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|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|17450||2000||32 صفحه PDF||سفارش دهید|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Journal of Development Economics, Volume 61, Issue 2, April 2000, Pages 495–526
The purpose of this paper is twofold: to apply to a group of low-income borrowers from the IMF, the most commonly used technique for measuring the independent effects on economic developments of IMF support; and to develop a minimum set of diagnostic tests for determining whether necessary conditions for using the methodology exist. The modified control-group methodology is used to measure the effect of IMF support on three key variables — output growth, inflation, and the external debt/service ratio. The sample comprises adjustment programs begun during 1986–1991 supported by the IMF's Enhanced Structural Adjustment Facility (ESAF). The distinguishing feature of the modified control-group approach is the estimation of a policy counterfactual — policies that would have been followed in the absence of IMF support against which to compare actual policies and resulting outcomes. Using this approach for the ESAF, the sample reveals statistically significant beneficial effects of IMF support on output growth and the debt/service ratio but no effects on inflation. Diagnostic tests of these results, rarely if ever reported in the literature, are shown to be critical in interpreting the validity of the results of assessments of adjustment lending. For this sample, at least, the diagnostic tests cast doubt on the reliability of estimates of the effects of IMF-supported programs using panel data in a modified control-group model. The most obvious and manageable modifications to the model do not overcome its basic weaknesses.
Evaluations of macroeconomic programs supported by international financial institutions (IFIs) do not all address the same question. Some look at the design of such programs to see if they represent “best practices” for correcting countries' macroeconomic problems. Others examine whether programs are effectively implemented. Another question that has attracted attention recently is whether IFI support has significant independent effects; i.e., does it bring about developments significantly different from those that would have occurred in the absence of support from the IFI in question? This is a difficult question to address because it requires the construction of a counterfactual indicating what policies and outcomes would have been in the absence of IFI support. The independent effects are then calculated as the difference between outcomes that would have occurred in the absence of IFI support and actual outcomes. Since the mid-1980s, several papers have considered how to construct a counterfactual for such exercises and how to address other problems in identifying independent effects of IFI-supported programs. In particular, differentiating the effects of the counterfactual policies from exogenous developments, initial conditions and IFI support. The methodology that has been most widely applied was developed by Goldstein and Montiel (1986) by adapting techniques from the literature on labor training evaluation. Essentially, this technique, referred to as the General Evaluation Estimator (GEE) or modified control group, involves using policy reaction functions estimated for countries that did not have support from a particular IFI to approximate the counterfactual for countries that did have IFI backing for their program.1 The GEE is a potentially powerful technique, although, as Goldstein and Montiel point out, it entails many restrictive assumptions; e.g., it must be possible to characterize macroeconomic policy choices in a relatively simple reaction function based on quantifiable data, and it must be credible that the reaction functions estimated for countries that do not receive IFI support describe the counterfactual for countries that do receive such support. The purpose of this paper is both to apply the GEE methodology to data for low-income countries eligible for the IMF's Enhanced Structural Adjustment Facility (ESAF)2 and to examine in greater detail than previous studies have done the conditions that must be met for the GEE to give robust results. To do this, we calculate the effects of ESAF-supported programs during the first 6 years of the facility's existence (1986–1991) on three macroeconomic variables that are typically the main objectives of the programs: output growth, inflation and, a key indicator of progress toward external viability, the external debt/service ratio. We then perform several diagnostic tests to answer the question, “Are the restrictive assumptions underlying the standard GEE consistent with the sample?”. Three main issues are addressed in these tests: does the single, relatively simple macroeconomic model used in applications of the GEE capture the interaction between macroeconomic policies and outcomes for a large number of countries over time; can a robust policy reaction function be estimated for periods when, and in countries where, IMF support is not in place; is it possible to address sample selection bias that is likely to characterize applications of the GEE to date? The results, like others for different data sets, point to significant positive effects of IMF-supported programs on growth and the debt/service ratio. The diagnostic tests, however, cast doubt on the appropriateness of the restrictive assumptions underlying the GEE and accordingly about the reliability of the results. This finding raises questions about whether there are inherent problems in estimating GEE models with panel data. At a minimum, it strongly indicates that future applications of the GEE on other data sets need to incorporate standard diagnostic tests to ascertain whether the GEE methodology is valid for the sample under study.
نتیجه گیری انگلیسی
With respect to the central objectives of this paper — to use the GEE framework to identify the independent effects of ESAF support during 1986–1991 on key macroeconomic variables and to assess whether the assumptions underlying the GEE are applicable to the ESAF-eligible countries — conclusions can be summarized as follows. For output growth and the debt/service ratio, sizable beneficial effects that are statistically significantly different from zero are identified.37 The effects on inflation are not significantly different from zero. These results are similar to those found in other studies, albeit for samples of countries that differed from those used here. The present paper, however, goes beyond others applying the GEE and asks the questions: “Are the assumptions underlying the model valid for the cross-section of ESAF countries and, by extension, are GEE results for these countries reliable?” In fact, a battery of diagnostic tests casts doubt on the applicability of the GEE framework at least to the ESAF-eligible countries: the overall fit of the model is poor; estimates of the coefficients on many variables are insignificantly different from zero; regression residuals are heteroschedastic and nonnormally distributed; and the estimates of the coefficient on the dummy for ESAF support are quite sensitive to variations in the sample. A striking finding is that the counterfactual policy reaction function does not have any significant explanatory power for the sample of nonprogram observations. These results raise questions about the validity of other applications of the GEE that do not rigorously test underlying assumptions. The GEE is a rigorous framework, conceptually superior to before–after and simple control-group comparisons for identifying the independent effects of IFI financial support. It is, however, based on many restrictive assumptions that are necessary to define the counterfactual and to specify in a simple framework the main determinants of important endogenous macroeconomic variables. A major shortcoming of most applications of the GEE is their focus on the bottom line — the estimates of the effects of IMF support — with little or no evaluation of the validity of the underlying model; indeed, some studies have reported only estimated coefficients on the dummy variables and their standard errors, without diagnostic statistics or the estimates for other coefficients. One important lesson to be drawn from this study is that the validity for any given sample of the premises of the GEE methodology must be investigated before reliable conclusions about the independent effects of IMF support can be drawn from it. Indeed, on the basis of this study, it cannot be ruled out that the inherent limitations of panel data covering countries facing highly diverse circumstances render it impossible to obtain reliable estimates of the independent effects of IMF-supported programs.