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Implementation Uncertainty and the Design of IMF Conditionality
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Implementation Uncertainty and the Design of IMF Conditionality
Martin S. EdwardsWhitehead School of Diplomacy
Seton Hall University
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The Limits of Conditionality
40% of International Monetary Fund lending programs are suspended for noncompliance
Program suspension has real costs for both IMF and the borrowing state
To what extent is the IMF to blame for the failings of conditionality?
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Question
How does the IMF design loan programs if it does not know ex ante whether the borrowing state will honor its promises?
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The Argument:
IMF devises conditionality both prospectively and retrospectivelyConditionality is front-loaded in states with
approaching elections and federal statesConditionality is front-loaded in states with a
history of poor program implementation.
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Does Implementation Uncertainty Matter for the IMF? Joseph Stiglitz (2002:52): “Sometimes conditionality was
even counterproductive, either because the policies were not well suited to the country or because the way they were imposed engendered hostility to the reform process.”
Stanley Fischer (1998): “We don't need to form very sophisticated judgments about the political forces in (those) countries. We basically have to form a judgment on whether the government will do what it says it will do in an overall satisfactory way.”
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Forming international agreements
Variations in the form of international agreements are responses to uncertainty Escape clauses / renegotiation are ways to adjust
agreements
Agreements made under high transaction costs look different than those in which parties face low transaction costs Ex ante commitments can be used to make promises
more credible
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Assumptions
Fund faces uncertainty about borrower commitment
Program causes domestic dislocation Renegotiation costly for IMF Renegotiation costly for borrower
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If I’m right…..
Expect more conditions in states with a higher level of implementation uncertainty.
But these conditions should be imposed on states ex ante. IMF imposes conditions (prior actions) in
order for Executive Board to approve program
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What shapes implementation uncertainty? Approaching elections
We know that electoral cycles are common in developing countries, and that elections often coincide with program interruptions
Federalism Economic adjustment more difficult in these states
Past performance Failed programs lead to changes
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Expectations
Prospective Programs with approaching elections are more likely
to have prior actions than those in which elections are not approaching
Federal states more likely to have prior actions Retrospective
Programs negotiated in the wake of a suspended program are more likely to have prior actions than those negotiated following a successfully completed program.
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Cases
Random Sample of 38 States under Programs from 3rd qtr 1997 to 2nd qtr 2003.Asia (7 states), Latin America (8), Africa (11),
Eastern Europe (12)183 agreements initiated in this time periodStates required to submit new memoranda as
part of program review process
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Dependent Variable
Count of fiscal prior actions for each agreementRange: 0-12
Prior actions are those policy measures that are prerequisites for review by Executive Board
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Examples of Fiscal Prior Actions
Measures adopted to reduce wage bill Cambodia 99q3: freeze on new hiring for civil service
Measures to increase revenue Russia 99q3: Delay law on VAT reduction Pakistan 01q1: Mandated increases in rates for electricity and
gasoline Measures to reduce expenditure
Armenia 98q4: Publish decree detailing govt plan to reduce expenditures by 7 billion dram.
Passage of Fund-compliant budget by legislature
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Why Fiscal Prior Actions?
Have to look at prior actions to ascertain whether Fund incorporates implementation uncertainty Looking at performance criteria makes causal chain unclear
Fiscal criteria serves as “most likely” case Electoral cycles manifest themselves through higher levels of
spending Federal states esp. prone to fiscal problems Noncompliance stems most frequently from fiscal shortfalls
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Independent Variables
Policy Stance Lagged budget deficit / GDP (-)Lagged growth of expenditures / GDP (+)Lagged growth of reserves (-)Lagged GDP (-)
Type of Agreement Dummy for PRGF/ESAF (+)
US influenceLagged US foreign aid / GDP (-)
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Independent Variables
Approaching elections (Dummy) Is an executive election six months away?
Federalism (Dummy)
Status of past program (Dummy)Did the Fund interrupt the program for
noncompliance?
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Research Design
Confront substantial missing data problemsMissingness on fiscal variables approaches
40% of sample Used multiple imputation (King et al 2000)
to address missing data
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Research Design
Empirical Test is a negative binomial modelAppropriate because data are countsDistribution of count dictates model
specification Population averaged to address panel
heterogeneity
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Change in Total Reserves t-1 -0.00025**(9.102 E-05)
GDP t-1 -2.43 E-06(1.008 E-05)
Budget Deficit / GDP t-1 0.0114(0.0159)
Change in Expenditure / GDP t-1 0.0022 (0.0013)
PRGF Dummy -0.1651(0.2652)
US Foreign Aid / GDP t-1 0.3860(0.5012)
Approaching Elections 0.7242*(0.3591)
Prior Program Noncompliance 0.8669***(0.2581)
Federalism 1.061*(0.5360)
Number of Performance Criteria 0.0879 (0.0504)
Dummy for Ukraine Program 2.6957***(0.2711)
Constant -0.6510 (0.3481)
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Change in Total Reserves t-1 -8.510
GDP t-1 -1.685
Budget Deficit / GDP t-1 1.509
Change in Expenditure / GDP t-1 1.199
PRGF Dummy -.403
US Foreign Aid / GDP t-1 1.288
Approaching Elections 2.572
Prior Program Noncompliance 3.338
Federalism 4.571
Number of Performance Criteria 2.816
Dummy for Ukraine Program 2.256
Substantive – Discrete Change
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Robustness Checks
Results hold in the presence of the followingControls for Quota in IMFControls for DemocracyTrade OpennessChanges in Exchange Rate level
Results unchanged with nine-month window.
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Summary
IMF does not lend “in the dark”Expectations about electoral horizons affect
program designPrograms look differently in federal statesExpectations about program compliance
affect program design
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A Further Question to Consider
Do prior actions make a difference ex post? In fiscal performance? In the probability of program suspension?