underscores two problems with the reform data â although planned reform is .... designed to achieve big improvements in the four financial indicators that we ...
Financial Sector Reform: What Works and What Doesn’t*
Robert Cull World Bank
*
The findings, interpretations, and conclusions are those of the author and should not be attributed to the World Bank, its Executive Board of Directors, or any of its member countries. I thank Jerry Caprio, George Clarke, Asli Demirguc-Kunt, Phil Keefer, Ross Levine, Nicolas Mathieu, Mary Shirley, Colin Xu, and Craig Burnside for many helpful comments and suggestions. I thank Salman Anees, Charles Chang, and Anqing Shi for providing data. All remaining errors are mine.
I. Introduction A growing body of evidence demonstrates that financial sector development is important for economic growth. 1 That development, however, likely comes with risks. The past twenty years have been witness to bank insolvencies in nearly 100 countries. Both their size – in many cases, the cost of bail-out was greater than 15% of GDP – and the fact that these crises often recur, reflect fundamental weaknesses in the financial sectors of many countries.2 It should come as little surprise, therefore, that the World Bank has increasingly granted loans with conditionalities designed to achieve specific financial sector reforms. This paper summarizes the Bank’s experience in financial sector lending operations from 1985-1996, including the types of loans issued, the reforms covered in the loans’ conditionalities, and the extent of financial sector development in the wake of the lending operations. The paper goes on to test whether variation in financial development is best explained by the characteristics of the recipient country or by features of the lending instrument. The paper closes by examining whether the probability of banking crisis increased in those cases where improvement occurred across a variety of financial indicators. In short, the paper addresses three simple questions: Where have financial sector lending operations been most successful? Why? And has financial development come at a cost in terms of stability? 2. Financial Sector Lending Operations: A Summary Reform identification in this paper is based on a recent methodology developed by the World Bank’s Operations Evaluation Department (OED) to identify the presence or absence of policies
1
. For an excellent review of that evidence see Ross Levine, “Financial Development and Economic Growth: Views
2
and Agenda,” Journal of Economic Literature 35 (March 1997): 688-726.
. Gerard Caprio Jr. and Daniela Klingebiel, “Bank Insolvency: Bad Luck, Bad Policy, or Bad Banking?” Supplement to the World Bank Economic Review and the World Bank Research Observer, Proceedings of the World Bank Annual Conference on Development Economics 1996, (Washington DC: World Bank, 1996).
2
in Bank-assisted financial sector reform programs across countries.3 OED classified financial sector policies in sixteen broad categories. The loans and the categories they covered are listed in Table 1. To date, OED has applied this methodology to eighty-five ‘adjustment related operations’ in fifty-six countries. Of the fifty-six potential country observations, however, only thirty-seven enter into this analysis because, in the other nineteen cases, either sufficient time has not yet elapsed since the project’s inception to evaluate the outcomes, or data on financial development are not available. In addition, while Table 1 lists all loans made to each of the thirty-seven countries, only a single loan per country is used in the statistical analysis.4 Because some loans were but one in a series to a country, we can test whether their place in the sequence affected their success.
3
. See Nicolas Mathieu, Financial Sector Reform: A Review of World Bank Assistance, World Bank Operations Evaluation Department (Washington, DC: World Bank, 1998). I am deeply indebted to OED and, in particular, Nicolas Mathieu, for providing the dataset that summarizes the individual interventions.
4
. The loan that entered the analysis for each country was chosen at random. Initially, the author tried to create his own database on financial sector lending operations. That database comprised only a subset of the final OED database. After incorporating the OED information, it became clear that the loans from the initial sample fit into the sequence of individual countries’ financial sector loans at different points, and that this might be a good source of variation to exploit. The loans chosen do not appear to be biased towards a particular point in the sequence (i.e., early or late).
3
Table 1: Sample of World Bank Financial Sector Lending Operations Country
Yr
Typea
Algeria* Algeria Argentina* Argentina Argentina Argentina Bangladesh* Bolivia Bolivia* Bolivia Burk. Faso* Chile Chile Chile* Chile China* Costa Rica* Ecuador* Ecuador Egypt* Ghana Ghana* Guatemala* Honduras* Hungary* Indonesia Indonesia Indonesia Indonesia* Ivory Coast* Jamaica Jamaica* Kenya* Korea* Madagascar Madagascar* Malawi* Malaysia* Mexico* Mexico Mexico Morocco Morocco* Morocco
91 95 93 94 94 96 90 87 88 92 93 86 87 88 90 93 85 87 93 92 88 91 93 89 91 88 89 91 93 92 87 91 89 85 87 90 91 87 89 95 95 86 91 96
SAD SAL SAL FIL TAL SAD SAD TAL SAD SAL SIL SAL SAL SAL FIL TAL SAL SAD FIL TAL SAD SAD SAL SAL SAL SAD SAL SAL FIL SAD SAD SAD SAD SAD SIM SAD FIL SIL SAD SAD TAL SAD SAD SAD
Int. Rate Distort. X
Ind. Mon. Instru. X
X
X
Direct ed Credit
Capit. Account Liber. X
X
Bank Privatiz ation
Comp anies Law
X
X
Differ Tax Treat ment
Foreign Entry
X
Central Bank Law
X
X
X
X X
Prudent. Regs. X
NonBank Fin. Regs. X
Money Mark. Dev.
X
X
X
X
X
X
X
X
X
Rights Oblig. of Fin Agent
Bank Super vision
Bank ReCapit.
X
X
X
X
X
X
X
X X
X
X
X X X
X
X
X
X
X X X
X X
X X
X
X
X X X
X
X X
X
X
X X X X -
X
-
-
X -
-
-
X -
-
-
X -
X -
-
X X X
X X X
X
X
X -**
X
X
X
X X X X
Other Bank Instit. Refrm X
X
X X
X X X
X
-
X X
X
-
X X -
X
X
4
X
X X
-
X -
X
X
X X
X X
-
-
X -
X -
-
-
-
X
X
X X X
-
X
Amount $ millions 350 150 400 500 8.5 500 175 11.5 70 40 7 250 250 250 130 60 80 100 75 9 100 100 120 50 250 300 350 250 307 200 40 30 120 222 83 48 32 65 500 1000 23.6 200 235 250
Nepal* 89 SAL X X X X X X 60 Pakistan* 89 SAD X X X X X 150 Pakistan 95 FIL 216 Peru* 92 SAD X X X X X X X X X 400 Philippines* 89 SAD X X X X X X 300 Poland 91 SAD 200 Poland 91 SAL 300 Poland* 93 SAL X X X X X X X X 450 Senegal 87 SAL 93 Senegal* 89 SAD X X X X X X X X 45 Sri Lanka* 93 SIL X X X X X X 60 Tanzania* 91 SAD X X X X X X 200 Tanzania 96 SIL 10.9 Tunisia 88 SAL 150 Tunisia* 92 SAL X X X X X X 250 Turkey 86 SAD 300 Turkey* 88 SAD X X X X X X X 400 Uganda* 93 SAD X X X X X X X X X 100 Uruguay* 89 SAL X X X 140 Venezuela* 90 SAD X X X X X X 300 * indicates the loan that was used in the empirical analysis that follows. a Loan types acronyms are as follows: SAD – Sector Adjustment Loan; SAL – Structural Adjustment Loan; FIL – Financial Intermediary Loan; TAL – Technical Assistance Loan; SIL – Specific Investment Loan; SIM – Specific Investment and Maintenance Loan.
5
For the purposes of this research, the OED classification procedure carries some limitations. For example, OED considered a reform to have been attempted largely on the basis of the objectives (summarized in the policy matrix) stated in the President’s Report that accompanied each loan. The matrix was, however, an ex-ante indication of planned reform, not necessarily an ex-post measure of actual reform. During the course of a loan, plans may change. Some reforms are scrapped; others are altered. In Pakistan’s Financial Sector Adjustment Loan (SAD), for example, a major component was the restructuring of many state-owned banks. Upon implementation, the Government decided that its restructuring efforts would be less effective than bank privatizations. Although the Bank later applauded the shift in emphasis, the OED classification indicates that the Pakistan loan attempted restructuring but not privatization. Of course, that classification may be partially accurate in that, although Pakistan’s was a 1989 loan, little privatization had occurred as of 1996.5 The episode underscores two problems with the reform data – although planned reform is different than actual reform, and substantial reform is different than minor reform, those differences are sometimes difficult to capture in simple dummy variables that are based largely on the expressed intentions of the parties to these loans. All that said, to the extent that expressed intentions are reliable indicators of ensuing reform and that the Bank’s loan documentation adequately summarizes those intentions, the measurement error associated with the OED variables should not be debilitating. However, in what follows, it will become clear that variation in post-loan financial development is better explained by country characteristics than by loan 5
. World Bank, Pakistan FSAL: Project Completion Report, (Washington, DC: World Bank, 1995), esp. 611.
6
characteristics. It should be noted at the outset, therefore, that one possible explanation for these results is that the OED dummy variables do not adequately capture the actions taken by the World Bank. Another possibility is that the variables that will be used to control for country characteristics in this analysis helped determine the types of reforms that were included in loan conditionalities. For example, countries at an early stage of financial sector development likely needed a different a menu of reforms than did countries with more developed financial sectors. To shed some light on that issue, Table 2 presents simple correlation coefficients between dummy variables that indicate whether a loan contained conditionalities in a specific OED reform category and four indicators of financial development. Those indicators are (1) the ratio of deposit money banks’ credit to the private sector to GDP (“Priv Credit”); (2) the ratio of M2 to GDP (“M2”); (3) the ratio of Quasi-money to GDP (“Quasi-money”); and (4) the ratio of liquid liabilities in the financial sector to GDP (“Liquid Liab”).6 Additional information on the sources and construction of these variables is presented in Table 6 (Appendix).
6
. Priv credit includes all assets of deposit money banks classified as claims on the private sector. M2 includes the sum of all currency held outside of banks, demand deposits other than those of the central government, and time, savings, and foreign currency deposits of “resident sectors other than the central government.” Liquid liab include M2 plus demand and interest bearing liabilities of non-bank financial intermediaries such as savings banks, postal savings institutions, and finance companies. Quasi-money is M2 minus currency held outside of deposit money banks and transferable (demand) deposits.
7
Table 2: Correlations Between Type of Reform and Stage of Financial Development Reform Area
Private Credit t=0 (n=35)
M2 t=0 (n=35)
Liquid Liabilities t=0 (n=22)
QuasiMoney t=0 (n=35)
-.06 .08 .08 .02
-.08 .01 .02 .11
-.10 -.12 -.11 .00
-.27 -.16 -.07 -.04
-.34** .21 -.14 .15
-.23 .15 -.16 .12
.08 -.19 -.12 .00
-.18 .13 -.15 .07
-.31* .14 .04 .17
-.28* -.02 -.19 .15
.23 -.20 .12
.08 -.24 .27
Interest Rate and Credit Distortions Interest Rate Liberalization Indirect Instruments of Monetary Control Dismantling of Directed Credit Opening Capital Account Remove Impediments to Competition Privatization of Banks Companies Laws: Entry and Exit Differential Taxation of Banks Foreign Ownership Restrictions Strengthen Financial Infrastructure Legal Framework for Central Bank Prudential Regulation of Banks Regulation of Non-Bank Finan. Intermed. Rights and Obligations of Fin. Agents
-.25 -.36* -.37* -.03
-.18 -.13 -.18 .21
Strengthen Institutions Bank Supervision Bank Re-Structuring & Re-Capitalization Bank Institutional Reforms
Type of Lending Operation -.41** SAD- Financial Sector Adjustment Loan *significant at .10 level; ** significant at .05 level.
-.02 -.23 .23
-.13 -.23 .30*
-.39* -.45**
-.46**
The correlation coefficients in Table 2 indicate that there is some relationship between the level of financial sector development at the time of a World Bank financial sector lending operation and the conditionalities covered. The most pronounced relationship is the negative one between the Financial Sector Adjustment Loan (“SAD”) dummy variable and all four indicators of financial sector development at the time of the loan. SADs, loan instruments dedicated only to reform of the financial sector, tend to cover more reform areas (6-7) than other types of loans that included financial sector 8
components (4-5).7 The negative correlation, therefore, indicates that countries at a low of financial development tended to receive loans with a more comprehensive set of conditionalities. Not only the comprehensiveness but also the types of reforms covered varied according to a country’s level of financial development. Although the results are not robust across all financial indicators, the correlation for three of the four variables in the sub-group labeled by OED as “strengthening financial infrastructure” tended to be negative, and was significantly different from zero, or nearly so, in a number of cases. Those three variables (legal framework for the Central Bank, prudential regulation of banks, and regulation of non-bank financial intermediaries) all concern the laws and regulations that govern financial actors. This indicates that countries at an early stage of financial development tended to receive loans with conditionalities concerned with establishing an appropriate regulatory framework. That emphasis is also reflected in the negative correlation between all four indicators of financial development and removal of differential tax treatment of banks and non-banks (although those correlation coefficients do not quite achieve significance). Countries with relatively under-developed financial sectors also tended to face conditionalities related to the re-structuring of their financial institutions. The correlation between the bank privatization and the bank re-structuring and capitalization variables and the four financial indicators tended to be negative and approached (if not achieved) significance in most cases. By contrast, the correlation between the more general bank
7
. Robert Cull, “Financial Sector Adjustment Lending: A Mid-Course Analysis,” (Policy Research Working Paper no. 1804, World Bank, August 1997).
9
institutional reform variable and financial indicators was positive in all cases and approached or achieved significance in three of the four cases. A general picture emerges that countries at relatively low levels of financial development tended to receive loans targeted specifically for their financial sector that covered a relatively high number of reform areas. Those reform areas tended to include regulatory improvement and very specific structural changes to individual financial institutions. Countries at relatively advanced stages of financial development tended to receive loans that covered fewer areas, and the area most emphasized was bank institutional reform not associated with specific structural changes. It is possible that certain types of reform are easier to achieve than others, or that some reforms may not be designed to achieve big improvements in the four financial indicators that we look at here. Because reform choices appear to be somewhat tied to a country’s level of financial development, both the reform dummy variables and the level of financial development (at the time of the loan) are included as explanatory variables in the regressions that follow. This should make it easier to isolate the effect of the stage of financial development (as opposed to the type of reform) on post-loan financial development. 3. Post-Loan Financial Development The indicators of financial development in this analysis were chosen for specific reasons. M2, Quasi-money, and Liquid Liab were chosen to describe financial development as reflected in the liabilities side of the balance sheets of financial institutions. M2, which includes Quasi-money plus transferable deposits and currency held outside of banks, is the broadest measure of financial depth. Quasi-money, which includes only time, savings, and foreign currency deposits, provides a better indication of
10
the level of less liquid liabilities held by banking institutions. Liquid Liab adds the liabilities of non-bank financial institutions to M2. 8 Each, therefore, provides a slightly different perspective on the liabilities of financial institutions. An increase in financial sector liabilities is one indication of financial development, but it is just as important to know whether those liabilities are being effectively intermediated. Private Credit is used, therefore, to track changes on the asset side of the balance sheets of financial institutions. In the next section, the quality of intermediation is addressed by looking at whether increased intermediation coincided with increased financial sector fragility. The more limited goal of this section is to analyze whether the determinants of post-loan financial development were similar across both sides of the balance sheet. A. Construction of Dependent Variables Two different measures of development were constructed for each financial indicator. For M2 the first measure is simply:
Y(1) = M23-M20 (1)
where M20 is measured in the year of the loan and M23 is measured three years hence. 9 Similar variables are constructed for the other three financial sector indicators.10 This
8
. The developing countries studied here tend to have financial sectors dominated by banks. As a result, the liabilities of non-bank financial institutions tend to be small, so small that Liquid Liab is reported for only about sixty percent of the sample observations.
9
. Y was multiplied by 100 in the regression results that follow.
10
. See Table 5 for the raw data use to construct the indicators of financial development and Table 6 for complete descriptions of the construction and sources of all variables incorporated in the empirical analysis that follows.
11
measure may overstate the degree of financial development in countries with relatively developed financial sectors. Consider, for example, Malaysia, which had a private credit and an M2 ratio near 70% when it received its financial sector loan in 1987. Year to year variations in Y(1) for Malaysia are often about 3-5 percentage points. Those changes are not that large for a country at Malaysia’s stage of financial development, but for the majority of the countries studied here, countries with private credit ratios averaging about 20%, a 3-5 point move in any of the financial ratios would be substantial. In short, Y(1) may overstate the degree of post-operation financial development for countries that are relatively financially developed. The simple solution is to construct a second measure of development:
Y(2) = M3/M0 (2)
Similar variables are constructed for each financial indicator. Y(2), which measures the rate of change in M2, may give a more accurate reflection of post-operation financial development in countries like Malaysia, but it too has limitations. In countries at relatively low stages of financial development, small values for Y (1) may translate into relatively large values for Y (2). For a country with an M2 ratio near 5%, this may overstate the financial development associated with relatively small positive values for Y(1) (1-2 points). Because Y (1) and Y(2) measure financial development somewhat differently, a simple robustness check on the regression results that follow is whether similar qualitative results obtain for both types of dependent variables.
12
B. Explanatory Variables: Hypotheses Three country characteristics play important roles in the empirical analysis. The first is initial level of financial sector development at the time of the Bank’s lending operation, which is measured as private credit 0.11 The are a number of reasons to expect that countries at relatively advanced stages of financial sector development might expect less financial deepening and development than others in the wake of a World Bank lending operation. First, removing distortions, that is, allowing market-determined interest rates to provide the “right” signals, can have a large impact on financial development (in a stable policy environment), and countries at low initial stages of financial development tend to receive World Bank loans with conditionalities aimed at removing such distortions. 12 In other words, there may be diminishing marginal returns to reform efforts as financial sectors become increasingly developed. This may be due, in part, to the inherent difficulties associated with certain types of institutional reform, reform more likely to be undertaken by countries with relatively developed financial sectors. It may also be because, after a certain level of financial sector development, private investment flows become much more important in subsequent financial sector development, and World Bank loans and the associated conditionalities may have little influence on the direction of such flows.
11
. Private credit0, therefore, is a level measure. The dependent variables in the analysis measure changes in financial development. The choice of private credit0 as the measure of initial financial sector development is not a crucial one. Similar empirical results obtain if measures of total liabilities (M2, quasi-money, or liquid liabilities) are used to measure financial development at the time of the loan.
12
. In weak environments (characterized by macroeconomic instability, little respect for the rule of law, and poor contract enforcement), interest rate liberalization can lead to rapid increases in both nominal and real interest rates which, in turn, lead to financial sector fragility. See Asli Demirguc-Kunt and Enrica Detragiache, “Financial Liberalization and Financial Fragility,” (Policy Research Working Paper no. 1917, World Bank, May 1998).
13
Finally, there may be feedback that affects financial development through the real growth rate. Poorer countries tend to catch up to richer ones (if only in a conditional sense) through relatively high growth rates. 13 Moreover, financial development and economic growth are positively associated.14 If poorer countries are growing at faster rates (ceteris paribus), we might, therefore, expect them to experience greater financial development. To the extent that those poorer countries also had lower financial sector development at the time of the loan, one would expect a negative relationship between indicators of initial financial sector development and subsequent financial development. In short, there are multiple reasons to expect diminishing marginal returns to World Bank lending as a country’s financial sector becomes increasingly developed, and thus a negative relationship between private credit0 and subsequent financial development (as reflected in Y(1) and Y(2)). A country’s population at the time of a financial sector lending operation may also affect subsequent financial development. Financial systems exist to allocate investable resources to the most productive endeavors. Higher productivity may depend on specialization, and the potential for specialization may be greater in countries with larger populations. One would expect, therefore, a positive relationship between population and subsequent financial sector development. The third country characteristic expected to have an impact on post-loan financial sector development is macroeconomic stability as reflected in the inflation rate. Whereas initial financial sector development and population are measured in the year of the loan 13
. Ross Levine and David Renelt, “A Sensitivity Analysis of Cross-Country Growth Regressions,” American Economic Review 82 (September 1992): 942-63.
14
(to reflect the country’s potential for development), the inflation rate is a contemporaneous measure intended to reflect the broader policy environment in which the financial sector loan tried to achieve its objectives. Inflation is the average inflation rate in the three years after the loan. This measure can be narrowly interpreted as a measure of the soundness of monetary policy, or as an indication of the soundness of the overall institutional framework. With respect to financial sector development, relatively stable price levels make it easier to structure longer-term financial contracts. We would, therefore, expect a negative relationship between inflation and post-loan financial sector development. While the three country characteristics – initial financial development, population, and inflation – are not directly under the World Bank’s control, the Bank may have much greater discretion over such factors as the amount of the loan and the conditionalities attached. We also control for these Bank-driven factors in the simple regressions that follow, although, as will be demonstrated, none of them provide much explanatory power regarding subsequent financial development. C. Regression Results The most robust result is that a high level of financial sector development at the time of the loan (private credit0) was negatively associated with subsequent financial development. With only minor exception, the estimated coefficient for private credit, which is always negative, achieves statistical significance across all specifications in Table 3. The dependent variables cover all four indicators of financial development (changes in M2, private credit, quasi-money, and liquid liabilities), and both the Y(1) and 14
. Robert G. King and Ross Levine, “Capital Fundamentalism, Economic Development, and Economic Growth,” Carnegie-Rochester Conference Series on Public Policy, 40 (June 1994): 259-92.
15
Y(2) variable constructions for each indicator. The one minor exception is for liquid liabilities, although the coefficient does approach significance in one specification. The liquid liabilities result (or lack thereof) is not too troubling, however, in that the sample size is cut dramatically when using that dependent variable due to data availability. For the other indicators, the result is quite robust. Countries at higher stages of financial development benefited less from World Bank lending to the financial sector. There appear to be diminishing returns to financial sector lending as that sector develops. A second relatively robust result is that, as expected, post-loan financial sector development was negatively associated with contemporaneous inflation. Although the result is more robust across the Y(1) constructions of the dependent variables, coefficients are negative and significant across all indicators of financial development involving the total liabilities of financial institutions (changes in M2, quasi-money, and liquid liabilities). The result does not carry over to the asset side of financial institutions’ balance sheets, as changes in private credit were not significantly related to contemporaneous inflation. This suggests that depositors and other liability holders respond more quickly to an unstable currency than do financial institutions, which is, of
16
Table 3: Financial Development Regression Results Explan. Variable
M23-M20
Constant
(1) 16.87** (3.62)
Private Credit 3Private Credit 0 (2) 7.77 (0.87)
Liquid Liab3Liquid Liab0 (3) 19.98** (2.12)
QuasiMoney3QuasiMoney0 (4) 9.70** (2.45)
M23/ M20 (5) 156.9** (7.82)
Private Credit 3 / Private Credit 0 (6) 149.8** (3.81)
Liquid Liab3 / Liquid Liab0 (7) 181.9** (4.72)
QuasiMoney3 / QuasiMoney0 (8) 151.4** (5.11)
Initial Priv.Cred
-.141** (2.92)
-.161* (1.74)
-.104 (1.12)
-.078* (1.89)
-.608** (2.92)
-1.04** (2.56)
-.632 (1.60)
-.535* (1.74)
-.822** (2.98)
-1.67** (3.12)
-1.11** (3.03)
-2.21** (2.95)
-.582** (2.36)
-.889** (2.26)
Current Inflation
-.099** (2.70)
-.034 (0.48)
-.124* (1.86)
-.057* (1.84)
-.269* (1.71)
-.146 (0.48)
-.461 (1.64)
-.198 (0.86)
-.361* (1.88)
-.433 (1.16)
-.412* (1.75)
-.212 (0.44)
-.266 (1.34)
-.080 (0.26)
Population
.013** (2.86)
.007 (0.82)
.012 (0.32)
.014** (3.64)
.032 (1.57)
.054 (1.37)
.039 (0.24)
.037 (1.26)
.038 (1.67)
.084* (1.89)
.053* (1.88)
.123** (2.15)
.033 (1.46)
.042 (1.15)
.0003 (0.90)
.008 (1.48)
.001 (0.32)
.007 (1.10)
Sector Adj Loan
3.65 (0.44)
-9.35 (0.55)
Bank Inst Change
-.409 (0.04)
-3.33 (0.16)
Bank Privatiz.
-20.93* (1.83)
11.56 (0.50)
Aid Per Capita
-.098 (0.32)
-.949* (1.94)
Policy* Aid
.149 (1.14)
.536** (2.57)
.18 30
.19 30
Income Per Capita
Adj R2 Obs.
.31 37
.01 37
.06 22
.33 37
.18 37
.06 22
.09 37
*significant at .10 level; ** significant at .05 level; t-statistics in parentheses.
17
.02 37
M23/ M20 (9) 174.3** (7.23)
Private Credit 3 / Private Credit 0 (10) 182.9** (3.89)
.26 28
.18 28
M23/ M20 (11) 187.2** (6.49)
Private Credit 3 / Private Credit 0 (12) 172.6** (2.94)
(13) 152.6** (5.81)
Private Credit 3 / Private Credit 0 (14) 143.9** (3.42)
.29 26
.15 26
M23/ M20
course, sensible when one considers that the stock of credit contracts are not as nearly liquid as most types of financial institution liabilities (e.g., demand deposits). The coefficient on population is, as expected, positive in all specifications in Table 3, although it is significant in only two specifications that include all thirty-seven sample countries (for M2 and quasi-money under the Y(1) constructions of those variables). The inclusion of additional regressors, especially variables related to per capita income levels, yields significant coefficients for population across multiple specifications. For both private credit and M2, the population coefficient achieves or just misses significance in all specifications in which some form of the income per capita variable also appears as a regressor. The robustness of the result across dependent variables from both sides of financial institutions’ balance sheets indicates that larger countries have experienced more post-loan financial development than smaller ones, a sign, perhaps, that the potential for specialization and improved resource allocation may be greater in larger populations. Per capita income is often included as a regressor in cross-country regressions as a proxy for overall institutional development. 15 One advantage to incorporating the more general measure of institutional development here is that the inflation variable can be more readily interpreted as a measure of only the quality of macroeconomic, especially monetary, policy. The only drawback is that almost a quarter of the sample is lost by including per capita income. Other country characteristics such as the current account deficit, fiscal surplus, import-export measures, and real growth have also been 15
. See, for example, Stephen Knack and Philip Keefer, “Institutions and Economic Performance: Cross Country Tests Using Alternative Institutional Measures,” Economics and Politics 7 (November 1995): 207-227, or Asli Demirguc-Kunt and Enrica Detragiache, “The Determinants of Banking
18
incorporated into these specifications (results not reported). Their inclusion yields no results that are robustly significant across indicators of financial development. Whereas inflation, private credit, and population performed as expected, none of the variables included to capture loan characteristics – factors more directly under the World Bank’s control – explain much variation in post-loan financial development. Neither the loan amount nor the reform areas covered in the loan conditionalities are significant, except in rare instances. None display the robustness of the results for country characteristics. In columns 11 and 12 of Table 3, specifications appear that incorporate as regressors income per capita and three dummy variables, one indicating whether the loan was a sector adjustment loan (SAD), and two others indicating whether the loan contained conditionalities related to bank privatization or bank institutional change. Recall that the presence of these loan characteristics appeared to be tied to a country’s level of financial development at the time of the loan (Table 2). Only the bank privatization dummy is significant (negative), and that result is not robust across dependent variables. Most importantly, controlling for these (and other) loan characteristics, the negative relationship persists between initial private credit (private credit) and post-loan financial development. 16 Some types of reform may be harder to achieve than others, or they may be reflected less clearly in the indicators of financial development studied here. These last two specifications indicate that, controlling for such possibilities, a country’s level of financial development at the time of a loan helps determine the subsequent amount of financial development. Crises in Developing and Developed Countries,” International Monetary Fund Staff Papers, 45 (March 1998): 81-109.
19
The general finding is that country characteristics were more important than loan characteristics in determining the relative success of a loan (at least as measured by this set of financial development indicators). The result mirrors a more general recent finding that variables under the World Bank’s control, such as the number of conditions or resources devoted to preparation and supervision, have had no significant effect on the probability of success or failure of reform. 17 This is not to argue that the financial sector lending operations have had little impact on financial development. The point is simply that post-loan financial development has been best in countries with sound policy environments (as reflected in the inflation variable) and the most potential for financial growth (low initial financial development and a high population). In short, the details of the lending operation itself appear to be less important than the conditions under which the reform is carried out. When conditions are favorable, meaning that domestic constituencies are committed to reform, adjustment loans and foreign aid can help consolidate policy gains in three ways: “First, conditional loans are a means by which a reform-minded government can publicly commit to policy measures. Second, conditionality sends a signal to the private sector that a reform program is credible, and this should encourage a
16
. I experimented with dummy variables for all of the types of loan conditionalities in Table 2 and for dummy variables indicating where a loan fell in the sequence of financial sector loans to that country. None of those variables produced robust results.
17
. See David Dollar and Jakob Svensson, “What Explains the Success or Failure of Structural Adjustment Programs?” (Policy Research Working Paper no. 1938, World Bank, June 1998) and World Bank, Assessing Aid: What Works, What Doesn’t, and Why (New York: Oxford University Press, 1998).Those studies examined the outcomes of projects across a wide variety of sectors.
20
quicker response from investors. Third, aid spurs growth in a good policy environment.” 18 All of these factors could help explain why certain countries have experienced larger gains after financial sector lending operations. Burnside and Dollar established the link between aid and economic growth in an effective policy environment. That link could also be reflected in greater financial development. The last two columns in Table 3 incorporate the Burnside/Dollar measures of aid effectiveness as explanatory variables.19 Effective development assistance (“EDA”) was interacted with a measure of the quality of government policies (“policy”). Both were measured in the year of the loan. 20 The policy measure differs slightly from that used by Burnside and Dollar. In their paper: Policy = 1.3 + 5.4 x Budget Surplus – 1.4 x Inflation + 2.1 x Openness (3) The policy index was formed using coefficients from a growth regression. In this way, the relative importance of individual policies was determined based on their contributions to economic growth. Because inflation already enters the financial development regressions, it was set equal to the sample median in constructing the policy index used
18
. Ibid. p. 18.
19
. I am indebted to Craig Burnside and Charles Chang for providing me with the aid data and the policy variables used in Craig Burnside and David Dollar, “Aid, Policies, and Growth,” (Policy Research Working Paper no. 1777, World Bank, June 1997).
20
. One might argue that, like inflation, the aid and policy variables should be measured in the years after the loan to control for the policy environment in which the lending operation had to accomplish its objectives. Similar qualitative results obtain when EDA and policy are averaged over the two years after the loan’s inception. Averaging over three years is not possible, however, due to missing data problems.
21
here.21 The trade openness measure is the dummy variable developed by Sachs and Warner. 22 Per capita EDA is negatively and significantly associated with subsequent financial development in the private credit regression. The interaction term (Policy*EDA) was positively and significantly linked to private credit expansion. 23 The results indicate that post-loan financial development has been greatest where substantial aid was injected into sound policy environments. The result does not, however, hold for M2/GDP, or for the other financial indicators focussed on the liabilities of financial intermediaries. Nor does it hold when EDA is replaced by either the amount of the loans studied here or by the total lending for financial sector development undertaken by the Bank (in the 3-5 years prior to the loan in this sample). The EDA results in the private credit regression provide further support for the idea that variation in post-loan financial development is better explained by general indicators of a country’s potential for (and commitment to) reform rather than the specifics of the lending operation (e.g., the policy areas covered, or the loan amount). This does not necessarily imply that such details are unimportant. It could merely indicate that the importance of such details is not well reflected in the broad indicators of 21
. The index used here can be interpreted as a country’s predicted growth rate, given its budget and trade policies, assuming that it had average values for all other characteristics that enter the growth regression. The benchmark period used to estimate the growth regressions in Burnside and Dollar was 1990-93.
22
. Jeffrey D. Sachs and Andrew Warner, “Economic Reform and the Process of Global Integration,” Brookings Papers on Economic Activity, 0(1), (1995): 1-118.
23
. Again, EDA is a per capita measure and private credit is measured as a share of GDP. The EDA measure used here differs slightly from that in Burnside and Dollar, who use EDA as a share of GDP. They used Summers-Heston GDP figures. I lack sufficient Summers-Heston country coverage to do the same thing here and thus rely on per capita EDA. They also present specifications that treat their aid and policy measures as endogenous variables. I lack the degrees of freedom necessary to do the same.
22
financial development studied here. Or, much of the information that would have been conveyed in the details of the lending operation may have been subsumed in the initial private credit variable. That is, the terms of these loans may have been partially dictated by the level of financial development in the recipient country. In any event, the EDA*Policy result indicates that, when directed to countries pursuing sound policies, development assistance can contribute to improved financial sector development. 4. The Quality of Financial Development: Indicators of Fragility The most robust result of the paper is that countries with under-developed financial sectors at the time of a loan tended to experience greater post-loan financial development. As a final empirical exercise, this section examines the quality of the development in these initially under-developed countries. In particular, it asks whether that development has come at a cost in terms of sector stability. Recent empirical work has identified a number of factors associated with systemic banking crisis.24 Factors positively and significantly associated with crisis across a wide variety of econometric specifications include inflation, real interest rates, and rapid private credit growth. Factors negatively associated with crisis include real GDP growth and income per capita. Table 4 presents information regarding financial development, banking crisis, and the five factors identified by Demirguc-Kunt and Detragiache (DD) that lead to crisis. Data are presented both before and after the inception of the Bank’s lending operation for a sample of nineteen countries that appear in both the DD analysis and this one. 25 24
. Demirguc-Kunt and Detragiache, “The Determinants of Banking Crises in Developing and Developed Countries.”
25
. Ibid. They define a systemic banking crisis as an episode in which one or more of the following hold: “the ratio of non-performing assets to total assets in the banking system exceeded 10 percent; the cost of the rescue operation was at least 2 percent of GDP; banking sector problems resulted in a large scale nationalization of banks; extensive banks runs or emergency measures such as deposit
23
Countries are ordered (from lowest to highest) according to their private credit ratios at the time of loan inception. Those at the top of the list did tend to experience the most improvement in their financial indicators. Yet, of the ten countries with private credit below 20% at loan inception, six experienced systemic banking crisis at some point within the ensuing five years.26 Of the nine countries with private credit ratios above 20%, only one experienced a crisis. The evidence suggests that financial development among initially under-developed countries came at a cost in terms of increased fragility.
freezes, prolonged bank holidays, or generalized deposit guarantees were enacted by the government in response to the crisis.” I am indebted to Asli Demirguc-Kunt and Anqing Shi for making the DD data available to me. 26
. Admittedly, in one case (Nepal), crisis occurred both before and after the loan, and so relatively rapid financial development was not solely responsible for increased fragility.
24
Table 4: Financial Development and Banking Stability Country
Pop
Private Credit
M2
Liquid Liab.
QuasiMoney
Pre-Crisis
Peru
Date of WB Loan 92
PostCrisis w/in 5yrs N
Real Growth
N
PostCrisis w/in 3yrs N
Inflation
Credit Growth
-3.3 9.2
Real Interest Rate -117.8 1.5
232.9 26.0
-13.3 15.7
Income Per Capita 873 979
22.5
7.8a 14.6b
15.6 18.7
15.8 18.8
10.1 13.0
Nepal
89
18.4
12.8 13.4
31.5 33.0
-
18.4 19.3
Y
Y
Y
2.6 4.4
-5.7 -4.6
11.0 13.2
7.6 14.0
165 191
Bolivia
88
7.0
13.1 26.6
17.2 29.8
17.2 29.8
11.3 22.2
Y
N
N
5.5 6.1
-97.2 10.6
127.7 13.1
20.7 29.1
637 653
Mexico
89
84.3
15.9 32.6
18.3 29.2
19.2 30.6
12.6 17.4
N
N
Y
2.7 4.3
-5.6 1.3
62.6 21.9
2.6 27.6
1728 1806
Tanzania
91
26.4
16.3 11.6
23.0 31.3
-
8.2 13.3
N
Y
Y
2.4 5.4
-20.3 -
29.2 50.2
2.1 98.3
148 151
Turkey
88
53.7
16.4 15.5
28.8 26.9
29.9 26.6
20.0 19.9
N
Y
Y
2.1
-7.0 -11.7
49.1 66.4
12.3 -0.6
1657 1690
Venezuela
90
19.3
16.5 15.8
33.5 27.8
42.3 36.1
20.6 19.9
N
Y
Y
-0.5 5.4
-21.4 28.4
65.6 27.1
3.8 -9.7
2509 2792
Philippines
89
60.1
17.3 20.4
32.4 36.2
35.0 40.0
23.6 27.5
N
N
N
6.5 0.9
7.3 7.9
9.3 12.5
-5.7 12.3
615 609
Ecuador
87
9.6
18.8 19.9
22.8 21.8
23.8 23.3
9.7 11.3
N
N
N
-1.4 4.6
-6.4 -29.1
29.4 59.1
-5.3 -12.0
1152 1175
Kenya
89
24.9
19.1 22.9
28.2 37.7
40.1 50.7
15.6 19.5
N
N
Y
5.4 1.6
5.8 3.0
7.9 12.9
3.9 6.0
355 369
Egypt
92
55.7
22.3 32.6
84.5 79.4
86.6 82.4
62.4 59.1
N
N
N
4.6 10.2
-1.7 -2.6
20.9 17.3
1.44 -7.51
729 708
Honduras
89
5.0
25.2 23.1
31.7 30.4
33.7 33.1
17.2 17.0
N
N
N
3.9 3.1
1.8 -7.9
6.8 18.8
11.2 1.3
911 893
Jamaica
91
2.4
26.4 22.5
43.2 45.9
49.4 49.9
25.9 31.0
N
N
N
2.8 1.4
-17.2 -2.7
43.3 38.1
13.5 -13.7
1475 1597
Senegal
89
7.3
29.9 25.9
25.0 23.9
25.3 -
9.4 10.4
Y
N
N
1.8
8.7
1.5
-3.6
689
-
10.7
0.8
-0.3
676
N
7.0 6.8
-2.9 11.5
23.0 18.6
-7.45 -0.7
1695 1944
Chile
88
12.8
44.0 42.9
Uruguay
89
3.1
39.1 40.6
57.3 45.7
-
49.4 38.5
N
N
N
0.6 4.0
6.6 -12.5
69.7 88.4
-11.2 0.1
2404 2507
Korea
85
40.8
48.7 44.3
34.8 36.8
39.8 47.0
25.6 27.6
N
N
N
7.7 11.4
-0.1 1.9
5.1 5.4
14.5 10.7
2599 3282
Malaysia
87
16.5
64.4 71.4
70.8 66.3
124.8 -
50.2 44.3
Y
Y
Y
3.3 9.3
5.1 1.7
-1.6 3.7
13.8 5.3
1888 2170
38.6 39.4
39.3 40.2
30.0 30.6
Y
N
a
Peru’s private credit ratio (relative to GDP) at time t=0, the inception year of the World Bank financial sector loan. Peru’s private credit ratio (relative to GDP) at time t=3, three years after the inception of the loan. For all variables for which two observations per country appear, the same is true. That is, the top line indicates the situation in the year of the loan’s inception; the bottom is for three years hence (t=3). b
26
Table 5: Financial Sector Lending Operations, Index of Success Country
Uganda Ghana Peru Burkina Faso Malawi Guatemala Poland Nepal Bolivia Mexico Tanzania Turkey Madagascar Venezuela Argentina Costa Rica Philippines Ecuador Kenya Morocco Egypt Bangladesh Sri Lanka Honduras Pakistan Jamaica Senegal Ivory Coast Algeria Hungary Uruguay Chile Korea Indonesia Tunisia Malaysia China
Date
93 91 92 93 91 93 93 89 88 89 91 88 90 90 93 85 89 87 89 91 92 90 93 89 89 91 89 92 91 91 89 88 85 93 92 87 93
Pop
18.4 15.5 22.5 9.7 8.6 10.0 38.5 18.4 7.0 84.3 26.4 53.7 11.2 19.3 33.9 2.6 60.1 9.6 24.9 25.0 55.7 108.1 17.6 5.0 109.1 2.4 7.3 12.7 25.6 11.2 3.1 12.8 40.8 189.1 5.4 16.5 1196.4
Private Credit t=0
Private Credit t=3
M2 T=0
M2 t=3
3.5 3.7 7.8 10.0 10.9 11.6 12.2 12.8 13.1 15.9 16.3 16.4 16.4 16.5 16.5 17.3 17.3 18.8 19.1 20.0 22.3 22.6 22.7 25.2 25.4 26.4 29.9 32.0 38.6 38.8 39.1 44.0 48.7 48.9 54.0 64.4 95.5
4.4 5.5 14.6 7.8 10.8 16.2 15.9 13.4 26.6 32.6 11.6 15.5 16.5 15.8 18.1 16.9 20.4 19.9 22.9 25.2 32.6 20.2 25.1 23.1 24.0 22.5 25.9 20.0 6.6 26.2 40.6 42.9 44.3 55.4 53.7 71.4 91.6
9.2 14.2 15.6 20.6 19.7 25.5 36.0 31.5 17.2 18.3 23.0 28.8 16.2 33.5 17.6 38.4 32.4 22.8 28.2 55.3 84.5 31.8 32.3 31.7 38.9 43.2 25.0 28.8 49.2 47.5 57.3 38.6 34.8 43.4 46.6 70.8 100.7
10.0 19.6 18.7 24.9 23.7 25.3 37.6 33.0 29.8 29.2 31.3 26.9 23.0 27.8 20.8 43.0 36.2 21.8 37.7 62.4 79.4 34.6 33.0 30.4 42.5 45.9 23.9 28.7 49.8 45.8 45.7 39.4 36.8 52.1 45.2 66.3 109.7
Liquid Liab. t=0 15.8 22.9 25.3 17.2 19.2 29.9 17.8 42.3 17.8 38.5 35.0 23.8 40.1 62.5 86.6 40.7 33.7 39.7 49.4 25.3 39.3 39.8 49.0 124.8 -
27
Liquid Liab. t=3 20.3 18.8 26.9 25.3 29.8 30.6 26.6 25.4 36.1 20.9 43.1 40.0 23.3 50.7 71.2 82.4 41.7 33.1 43.2 49.9 40.2 47.0 47.8 -
QuasiMoney t=0 2.5 4.5 10.1 6.6 9.3 17.7 23.3 18.4 11.3 12.6 8.2 20.0 3.7 20.6 11.8 22.0 23.6 9.7 15.6 12.5 62.4 22.8 20.4 17.2 10.8 25.8 9.4 11.9 10.7 24.9 49.4 30.0 25.6 33.2 25.5 50.2 52.1
QuasiMoney t=3 3.1 5.6 13.0 5.9 10.0 16.1 23.2 19.3 22.2 17.4 13.3 19.9 7.1 19.9 14.4 24.3 27.5 11.3 19.5 16.5 59.1 24.9 22.8 17.0 11.8 31.0 10.4 9.7 16.8 25.3 38.5 30.6 27.6 42.4 24.1 44.3 65.5
Banking Index
New Crisis
Crisis Index
Overall Success
Pass Pass Pass Fail Fail Fail Fail Pass Pass Pass Fail Fail Pass Fail Pass Pass Pass Fail Pass Pass Fail Fail Pass Fail Fail Fail Fail Fail Fail Fail Fail Fail Fail Pass Fail Fail Fail
No No No Yes Yes Yes Yes No No Yes No No No No No No No Yes No -
Pass Fail Pass Pass Fail Pass Pass Fail Pass Fail Pass Fail Pass Fail Pass Fail Pass Pass -
Success Partial Success Partial Failure Failure Failure Partial Failure Failure Failure Failure Failure Failure Failure Failure Failure Partial Failure -
An attempt to characterize the loans as successes or failures based on all available information appears in Table 5. A loan was said to have “passed” the development test if all four indicators of financial sector development improved in the three years after the inception of the loan. Countries are again listed in order of their initial levels of financial development, and the majority of countries that pass this test are found in the top half of the table. Of the twenty countries with initial private credit ratios at or below 20%, more than half (twelve) pass the test. Of the seventeen countries with private credit ratios above 20%, only two pass. Countries that passed the development test were considered a full success if (1) they experienced no new systemic crisis in the three years after the loan’s inception, and (2) the majority of the DD crisis indicators (“crisis index”) did not worsen. 27 They were considered a partial success if either of those conditions did not hold, and a failure if neither held. This is a very stringent test in that it requires financial development across multiple indicators without substantial increase in financial fragility. Only two of the nineteen countries for which all information is available pass the test (Peru and Bolivia). Four additional countries are rated partially successful, meaning they passed the development test but failed some aspect of the fragility test. Both full successes and two of the four cases rated at least partially successful had an initial private credit ratio below 15% (i.e., in the lowest quartile of the sample). At the risk of reading too much into that clustering, it would appear that the countries with especially under-developed financial sectors underwent the initial stages of financial development without incurring much additional fragility.
27
. Those that did not pass the development test were automatically deemed failures.
29
5. Conclusions Countries with relatively under-developed financial sectors have experienced more sector growth than others in the three years after the inception of a World Bank loan tailored for that purpose. This indicates that there are diminishing marginal returns to World Bank financial sector lending operations as a country’s financial sector becomes increasingly developed. The result could be attributable to the decreased influence that lending from development banks may have on financial sectors that become increasingly driven by purely private financial intermediation; or it could indicate that payoffs to financial operations are simply bigger in the very earliest stages of financial development. This could be because removal of market distortions in early stages of development is easier to accomplish than the institutional change (e.g., improved supervision of financial entities) that tends to be required at more advanced stages of development. Whatever the underlying cause, the result could argue for increased country selectivity with respect to World Bank financial sector loans, or could argue for increased technical assistance (rather than large adjustment loans) to countries at relatively advanced stages of financial sector development. At the least, it suggests that the Bank revise its expectations for success to take into account initial financial sector conditions in a recipient country. That selectivity or those expectations could be further refined to account for two additional findings. First, financial development has been greatest in those countries that have maintained relatively low inflation rates after a financial loan’s inception. The second, slightly less robust, finding is that post-loan development was greater in countries with larger populations, a reflection, perhaps, that those countries had greater potential for productivity improvement through specialization, and thus greater potential gains from improved resource mobilization through financial intermediation. In short, post30
loan financial development has been best in countries with sound policy environments (as reflected in the inflation variable) and the most potential for financial growth (low initial financial development and a high population). The details of the lending operation itself appear to have been less important than the conditions under which the reform was carried out. However, the interaction between aid and an index of policy quality was positive and significant, which indicates that such assistance does contribute to financial sector development in a sound policy environment. These results should not be interpreted as indicating that lending should be focused only on populous countries with low inflation rates and low levels of financial development, and that the details of those lending operations be of secondary importance. There is some evidence that the relatively large increases in post-loan financial sector development among initially under-developed countries (in a financial sense) came at a cost in terms of increased sector instability. This suggests that regulatory and supervisory capacity (i.e., institutional change) needs to improve as the financial sector develops. While the results suggest that the payoff to such institution building may be smaller, at least in terms of improvement on basic indicators of financial development, it would be foolhardy to neglect such issues. Finally, the simple hope here is that by summarizing the Bank’s experience, this paper, though far from the last word on the usefulness of financial sector lending operations, begins to explain what works and why.
31
APPENDIX
Table 6: Variable Description Variable Name Financial Sector Indicators
Definition
Source
Private Credit
Ratio of Domestic Credit from Deposit Money Banks to the private sector to GDP
Domestic credit to the private sector is IFS line 22d. GDP is IFS line 99b.
M2
Ratio of M2 to GDP
M2 is money plus quasi-money, IFS lines 34 + 35.
Quasi-Money
Ratio of Quasi-Money to GDP
Quasi-money is IFS line 35.
Liquid Liabilities
Ratio of Liquid Liabilities to GDP.
Liquid Liabilities is IFS line 55l.
Real Growth
Rate of Growth of real GDP.
Taken from Demirguc-Kunt and Detragriache (DKD) database. IFS where available. Otherwise, WEO.
Inflation
Rate of Change of the GDP deflator.
DKD data. Taken from IFS.
Credit Growth
Rate of growth of real domestic credit to the private sector.
DKD data. IFS line 32d divided by the GDP deflator.
Real Interest Rate
Nominal interest rate minus the contemporaneous rate of inflation.
DKD data. Where available, nominal rate on short-term government securities. Otherwise, a rate charged by the Central Bank to domestic banks such as the discount rate; otherwise, the commercial bank deposit rate.
Income Per Capita
Income per capita in 1985 $US.
Summers-Heston.
Population
Population at the time of the loan, measured in millions.
IFS line 99z.
Effective Development Assistance (EDA)
Calculated in the year of the loan. Measured in 1985 $US.
Burnside-Dollar (1997).
Openness Dummy Variable
Sachs-Warner dummy indicating openness to trade in year of loan.
Sachs-Warner (1995).
Government Surplus/Deficit
Gov’t surplus or deficit (relative to GDP) in year of loan.
IFS line 80zf.
MacroEnvironment/Bank Stability
Aid Variables/Policy Index
32
