metadata: authors: 0: author: Conway,Patrick J.
docna: 0: docna: How successful is World Bank lending for
            structural adjustment?
docty: Policy Research Working Paper
subtopic: Economic Theory & Research,Industrial Economics,International Trade and Trade Rules,Economic Growth,Inflation,Macroeconomic Management
teratopic: Poverty Reduction
abstracts: cdata!: To measure the effectiveness of the
            World Bank's structural adjustment programs, the author
            examines the data on actual economic performance for 75
            countries for the period 1976-86. He finds a clear
            association between participation in a World Bank adjustment
            lending program and cross-country differences in economic
            performance and policy. Countries that participated in
            adjustment lending programs tended to have the following
            characteristics, compared with countries that did not
            participate in such programs: (a) more rapid economic
            growth; (b) more rapid inflation; (c) a less negative
            current account balance as a percentage of GNP; (d) deeper
            financial sectors; (e) a lower ratio of current government
            spending to GNP; and (f) depreciation of the real exchange
            rate. The first three indicators reflect differing
            performance; the second three, different policy mixes. In
            other words, the countries have not benefited merely by
            increased financing at the margin but have also undertaken
            significantly different economic policies.
repnme: repnme: How successful is World Bank lending for
            structural adjustment?
display_title: How successful is World Bank lending
            for structural adjustment
listing_relative_url: /research/1991/01/700101/successful-world-bank-lending-structural-adjustment
topicv3: Economic Growth m1326241 471,Current Account m1326278 1135,Inflation m1326709 0870F4727ACED1CF8525815C00471347,Trade m1326924 698,Balance of Payments m1326965 441
publishtoextweb_dt: 2010-07-01T00:00:00Z
historic_topic: Poverty Reduction
origu: Policy, Research & Ect Affairs
no_of_pages: 36
author_keys: 0: author_key: 390741
model_extractions: <!-- Start of picture text --> Tr"% Pdkqy<br>WPS 581<br><!-- End of picture text --> Ttds paper- a product of the Trade Policy Division, Country Economics Departnent- is part of a larger effort in PRE to measure the effectiveness of structural adjustment efforts, especially trade refonn, in developingcountries. It includes both this empirical analysis and otherresearch identifying possible causal links between policy and performance. Copies are available free from the World Bank, 1818 H Street NW, Washington DC 20433. Please contact Sheila Fallon, room. N10-035, extension 37947 (31 pages).

To measure the effectiveness of the World Bank's structural adjustment programs, Conway examines the data on actual economic performance for 75 counties for the period 1976-86.

He finds a clear association between participation in a World Bank adjustment lending program and cross-country differences in economic performance and policy. Countries that paricipated in adjustment lending programs tended to have the following characteristics, compared with countries that did not participate in such programs:

- More rapid economic growtt

- More rapid inflation

• A less negative current account balance as a percentage of GNP

- Deeper financial sectors

# * Depreciation of the real exchange rate.

The first three indicators reflect differing performance; the second three, different policy mixes. In other words, the countries have not benefited merely by increased financing at the margin but have also undertaken significantly different economic policies.

Conway speaks of the association and correlation, not causes. No components of adjustrnent lending prograns are singled out for praise or blame. The atheoretic methodology he uses does not identify causal links between bank adjustment programs and these measures, and provides no means of separating the effecLt of Bank lending fiom other factors. The adjustment lending programs were often concurrent, for example, with IMF stabilization policies, so to that extent the correlations are measures of the joint impact of the two.

* A lower ratio of current government spending to GNP

The PRE Working Paper Saies disernninates the findings of work under way in the Bank's Policy, Research, and Extenal Affairs Complex. An objective of the sries is to get these findings out quickly, even if presentations are less than fully polished. The findings, interpretations, and conclusions in these papers do not necessarily represent official Bank policy.

Produced by PRE Editorial Services
# **How Successful is World Bank Lending** for Structural Adjustment?

by Patrick Conway*

# Table of Contents

|I.|Measuring Structural Adjustment|4|
|---|---|---|
|**II.**|**Evaluating a**Country's Economic**Performance**|6|
|III.|<br>Estimation of the Impact of Adjustment Lending|8|
|IV.|Conclus&ons|22|
|Bibli|ography|23|
|Appen|dix|25|

* This paper was prepared from research funded by World Bank research grant 675-32. I have benefited greatly from the comments of my co-researchers Jaime de Melo, Lant Pritchett, and Dani Rodrik, as well as from those of participants in seminars at the World Bank, North Carolina State University, and the University of Florida at Gainesville. Jeff Konz provided excellent research assistance.
The World Ban. nas played a major<sup>role in encouraging countries to</sup> implement structural adjustment<sup>policies. Its Structural Adjustment Lending</sup> (SAT.) programs are designed to "increase<sup>efficiency economy-wide through</sup> changes in pricing and trade<sup>policies, in the size and structure of government</sup> expenditure, and in the extent<sup>of the government's controls on productive</sup> activity" [Nicholas (1989,<sup>p.vii)]. Sectoral Adjustment Lending (SECAL)</sup> programs are designed to "support<sup>more narrowly focused programs of reform and</sup> restructuring, ranging from<sup>major changes in macroeconomic policy in a sector</sup> such as trade cr agriculture<sup>to the establishment of an appropriate framework</sup> for investments in a sector<sup>such as energy or elucation" (Nicholas (1989, p.</sup> vii)]. The World Bank has made<sup>a large number of these loans since 1980, with</sup> 52 countries being recipients<sup>of one or more of either of these. [Nicholas</sup> (1989, pp. 42-45)]. I will<sup>refer to the two together as Adjustment Lending</sup> (AL) programs.

There is some controversy as<sup>to the impact of AL programs. Nicholas</sup> (1989) provides the World Bank<sup>view: although there have been some</sup> difficulties in implementation<sup>and oversight, they have on the whole been</sup> effective instruments for<sup>structural adjustment. World Bank (1988, 1990)</sup> provide statistics that support<sup>that view. Critics include Berg and</sup> Batchelder (1985) and Sachs (1986)<sup>who suggest that these programs have much</sup> less of an impact than the World<sup>Bank claims for them. Mosley (1987) takes</sup> the agnostic middle ground<sup>in saying:</sup> .by the end of 1985 **countries**<sup>that</sup><sup>**had adhered to SAL conditions**</sup> had done better than those<sup>that had not, andI...]</sup> not **all of the difference was due to underlying**<sup>**disparities in the capabilities**</sup> **of their economies. But this**<sup>**encouraging short-term result**cannot</sup> **be used to make a definitive assessment**<sup>**of a medium-term reform**</sup> program; some of the success<sup>[ ... ]may have been due</sup><sup>**to luck**</sup> rather than judgement. (Mosley<sup>(1987, p. 29); emphasis added]</sup>
3 The effectiveness of AL programs must in the end be investigated empirically. There are two parts to<sup>any such investigation. First, the</sup> performance of recipient countries must<sup>be compared to that of non-recipient</sup> countries: this requires a methodology<sup>for correcting for the external</sup> environment that I will explain below.<sup>Second, if a significant difference in</sup> behavior is found it could be due<sup>to the policy reform or to the additional</sup> funding linked to the AL program; to differentiate between these it is useful to investigate whether policy in recipient countries<sup>diitered significantly</sup> from that of non-recipient countries.1 In this paper I outline a methodology for assessing the success<sup>of World Bank adjustment lending and</sup> implement it for a 75-country panel<sup>of data for the period 1976-1986. The</sup> evidence suggests that there is a significant<sup>association between</sup> participation in a World Bank adjustment<sup>lending program and more rapid real</sup> economic growth, an improved current<sup>account as a percentage of gross national</sup> product (GNF), and higher inflation.<sup>The first two are positive features of a</sup> structural adjustment package, but<sup>the third calls into question the long-run</sup> sustainability of the efforts. This association does<sup>not appear to be "luck"</sup> or simply a response to added financing;<sup>similar statistical analyses indicate</sup> that participation in a SAL program<sup>is significantly</sup> correlated with both real depreciation of the country's exchange<sup>rate, reduction in current government</sup> expenditure as a share of GNP and financial<sup>deepening in dcmestic capital</sup> markets.

1 AL programs represent a small proportion<sup>of the total international</sup> indebtedness of most recipients. However, AL disbursements represent a larger percentage of total international disbursements: for all recipient countries<sup>AL</sup> flows represented over five percent of<sup>total international flows on average</sup> during the period 1986-1988, while for Sub-Saharan Africa the comparable<sup>figure</sup> is over 12 percent. These and other<sup>figures on the magnitude of AL financing are</sup> found in World Bank (1990).
4 Section I defines structural adjustment and describes different philosophies for its measure. Section II presents the decomposition by which observed economic behavior is decomposed into those parts attributable to policy, the hospitality of the external environment and participation in an adjustment lending program. Section III presents the empirical results, and in Section IV I summarize the results of the paper and suggest extensions to this research.

# I. Measuring Structural Adjustment.

Structural adjustment programs are based upon the need in the mediuin and long run to maintain external balance but to sustain positive economic growth and development. Structural adjustment is thus a reallocation of resources to best compete in and take advantage of the world environment. Such reallocations are necessary because the world economy has changed greatly for developing countries since the mid-1970s. Prices of crude oil have quadrupled and then halved in real terms; real interest rates have varied from substantially negative values to substantially positive values; international credit availability for many of these countries has gone from ample to nonexistent.

Despite the importance of structural adjustment, there is little agreement on how best to measure it. One method is to examine the policies undertaken by the developing-country governments.2 If these policies accord with the observer's theory for how structural adjustment is to be fostered, then there is a presumption of structural adjustment. For an inwardly 2 This is the approach followed, for example, by Michalopoulos (1987) and Yagci, Kamin and Losenbaum (1985).
5 orientec econcmy, f example, reduction of tariffs and non-tariff barriers would in tnis method be an indicator of structural adjustment. A second method uses actual economic performance as a gauge for the success of structural adjustment. In the example above, the announcement of trade liberalization would not be the indicator of structural adjustment: rather, the improvement of the current account or an :.ncrease in economic growth would be.

I follow the second method in this paper. Me.sures cf economic performance include the growth rate in real gross domestic product (GDP), the inflation rate in the GDP deflator, the ratio of the current account balance to gross national product (GNP) and the ratio of domestic investment to GNP. The first two provide an indication of the internal balance of the economy, while the remaining are indicators of external and intertemporal balance, respectivel,. Performance is measured over the period 1975-1986. As mentione6 above, any investigation must bcch control for the severity of the external environment and evaluate the degree to wlich policies can be found to respond to receiving an AL program. The severity of Lhe external environment is controlled for with the econometric methodology JuLlined in the next section. I impose no theoretical lir,kage between policy and performance variables, but examine three commonly discussed policy instruments: the real exchange rate, the ratio of government current expenditure to GNP, and the degree of financial deepening of the economy. Significant differences of policies in recipient countries from non-recipient countries will provide an indication that AL programs are not just financing additional expenditure, but are working on the policy level to alter goverr"ient behavior. These policies are also examined while controlling for the external environment.
6

**There** are **a** number of notable antecelents to this<sup>work. Goldstein and</sup> Montiel (1986) stress the importance<sup>of vntrolling for differences in</sup> environment and present an analytical<sup>blueprint for doing so. World Bank</sup> (1988) piovides preliminary empirical<sup>evidence on the success of AL p:ograms,</sup> but does not provide statistical<sup>tests. Among contemporary</sup> papers, World Bank (1990) (as revised in Corbo<sup>and Rojas (1990)] applies the Goldstein/Montiel</sup> blueprint to evaluating AL programs.<sup>The latter paper differs from this one</sup> in a number of methodological and statistical ways; its results when comparable are similar to those<sup>of this paper.</sup>

# II. Evaluating a Country's Economic<sup>Performance.</sup>

Measures of economic performance will respond systematically to four sets of determinants: external<sup>incentives, secular economic development</sup> trends, economic policy choices and<sup>country-specific</sup> structural factors. The observed historical performance<sup>will be attributable to all of these factors,</sup> and thus observed success could<sup>be due either to the refo:ms .ssociated with</sup> adjustment lending or to the serendipity<sup>of</sup><sup>**a**favorable externa. environment.</sup> From the country's point of view,<sup>of course, either is welcome. However, for</sup> purposes of measuring the<sup>success of adjustment lending it is important to</sup> decompose performance into that<sup>part attributable</sup> to the policies and that part due to external incentives<sup>or secular trends.</sup> The 'fixed-effect" statistical methodology provides this decomposition. The decomposition is derived rigorously<sup>in the appendix, but the gist of the</sup> method **can be presented** in **Figure**<sup>**1. Suppose that the economic**perforriance</sup> measure of interest is the current<sup>account/GNP ratio (C), and that Count.ies A</sup> and B have observed (negative) ratios<sup>of CA and CB, respectively,</sup> in this
7 period. The two countries have observed terms-of-trade in that pe..iod of TA and TB, respectively, and otherwise face an identical external environment. CA is less than CB, so that an initial examination of the evidence suggests that B has a more successful external-account performance than A. However, there is a 'normal" relationship between the terms of trade for a country and its current account: as the terms of trade improve (T rises) so also will the current account.<sup>3</sup> This 'normal" relationship is illustrated in Figure 1 by the slope of the line C(T).

To adjust for the external environment, both countries' performance should be evaluated as if they faced the same terms of trade. By doing this, the comparison is corrected for external dlfferences and focuses on policy<sup>and</sup> structural differences between the economies. In Figure 1 this comparison is made by project.ng points A and B onto the vertical axis using the slope of the "normal" relationship.4 The adjusted current account performance for A and B is defined relative to CO and is given by the measures aA and a<sup>0</sup> B The choice of C0 is not of importance in comparisons of adjusted performance. The ranking of adjusted performance for countries A and B is reversed from the historical ranking -- country A was more successful than the norm in deaLing with a deteriorated terms of trade, while country B was less successful given its elevated terms of trade. As the performance measures aA and aB control for the external environment, a measure of successful structural adjustment 3 Use of the current-account ratio provides a comparable index of performance across countries. Similar difficulties arise in deriving comparable indices ot the terms of trade across countries. In the empirical sectior of<sup>this</sup> study I use a normalization of the terms of trade and real exchange rate indices to ensure this comparability.

4 This projectinn could be done to any common terms of trade -- in the empirical section of this study I derive a "normal" value of T for this evaluation.
8 will be **the** degree to which<sup>these</sup><sup>**are**shifted upward by introductiori</sup> of **an** AL program.

The norm is derived in this<sup>study through regression analysis</sup> The fixed-effect econometric<sup>methodology used here Dermi%-s si.multaneous</sup> estimation of the normal response<sup>to the external environment (;he slope of</sup> C(T) in Figure 1), the country-specific<sup>economic performance (the OA and OB)</sup> and the average contribution<sup>to recipient countries of AL programs.</sup> III. Estimation of the Impact<sup>of Adjustment Lending.</sup> I have assembled data for 76 countries<sup>from the 1989 World Tables and</sup> World Debt Tables of the World Bank;<sup>the characteristics and precise</sup> definitions of these data and<sup>countries are given in the appendix. Economic</sup> growth (YGR) and the rate<sup>of domestic inflation (DINF) are indicators of</sup> internal balance: success<sup>in structural adjustment occurs when resources are</sup> being allocated efficiently<sup>and with little excess demand. The current</sup> account surplus or deficit (CAR)<sup>mearures performance in attaining external</sup> balance. Structural adjustment<sup>has most recently required adjustment to</sup> limited access to international<sup>credit, and this variable measures relative</sup> success in that. The investment<sup>ratio (IR) is a measure of intertemporal</sup> balance: even though policies<sup>and external '.vents may stimulate growth and</sup> adjustment, this will not be<sup>sustainable without a concomitant expansion in</sup> productive capacity.

I have collected as well comparable<sup>data on economic policy choices in</sup> these countries. The ratio of government<sup>current expenditure to GNP (GOV) is</sup> a measure of fiscal policy<sup>stance. The ratio of money, broadly defined, to</sup> nominal GNP (MON) is an indicator<sup>of the monetization and financial deepening</sup>
c **Cs** Figure 1 Comparisons of Historical and Adjusted Current-Account Performance
9 of the economy. rhe real exchange rate index<sup>(RERA, RERB',</sup> illustrates government's short- and medium-term efforts to maintain<sup>competitiveness</sup> in international trade.

The environment within which structural adjustment policies<sup>are made and</sup> economic performance is attained is characterized by country-specific realizetions of external variables. The real international interest rate (RR) is defined ex post by subtracting the US inflation rate from the<sup>country's</sup> average nominal rate on interiiational borrowing, Tnternational debt is total debt, including private, public and publicly guaranteed, deflated to billions of 1980 US dllars. It is stated in Rer caRita form, and is divided<sup>into a</sup> longer-term component (LTDPC) and a short-term component (STDPC).5 The terms of trade (TOTA, TOTB) is the ratf.o of average expor to average import prices. The share of tot:al output produced in the agricultural sector (YASHR) is a proxy inverse'.y ralated to the country's secular stage of economic develo ent. It is likely that there are other cotrmon international influences on economic performance in these countries as well, and<sup>to measure</sup> the impact of these I introduce a series of year-specific dummy variables (D7 for 1977 through D5 for 1985) as explanatory variables. These will register, for example, the average annual impact of the restrictions on international credit that as Sachs (1989b) documents were imposed in the<sup>post-1982 period.6</sup> These data were adjusted to address two conceptual problems. Fir¢F.<sup>the</sup> terms of trade and real exchange rate variables must be adjusted<sup>to provide</sup> 5 The lcng-term/short-term distinction is made as in World Bank (1987). Long-term refers to debt with original maturity of one year or more.

6 There is also a strong common element to movements in the terms of trade and the real interest rate across countries. Introduction of the year-specific dummy variables will thus lower the significance of TOTB and RR variables<sup>in</sup> least-squares regression but will not bias the estimation of fixed-effect terms.
10 cross-country comparability They are originally presented as indices with 1980-100, but it is certainly true that the underlying real exchange rate was not identiccl for all countries in that year. I thus constructed two comparable variants of each series based upon the country-specific distributions of the series over a long time horizon.7 Second, I assume that the external environment variables in period t are exogenous to the country's economic performance in that year. For TOTB and RR this is equivalent to asserting that each sample country is small in its goods and capital markets. For the debt variables I define the long- and short-term debt for period t to be that amount realized at the end of period t-l. If contemporaneous debt were used, it could well be positively associated with performance in that an increase in the debt burden would finance an increased current account deficit and perhaps increased investment and economic growth. Use of the lagged value avoids that simultaneity issue and investigates in isolation the impact of the existing debt burden on present performance.

Participation in an AL program is measu,red through the use of the variable DAL. It is defined to be unity during years in which countries are participating in a SAL or SECAL program as documented by Nicholas (1988, Annex 1). In the year that a country first participated, the value of DAL is equel to the percentage of the year remaining after tne AL programs had been approved. Use of DAL in regression on performance and policy measures would introduce a selection bias; to avoid this pitfall I construct the instrumental variable IAL equal to DAL but becoming unity 12 months later for each 7 Details of these calculations are provided in the appendix.
11 recipient country.<sup>8</sup> Least-squares estimation is used to calculate the normal response of performance and policy measures to the external environment and to derive the appropriate country-specific adjusted measures. The intercept is set so that at panel averages of the external factors the equation generates the average, or norm, of the dependent variable. The fixed-effect coefficients in the regression results then represent the deviation of country-specific performance from that normal performance. The coefficient of IAL represents the average annual increase in country-specific performance associated with participation in an AL program.

Given the cross-country and time-series nature of the panel data, it is reasonable to expect elements of both heteroskedasticity and country-specific serial correlation in the errors. Use of least-squares estimation techniques will assure unbiased estimates of the parameters even in the presence of these elements. However, the variance-covariance matrix of coefficient estimates must be corrected to test hypotheses about these estimates. The results 8 Use of a SAL/SECAL lending decision contemporaneous with the economic performance measure would introduce sample selection bias as the decision by the World Bank and by the recipient country to enter an AL program would depend in part on the contemporaneous realization of economic performance. Mosley (1987) discusses explicit modeling of this participation process. The variable IAL is an appropriate instrumental variable for this decision because it is highly correlated with DAL (correlation coefficient of .89) and because its variation is uncorrelated with the error in the period the AL program was actually introduced. Other instrumental variables are possible: for example, Corbo and Rojas (1990) use one that can be interpreted as the prior probability that a country will enter the program based on information available in the previous period. Their estimates of AL program effects **are** quite similar on economic growth, but the measurement of effects on domestic investment differ as discussed below.

There are to date no reported incidents of countries renouncing or graduating from AL programs. The treatment of AL programs in DAL as in place through the end of the time period under consideration is thus acceptable, but should be reconsidered once evidence to the contrary exists.
12 presented below are derived from a generalized least-squares process correcting for country-specific heteroskedasticity and autocorrelation of errors. Right-hand side variables are YASHR, TOTB, RR, LTDPC, STDPC, countryspecific dummy variables, year-specific d=mmy variables and IAL. I report here the coefficients of the external environment variables and IAL. The results of the country-specific effects are of independent interest and are examined in Conway (1990).

The coefficients of IAL in Table 1 represent the amount by which the dependent variable rises on average during years when a SAL or SECAL is in force. Adjustment lending programs are correlated with an increase of real GDP growth of 1.98 percent per year and with an increase in the annual inflation rate of 10 percentage points. Countries with adjustment lending programs had current-account deficit ratios to GNP that were roughly 2.1 percentage points more positive than those without. The investment ratio is positively but insignificantly correlated with participation in an adjustment lending program: there is a rise in the ratio of on average .56 percentage point annually for those economies participating ia the programs. All of these correlations are significantly different from zero at the 95-percent level of confidence except for that of the investment ratio.
1 3 Table 1 THE SIZE AND SIGNIFICANCE OF AL PROGRAM EFFECTS 76-country sample IAL Dependent variable Coefficient T-statistic Performance measures: YGR 1.98 3.94 DINF 10.04 3.84 CAR 2.10 3.58 IR 0.56 1.08 **Policy realizations:** MON 1.91 3.72 _COV_ -0.48 2.80 RERA -7.15 5.23 RERB -0.27 4.32 Critical T values for both samples at: 95 percent level - 1.96 90 percent level - 1.64 The reported T statistics include a correction to the sum of squared errors from the instrumental-variable equation appropriate to obtain an unbiased estimate of the variance. This necessary adjustment differed by equation but was in all cases no larger than 1.4 percent of the size of the variance.
14 There were also significant differences<sup>in policies implemented by AL</sup> program and non-AL program countries.<sup>Government current expenditure is lower</sup> by .48 percentage points of GNP in<sup>SAL recipients, while financial deepening</sup> is increased by 1.9 percentage<sup>points. Those countries with AL programs,</sup> finally, experienced depreciated<sup>real exchange rates relative to those</sup> countries that did not participate.<sup>All of these correlations are</sup> significantly different from zero at the 95-percent<sup>level of confidence.</sup> The comparative picture thus exhibits<sup>significant differences across</sup> countries that provide clear responses<sup>to the two questions relevant to</sup> assessment of AL programs. First,<sup>there are significant differences between</sup> the performance of recipients<sup>of AL programs and of those who did not:</sup> economic growth is more rapid and<sup>the current account closer to balance on</sup> average for recipient countries,<sup>while infl&tion is also significantly</sup> higher in those countries. The sign<sup>of the effect on domestic investment is</sup> encouraging, although the coefficient<sup>is insignificant.</sup> 9 Second, these effects are contemporaneous with a significant policy shift among recipient 9 This positive effect on investment<sup>is the opposite of what was recorded</sup> in Corbo and Rojas (1990), although<sup>there as well the analogous coefficient was</sup> insignificant. The change in sign<sup>may be in part due to selection bias; when</sup> these equations are estimated using<sup>DAL rather than its instrument the</sup> coefficient is negative and insignificant.<sup>These biased coefficients are as</sup> follows for all equations: Eauation DAL coefficient YGR 1.94 DINF 10.00 CAR 2.01 IR -0.48 MON 0.08 GOY -0.67 RERA -9.11 RERB -0.46 The differences are minor except<sup>for the IR and MON equations.</sup>
15 countries. Government current expenditure as a share of GNP is lower, financial deepening is more pronounced, and the real exchange rate is depreciated on average when compared with non-recipient countries. All these differences are statistically significant. In sum, recipient countries have not been merely relying upon international lending at the margin but have also been restructuring their economies along the lines of economic liberalization advocated in the AL agreements.

These results are simultaneously determined with the "normal" response to the economic environment, and any implausibility in the latter will call them into question. Table 2 presents statistics and coefficients on external variables from the underlying generalized least-squares regressions that provide strong intuitive support to the notion of a normal response.<sup>10</sup> The explanatory equation for economic growth provides quite plausible and significant relations between the external environment and growth performance. Each standard-deviation improvement in the terms of trade is associated with an additional 1.07 percentage points in growth, while each percentage point increase in the real interest rate facing a country is correlated with a .22 percentage point fall in economic growth. Both longand short-term debt burdens reduce economic growth significantly; each $1 increase in per capita debt is associated with a fall on average of 2.5 and 8.0 percentage points in the growth rate. All of these effects are significantly different from zero at the 95 percent level of confidence.

The DINF equation suggests a number of significant common features of the inflation experience in the sample countries. Less-developed countries 10 Excluded from Table 2 are the coefficients on the 75 country-specific dummy variables and the year-specific dummy variables. These are available from the author on request, and are summarized in Conway (1990).
16

# Table 2 Normal Response to the External Environment Various Performance and Policy Measures

# Dependent variable: **YGR**

- F value of regression: 13.11

Probability given the null (all coefficients insignificant): 0.0001

|Explanatory<br>Variable|<br>Coefficient|Standard<br>Error|T value|
|---|---|---|---|
|**..**...<br>.........|......................|.................................|.......................<br>............**...**.........|
|YASHR|0,019|0.045|0.426|
|TOTB|1.069|0.200|5.348|
|RR|-0.224|0.037|-6.061|
|LTDPC|-2.590|1.387|-1.867|
|STDPC|-7.952|2.231|-3.564|

# Dependent variable: DINF

- F value of regression: 6.50

Probability given the null (all coefficients insignificant): 0.0001

|Explanatory<br>Variable|<br>Coefficient|Standard<br>Error|T value|
|---|---|---|---|
|USINF|-0.037|0.288|-0.128|
|YASHR|0.602|0.311|1.936|
|TOTB|1.166|0.834|1.398|
|RR|-0.569|0.271|-2.099|
|LTDPC|12.346|5.598|2.205|
|STDPC|2.507|7.512|0.334|

# Dependent variable: CAR

- F value of regression: 15.22

- Probability given the null (all coefficients insignificant): 0.0001

|Explanatory||Standard||
|---|---|---|---|
|Variable|Coefficient|Error|T value|
|.......................................................|...........|||
|YASHR|0.077|0.061|1.270|
|TOTB|1.797|0.228|7.896|
|RR|0.067|0.076|0.875|
|LTDPC|8.333|1.716|4.855|
|STDPC|1.820|2.728|0.667|
17

# Table 2 (continued)

# Dependent **variable:** IR

F value of regression: 78.23 Probability given the null (all coefficients insignificant): 0.0001

|Explanatory||Standard||
|---|---|---|---|
|Variable|Coefficient|Error|T value|
|YASHP|-0.221|0.048|-4.628|
|TOTB|0.399|0.182|2.191|
|RR|-0.103|0.060|-1.712|
|LTDPC|-8.365|1.560|-5.361|
|STDPC|-3.534|2.331|-1.516|

# Dependent variable: MON

F value of regression: 82.47 Probability given the null (all coefficients insignificant): 0.0001

|Explanatory||Standard||
|---|---|---|---|
|Variable|Coefficient|Error|T value|
|YASHR|0.018|0.044|0.413|
|TOTB|-0.422|0.193|-2.184|
|RR|0.320|0.059|5.418|
|LTDPC|7.856|1.906|4.122|
|STDPC|8.017|2.790|2.874|

# Dependent variable: COV

- F value of regression: 192.09

Probability given the null (all coefficients insignificant): 0.0001

|ExpLanatory||Standard||
|---|---|---|---|
|Variable|Coefficient|<br>Error|T value|
|.<br>.............................................................|...|||
|YASHR|-0.146|0.018|-8.062|
|TOTB|-0.397|0.067|-5.914|
|RR|**0.076**|0.012|6.444|
|LTDPC|-0.677|0.406|-1.666|
|STDPC|0.814|0.712|1.144|
18

# Table 2 (continued)

# Dependent variable: **REA**

F value of regression: 10.29 Probability given the null (all coefficients insignificant): U.0001

|Explanatory||Standard||
|---|---|---|---|
|Variable|Coefficient|Error|T value|
|.. . . .....<br>.........|..<br>......<br>...............|.<br>...|.<br>.<br>.<br>.<br>.<br>.<br>.<br>.|
|YASHR|0.757|0.181|4.192|
|TOTB|-1.479|0.658|2.247|
|RR|0.103|0.178|0.583|
|LTDPC|-4.090|6.009|-0.681|
|STDPC|11.570|8.884|1.302|

# Dependent variable: RERB

F value of regression: 6.636 Probability given the null (all coefficients insignificant): 0.0001

|Explanatory||Standard||
|---|---|---|---|
|Variable|Coefficient|Error|T value|
|YASHR|0.029|0.008|3.460|
|TOTB|-0.085|0.034|-2.468|
|RR|0.006|0.008|0.712|
|LTDPC|-0.529|0.252|-2.099|
|STDPC|1.118|0.464|2.412|

I I 1 IL 1 l I 1 LlL ILLl I 1IILL I L LLiI I II I I I II I II I I I I I I !ii I 111111 The coefficients reported in this table are a subset of those actually derived in the regressions. Also included as explanatory variables in all cases were country-specific dum=my variables for the 76 countries in the data set, the IAL variable (whose coefficient is reported in Table 1), and yearspecific d=mmy variables in equations where they contr!'.Ited significantly as a group (CAR, IR, MON, RERA, RERB, MOR).

Regressions include both autoregressive and heteroskedastic corrections so that both coefficient and standard error estimates are consistent. Reported standard errors include correction for use of instrumental variables.
19 tended to have higher inflation as indicated by the positive coefficient on the YASHR variable. Per capita debt contributes positively to the inflation rate, while increases in the real international interest rate are negatively correlated. As interesting are the effects not significantly correlated: there is no evidence of pass-through from world inflation (as proxied by USINF) and only an insignificant positive correlation of terms of trade improvements with inflation.

The CAR regression results do not accord well with the predictions of the balance of payments constraint and thus throw doubt on the AL lending coefficient in Table 1. As expected, an improvement in the terms of trade is correlated with a significant improvement in the current account. However, the real interest rate and per capita debt variables have positive coefficients; the balance of payments identity suggests that these should be negative. This may be due to the investment uses of that debt generating exportable or import-competing product. The year-specific dummy variables (not reported in Table 2) ndicate a sample-wide ability to sustain larger negative current-account ratios in years previous to 1986 than in 1986 itself. This ability was most pronounced in the period 1980-1982; in 1982 the sample average current-account ratio was ceteris paribus 1.8 percentage points more negative than in 1986.

Coefficients in the investment-ratio equation accord quite well with theoretical predictions. A smaller agricultural sector (as **a** proxy for the level of economic development of the economy) is significantly correlated with a larger investment ratio; so also is an improved terms of trade. Higher real interest rates, short-term and long-term debt burdens are all significantly
20 associated with reduced investment ratios.11 An increase of one percentage point in the real interest rate is correlated with **a** fall of .10 percentage points in the investment ratio, while $1 increases in £er capita debt are associated with reductions of the investment ratio of roughly 3.5 to 8.4 percentage points.12 The year-specific dummv variables indicate a samplewide tendency toward higher investment ratios during the pre-debt crisis period. In 1978 through 1981 the average investment ratio was ceteris paribus over 2 percentage points higher than in 1986, while in the 1983-1985 period investment ratios were on average slightly below that of 1986.

It is also instructive to examine the "normal" impact of the external environment on the policy structure of economies. The second half of Table 2 examines these common impacts for current government expenditure (GOV) and money broadly defined (MON) as percentages of GNP as well as for two measures of the real exchange rate (RERA and RERB).

I consider MON an indicator of financial deepening in the economy.<sup>13</sup> As McKinnon (1973) suggested, non-inflationary monetization of the economy may increase efficiency in allocation of goods while increased use of other financial instruments may improve efficiency in allocation of saving. This ratio will register both, but will exclude monetization leading only to 11 Note the importance here of considering lagged per capita debt as the explanatory variable.

12 In the IR and CAR regressions the coefficients of RR are insignificantly different from zero at the 95 percent level of confidence. This insignificance can be explained by the presence of the year-specific dummy variables; these variables are picking up some of the effect properly due to the real-interestrate variables.

13 Use of quasimoney alone as an alternative measure of financial deepening yields qualitatively results.
21 inflation. The regression results suggest that financial deepening is significantlv associated with greater levels of development, wich higher world real interest rates and with higher per capita international debt. There has been as well a sample-wide tendency toward financial deepening, with ratios in 1986 being on average nearly 3 percentage points higher than in 1977.

Government current expenditure as a share of GNP is rising with level of development. It is falling with improvements in :erms of trade, perhaps because social expenditures need increase less rapidly than GNP as the terms of trade improve. Higher real interest rates and increased short-term international debt are associated with an increase in GOV, while higher longterm debt is negatively correlated: only the real interest rate coefficient is significantly different from zero.

The two measures of the real exchange rate have identical patterns of responses to the external environment. The coefficient on YASHR indicates that the less developed the country, the more appreciated (more positive) real exchange rate. Improvements in the terms of trade are significantly associated with depreciations in the real exchange rate; this suggests that nominal exchange rate choice is not the dominant determinant of the real exchange rate, since real depreciation due to nominal depreciation should also be correlated with terms-of-trade deterioration. Increased short-term debt per capita is associated with an appreciation of the real exchange rate. There is evidence of sample-wide real appreciation as well during the period 1981-1985 after other factors have been controlled for, with a sharp average real depreciation in 1986. The real appreciation of 1981-1985 is the backdrop against which the real depreciations of those under AL programs stand out so sharply in Table 1.
22

# IV. **Conclusions.**

There is a clear association in the data of developing countries between participation in a World Bank adjustment lending program and significant differences in economic performance and policy. These differences include

- more rapid economic growth;

- more rapid inflation;

- improved current account/GNP ratio;

- deepening of financial markets;

- lower ratio of government current expenditure to GNP; and

- depreciation of the real exchange rate

compared with those countries not participating in such programs. The first three points stress the performance differential for those recipients of AL programs. The last three stress that these countries have employed significantly different policy mixes during the AL program period -- they have not merely benefited through increased financing at the margin.

I have been careful throughout to speak of association and correlation rather than causation. The atheoretic methodology of this st.udy does not identify the linkages between Bank adjustment programs and these measures, and does not provide a means of separating the effects of Bank iending from other concurrent factors. For example, the AL programs in many cases were concurrent with IMF stabilization policies; to that extent, then, the coefficient is a measure of the joint impact of the two. Further research would be useful in making more precise this and other concurrent relationships.