effectiveness of imf-supported stabilization...

Journal of International Money and Finance21 (2002) 565–587

www.elsevier.com/locate/econbase

Effectiveness of IMF-supported stabilizationprograms in developing countries

Ayse Y. EvrenselDepartment of Economics, Portland State University, Portland, OR 97207-0751, USA

Abstract

This paper examines the effectiveness of Fund-supported stabilization programs byinvestigating whether the IMF achieves its own objectives in such programs. Even though theFund’s conditionality prescribes fiscal and monetary discipline in program countries, the resultsof the empirical analysis show that the IMF cannot impose its conditionality even duringprogram years. Furthermore, when successive interprogram periods are considered, programcountries enter a new program in a worse macroeconomic condition than they entered theprevious program. These results and the fact that stabilization programs have a revolving natureare inconsistent with the effectiveness of IMF-supported stabilization programs and may signalthe existence of moral hazard. 2002 Elsevier Science Ltd. All rights reserved.

JEL classification: E63; F33; F40

Keywords: IMF; Stabilization programs; Conditionality; Moral hazard

1. Introduction

In its 58 years of existence, the IMF has been criticized because of its institutionalstructure and lending practices. Some argue that the IMF is a bureaucratic and non-transparent institution with no accountability for its actions. It has also been sug-gested that Fund-supported stabilization programs are ineffective and may createmoral hazard.

The motivation to provide another study on the IMF is based on three points.First, although there are a large number of publications about the IMF and its pro-

E-mail address: [email protected] (A.Y. Evrensel).

0261-5606/02/$ - see front matter 2002 Elsevier Science Ltd. All rights reserved.PII: S0261 -5606(02 )00010-4

566 A.Y. Evrensel / Journal of International Money and Finance 21 (2002) 565–587

grams, most publications express opinions about the Fund without providing quanti-tative evidence. There are several quantitative evaluations of Fund programs, mostof which have been provided by the IMF (Reichmann and Stillson, 1978; Donovan,1982; Loxley, 1984; Goldstein and Montiel, 1986; Khan, 1990; Joyce, 1992; Dorood-ian, 1993; Conway, 1994; Killick, 1995; Santaella, 1996; Knight and Santaella,1997).1

Second, the recent efforts to widen the IMF’s responsibilities make a quantitativestudy on the effectiveness of Fund-supported adjustment programs both timely andappropriate. In 1997, the IMF introduced the Supplemental Reserve Facility thatprovides large, short-term loans to countries in financial crises, as in the cases ofKorea, Russia, and Brazil. Third, motivated by the idea that Fund resources provideex-post assistance in a crisis, but realizing that they do not reduce the frequency andintensity of financial crises, it has recently been suggested that the IMF shouldassume the role of an international lender of last resort (Fischer, 1999). However,before defining new responsibilities for the IMF, one should be concerned with theperformance of the Fund in its traditional roles.

This paper focuses on the effectiveness of Fund-supported stabilization programsfor developing countries and has four characteristics. First, this study does not ques-tion the IMF’s existence, its rationale, its programs, and the content of conditionalityassociated with these programs.2 This paper’s approach to program evaluation is touse the IMF’s criteria to see whether the IMF achieves its own goals in these pro-grams. Second, this study uses a broader data set than previous program evaluationsin terms of the types of balance of payments programs (four types), the number ofprogram countries (91), and the length of the period under investigation (1971–97).Third, it provides a discussion of alternative evaluation methods and their weaknessesbefore the selection of the evaluation method. Fourth, the method of program evalu-ation is based on the observation of relevant variables during pre-program, program,and post-program years. Additionally, this paper attempts to relate program evalu-ation to moral hazard associated with the Fund’s lending.

The organization of the paper is as follows. Section 2 describes this study’sapproach to program evaluation, and provides a critique of previous evaluations.Section 3 constitutes the empirical part in which Fund-supported stabilization pro-grams are evaluated using the data on 91 developing countries for the period 1971–97. Finally, Section 4 summarizes the results of the empirical analysis and discussesthe effectiveness of stabilization programs.

2. Approach to program evaluation

2.1. Alternative approaches to program evaluations

There are three alternative approaches to the evaluation of adjustment programs.First, the outcome vs. alternative outcome approach compares the actual outcome in

1 Ul Haque et al. (1998) provide a review of previous program evaluations.2 See Vaubel (1991) and Willett (2000) on the political economy of international financial institutions.

567A.Y. Evrensel / Journal of International Money and Finance 21 (2002) 565–587

an adjustment program with the outcome in an alternative program that would haveachieved a similar degree of adjustment. This approach has been suggested as theclosest approach to the ideal evaluation (Edwards, 1989; Krueger, 1998). However,in addition to the difficulty associated with estimating a robust alternative model, itis problematic to provide a meaningful definition of the term “similar degree ofadjustment” (Edwards, 1989). Therefore, this approach has not been used in pre-vious evaluations.

Second, the outcome vs. counterfactual approach describes the program effect asthe difference between the actual performance observed in a program and the per-formance that would have taken place in the absence of a program. Some evaluationstudies use this approach by considering the developing members of the IMF thathave not been involved in any IMF program as the control group (Goldstein andMontiel, 1986; Khan, 1990; Santaella, 1996).

The third way of evaluating adjustment programs is the outcome vs. targetapproach that determines whether the program objectives have been achieved. Theoutcome vs. target approach is difficult to implement, because the IMF does notmake the content of individual adjustment programs public.3 However, a generalizedversion of this approach, the outcome vs. purpose approach, has been used in almostall previous evaluations (Reichmann and Stillson, 1978; Donovan, 1982; Loxley,1984; Goldstein and Montiel, 1986; Khan, 1990; Santaella, 1996; Joyce, 1992;Doroodian, 1993; Conway, 1994; Knight and Santaella, 1997).

The outcome vs. purpose approach is based on the fact that the Fund’s purposein adjustment programs is to reduce or eliminate balance of payments problems. TheMonetary Approach to Balance of Payments (MBOP) that underlines the Fund’sconditionality suggests that the balance of payments problems are caused by incom-patible exchange rate, monetary, and fiscal policies in program countries. Therefore,the main purpose of adjustment programs is to induce program countries to controlthe size of the public sector and to exercise monetary discipline under peggedexchange rate regimes to prevent the depletion of international reserves.

2.2. Critique of previous program evaluations

The outcome vs. counterfactual approach (Goldstein and Montiel, 1986; Khan,1990; Santaella, 1996) has been applied to the program country vs. nonprogramcountry comparison, where nonprogram countries are believed to represent the con-trol group. The estimation of the counterfactual through the control group approachmay be misleading. Viewing the control group as the counterfactual implies thatthe macroeconomic performance of nonprogram IMF-members is indicative for the

3 This means that the selection of target variables, their values as suggested by conditionality, and anychanges in conditionality due to Article IV consultations are not made public. These consultations referto the periodic meetings between the Fund’s staff and the authorities of member countries that take placein the member country to collect and analyze economic data (IMF, Annual Report, 1992). Since May1997, the results of Article IV consultations are made public with the permission of the member country(IMF, Annual Report, 1998).


macroeconomic performance of program countries in the absence of an IMF pro-gram. However, being a program or a nonprogram country is a self-selected attribute.If anything, the difference between program and nonprogram countries in their mac-roeconomic performance will determine which country will become a program coun-try. Therefore, the outcome vs. counterfactual approach will not be used in thisstudy.4

Previous evaluations that use the outcome vs. purpose approach employ differentmethods to capture the Fund-effect: pooled regressions with a program year dummy,logit or probit models to discriminate between program and nonprogram years, andthe before–after method.

Pooled regressions with a program year dummy are used to explain the determi-nation of the subaccounts of the balance of payments where the sign and the signifi-cance of the program dummy is believed to explain the program effect on balanceof payments (Goldstein and Montiel, 1986; Khan, 1990; Doroodian, 1993). Thereare two problems associated with this approach. First, the fundamental problem isthe lack of theoretical background. Dependent and independent variables are inter-changed without any consideration of the direction of causality.

Second, the meaning of the program year dummy in pooled regressions shouldbe reconsidered. The program year dummy implies that adjustment programs affectthe outcome in target variables in a way that is not captured by other independentvariables in the model. For example, if being in a program year leads to significantlyhigher reserves, then this could be interpreted as the catalytic effect of adjustmentprograms. Such effects imply that program countries may have an easier access toprivate capital markets, if lenders view the IMF’s involvement in a country as asignal of stability. Therefore, the program dummy in pooled regressions does notreflect whether conditionality is imposed successfully.

Third, there is an implied assumption regarding the counterfactual in pooledregressions with a program dummy. It is assumed that nonprogram years representthe counterfactual for program years. However, they do not, because the informationregarding the availability of Fund programs is already imbedded in the variables fornonprogram years. Countries may follow riskier macroeconomic policies that willlead to a balance of payments crisis, knowing that Fund support will be available.Also, there may be a feedback from IMF programs on variables in question. There-fore, the sign and significance of the program year dummy in pooled regressionscannot be generalized as the program effect.

The discrimination analysis (logit or probit) is also employed to distinguishbetween program and nonprogram years (Joyce, 1992; Conway, 1994; Knight and

4 Although nonmembers of the IMF may be a proxy for the counterfactual, there are various problemsassociated with using them as such. Monaco, Liechtenstein, Andorra, and Vatican City do not qualify tobe in the sample not only because these countries do not have any control over their monetary policies,but also they are considered developed countries. No data are available for Nauru, Palau, and Tuvalu.Zaire became a nonmember country in 1997, which marks the end of the sample period. Taiwan is leftas the only nonmember country that could be used as the counterfactual sample, which is not enough todraw any conclusions.


Santaella, 1997). The problem with this technique is that it is difficult to find explana-tory variables that are not simultaneously determined. That is, it is very difficult tocome up with truly exogenous variables with which one can distinguish betweenprogram and nonprogram years.5 Additionally, the problem with the counterfactualstill exists. In this setting, the program year dummy is the dependent variable; how-ever, the right-hand side variables may not appropriately distinguish between pro-gram and nonprogram years because of the above mentioned effects of expectationsand feedback.

The before–after method of program evaluation has also been used where thedifference in the mean values of evaluation variables between program and nonpro-gram years is interpreted as the program effect (Reichmann and Stillson, 1978; Dono-van, 1982; Loxley, 1984; Khan, 1990). As in other types of evaluations, the problemwith the counterfactual also exists in the before–after method. Ul Haque et al. (1998)note that the before–after approach implies a constant counterfactual with respect tothe policies and the external environment of the program country.

It is obvious that estimating the counterfactual represents the main problem inprogram evaluations. In an attempt to calculate the “ true” effects of Fund-supportedprograms, some studies employ an estimator of the Fund effect that distinguishesbetween policy and target variables (Goldstein and Montiel, 1986; Khan, 1990).6

The target variables are determined by the vector of policy variables, exogenousshocks, and the program dummy. Similar to pooled regressions, the program dummyis assumed to reflect the Fund effect. These studies recognize that policy variablesare not directly observable in program countries. The counterfactual for policy vari-ables is constructed by using the difference between desired and actual (lagged)values of the target variables. This estimation of the Fund effect suffers from thepractice of interchanging the dependent and independent variables, because targetvariables are affected by policy variables and vice versa.7

The discussion of evaluation methods indicates that all types of program evalu-ations are problematic, and a perfect solution to the problems of program evaluationdoes not exist. However, the recognition of these problems is important with regardto the selection of the evaluation method and the interpretation of evaluation results.

2.3. This study’s approach to program evaluation

Although there are many interesting questions regarding the effectiveness of Fundsupported programs, the question to which there is a methodologically correct answer

5 The lack of exogeneity represents a problem also in the simulation study of Khan and Knight (1981)in which a system of equations determines output, prices, reserves, money, and fiscal policy.

6 In Goldstein and Montiel (1986), this is called the modified estimator of the Fund effect.7 Theoretically, there is a superior way of estimating the counterfactual. Because an IMF member is

expected to include the availability of Fund support in her macroeconomic decisions, the data based onmembership years should not be used to estimate the counterfactual. Table 1 indicates that some countriesbecame IMF members during the early or mid-1980s. Using the data from nonmember years, the coun-terfactual may be estimated for the member years. Unfortunately, the pre-membership data have manymissing observations regarding late members so that forecasting the counterfactual was not possible.

570 A.Y. Evrensel / Journal of International Money and Finance 21 (2002) 565–587T

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97.


is the one regarding the conditional effect of a program. For example, the Fundviews an unsustainable increase in domestic credit (unsustainable at the givenexchange rate) as the main cause of balance of payments problems. Therefore, con-ditionality associated with adjustment programs prescribes a reduction in domesticcredit creation. One can ask whether domestic credit creation differs significantlybetween the pre-program, program and post-program periods.

In this paper, the premise of program evaluation is what the Fund expects programcountries to do and whether these objectives are achieved. The Fund expects programcountries to reduce their domestic credit creation, budget deficit, domestic borrowing,inflation rate, current account and capital account deficit. The relevant question iswhether we observe significant improvement in these variables under an IMF pro-gram.

At this point, the following trio of critique appears immediately. First, the IMFdoes not have any authority over sovereign countries, which means that programcountries may not follow the IMF’s advice. Second, even if program countries tryto follow the IMF’s advice, they may face exogenous shocks that prevent countriesfrom improving upon evaluation variables. Third, program countries may have scoredworse without an IMF program.

With regard to the first point, there is a valid reason for conducting programevaluations to measure the IMF’s success, and not program countries’ willingnessto improve their macroeconomic performance. Since the IMF provides programcountries with subsidized loans justified by the existence of conditionality, the Fundis expected to demonstrate its ability to impose the content of conditionality. Second,if program countries were struck by exogenous, adverse shocks in a systematicfashion during a period of, say, 30 years, program countries would be consideredas victims of economic disasters. Then the IMF would become the financial RedCross and provide disaster relief without imposing conditionality.

Third, the fact that program countries may have been worse off without the IMF’ssupport is not the only possible outcome. Suppose the inflation rate in a countrybefore and during an IMF program was 40 and 60%, respectively. Although onemay interpret this as a sign of IMF’s ineffectiveness in reducing the inflation rate,it is possible that the inflation rate could have been 80% in the absence of an IMFprogram. However, it is also possible that, in the absence of the IMF support, coun-tries may have decided to follow sounder macroeconomic policies. Again, the pointis that the IMF’s conditionality is supposed to increase the shadow price of the IMFsupport to program countries. The question is whether it does so. This does not meanthat the counterfactual is irrelevant. However, the actual data should not be dismissedtoo quickly, because it shows the extent to which conditionality is enforced, every-thing else remaining the same.

In this paper, Fund-supported programs are evaluated based on the outcome vs.purpose approach using the before–after method. As opposed to previous before–after evaluations that consider one-year lags before and after a program, this studyuses lags of up to three years to observe changes in the evaluation variables fromthree years before the start of a program to three years after the end of a program.This method demonstrates how evaluation variables gradually change toward a pro-


gram and after a program. To support the results of the before–after analysis, thetemporal interprogram analysis is used to illustrate the possibility of moral hazardassociated with Fund programs.

3. Empirical analysis

3.1. Participation in IMF programs, 1971–978

In 1997, 181 out of 191 independent countries in the world were IMF-members.9

Table 1 contains 118 developing members of the IMF during the period 1971–97,and the types of adjustment programs they have received.10 During the sample period,91 countries received any of the four structural adjustment programs: standby,Extended Fund Facility (EFF), Structural Adjustment Facility (SAF), and EnhancedStructural Adjustment Facility (ESAF).11 Table 1 indicates an increase in the fre-quency of IMF-supported stabilization programs since the mid-1980s, which can beexplained by the introduction of SAF and ESAF in 1986 and 1987, respectively.Prior to the mid-1980s, only standby and EFF agreements were available. With theintroduction of SAF and ESAF, most low-income developing countries have receiveddifferent types of programs simultaneously.12

A summary of Table 1 in the form of chi-squared tables indicates that, during theperiod 1971–97, the probability of any developing IMF member receiving a structural

8 The choice of the period rests on the availability of data. Data on macroeconomic variables areobtained from the IMF’s International Financial Statistics of March 1997 on CD-ROM. Informationregarding the type of programs comes from Annual Reports of the IMF for the years 1971 through 1997.

9 Nonmembers of the IMF include micro-states in Europe (Andorra, Liechtenstein, Vatican City, andMonaco), the Pacific (Tuvalu, Palau, and Nauru), Zaire, Cuba, and Taiwan. The remaining 63 nonde-veloping members of the IMF include the former Soviet Union and the countries of Europe, EasternEurope, North America, the Pacific, and the Middle East (oil exporters). Twenty-seven developing mem-bers of the IMF have never received stabilization programs and constitute the so-called nonprogramIMF members.

10 In Table 1, the duration of each program is not marked to keep the table simple, which means thattabulated standby, EFF, SAF, and ESAF arrangements correspond to different arrangements that last twoto four years. Typically, there is a relatively short period between successive programs that extends froma couple of weeks to a couple of months.

11 While standby arrangements provide balance of payments support to middle- and high-incomedeveloping countries, EFF, SAF, and ESAF are designed for low-income developing countries. Standbysare provided for a year with a possible extension up to three years. Other programs last longer and implylonger periods of repayment (5–10 years). See Johnson (1993), Guitian (1995), and Schadler et al. (1995)for more information on these programs.

12 During the pre-1986 period, some countries received standby and EFF simultaneously. During theperiod 1986–97, the combination was changed to SAF and ESAF, and was primarily given to low-income countries.


adjustment program is 0.3242.13 If 1986 is taken as a benchmark to divide the periodin two sections, it becomes apparent that the probability of being in a program ishigher during the period 1986–97. While the probability of receiving any programis 0.2192 for the pre-1986 period, it increases to 0.5054 during the period 1986–97.For low-income countries, the likelihood of being in a program increased from 0.216to 0.6235 between the two periods. Similarly, middle-income countries were twiceas likely to be in a program during the period 1986–97 (0.432) than during the pre-1986 period (0.2177).

Although the Fund’s Articles of Agreement state the temporary nature of theFund’s financial support, the data on program status indicate that many programcountries have been under the IMF’s care almost continuously. This raises the ques-tion as to why most of the program countries are repeat offenders, i.e., they keepgetting into balance of payments problems and receiving financial support from theIMF. Provided that conditionality contains the correct description of and solution tobalance of payments problems of program countries, and that conditionality is fullyimplemented during the program period and sustained by program countries’ govern-ments during the post-program periods, it is plausible that continuing IMF supportshould be rare or nonexistent. In the following, using the before–after and temporalinterprogram analysis, the revolving nature of program participation is explained.

3.2. Before–after analysis

The almost continuous nature of Fund-supported programs creates a problem forthe comparison of pre-program, program, and post-program years in terms of relevantvariables. For the majority of low-income countries in the sample, as one programends, another one starts in the same year. Additionally, since the mid-1980s mostprogram countries have been involved in more than one program in a given year,which makes pre-program, program, and post-program comparisons noisy. If onlyone type of program is considered, the before–after comparison may be affected byanother type of IMF-program. If all programs are considered, a possible differenceamong programs may be overlooked. To reduce the noise, mean values of the evalu-ation variables in different periods are compared not only for all programs but alsofor different program types (standby, EFF, SAF, and ESAF). Since program typesand income levels of program countries are closely related, by considering thebehavior of evaluation variables for all programs and under different programs, someof the noise associated with the aggregation of the Fund-effect under different (andsometimes overlapping) programs may be reduced.

13 Chi-squared tables are constructed using program types and income levels of countries. Income cate-gories are defined based on the following levels of 1995 GDP per capita (Y): low-income country ifY�US$1500; middle-income country if Y�US$6000; high-income country if Y�US$6000. The Pearsonc2 test on the independence of rows and columns indicates that program types and income levels are notindependent, which is consistent with the IMF’s attempt to provide different programs to countries withdifferent income levels.


Table 2 shows the results of the t-test that provides a comparison of evaluationvariables in successive periods. Pre-program periods extend from three years to oneyear before a stabilization program starts (t�3, t�2, and t�1). Post-program periodsextend from one year to three years after a program ends (t+1, t+2, and t+3). Usinglags of three years allows the observation of changes in evaluation variables whena country is nearing a program and when it completes a program.

Table 2 indicates that when all programs are considered, program countries’ per-formance worsens significantly toward a program in current account and overallbalance of payment. Significantly smaller reserves and slower real growth are alsoobserved. During program years, significant improvements are achieved in the areasof current account and reserves. While current account deficit is lower, reserves arehigher during the program years. With respect to reserves, however, the definitionof reserves makes a difference. If reserves are defined net of IMF-credit, there is nosignificant improvement in reserves due to a Fund program. Significantly smallerdomestic borrowing and larger foreign debt are also observed. During post-programyears, significant improvements occur in the immediate period after the end of aprogram (t+1) in financial account and overall balance of payments. However, inthe latest post-program year (t+3), money supply increases significantly.

When only standby arrangements are considered, a significant worsening in thecurrent account, greater depreciation in the exchange rate, a lower real growth areobserved during pre-program years. During a standby program, significant improve-ments in current account, financial account, and reserves are accomplished.14

Immediately after the end of a standby (t+1), significant improvements are observedin overall balance of payments.

Considering only EFF arrangements, none of the mean differences among variousperiods in evaluation variables is significant during pre-program, program, and post-program periods. When only SAF and ESAF are considered, mean values of evalu-ation variables do not differ significantly among pre-program periods. Program yearsare associated with significant improvements in financial account, reserves, andbudget deficit. Although program years imply a significant increase in domestic cre-dit, immediately after a SAF or ESAF (t+1), domestic credit becomes significantlysmaller. In the later period (t+2), reserves decline significantly.

The results of the before–after analysis can be generalized as follows. As countriesapproach a stabilization program, current account deficit and reserves deteriorate.This situation represents the very reason why a country asks for a Fund-stabilizationprogram in the first place. The evidence is such that especially standby arrangementsprovide a balance of payments relief during the program period.

The results summarized in Table 2 raise questions regarding the implementationof conditionality during a program. The Fund believes that the lack of monetarydiscipline under a pegged exchange rate regime is the source of the balance of pay-

14 This is the most common result of before–after evaluations. Previous before–after evaluations includeReichmann and Stillson (1978), Donovan (1982), Loxley (1984) and Khan (1990). Of course, these studiesdiffer in terms of sample periods, program types, countries, and evaluation variables.


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ments problems. Consequently, the conditionality attached to stabilization programsadvises a reduction in the size of the public sector and money creation along withthe depreciation of the currency. At least during the program years, one would expecta significantly lower budget deficit, domestic creation, money supply, domestic bor-rowing, and inflation rate. However, these primary targets of stabilization programsare not significantly affected during the program period. When looking at the post-program performance of program countries, the improvements in balance of pay-ments and reserves achieved during an IMF program disappear. This raises questionswith respect to the sustainability of the balance of payments improvement in thepost-program period.

The results of the before–after analysis should be considered in connection withTable 1, which indicates an almost continuous IMF-support in program countries.The revolving nature of the IMF support may be due to the short-term nature of itseffects. The results indicate that the Fund provides program countries with hardcurrency, and eliminates the balance of payments crisis during the program period.However, in the absence of long-term incentives, the short-term improvement inbalance of payments does not last, and it is even reversed once the program is over.15

3.3. Temporal interprogram analysis

The issue of moral hazard regarding Fund-supported programs implies the possi-bility that the governments of program countries may adopt unsustainable macroe-conomic policies due to the availability of the Fund credit. If stabilization programscreated moral hazard, this would be inconsistent with the effectiveness of stabiliz-ation programs. Moreover, one would expect that the interprogram periods wouldbe associated with increasingly unsustainable macroeconomic policies as the numberof programs a country receives increases.16 If a country has had Fund support before,the cost of macroeconomic policies that lead to the depletion of international reservesmay be lower to the country.

The identification of interprogram periods is based on Table 1. The identificationprocess is quite problematic, because the continuous nature of the Fund makes itdifficult to identify two interprogram periods. It turns out that there are only 42countries for which two interprogram periods can be identified during the period1971–97.17 Table 3 shows the results of the temporal interprogram analysis. Theresults suggest that the second interprogram period is associated with significantlyworsening macroeconomic performance than the first interprogram period. Compared

15 This point that the short-run nature of program effects is responsible for the ineffectiveness of IMFprograms is also suggested by Edwards (1989).

16 Interprogram periods are defined as periods that are not associated with any of the four IMF programsand are located between two program periods.

17 It is important to realize that the temporal interprogram analysis requires the actual data. As discussedearlier, the use of the actual data in program evaluations is problematic, because the actual data incorporateprogram countries’ expectations regarding the availability of Fund programs. However, the actual dataare exactly what is needed here.


Table 3Temporal interprogram analysis

Policy variablesa Second vs. first inter-program period

Difference t-value Change with respect to theearlier periodb

Reserves �0.0116 �2.7245 Smaller∗∗∗Domestic credit 0.1639 4.1875 Larger∗∗∗Inflation rate 0.1192 3.5838 Higher∗∗∗Budget deficit 0.0126 1.7148 Larger∗Net domestic borrowing 0.0449 2.5896 Larger∗∗Net foreign borrowing 0.0078 2.8405 Smaller∗∗∗Net domestic debt 0.1922 2.683 Larger∗∗∗Net foreign debt 0.2757 3.3762 Larger∗∗∗

a Policy variables are expressed as percentage of GDP except for the inflation rate.b ∗, ∗∗, ∗∗∗ denote 10, 5, and 1% level of significance, respectively.

to the first interprogram period, the second interprogram period is associated withsignificantly smaller reserves, higher domestic credit creation, inflation rate, budgetdeficit, domestic borrowing, domestic and foreign debt. This means that, as a countrygoes in and out of IMF programs, on average, the country enters a new IMF programwith worse macroeconomic conditions than when it entered the earlier program.

The results of the temporal interprogram analysis should be interpreted in a strictall-else-equal sense. As in the before–after evaluation, this analysis also assumesaway any external shocks that may have created the same results of program coun-tries entering new programs in increasingly worse macroeconomic conditions. More-over, the counterfactual remains to be a problem. However, as suggested by Tables1 and 2, the Fund support tends to be revolving and of short-term nature with respectto its balance of payments relief. The fact that stabilization programs on averagedo not change the macroeconomic fundamentals of program countries and that theavailability of these programs may imply moral hazard by motivating countries tofollow riskier macroeconomic policies raises questions regarding the effectivenessof Fund-supported stabilization programs.

4. Conclusion

During the period 1971–97, developing members of the IMF received a stabiliz-ation program for more than one-third of the time. There has been an increase inthe frequency of IMF-supported stabilization programs since the introduction of SAFand ESAF in 1986 and 1987, respectively. In the post-1986 period, countries receivedsupport from the IMF almost half of the time.

The results of the before–after analysis indicate that stabilization programs sig-nificantly improve current account and reserves during the program years. Although


stabilization programs seem to provide short-term balance of payments relief, theseimprovements are not sustained during the post-program period. Additionally, con-ditionality may not be effectively imposed even during the program years. Althoughconditionality prescribes a reduction in the size of the public sector, variables suchas domestic credit creation and budget deficit are not significantly affected by con-ditionality during the program years.

The results of the temporal interprogram analysis suggest that, on average, pro-gram countries enter a new program in a worse macroeconomic situation than before.Considering the revolving nature of the Fund support, this result is inconsistent withthe effectiveness of stabilization programs and may be interpreted as a signal ofmoral hazard.

The currency crises of the last few years have intensified discussions regardingthe role of the IMF in the international financial system where the emphasis hasbeen on the future role of the Fund. More recently, some would like to give the IMFthe responsibility of becoming the international lender of the last resort. Suggestionsregarding the Fund’s future will be misguided if its past performance is ignored.

Acknowledgements

I am grateful to Gerald P. Dwyer Jr for his comments on the paper. Commentsreceived from S. Nuri Erbas, David B. Gordon, Erdogan Kumcu, James R. Lothian,Gary Santoni, Myles Wallace, John T. Warner, Thomas D. Willett, and two anony-mous referees are also greatly appreciated. All errors are mine.

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