance

The global financial crisis

> Heightened risk aversion> Heightened risk aversion

> Global recession forecast> Global recession forecast

> Tumbling commodity prices> Tumbling commodity prices

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Analytical frameworkAnalytical framework Direct liquidity risk: Direct exposure of the banking system to the global financial markets, measured by short-term liquid external assets over liquid external liabilities

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

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 economiesInsufficient 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

Hig

her

risk

Fiscal risk: Potential for fiscal strains due to the need of bailing out or providing stimulus, measured by fiscal deficit and debt service

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Risk categoriesRisk categories

3 Risk categories:High: above empirically determined thresholdMedium: above 50% of thresholdLow: below 50% of threshold

High

Medium

Low

Threshold determined by optimizing the fit of probit regressions explaining - banking, - currency and - debt crises of a panel of 161 countries,1970-2007

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Fiscal

Flows

ExportsReserves

Direct

Domestic

Estimated thresholdsEstimated thresholdsDependent variables

Explanatory variables

Banking crisis

Debt crisis

Estimated Thresholds

Liquid external assets over liabilities

Credit to private sector (% of GDP)

Prior average credit growth

Currency crisis

Reserves (months of imports)Dependence on exports to adv. econ (% of GDP)

Dependence on portfolio investments (% of GDP)

Prior government deficits (% of GDP)

Prior debt service (% of exports)

0.805

187 %20.2%

1.6

22.3 %7.3 %

Dependence on remittances (% of GDP) 7.6 %

3.6 %

9.2 %

Vulnerabilities

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Results: HIPCs compared to all LICsResults: HIPCs compared to all LICs

Notes: Averages weighted by GDP. Afghanistan, Kyrgyz Republic, and Somalia not included.

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.

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Results: Differences within HIPCResults: Differences within HIPC

Reserves are the lowest in thepre-decision point countries

Decision point countries face greater external vulnerabilities than completion point countries

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Results: country by countryResults: country by countryCompletion point countries 1/3

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Results: country by countryResults: country by countryCompletion point countries 2/3

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Results: country by countryResults: country by countryCompletion point countries 3/3

Decision point countries 1/2

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Results: country by countryResults: country by countryDecision point countries 2/2

Pre-decision point countries 1/1

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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

ConclusionConclusion

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Methodology: Mapping past risks and past Methodology: Mapping past risks and past crisescrises

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

Currency

crisis

Debt crisis

Data source: IMF working paper by Laeven and Valebcia (2008)

Banking crisis

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Methodology: Target regressions to determine ‘optimal’ thresholdsMethodology: Target regressions to determine ‘optimal’ thresholds

Banking crisis dummy =

Dependent variables

Prior average credit growth,Credit to private sector,Liquid external assets over liabilities

Currency crisis dummy =Gross portfolio investments +Gross remittances,Exports to advanced economies,Reserve cover of imports

explained by*

Debt crisis dummy =Prior government deficits,Debt service in % of exports

F (

)

F ()

F (

)

Banking crisis

Currency

crisis

Debt crisis

* 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.

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Banking crisis dummy =Prior average credit growth,Credit to private sector,Liquid external assets over liabilities

F (

)

Methodology: Methodology: Example: Searching for optimal thresholds to explain banking Example: Searching for optimal thresholds to explain banking crises crises

Banking crisis dummy =

Prior average credit growth,Credit to private sector,

Liquid external assets over liabilities

F (

)

Credit growth dummy = 1 if credit growth > threshold_cgCredit to private dummy = 1 if credit to priv. > threshold_cp

Liquidity dummy = 1 if liquidity < threshold_li

Iterative search to identify of those ‘optimal

thresholds’ that maximize the fit of the target probit

regression with the respective dummies

Search function

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Methodology: Methodology: Example: Searching for optimal thresholds to explain banking Example: Searching for optimal thresholds to explain banking crisescrises

Threshold for explaining a banking crisis: (1) Avg. credit growth in last two years: 20.15

-.02

-.01

0.0

1.0

2M

arg.

effe

ct (r

ight

axi

s)

.061

.062

.063

.064

.065

Pse

udo

R2

(left

axis

)

0 10 20 30 40Threshold

Pseudo R2 (left axis) Marg. effect (right axis)

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Methodology: Methodology: Example: Searching for optimal thresholds to explain banking Example: Searching for optimal thresholds to explain banking crisescrises

Threshold for explaining a banking crisis: (2) Liquid external liabilities over assets: 124%

.01

.015

.02

.025

Mar

g. e

ffect

(rig

ht a

xis)

.054

.056

.058

.06

.062

.064

Pse

udo

R2

(left

axis

)

50 100 150Threshold

Pseudo R2 (left axis) Marg. effect (right axis)

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Methodology: Methodology: Example: Searching for optimal thresholds to explain banking Example: Searching for optimal thresholds to explain banking crisescrises

Threshold for explaining a banking crisis: (3) Credit to the private sector, % of GDP: 187

0.0

5.1

.15

Mar

g. e

ffect

(rig

ht a

xis)

.06

.061

.062

.063

.064

.065

Pse

udo

R2

(left

axis

)

100 120 140 160 180 200Threshold

Pseudo R2 (left axis) Marg. effect (right axis)

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Methodology: Methodology: Example: Regressions for optimal thresholds to explain banking Example: Regressions for optimal thresholds to explain banking crisescrises

Banking crisis regressions

Pooled Panel with random effects (1) (2) (3) (4) (5) (6) (7) (8) (9) VARIABLES banking banking banking banking banking banking banking banking lnsig2u dF / dx credgro_d 0.242 0.255* 0.142 0.187 0.0199 0.255* (0.158) (0.144) (0.139) (0.129) (0.0131) (0.144) liab_d 0.320*** 0.330*** 0.334*** 0.277*** 0.0248*** 0.330*** (0.124) (0.109) (0.105) (0.102) (0.00919) (0.109) cred_d 1.422*** 0.872* 0.863* 0.891** 0.123 0.872* (0.549) (0.454) (0.457) (0.353) (0.106) (0.454) credgro_2y 0.000631 (0.00332) liabcover_l1 0.000170 (0.000166) cred_l1 -0.00291* (0.00167) real_growth -0.0499*** -0.0500*** -0.0311*** -0.0363*** -0.0319*** -0.00328*** -0.0500*** (0.00955) (0.00929) (0.00640) (0.00780) (0.00585) (0.000605) (0.00929) Constant -1.749*** -1.833*** -1.956*** -1.817*** -1.767*** -1.770*** -1.833*** -14.79 (0.0927) (0.0769) (0.0718) (0.0517) (0.0664) (0.0458) (0.0769) (26.68) Observations 2091 2122 2157 3092 2269 3310 2122 2122 2122 Pseudo R2 0.0741 0.0652 0.0218 0.0265 0.0380 0.0343 0.0652 Number of id 144 144 Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

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Methodology: Definition of fitMethodology: Definition of fit

Definition of the maximized Pseudo R2 (McFadden, 1973)

Mfull = Model with predictors Mintercept = Model without predictors

Intercept

Full

MLMLR ˆln

ˆln12

L̂ = Estimated likelihood

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Selected ReferencesSelected 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

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Countries in panel 1970-2007:

BackupBackup

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