MAs tql POLICY RESEARCH WORKING PAPER 1917 Financial Liberalization Banking crises are more likely to occur in liberalized financial and Financial Fragility systems. Financial liberalization should be approached cautiously - Asli Demirgu,c-Kunt even where macroeconomic Enrica Detragiache stabilization has been achieved - in countries where there is little respect for the rule of law, poor contract enforcement, and a high level of corruption. The World Bank Development Research Group and International Monetary Fund Research Department May 1998 POLICY RESEARCH WORKING PAPER 1917 Summary findings Demirgiiu-Kunt and Detragiache study the empirical They examine evidence on the behavior of bank relationship between banking crises and financial franchise values after liberalization. They also examine liberalization using a panel of data for 53 countries for evidence on the relationship between financial 1980-95. liberalization, banking crises, financial development, and They find that banking crises are more likely to occur growth. in liberalized financial systems. But financial The results support the view that, even in the presence liberalization's impact on a fragile banking sector is of macroeconomic stabilization, financial liberalization weaker where the institutional environment is strong - should be approached cautiously in countries where especially where there is respect for the rule of law, a institutions to ensure legal behavior, contract low level of corruption, and good contract enforcement. enforcement, and effective prudential regulation and supervision are not fully developed. This paper - a joint product of the World Bank's Development Research Group and the International Monetary Fund's Research Department - is part of a larger effort to study financial liberalization. Copies of the paper are available free from the World Bank, 1818 H Street NW, Washington, DC 20433. Please contact Paulina Sintim-Aboagye, room MC3-422, telephone 202-473-7656, fax 202-522-1155, Internet address psintimaboagye@worldbank.org. The authors may be contacted at ademirguckunt@worldbank.org or edetragiache@imf.org. May 1998. (48 pages) The Policy Research Working Paper Series dosseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polisbed. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, andf conclusions expressed in this paper are entirely those of the autbors. They do not necessarily represent the viewv of the World Bank, its Executive Directors, or the countries they represent. Produced by the Policy Research Dissemination Center Financial Liberalization and Financial Fragility by Asli Demirguc,-Kunt and Enrica Detragiache* *Development Research Group, The World Bank, and Research Department, International Monetary Fund. T'his paper was prepared for the 1998 World Bank Annual Conference on Development Economics. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the World Bank, the International Monetary Fund, their Executive Directors, or the countries they represent. We wish to thank Jerry Caprio, George Clarke, Stijn Claessens, Phil Keefer, Ross Levine, Miguel Savastano, and Peter Wickham for helpful comments, and Anqing Shi and Thorsten Beck for excellent research assistance. 2 1. Introduction In the last three decades several developed and developing countries have moved towards liberalization of their financial system. Countries eased or lifted bank interest rate ceilings, lowered compulsory reserve requirements and entry barriers, reduced government interference in credit allocation decisions, and privatized many banks and insurance companies. Also, some countries actively promoted the development of local stock markets, and encouraged entry of foreign financial intermediaries. Generally, the trend towards financial liberalization is part of a broader trend towards reduced direct intervention of the state in the economy. In a number of developing countries, however, financial liberalization is also a deliberate attempt to move away from "financial repression" as a policy to fund government fiscal imbalances and subsidize priority sectors, a move strongly advocated by the influential work of McKinnon (1973) and Shaw (1973). According to McKinnon and Shaw, financial repression, by forcing financial institutions to pay low and often negative real interest rates, reduces private financial savings, thereby decreasing the resources available to finance capital accumulation. From this perspective, through financial liberalization developing countries can stimulate domestic savings and growth, and reduce excessive dependence on foreign capital flows.' The work of McKinnon and Shaw also stimulated a fast-growing strand of research that analyzes how linancial development can stimulate economic growth by accelerating ' Empirical research on the relationship between interest rates and savings in countries that liberalize financial markets has generally failed to find clear evidence of a significant and sizable positive correlation. This failure is generally attributed to the strong positive wealth effect of interest rate increases (see Fry, 1997, for a survey). However, empirical studies tend to support the proposition that moderately positive real interest rates have a positive effect on growth (see, among others, Roubini and Sala-i-Martin, 1992 and Bandiera and others, 1997). 3 productivity growth rather than through saving mobilization (see Levine, 1997, for a survey).2 This research includes a number of empirical studies on the relationship between financial development and growth; most studies find various measures of financial development to be positively correlated with both contemporaneous and future growth rates of GDP, suggesting that financial liberalization, by fostering financial development, can increase the long-run growth rate of the economy (King and Levine, 1993). This positive view of financial liberalization, however, is somewhat clouded by the marked increase in financial fragility experienced by both developed and developing countries in the 1980s and 1990s. Particularly, banking sectors around the world were hit by a remarkable number of problems, some of which erupted in full-fledged systemic crises as documented in the extensive studies of Caprio and Kliengebiel (1995) and Lindgren, Garcia, and Saal (1996). In a number of cases, for example in Chile in 1981, banking sector problems emerged shortly after the financial sector was deregulated.3 These experiences suggest that the benefits of financial liberalization may have to be weighed against the cost of increased financial fragility, and some prominent voices in the policy debate have taken the view that 2 Financial markets allow agents to diversify and hedge risk, thereby making high-risk, high- return investments attractive to investors; financial markets also allow the pooling of liquidity risk, as in Diamond and Dybvig (1983); stock markets disseminate information over corporate values (although -- if information revelation is too extensive this may actually make incentives for information collection too low, as argued by Stiglitz, 1985), and allow the market for corporate control to emerge. Financial intermediaries, such as banks, make savings available to entrepreneurs who may lack own resources to finance investment and technology acquisition; they also screen and monitor loan applicants, thereby improving the allocation of resources. By exploiting economies of scale, intermediaries can also make saving mobilization more efficient (Levine, 1997). 3 The Chilean experience, which shares many features with the current East Asian crises, is analyzed in Diaz-Alejandro (1985). Other case studies of banking crises are presented in Sundararajan and Balifio (1991), Drees and Pazarbasioglu (1995), and Sheng (1995) 4 some degree of iEnancial regulation is preferable to premature liberalization in developing countries (Caprio and Summers, 1993, Stiglitz, 1994). While the link between financial development and economic growth has been documented through careful empirical studies, the connection between financial liberalization and financial fragility has not been the object of systematic econometric investigation so far. This paper is an attempt to fill this gap. Building upon our previous research on the determinants of banking crises (Demirguc-Kunt and Detragiache, 1997), we construct a financial liberalization dummy variable for a large number of developed and developing countries during 1980-95. To date liberalization we choose an observable policy change, namely the deregulation of bank interest rates, since case studies indicate that this is often the centerpiece of the overall liberalization process. The data set encompasses countries that liberalized financial markets well before the 1980s as well as countries that liberalized at different dates during the sample period. Using a multivariate logit framework, we test whether banking crises are more likely to occur in liberalized financial systems when other factors that may increase the probability of a crisis are controlled for. The set of control variables includes macroeconomic variables, characteristics of the banking sector, and institutional variables. We also test whether crises are more likely to occur during the transition to a less controlled financial system, or if fragility is a permanent feature of liberalization. Another issue often raised in the debate over financial liberalization is whether the dangers of liberalization are greater in countries where the institutions needed to support the efficient functioning of financial markets are not well developed. Such institutions include effective prudential regulation and supervision of financial intermediaries and of organized 5 security exchanges, and a well-functioning mechanism to enforce contracts and regulations. We investigate this issue by testing whether the relationship between banking crises and liberalization is stronger in countries with weaker institutional environments, as proxied by GDP per capita and various indexes of institutional quality. Finally, we subject our results to a variety of robustness checks. The general result is that banking crises are indeed more likely to occur in countries with a liberalized financial sector, even when other factors (including the real interest rate) are controlled for; furthermore, increased banking sector fragility is not a characteristic of the immediate aftermath of liberalization; rather, it tends to surface a f.ew years after the liberalization process begins. The data also support the conjecture that a weak institutional environment makes liberalization more likely to lead to a banking crisis; specifically, in countries were the rule of law is weak, corruption is widespread, the bureaucracy is inefficient, and contract enforcement mechanisms are ineffective financial liberalization tends to have a particularly large impact on the probability of a banking crisis. Thus, there is clear evidence that financial liberalization has costs in terms of increased financial fragility especially in developing countries, where the institutions needed to support a well-functioning financial system are generally not well-established. To explore a possible channel through which liberalization may affect bank fragility, we use bank level data to examine the correlation between variables proxing bank franchise values and the financial liberalization dummy variable. We find evidence that franchise values tend to be lower when financial markets are liberalized, possibly because bank monopolistic power is eroded. This suggests that theories attributing increased moral hazard to low bank 6 franchise value may help explain why financial liberalization tends to make banking crises more likely (Caprio and Summers, 1993, and Hellman, Murdock and Stiglitz, 1994). These findings raise the question of whether the many benefits of financial liberalization highlighted in the literature may not be offset by the costs in terms of greater vulnerability to banking crises. A rigorous answer to this complex question is beyond the scope of this paper. Nonetheless, using our data set we attempt to throw some light on one particular aspect of the issue, namely the effect of financial liberalization and banking crises on financial development and growth. First, we show that financial development is positively correlated with output growth in our sample, confirming the results of King and Levine (1993). Second, we find that, conditional on no banking crisis, countries/time periods in which financial markets are liberalized have higher financial development that countries/time periods in which markets are controlied. However, countries/time periods with both financial liberalization and a banking crisis have approximately the same level of financial development as countries/time periods with neither, so that the net effect on growth through financial development is not significantly different from zero. To explore this issue further, we split the sample between countries that were financially repressed at the time of liberalization and countries that were financially restrained, where the state of financial repression (restraint) is identified by the presence of negative (positive) interest rates in the period before liberalization. The same tests described above are then performed for the two subsamples. For the restrained group, the results resemble those for the whole sample. In contrast, for the repressed group financial liberalization is accompanied by higher financial development even if a banking crisis also takes place. These findings suggest that financial liberalization is likely to have a positive effect on growth 7 through financial development in countries characterized by financial repression, even if it increases financial fragility. The paper is organized as follows: the next section reviews the mechanisms through which financial deregulation may increase banking sector fragility. Section 3 describes the data set and explains the methodology used in the empirical tests. Section 4 contains the main results, while Section 5 summarizes the outcome of various sensitivity tests. Section 6 discusses the relationship between liberalization and bank franchise value. Section 7 discusses the effects of financial liberalization and banking crises on financial development and growth. Finally, Section 8 concludes. 2. Theory While the focus of this paper is primarily empirical, to put the empirical results in perspective it is usefal to briefly review some of the theoretical reasons why a liberalized banking system may be more vulnerable to crises. In tightly controlled financial systems, bank lending interest rates are usually subject to ceilings, which make it impossible for banks to charge high risk premia. Thus, loans to high risk customers cannot be profitable. As ceilings are lifted during financial liberalization, it becomes possible for banks to finance riskier ventures in return for a higher promised return. Indeed, one of the benefits of financial liberalization is that socially desirable high-risk, high- return projects will find the necessary financing.4 If loan-specific risk is hedged by holding a 4 In some countries, the authorities may explicitly forbid commercial banks from entering certain segments of the credit market that are deemed excessively risky, such as credit to security dealers. Such restrictions are sometimes relaxed as part of the liberalization process. 8 well-diversified portfolio, then financing riskier loans need not increase the risk of bank insolvency nor, at am aggregate level, the risk of a systemic banking crisis. However, portfolios of risky loans, even if they are well-diversified, are typically still vulnerable to the risk of economy-wide adverse shocks (such as a recession). Also, managing the risk of a bank loan portfolio is a complex task, and bank staff trained in a tightly regulated financial system may not have the skills and experience necessary. Evaluation of risky investment projects and monitoring of the borrower during the life of the loan also require skills that may be in short supply in a banking system where lending to the government and collateral-based private lending were the primary activities for many years. Such skills may also be difficult to import from abroad. In a liberalized financial system where interest rates are market-determined, nominal interest rates are likely to be more variable than in a controlled one (although real rates may not be)5; since one of the functions of banks as financial intermediaries is to "transform" short- term liabilities (deposits) into long-term assets (business and consumer loans), banks are exposed to the risk of an increase in nominal interest rates, and may become more vulnerable in an environment where interest rates are more volatile. Also, when liberalization takes place before a well-developed interbank market develops, banks may find it difficult to deal with temporary liquidity shortages, unless the central bank is ready to step in. Liquidity problems at an individual bank may spread to other banks and become a panic when agents are imperfectly informed, as described by Chari and Jagannathan (1988). 5 This problem is exacerbated if financial liberalization takes place before macroeconomic stabilization, as emphasized by McKinnon (1993). 9 Since liberalization increases the opportunity for banks to take on risk, any mechanism that may prevent bank managers from appropriately evaluating the downside risk of their lending decisions becomes especially dangerous. Clearly, limited liability is such a mechanism. The presence of implicit or explicit government guarantees to depositors and/or other bank claimholders makes moral hazard even more dangerous. As emphasized by Caprio and Summers (1993) and Hellmann, Murdock and Stiglitz, (1994), another factor that may contribute to moral hazard is the erosion of bank franchise value due to the removal of ceilings on deposit interest rates and to the reduction of other barriers to entry: as monopolistic profits disappear due to increased bank competition, the cost of losing a banking license when the bank becomes insolvent is reduced, and incentives to choose a riskier loan portfolio increase. Unless these perverse incentives are controlled through effective prudential regulation and supervision, increased risk taking due to moral hazard can become a powerful source of financial fragility, as demonstrated in numerous banking crisis episodes. In many countries financial liberalization was accompanied by the reduction or removal of controls on international capital movements. This process opened the way for the newly liberalized financial intermediaries to take on yet another type of risk, foreign exchange risk, by raising funds in foreign currency on international markets and lending them to local borrowers. Prudential limits on foreign currency exposure were often circumvented in various ways, or currency risk was transformed into credit risk by lending in foreign currency to unhedged domestic borrowers; not surprisingly, currency crises often preceded or accompanied banking crises (Kaminsky and Reinhart, 1996). To summarize, financial liberalization, by giving banks and other financial intermediaries more freedom of action, increases the opportunities to take on risk. This tends 10 to increase financial fragility, but it is not necessarily bad for the economy, as high-risk, high- returns investment projects may dominate low risk-low return ventures. However, because of limited liability compounded with other forms of implicit and explicit guarantees, bankers' appetite for risk is likely to be far greater than what is socially desirable. If prudential regulation and supervision are not effective at controlling bank behavior and at realigning incentives, liberalization may increase financial fragility well above what is socially desirable. Also, to the extent that the skills to screen and monitor risky borrowers and to manage a risky loan portfolio, as well as the skills to perform efficient supervision, can only be acquired gradually and through "learning-by-doing", banks in newly liberalized systems are likely to be more vulnerable. All these considerations suggest that, other things being equal, the risk of bank insolvency and, more generally, of systemic banking crises may be greater in liberalized financial systems. In the next section, we perform an econometric test of various aspects of this linkage. 3. Data and Methodology The Sample To select which countries to include in the panel, we began with all the countries in the International Financial Statistics of the IMF except for centrally planned economies and economies in transition. To obtain a sufficiently large number of time series, we decided to limit our study to the 1980-95 period; as will be shown below, this period includes a substantial number of banking crises and of financial liberalization episodes, so that the data 11 set is sufficiently rich for the purposes of our investigation.6 Some countries had to be eliminated because of missing data, or because we could not find sufficient information on financial liberalization. A few countries were left out because their banking systems were in a state of chronic distress for the entire period under consideration, and it was therefore impossible to pinpoint a specific subperiod as a banking crisis period. Finally, two countries (Argentina, and Bolivia) were excluded because they are outliers with respect to two of the regressors that we use (inflation and the real interest rate).7 This process of elimination left us with 53 countries in the baseline specification (see Table 1). A Multivariate Logit Model To identify the impact of financial liberalization on financial fragility we estimate the probability of a banking crisis using a multivariate logit model, and we test the hypothesis that a dummy variable capturing whether the financial system is liberalized or not significantly increases the probability of a crisis when other factors are controlled for. Accordingly, our dependent variable, the banking crisis dummy, is equal to zero if there is no banking crisis, and it is equal to one if there is a crisis. The probability that a crisis will occur at a particular time in a particular country is hypothesized to be a function of a vector of n variables X(i, t) including the financial liberalization dummy variable and n- I control variables. Let P(i, t) 6 to lack of data, for some countries the observations included in the panel do not cover the entire 1980-95 period. ' If the outliers are introduced in the panel, the results do not change much, except that the estimated coefficient for inflation and the real interest rate become smaller. Peru also had a hyperinflation during the sample period, but the hyperinflation years are excluded from the panel because of missing data. 12 denote a dummy variable that takes the value of one when a banking crisis occurs in country i and time t and a value of zero otherwise. P is a vector of n unknown coefficients and F(j3'X(i, t)) is the cumulative probability distribution function evaluated at P3 'X(i, t). Then, the log- likelihood function of the model is: Ln L = t-t1..T =1 ..n{P(i,t)ln[F(P3'X(i,t))] + (1-P(i,t)) ln[1- F(P'X(i,t))]}. To model the probability distribution function F we use the logistic functional form, thus the estimated coefficients do not indicate the increase in the probability of a crisis given a one-unit increase in the corresponding explanatory variables as in standard linear regression models. Instead, the coefficients capture the effect of a change in an explanatory variable on ln(P(i,t)/(1-P(i,t)). Therefore, while the sign of the coefficient does indicate the direction of the change, the magnitude depends on the slope of the cumulative distribution function at (3 'X(i,t). After the onset of a banking crisis, the behavior of some of the explanatory variables is likely to be affected by the crisis itself; since these feed-back effects would muddle the estimation, years in which banking crises are under way are eliminated from the panel.8 Also, the probability that a crisis occurs in a country that had problems in the past is likely to differ from that of a country where no crisis ever occurred. To take this dependence into account, we include different additional regressors in the estimated equations such as the number of past crises, the duration of the last spell, and the time since the last crisis. 8 See Section 5 on sensitivity analysis for alternative approaches. 13 The Banking Crisis Variable To construct a banking crisis dummy variable, we have identified and dated episodes of banking sector distress during the period 1980-95 using primarily two recent studies, Caprio and Klingebiel (1996), and Lindgren, Garcia, and Saal (1996). For an episode of distress to be classified as a full-fledged crisis, we established -- somewhat arbitrarily -- that at least one of the following conditions must apply: 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 bank runs took place or emergency measures such as deposit freezes, prolonged bank holidays, or generalized deposit guarantees were enacted by the government in response to the crisis. In Section 5 below we explore the sensitivity of the results to the definition of a crisis. To establish the length of the crisis, we relied solely on the dates provided by the case studies. A list of the crisis episodes is presented in Table 1. The Financial Liberalization Variable Empirical studies of financial liberalization have often used the real interest rate as a proxy for financial liberalization (Fry, 1997 and Bandiera and others, 1997). Real interest rates, however, especially when measured ex post, are likely to be affected by a variety of factors that have little to do with changes in the regulatory framework of financial markets. This problem may be limited in a cross-country study, in which interest rates are averaged over long periods of time, but in a panel study like ours with an important time-series dimension proxying financial liberalization with the real interest rate would be potentially 14 misleading. For instance, a positive correlation between real interest rates and the probability of a banking crisis may simply reflect the fact that both variables tend to be high during cyclical economic downturns, while financial liberalization plays no role. To avoid this problem, in this study we construct a financial liberalization variable based on observed policy changes. This strategy, however, is not without its difficulties: first, no available data base records such policy changes, and we had to resort to case studies, IF country reports, and other miscellaneous sources of information. Furthermore, the process of financial liberalization has taken many different forms: some countries eliminated some restrictions before others; some countries, such as Greece or Japan, opted for a very gradual approach, while others like Egypt or Mexico switched regime quite rapidly; also, in some cases there were temporary reversals. After reviewing our information sources, it became clear that in most countries the removal of interest rate controls was the centerpiece of the liberalization process; thus, we chose this policy change as the indicator of financial liberalization. This left us with the choice of what to consider as the beginning date in countries where the process was gradual. Lacking a good theoretical ground for preferring one option over another, we chose the first year in which some interest rates were liberalized as the beginning date because it was easier to identify. Table 1 shows the dates of interest rate liberalization for the countries in our sample. For some countries, two sets of dates are entered because liberalization was temporarily reversed. While 63 percent of our observations are classified as periods of liberalization, 78 percent of banking crises occurred in periods of financial liberalization. The Control Variables 15 The set of control variables is taken from our previous study of banking crises (Demirguc-Kunt and Detragiache, 1997), and it reflects both the theory of the determinants of banking crises and data availability.9 A list of the variables and their sources is in the data appendix. The first group of control variables captures macroeconomic developments that affect bank performance especially through the level of non-performing loans; this group includes the rate of growth of real GDP, the external terms of trade, and the rate of inflation. The real short-term interest rate is also introduced as a control variable because, whether financial markets are liberalized or not, banking sector problems are more likely to emerge if real interest rates are high."0 The second set of control variables includes characteristics of the banking system, such as vulnerability to sudden capital outflows (measured by the ratio of M2 to foreign exchange reserves, as suggested by Calvo, 1996), liquidity (measured by the ratio of bank cash and reserves to bank assets), exposure to the private sector (measured by the ratio of loans to the private sector to total loans), and lagged credit growth. This last variable is introduced because high rates of credit expansion may finance an asset price bubble that, when it bursts, causes a banking crisis. Finally, GDP per-capita is used to control for the level of development of the country. Measures of Institutional Ouality 9 For more details on the relationship between the theory of banking crises and the choice of control variables, see Demirguc-Kunt and Detragiache (1997). 10 To minimize potential endogeneity problems, to measure the real interest rate we use the rate on short-term government paper or a central bank rate, such as the discount rate, and not a bank interest rate. In six countries, however, neither measure was available, and we used the bank deposit rate. 16 Since the quality of institutions may affect the degree to which financial liberalization increases the probability of a banking crisis, in alternative specifications we interact proxies of institutional quality with the liberalization dummy variables, and introduce the interaction term as a separate variable in the regression. We experiment with six alternative measures of institutional quality, GDP-per-capita and five indexes measuring the degree to which the rule of law is respected ("law and order"), the extent of bureaucratic delays, the quality of contract enforcement, the quality of the bureaucracy, and the degree of corruption. These indexes are increasing in the quality of the institutions. 4. Empirical Results Table 2 contains the results of the logit regressions estimating the probability of a banking crisis as a function of the financial liberalization dummy variable and of a set of control variables. The table also presents the usual diagnostic tests to assess the goodness of fit of the model.1" The columns correspond to different definitions of the financial liberalization dummy: in the first column, which is the baseline specification, the dummny is zero for periods in which interest rates are subject to controls, and one when liberalization " The model X2 tests the joint significance of the regressors by comparing the likelihood of the model with that of a model with the intercept only. The AIC criterion is computed as minus the log--likelihood of the model plus the number of parameters being estimated, and it is therefore smaller for better models. This criterion is useful in comparing models with different degrees of freedom. The percentage of crises that are correctly classified and the total percentage of observations that are correctly classified are reported to assess the prediction accuracy of the model. A crisis is deemed to be accurately predicted when the estimated probability exceeds the frequency of crisis observations in the sample (around 5 percent). This criterion tends to downplay the performance of the model, because in a number of episodes the estimated probability of a crisis increases significantly a few years before the episode begins and those observations are considered as incorrectly classified by the criterion (see Demirguc-Kunt and Detragiache, 1997, for some examples). 17 begins. The dummy remains one even if the liberalization is temporarily reversed under the assumption that the effects of liberalization persist even through short reversals. In the second column, the dummy variable is modified by treating periods of reversal as zeroes. The baseline specifications fits the data well, and it classifies correctly 77 percent of the observations. The macroeconomic control variables are all significant at least at the 5 percent level, and have the expected signs: banking crises tend to be associated with low GDP growth, adverse terms of trade changes, high real interest rates, and high inflation. Of the characteristics of the banking sector, vulnerability to a speculative attack against the currency is significant at the 1 percent level, while credit growth lagged by two periods is significant at the 10 percent level. The other variables are not significant. Finally, GDP per capita is significantly negatively correlated to the probability of a banking crisis, suggesting that, other things being equal, developing countries are more vulnerable. More interestingly, the financial liberalization dummy variable is strongly positively correlated with the probability of a banking crisis; as evident from column two, this is true regardless of the treatment of reversals. These results suggest that financial liberalization is a significant factor leading to banking sector fragility; furthermore, this effect is at work even after controlling for variables capturing the state of the macroeconomy (including the level of the risk-free short-term real interest rate). This suggests that, even if it is carried out after macroeconomic stabilization is achieved as recommended by McKinnon (1993), financial liberalization still increases financial fragility. An important question is whether the effect of liberalization on the probability of a crisis tends to be a transitional effect, that is to manifest itself only during the years immediately following the change in policy. To test this hypothesis, in columns 3 to 6 of Table 18 2 we presents estimates of the baseline regression using a liberalization dummy that takes the value of one only in the first 3, 4, 5, and 6 years after liberalization, as opposed to the entire period following the policy change. The redefined dummies are all less significant than the baseline one, and the overall goodness of fit of the model does not improve. In fact, the dummy corresponding to a transition of only 3 years is not significant, and that corresponding to a transition of 4 years is significant only at the 10 percent confidence level. Thus, the effect of financial liberalization on banking fragility does not appear to be characteristic of the immediate aftermath of the change in policy, but rather it manifests itself only over time. This result may also be due to the fact that in a number of countries interest rate deregulation was gradual, and we chose the beginning of deregulation as the date of the policy change. Another interesting question is whether the effects of financial liberalization on financial fragility dliffer in countries that were severely repressed at the time of liberalization relative to countries that were only financially restrained. To explore this issue, we interact the financial liberalization dummy variable with a the average real interest rate in the three years prior to liberalization, and introduce this interaction term as an additional regressor. A negative and significant coefficient for the new variable would suggest that fragility is less severely affected by liberalization in countries that were more financially repressed at the beginning of liberalization. As shown in column seven of Table 2, the estimated coefficient is negative but it is not significantly different from zero. Table 3 provides an illustration of the magnitude of the effect of financial liberalization on financial fragilily according to our empirical model: the third column contains the probability of a crisis as estimated by the baseline model for the 26 crisis episodes that took place in a liberalized regime. For those episodes, the probability of a crisis is then recalculated 19 after setting the liberalization dummy equal to zero (column 4, Table 3). As it is apparent, for all countries the predicted crisis probability falls substantially, and of the 20 episodes that were correctly classified as crises 11 would have switched to non-crisis status in the absence of financial liberalization. Thus, the effect of financial liberalization on the probability of a banking crisis not only is statistically significant, but it is also of a non-trivial magnitude. The Role of the Institutional Environment The theory reviewed in Section 2 suggests that the adverse effect of financial liberalization on banking sector fragility is stronger where the institutions needed for the correct functioning of financial markets are not well-established. To test whether this effect is supported by the data, in Table 4 we add to the baseline regression various alternative variables in the form of interaction terms between the liberalization dummy and proxies of the quality of the institutional environment. Negative and significant coefficients for the interaction variables mean that a better institutional environment tends to weaken the effect of financial liberalization on the probability of a banking crisis. The first proxy for the institutional environment is GDP per-capita, which was also used as a control variable in the baseline regression. The other five proxies are indexes of the degree to which the rule of law is respected ("law and order"), of bureaucratic delay, of the quality of contract enforcement, of the quality of the bureaucracy, and of the degree of corruption."2 All six interaction variables have the expected negative sign, and all except the 12 The indexes measuring "law and order", the quality of the bureaucracy, and corruption range between 0 and 6, while the index of bureaucratic delay and that of contract enforcement range from 0 to 4. 20 index of bureaucratic delay are significant at least at the 10 percent confidence level. The degree of law enforcement, GDP per capita, and corruption have the highest significance levels. Furthermore, the size of the effect is not trivial: for instance, consider the "law and order index". For a country with a score of zero (the lowest score), the net impact of financial liberalization on the crisis probability is 1.770, while for a country with an intermediate score of three the net impact falls to 0.555, and for a country with the maximum score of six the net impact becomes negative, namely financial liberalization tends to make banking crises less likely. Similarly, moving from the worst quality of contract enforcement to the best (a change in the index from zero to four) reduces the impact of liberalization on the crisis probability from 4.732 to 0.980. These results suggest that improving the quality of the institutional environment, especially reducing the amount of corruption and strengthening the rule of law, can curb the tendency of liberalized financial markets to harbor systemic banking crises."3 5. Sensitivity Analysis In this section, we report a number of robustness tests performed on the baseline regression. The first test concerns the treatment of years during which the crisis is under way. Those years are omitted from the baseline specification, an approach that requires accurate information on the year in which a crisis ended. Since the end of a crisis may be difficult to determine in practice, we also estimate the baseline regression using three alternative panels: 13 It is worth noticing that the proxies do not measure the quality of the laws and regulations in a particular country, but rather factors that affect the extent to which laws and regulations are enforced. 21 one that omits all years following a crisis, one that treats all crisis years as ones, and one that treats all crisis years (except the first) as zeroes. The results, reported in Table 5, show that, while there are some changes in the coefficients and standard errors of the control variables, the liberalization dummy remains strongly significant in all specifications. A second set of sensitivity tests (Table 6) uses a more stringent definition of a banking crisis relative to the baseline (ratio of non-performing loans to total loans of at least 15 percent and/or a cost of crisis of at least 3 percent of GDP) as well as a looser definition of crisis (ratio of non-performing loans to total loans of at least 5 percent, and/or cost of the crisis of at least 1 percent of GDP). Nothing much changes concerning the control variables, and the liberalization dummy remains significant, albeit only at the 10 percent confidence level. A third methodological issue, which always arises in panel estimation, is whether to include country (time) fixed effects to allow for the possibility that the dependent variable may vary across countries (years) independently of the explanatory variables included in the regression. In logit estimation, including fixed effects requires excluding from the panel countries (years) in which there was no crisis during the period under consideration (Greene, 1997, p. 899), and hence it excludes a large amount of information. For this reason, we omit fixed effects from the baseline, and estimate a model with fixed effects as part of the sensitivity analysis (Table 7, columns 2 and 3). In the case of both country and time fixed effects, the hypothesis that the coefficients of the country and time dummies are jointly significantly different from zero is rejected, suggesting that there are no fixed effects. In any case, the liberalization dummy is still positively and significantly correlated with the probability of a crisis. 22 Another sensitivity test involves using lagged values of the explanatory variables to reduce the risk that the regressors may not be exogenous determinants of a crisis (Table 7, column 2). The drawback of using lagged values on the right-hand side, of course, is that if the macroeconomic shocks that trigger the crisis work relatively quickly, then their effect would not be evident a year before the crisis erupts. In this regression, most macroeconomic control variables loose significance (except for the real interest rate), while the other controls remain significant; more interestingly, the liberalization dummy continues to be positively and significantly correlated to the probability of a crisis. To sumrnarize, the relationship between financial liberalization and banking sector fragility appears to be robust to various changes in the specification of the logit regression. 6. Financial Liiberalization and Bank Franchise Values The results of the previous sections suggest that liberalization increases the fragility of the financial system. One reason why financial liberalization may lead to increased banking sector fragility is that the removal of interest rate ceilings and/or the reduction of barriers to entry reduces bank franchise values, thus exacerbating moral hazard problems. As discussed in Caprio and Summers (1993) and Hellmann, Murdock, and Stiglitz (1994), interest rate ceilings and entry restrictions create rents that make a banking license more valuable to the holder. It is the risk of losing this valuable license which induces banks to become more stable institutions, with better incentives to monitor the firms they finance and manage the risk of their loan portfolio. Thus, when a reform -- such as financial liberalization -- leads to increased bank competition and lower profits, this erodes franchise values, distorting the risk- taking incentives of the institutions. Unless the reform effort incorporates adequate 23 strengthening of the prudential regulations and supervision to realign incentives, lower franchise values are likely to lead to increased fragility."4 In this section we use bank level data from the BankScope data base of IBCA to investigate whether there is any empirical evidence that bank franchise values fall with financial liberalization. The data set includes bank-level accounting data for 80 countries over the 1988-1995 period. In most countries, the banks covered in the IBCA survey account for at least 90 percent of the banking system. For each bank we construct three profitability measures: net interest margin, after tax-return on assets, and after-tax return on equity. Since none of these measures is a perfect indicator of future profitability, we also look at additional balance sheet ratios which may be associated with a fall in franchise value: a measure of capital adequacy (the book value of equity divided by total assets); a measure of liquidity (the ratio of liquid assets to total assets); and the share of deposits to total liabilities. These ratios are country averages of bank level figures. Both high capitalization and high liquidity should have an adverse effect on bank franchise value, since they decrease the amount of loans that a bank can extend for any given amount of deposits." Also, we examine the behavior of an indicator of market concentration (the ratio of assets of the largest three banks to total banking assets) and an indicator of foreign bank penetration (the proportion of foreign bank assets in total bank assets). More market concentration and less foreign bank penetration 14 Keeley (1990) presents empirical evidence that supports this view. First, he shows that in the 1 970s U.S. thrift institutions began to lose charter value owing to the relaxation of various regulatory entry restrictions and because of technological changes. Second, he shows that banks with larger charter value were less risky, as measured by the risk-premium on uninsured bank CDs. 15 Of course, for given franchise value, large capitalization and large liquidity should create less incentives to take on risk. 24 should be associated with more monopolistic powers for domestic banks, and, therefore, with higher franchise values. Table 8 reports the correlations of these banking variables with the financial liberalization dummy variable. Of course, simple correlations do not imply causality. However, this exercise can at least tell us whether the hypothesis that financial liberalization leads to lower bank franchise values can be dismissed out-of-hand or needs to be taken seriously. The correlations in the first column of the table are calculated using a dummy variable that is equal to one in all periods in which the financial market is liberalized, and zero otherwise; in the remaining colunns, the liberalization dummy is redefined to take a value of one during the transition to a liberalized system (where the transition is taken to last three, four, five, or six years alternatively), and zero otherwise. Thus, by comparing these sets of correlations we can see to what extent the fall in bank franchise value (if there is one) is a temporary or permanent effect of liberalization. The results in the first column indicate that liberalization leads to permanently lower bank profits measured as return on equity, while neither the net interest margin nor the return on assets are significantly correlated with the liberalization dummy. There is also evidence that financial liberalization leads to higher capitalization (which should reduce bank profitability), and lower liquidity (which should have the opposite effect). The extent of deposit mobilization in the long run cloes not appear to change significantly with liberalization. More interestingly, liberalization appears to be permanently associated with a lower bank concentration ratio (albeit significant only at the 13 percent confidence level) and a greater presence of foreign banks. Both of these effects are consistent with lower bank franchise values due to reduced monopolistic profits resulting from greater competition. 25 When we look at the correlations with the transition to a liberalized system, we see that bank margins, profits, capital, liquidity, and deposit mobilization are all higher during the transition period. However, a comparison with the correlations in the first column suggest that most of these effect do not survive in the long-run. During the transition, we do not see a significant coefficient for bank concentration or foreign bank penetration, suggesting that the structure of the banking sector changes only slowly after the liberalization process begins. Despite the cursory nature of the analysis, these results are broadly consistent with the theories that conjecture that liberalization would lead to increased bank fragility due to its negative impact on bank franchise values. The next logical step would be to test whether low bank franchise values are associated to increased bank fragility; unfortunately, we are unable to examine this issue because the number of banking crises that take place during the period covered by the BankScope data set is too small. 7. Financial Liberalization, Banking Crises, Financial Development, and Growth So far, we have established that financial liberalization has a cost in terms of increased financial fragility. Do these results imply that policy-makers should abandon liberalization in favor of increased direct intervention in financial markets? Of course, the answer depends on whether the welfare costs of financial fragility exceed the welfare benefits of liberalization, and on whether governments can be expected to design and implement regulations that correct market failures rather than reinforce them. An answer to these complex questions is well beyond the scope of this paper. Nonetheless, it is possible to use our data set to explore one aspect of this issue, namely whether financial liberalization and banking crises affect economic growth through their effect on financial development. 26 The focus on growth effects through financial development is suggested by the large existing literature documenting how financial development increases long-run growth rates (King and Levine, 1993, Levine, 1997): presumably, one of the main benefits of financial liberalization is that it fosters financial development and, through it, increases long-run growth. Conversely, the disruption caused by a systemic banking crisis is likely to have a direct adverse effect on financial development (at least in the short or medium term) and, through that avenue, have a negative impact on growth. The question addressed in this section is whether these effects can be detected in our data set, and, if so, how the magnitude of the adverse effect of banking crises on financial development compares with that of the positive effect of financial liberalization. To verify whether financial development tends to increase growth in our sample, we estimate growth regression using a panel obtained by splitting the sample period (1980-94) in three subperiods of five years each. The regressors include a set of control variables and four alternative indicators of financial development proposed by King and Levine (1993).16 These indicators are the ratio of liquid liabilities of the financial system to GDP (liquidity), the share of bank credit that goes to the private sector (private credit), the ratio of domestic bank assets to the sum of cenitral bank assets and domestic bank assets (bank assets), and the ratio of central bank domestic assets to GDP (central bank). The first three indicators are increasing with financial development, while the fourth is decreasing. The results of the growth 16 The control variables, also similar to those used by King and Levine (1993), are the logarithm of GDP per-capita and of the secondary school enrollment ratio at the beginning of the subperiod, the share of government consumption expenditure in GDP, the inflation rate, the ratio of the sum of imports and exports to GDP, the real interest rate, and a period dummy variable. 27 regressions are reported in the top panel of Table 9: although the R2 are generally quite low, two out of four indicators have significant coefficients of the expected sign (bank assets and central bank). Thus, there is some evidence that financial development is positively correlated with growth in our panel. To assess the impact of financial liberalization and banking crises on financial development, we then regress each financial development indicator on a constant, the liberalization dummy, and the banking crisis dummy, using the same panel as in the growth regressions."7 The estimated coefficients have a simple interpretation: the constant is the mean level of financial development for observations with neither financial liberalization nor a banking crisis. The coefficient of the liberalization dummy, on the other hand, indicates the difference between the level of financial development in a country/time period with financial liberalization but no banking crisis and the level of financial development in countries/time periods with neither liberalization nor a banking crisis. Similarly, the coefficient of the banking crisis dummy, if significantly less than zero, would indicate that, on average, observations corresponding to banking crises are accompanied by lower financial development, conditional on no liberalization having occurred. Finally, if the difference between the coefficients of the two dummies is significantly greater than zero, then a country/period with both financial 17 The financial liberalization dummy variable takes the value of one if interest rate liberalization began in any of the years of the subperiod or if markets were liberalized in the preceding subperiod; the banking crisis dummy variable takes the value of one if a crisis was on-going in any of the years of the subperiod. The results are robust to redefining the dummy variables by treating a subperiod as a one only if the change in policy (crisis) occurs in the first three years of the subperiod. If the change in policy (crisis) takes place in the last or second- to-last period, then the dummy for the following period is set to one. 28 liberalization and a banking crisis has, on average, a higher level of financial development than one with no crisis and controlled financial markets. Table 9 contains estimation results. The coefficient of the liberalization dummy is positive and significant in all the specifications, while the banking crisis dummy has a negative coefficient which is significant in all specifications except one. Thus, both financial liberalization and the occurrence of banking crises appear to significantly affect financial development. Turning now to the difference between the two coefficients, it appears that countries/ periods with both banking crises and financial liberalization have greater financial development but only if financial development is measured by private credit or by bank assets. For liquidity and central bank, the difference in the coefficients is not significantly different from zero. Private credit, however, does not have a significant impact on growth in our panel, as shown in the first row of Table 9. Only in one regression, the one using bank assets as an indicator of financial development, are both the net effect of the dummies on financial development and the effect of financial development on growth significant. Thus, these tests do not show clear evidence that choosing financial liberalization at the cost of experiencing a banking crisis pays off in terms of higher growth through higher financial development, or vice versa, at least in a medium term time frame. 18 Additional insights on this issue can be obtained by splitting the sample between countries that were repressed at the time of financial liberalization and countries that were only restrained. Countries are classified as repressed if they had a negative interest rate (on 18 When we estimate a growth regression including the banking crisis dummy and the financial liberalization durmmy, however, the coefficients are not significant, suggesting that the dummies have a negligible direct impact on growth. 29 average) during the three years preceding financial liberalization, and they are classified as restrained if they liberalized from a position of positive interest rates."9 Countries that maintained controlled financial markets during the entire sample period are omitted from this panel, since they cannot be classified in either group.20 When the sample is split in this fashion, for the restrained countries the results are quite similar to those for the sample as a whole (bank assets and central bank are significant), while for the repressed group, also private credit is significant (Tables 10 and 11). More interestingly, when we regress the financial development indicators on the liberalization dummy and on the crisis dummy, banking crises do not seem to lead to significantly lower financial development in repressed countries (where financial development is in any case lower than in the restrained group), while they do so in restrained countries, at least in two out of four regressions (Tables 10 and 11). In contrast, the positive impact of financial liberalization is present in both groups of countries. Thus, based on these estimated coefficients, a country that liberalized from a position of financial restraint and experienced a banking crisis has a level of financial development similar to a country that did not liberalize and escaped banking sector problems. In contrast, for countries that liberalized from a position of financial repression, the level of financial development is higher with liberalization even if the country experiences a banking crisis. Based on the coefficient estimated in the 19 Roubini and Sala-i-Martin (1992) find the negative growth effects of financial repression to be stronger in financially repressed countries than in financially restrained countries. 20 The panel includes countries that liberalized well before the beginning of the sample period. It may be argued that whether those countries were financially repressed or restrained at the time of liberalization should not affect their economic performance in 1980-94. As a robustness test, we repeated the tests described below dropping those countries from the panel. The basic results remain unchanged. 30 growth regression, the net positive effect on growth for this group of countries is of the order of 7/10 to 9/10 of a percentage point per-year (Table 11). To summarize, this section has shown some empirical evidence supporting the hypothesis that financial liberalization is associated with higher financial development and, through it, with higher output growth, while banking crises have the opposite effects. For countries that liberalize from a position of financial restraint, the gains from liberalization in terms of financial development are comparable to the costs of having a banking crisis, while in the case of financially repressed countries the gains from financial liberalization are larger. Although these results are suggestive, it is important to stress that they are tentative, and that the methodology used in deriving them leaves a lot to be desired: first, growth regressions are intended to study the determinants of long-run growth rates, which are usually taken to be averages of many years of data. To have enough data points, here we are forced to use five-year averages, which may not really capture the long-run rate of economic growth. In fact, the low R2 in the growth regressions may indicate that cyclical and other factors not controlled for are important in explaining the dependent variable. If there are omitted variables, and these variables are correlated with the development indicators, the estimates of the coefficient of the financial development indicator would be biased. This criticism, however, concerns only the growth regressions, where the linkage between financial development and growth is established for our panel. Since this linkage has already been documented in other, more rigorous studies, we are not excessively worried by this shortcoming. The more interesting part of the exercise is the test of the relationship between financial development, financial liberalization, and banking crises. Here our tests, besides 31 being confined to a short and medium-term horizon, are limited because they are basically differences of means, and ignore that factors other than liberalization and banking crises affect financial development. Also, the effect of financial liberalization on the probability of a banking crisis is not explicitly incorporated in the analysis. We leave more sophisticated explorations of this important issue to future research. 8. Concluding Remarks Increased liberalization of financial markets in general and of the banking sector in particular have been major items in the economic policy agenda of many countries during the last 30 years. In this time period, the frequency of systemic banking problems has increased markedly all over the world, raising the issue of whether greater fragility may be a consequence of liberalization. In this paper we have attempted to shed light on the issue by studying a large panel data set, covering 53 developed and developing economies during the period 1980-95. The panel includes countries that liberalized their financial markets several years before 1980, and others that liberalized at different dates over the sample period; also, countries that experienced one or more banking crises are represented along with countries that had a stable banking system throughout the period. Thus, the data set covers a large variety of experiences, from which it would be impossible to draw lessons without the help of econometric techniques. The first result that emerges from the analysis is that financial fragility is affected by a multiplicity of factors, including adverse macroeconomic developments, bad macroeconomic policies, and vulnerability to balance-of-payments crises. When these factors are controlled for, financial liberalization exerts an independent negative effect on the stability of the banking 32 sector, and the magnitude of the effect is not trivial. However, a strong institutional environment, characterized by effective law enforcement, an efficient bureaucracy, and little corruption, can curb the adverse effects of liberalization on the financial system. These findings suggests that institutional development needs to be emphasized early in the liberalization process; in countries where the institutional environment is weak, achieving macroeconomic stabilization before or during liberalization would certainly bring an important independent source of financial instability under control. However, even in an otherwise well- functioning economy weaknesses in the institutions and in the regulatory framework necessary for financial markets to operate efficiently may fail to check perverse behavior on the part of financial intermediaries, creating the foundations for systemic financial sector problems. Unfortunately, strong institutions cannot be created overnight, not even by the most reform- oriented government; thus, the path to financial liberalization should be a gradual one, in which the benefits of each further step towards liberalization are carefully weighed against the risks. Another implication of our findings is that more research effort should be focussed on the design and implementation of prudential regulations and supervision especially in developing countries. Support for a gradual approach towards financial liberalization also comes from our findings about the effects of liberalization and fragility on financial development and, through it, on growth: while for countries that were initially in a state of financial repression the positive effect of liberalization on financial development appears to be stronger than the negative effect of a banking crisis, this is not the case for countries that liberalized from a situation of financial restraint, where the two effects roughly offset each other. One way of reading these findings is that, once financial sector reforms are carried out to secure positive 33 interest rates, steps towards further liberalization may not necessary yields gains that offset the negative impact of increased fragility. 34 References Bandiera, O., Caprio, G., Honohan, P. and Schiantarelli, F., 1997, "Does Financial Reform Raise or Reduce Saving?", unpublished manuscript. Calvo, G. A., 1996, "Capital Flows and Macroeconomic Management: Tequila Lessons", International Journal of Finance & Economics, 1, 207-224. Caprio, G., and Klingebiel, D., 1996, "Dealing with Bank Insolvencies: Cross Country Experience", Washington, D.C., The World Bank. Caprio, G., and L. Summers, 1993, "Finance and its Reform: Beyond Laissez-Faire", Policy Research Working Paper No. 1171, The World Bank. Chari, V.V., and Jagannathan, R., 1988, "Banking Panics, Information, and Rational Expectations Equilibrium", Journal of Finance, 43: 749-761. Demirguic-Kunt, A., and Detragiache, E., 1997, The Determinants of Banking Crises: Evidence from Industrial and Developing Countries, Policy Research Working Paper No. 1828, The World Bank, also forthcoming, IMF Staff Papers, March 1998. Diamond, D., and Dybvig, P., 1983, "Bank Runs, Deposit Insurance, and Liquidity", Journal of Political Economy, 91, 401-419. Diaz-Alejandro, C., 1985, "Good-Bye Financial Repression, Hello Financial Crash", Journal ofDevelopment Economics, 19. Drees, B., and Pazarba§ioglu, C., 1995, "The Nordic Banking Crises: Pitfalls in Financial Liberalization?", IMF Working Paper No. 61. Fry, M. J., 1997, "In Favor of Financial Liberalization", Economic Journal, 107: 754-770. Hellmann, T., Murdock, K., and Stiglitz, J.E., 1994, "Addressing Moral Hazard in Banking: Deposit R.ate Controls vs. Capital Requirements", unpublished manuscript. Kaminsky, G., and Reinhart, C.M., 1996, "The Twin Crises: The Causes of Banking and Balance of Payments Problems", Federal Reserve Board, Washington, DC. Keeley, M. C., 1990, "Deposit Insurance, Risk, and Market Power", American Economic Review, 80, 1183-1200. King, R. G. and Levine, R., 1993, "Finance and Growth: Schumpeter may be Right", Quarterly Journal of Economics, 108: 717-737. 35 Levine, R., 1997, "Financial Development and Growth: Views and Agenda', Journal of Economic Literature, 35: 688-726. Lindgren, C.J., Garcia, G., and M. Saal, 1996, Bank Soundness andMacroeconomic Policy, IMF, Washington DC. Mc Kinnon, R. I., 1973, Money and Capital in Economic Development, Washington, DC: Brookings Institution. Roubini, N., and Sala-i-Martin, X., 1992, "Financial Repression and Economic Growth", Journal of Development Economics, 39: 5-30. Shaw, E., 1973, Financial Deepening in Economic Development, New York: Oxford University Press. Sheng, A., 1995, Bank restructuring, Washington DC, The World Bank. Stiglitz, J. E., 1985, "Credit Markets and the Control of Capital", Journal of Money, Credit, andBanking, 17: 133-152. Stiglitz, J. E., 1994, "The Role of the State in Financial Markets", in M. Bruno and B. Pleskovic (Eds.), Proceedings of the World BankAnnual Conference on Development Economics, Washington, DC: World Bank. Sundararajan, V., and Balifno, T. (Eds.), 1991, Banking Crises: Cases and Issues, Washington: International Monetary Fund. 36 Table 1 Interest Rate Liberalization and Banking Crisis Dates COUNTRY PERIODS OF INTEREST RATE BANKING CRisis DATE LIBERALIZATION DuRiNG 1980-95 Austria 1980-95 Australia 1981-95 Belgium 1986-95 Canada 1980-95 Switzerland 1989-95 Chile 1980-95 1981-87 Colombia 1980-95 1982-85 Denrmark 1981-95 Ecuador 1986-87, 1992-95 Egypt 1991-95 Finland 1986-95 1991-94 France 1980-95 Gernany 1980-95 Greece 1980-95 Guatenmala 1989-95 Guyana, 1991-95 1993-95 Honduras 1990-95 Indonesia 1983-95 1992-94 India 1991-95 1991-94 Ireland 1985-95 Israel 1990-95 1983-84 Italy 1980-95 1990-94 Jamaica 1991-95 Jordan 1988-95 1989-90 Japan 1985-95 1992-94 Kenya 1991-95 1993 37 Korea 1984-88, 1991-95 Sri Lanka 1980-95 1989-93 Mexico 1989-95 1982, 1994-95 Malaysia 1980-95 1985-88 Mali 1987-89 Nigeria 1990-93 1991-95 Netherlands 1980-95 Norway 1985-1995 1987-93 New Zealand 1980,1984-95 Papua New Guinea 1980-95 1989-95 Peru 1980-84, 1990-95 1983-90 Philippines 1981-95 1981-87 Portugal 1984-95 1986-89 Paraguay 1990-95 1995 El Salvador 1991-95 1989 Tanzania 1993-95 1988-95 Syria Sweden 1980-95 1990-93 Togo 1993-95 Thailand 1989- 95 1983-87 Turkey* 1980-82, 1984-95 1991, 1994-95 Uganda* 1991-95 Uruguay 1980-95 1981-85 US 1980-95 1980-92 Venezuela 1989-95 1993-95 Zaire* 1980-95 Zambia* 1992-95 * This country had additional banking crises during 1980-95, but these crises are not included in the panel because of missing data. 38 Table 2. Financial Liberalization and Banking Crises (1) (2) (3) (4) (5) (6) (7) Control Variables: GROWTH -.168*** -.164*** -.163*** -.162*** -.167*** -.168*** -.191*** (.040) (.039) (.039) (.039) (.039) (.039) (.044) TOTCHANGE -.052** -.050** -.043** -.043** -.049** -.049** -.050** (.023) (.022) (.020) (.020) (.022) (.022) (.025) REAL INTEREST .047*** .046*** .048*** .050*** .051*** .050*$* .044*** (.015) (.015) (.015) (.015) (.015) (.015) (.015) INFLATION .027*** .027*** .027*** .027*** .027*** .028*** .022** (.009) (.008) (.009) (.009) (.009) (.009) (.011) M2/RESERVES .022*** .021*** .016*** .017*** .017*** .017** .024*** (.007) (.007) (.007) (.007) (.007) (.007) (.007) PRIVATE/GDP .007 .007 .006 .006 .006 .006 .013 (.012) (.013) (.012) (.012) (.012) (.012) (.013) CASH/BANK -.018 -.019 -.020 -.020 -.021 -.020 -.022 (.014) (.014) (.014) (.014) (.014) (.014) (.016) CREDIT GROt2 .023* .022* .023 * .023* .023* .023* .013 (.013) (.013) (.013) (.013) (.013) (.013) (.014) GDP/CAP -.108** -.103** -.078* -.077* -.079* -.080* -.101* (.051) (.051) (.051) (.051) (.051) (.051) (.057) Financial Liberalization: FIN. LIB. 1.761*** 1.449** (.634) (.712) FIN. LIB (R) 1.423*** (.589) FIN. LIB. (3) .488 (A34) FIN. LI. (4) .639* (.415) FIN. LIB. (5) .892** (.415) FIN. LIB. (6) .811** (.418) FIN. LIB. x INITIAL -.026 INT. (.020) Past Crisis: DURATIONof .108** .115** .139*** .147*** .139*** .140*** .130** last period (.051) (.051) (.051) (.050) (.050) (.051) (.062) No. of Crisis 32 32 31 32 32 32 26 No. of Obs. 639 639 602 639 632 632 525 % correct 77 77 77 76 76 77 78 % crisis correct 63 63 68 59 59 56 62 model X2 61.42*** 58.79*** 52.52*** 54.49*** 57.32*** 56.48*** 55.95*** AIC 217 219 218 224 219 221 177 *, **and *** indicate significance levels of 10, 5 and 1 percent respectively. 39 Table 3. Impact of Interest Liberalization on Crisis Probability Countryt Bank Crisis Probability of Crisis Predicted Probability of Crisis had the Start Date Predicted by Baseline at Country not Liberalized on or prior to Crisis Datel the Bank Crisis Date Chile 1981 .174 .035 Colombia 1982 .047 .008 Finland 1991 .119 .023 Guyana 1993 .028 .005 India 1991 .221 .047 Indonesia 1992 .306 .071 Italy 1990 .028 .005 Japan 1992 .071 .012 Jordan 1989 .786 .387 Kenya 1993 .412 .108 Malaysia 1985 .170 .034 Mexico 1994 .207 .043 Nigeria 1991 .044 .008 Norway 1987 .031 .006 Papua N.Guinea 1989 .259 .057 Paraguay 1995 .114 .022 Peru 1983 .347 .084 Philippines 1981 .052 .009 Portugal 1986 .133 .026 Sri Lanka 1989 .104 .019 Sweden 1990 .033 .006 Turkey 1991 .221 .047 1994 .443 .121 Uruguay 1981 .358 .087 United States 1980 .459 .126 Venezuela 1993 .424 .113 t Probabilities for Mali, Mexico 1982, El Salvador, Israel,Tanzania, and Thailand are not reported since these countries had not liberalized prior to the banking crisis. : Countries in the baseline specification are classified as crisis cases if the predicted probability is greater than .05, which is equal to the ratio of number of crisis observations to total number of observations. 40 Table 4. Financial Liberalization and Banking Crises -- Institutional Environment (1) (2) (3) (4) (5) (6) Control Variables: GROWTH -.171*** -.214*** -.233*** -.238*** -.219*** -.223*** (.040) (.054) (.072) (.070) (.054) (.054) TOT CHANGE -.054** -.040* -.056* -.060* -.042* -.040* (.023) (.027) (.034) (.033) (.026) (.026) REAL INTEREST .045*** .052** .053** .050*** .049** .049** (.015) (.024) (.021) (.021) (.024) (.023) INFLATION .026*** .024* .022* .020* .021 .022 (.009) (.015) (.013) (.013) (.015) (.015) M2/RESERVES .022*** .018* .025** .025* * .022** .019** (.007) (.010) (.012) (.012) (.010) (.010) PRIVATE/GDP .002 -.003 .005 .006 -.003 -.003 (.011) (.011) (.012) (.012) (.011) (.011) CASH/BANK -.018 -.030 .020 .015 -.030 -.027 (.014) (.023) (.026) (.026) (.022) (.021) CREDIT GROt-, .024* .013 .045*** .043*** .011 .009 (.013) (.018) (.017) (.016) (.018) (.018) Financial Liberalization and Institutions: FIN. LIB. 1.956*** 1.770* 4.053*** 4.732*** 1.803* 1.823* (.657) (.986) (1.542) (1.557) (1.082) (1.030) FIN. LIB. x -.089*(6') GDP/CAP (.048) FIN. LIB. x LAW & -.405** ORDER (.205) FIN. LIB. x DELAY -.727 (.678) FIN. LIB. x CONT. -.938* ENFORCEMENT (.574) FIN. LIB. x BUR. -.380* QUALITY (.223) FIN. LIB. x 403*(6/) CORRUPTION (.2 15) Past Crisis: DURATION of .112** .181** .028 .031 .171** .156** last period (.051) (.081) (.067) (.067) (.079) (.078) No. of Crisis 32 22 21 21 22 22 No. of Obs. 639 425 406 406 418 418 % correct 77 72 78 80 72 73 % crisis correct 63 55 67 71 59 59 model X2 60.08*** 35.69*** 49.65*** 51.34*** 34.16*** 34.77*** AIC 218 161 140 138 162 162 *, **and * indicate significance levels of 10, 5 and 1 percent respectively. 41 Table 5. Sensitivity Analysis: Different Treatment of Crisis Years Baseline No years after Years of Years of first crisis crisis=l crisis=0 Control Variables: GROWTH -.168*** -.136*** -.067*** -.137*** (.040) (.041) (.023) (.036) TOTCHANGE -.052** -.043** -.014 -.047** (.023) (.023) (.014) (.021) RL. INTEREST .047*** .046*** .016*** .013** (.015) (.017) (.007) (.006) INFLATION .027*** .025*** .016*** .004 (.009) (.010) (.005) (.005) M2/RESERVES .022*** .017*** .017*** .008* (.007) (.007) (.004) (.005) PRIVATE/GDP .007 .015 .011** -.003 (.012) (.012) (.005) (.009) CASH/BANK -.018 -.007 -.016** -.005 (.014) (.014) (.008) (.012) CREDIT GRO,2 .023* .018 .002 .019* (.013) (.014) (.008) (.012) GDP/CAP -.108** -.134*** -.091*** -.080** (.051) (.052) (.022) (.041) Financial Liberalization: FIN. LIB. 1.761*** 2.154*** 2.187*** 1.178** (.634) (.618) (.343) (.557) Past Crisis: DURATION of .108** -.133*** .144*** lastperiod (.051) (.030) (.049) No. of Crisis 32 29 128 32 No. of Obs. 639 531 735 735 % correct 77 77 72 73 % crisis correct 63 66 69 59 model X2 61.42*** 50.50*** 141.82*** 42.67*** AIC 217 197 562 245 *, **and *** indicate significance levels of 10, 5 and 1 percent respectively. 42 Table 6. Sensitivity Analysis: Different Crisis Definitions Baseline More Stringent Less Stringent Definition Definition Control Variables: GROWTH -.168*** -.126*** -.160*** (.040) (.044) (.039) TOT CHANGE -.052** -.054** -.045** (.023) (.023) (.022) RL. INTEREST .047*** .067*** .044*** (.015) (.023) (.014) INFLATION .027*** .032*** .025*** (.009) (.012) (.009) M2/RESERVES .022*** .009 .020*** (.007) (.007) (.007) PRIVATE/GDP .007 .003 .001 (.012) (.017) (.011) CASH/BANK -.018 -.017 -.021 (.014) (.018) (.015) CREDIT GRO,2 .023* .022 .027** (.013) (.015) (.013) GDP/CAP -.108** -.150** -.069* (.051) (.071) (.044) Financial Liberalization: FIN. LIB. 1.761*** 1.098* 1.732*** (.634) (.692) (.607) Past Crisis: DURATION of .108** .106* .109** last period (.051) (.059) (.047) No. of Crisis 32 24 36 No. of Obs. 639 639 623 % correct 77 78 74 % crisis correct 63 58 61 model x2 61.42*** 52.88*** 59.73*** AIC 217 176 239 *, **and *** indicate significance levels of 10, 5 and I percent respectively. 43 Table 7. Sensitivity Analysis: Country and Time Fixed Effects, and Lagged Explanatory Variables' Baseline Country Fixed Effects Time Fixed Lagged Effects Explanatory Variables Control Variables: GROWTH -.168*** -.246*** -.177*** .057 (.040) (.060) (.047) (.044) TOT CHANGE -.052** -.054* -.044* -.004 (.023) (.031) (.026) (.022) RL. INTEREST .047*** .122*** .049*** .007* (.015) (.042) (.015) (.004) INFLATION .027*** .064*** .028*** .004 (.009) (.027) (.009) (.003) M2/RESERVES .022*** .026** .024*** .007** (.007) (.012) (.007) (.003) PRIVATE/GDP .007 -.011 .012 -.001 (.012) (.039) (.014) (.012) CASH/BANK -.018 .002 -.016 -.002 (.014) (.024) (.015) (.009) CREDIT GRO .2 .023* .032* .024* .019* (.013) (.021) (.014) (.012) GDP/CAP -.108** -.402 -.138*** -.077* (.051) (.423) (.056) (.046) Financial Liberalization: FIN. LIB. 1.761*** 1.962* 2.077*** 1.113** (.634) (1.196) (.702) (.555) Past Crisis: DURATION of .108** .501 .229** .073 last period (.051) (.132) (.113) (.049) No. of Crisis 32 32 32 31 No. of Obs. 639 333 565 605 % correct 77 75 76 67 % crisis correct 63 44 53 58 model X2 61.42*** 81.85*** 66.39*** 22.44*** AIC 217 210 235 246 *, "and *** indicate significance levels of 10, 5 and 1 percent respectively. 1 The coefficients of the country and time dummy variables are not reported. 44 Table 8. Correlation Coefficient between Financial Liberalization and Bank Franchise Value Indicators' FIN. L1B. FIN. LDB (3) FIN. LDB (4) FIN. LIB (5) FIN. LIB (6) net interest .024 .175*** .150*** .157*** .158*** margin .653 .001 .006 .004 .004 return on assets .088 .202*** .168*** .167*** .132** .139 .001 .006 .006 .030 return on equity -.118** .120** .097* .077 .068 .028 .029 .076 .158 .212 capital .20'7*** .058 .119** .116** .121** .000 .289 .028 .032 .026 liquidity -.55*** .154*** .184*** .152*** .168*** .004 .005 .001 .005 .002 deposit share -.033 .069 .161*** .170*** .121** .541 .210 .003 .002 .026 market -.087 .092 .053 .042 .035 concentration .137 .121 .377 .476 .552 share of foreign .109** -.012 .015 .020 .031 banks .06.2 .840 .799 .734 .606 t Pearson correlation coefficients are reported. P-values are given in italics. *, ** and *** indicate significance levels of 10, 5 and 1 percent respectively. Net interest margin is given by interest income minus interest expenses divided by total assets. Return on assets given by net profits divided by total assets. Return on equity is given by net profits divided by book value of equity. Capital is the book value of equity divided by total assets. Liquidity is the ratio of liquid assets to total assets. Deposit share is the share of deposits (customer and short term funding) in total liabilities. Market concentration is measured as the ratio of assets in the largest three banks to total bank assets. The share of foreign banks is the ratio of foreign bank assets to total bank assets. All bank level variables are average ratios for all banks in the BankScope data base in a country in a given year. 45 Table 9. Growth, Financial Development, Financial Liberalization, and Banking Crises - Full Sample Liquidity Private Bank Central bank credit assets Growth regressions' financial development -.407 .243 3.450** -2.010* (.765) (1.007) (1.633) (1.166) AdjustedR2 .11 .11 .14 .11 No of observation 136 136 137 134 Financial development regressions2 constant .466*** .252*** .682*** .187*** (.044) (.032) (.028) (.048) financial liberalization dummy .108** .202*** .152*** -.103** (.050) (.044) (.034) (.043) banking crisis -.104* -.085* -.066* .040 dummy (.055) (.047) (.037) (.039) Adjusted R2 .03 .09 .10 .03 No. of observations 156 156 159 153 aggregate impact on financial .004 .117** .086* -.063 development F=.00 F=4.62 F=3.32 F=.88 coefficient in growth regression -.407 .243 3.450** -2.010* impact on growth .002 .028 .297 .127 1 The dependent variable is the real per capita GDP growth rate. Each growth regression includes an alternative financial development indicator, as specified in the column header. Liquidity is ratio of liquid liabilities of the financial sysytem to GDP. Private credit is the ratio of bank credit to private sector to GDP. Bank assets is ratio of deposit money bank domestic assets to deposit money banks domestic assets plus central bank domestic assets. Central bank is the ratio of central bank domestic assets to GDP. Besides the financial development indicators, the regressions include the logarithm of initial real per capita GDP, the logarithm of initial secondary school enrollment, the ratio of government consumption expenditure to GDP, inflation rate, ratio of exports plus imports to GDP, the real interest rate, dummy variables for 5-year periods. White's heteroscedasticity-consistent standard errors are given in parantheses. *, ** and *** indicate significance levels of 10, 5 and 1 percent respectively. 2 The dependent variable is the financial development indicator listed in the column header. Regressions include a constant. 46 Table 10. Growth, Financial Development, Financial Liberalization, and Banking Crises - Financially Restrained Countries Liquidity Private Bank Central credit assets bank Growth regressions' financial development -.735 -.775 12.418*** -13.417* (.841) (1.007) (4.757) (7.362) Adjusted R2 .09 .09 .25 .13 No of observation 64 64 64 62 Financial development regressions2 constant .518*** .363*** .788*** .094*** (.075) (.059) (.030) (.012) financial liberalization dummy .157* .173** .112*** -.038*** (.084) (.074) (.033) (.014) banking crisis -.019 -.082 -.074* .038** dummy (.111) (.082) (.040) (.019) Adjusted R2 .01 .04 .14 .10 No. of observations 72 72 72 69 aggregate impact on financial .138 .091 .038 .000 development F=.86 F=.75 F=.51 F=.00 coefficient in growth regression -.735 -.775 12.418*** -13.417* impact on growth -.101 -.071 .472 .000 1 The dependent variable is the real per capita GDP growth rate. Each growth regression includes an alternative financial development indicator, as specified in the column header. Liquidity is ratio of liquid liabilities of the financial sysytem to GDP. Private credit is the ratio of bank credit to private sector to GDP. Bank assets is ratio of deposit money bank domestic assets to deposit money banks domestic assets plus central bank domestic assets. Central bank is the ratio of central bank domestic assets to GDP. Besides the financial development indicators, the regressions include the logarithm of initial real per capita GDP, the logarithm of initial secondary school enrollment, the ratio of government consumption expenditure to GDP, inflation rate, ratio of exports plus imports to GDP, the real interest rate, dummy variables for 5-year periods. White's heteroscedasticity-consistent standard errors are given in parantheses. *, ** and *** indicate significance levels of 10, 5 and 1 percent respectively. 2 The dependent variable is the financial development indicator listed in the column header. Regressions include a constant. 47 Table 11. Growth, Financial Development, Financial Liberalization, and Banking Crises - Financially Repressed Countries Liquidity Private Bank Central credit assets bank Growth regressions' financial development .421 5.189** 4.466** -2.865** (2.217) (2.266) (2.018) (1.453) Adjusted R2 .04 .12 .10 .08 No of observation 57 57 58 57 Financial development regressions2 constant .411*** .178*** .607*** .267*** (.065) (.024) (.048) (.100) financial liberalization dummy .060 .163*** .183*** -.162* (.073) (.048) (.058) (.097) banking crisis -.085 -.022 -.009 .026 duummy (.058) (.061) (.060) (.079) Adjusted R2 .00 .08 .11 .02 No. of observations 64 64 66 64 aggregate impact on financial -.025 .141*** .174** -.136 development F=.09 F=6.17 F=5.68 F=.97 coefficient in growth regression .421 5.189** 4.466*** -2.865** impact on growth -.011 .732 .777 .390 1 The dependent variable is the real per capita GDP growth rate. Each growth regression includes an alternative financial development indicator, as specified in the column header. Liquidity is ratio of liquid liabilities of the financial sysytem to GDP. Private credit is the ratio of bank credit to private sector to GDP. Bank assets is ratio of deposit money bank domestic assets to deposit money banks domestic assets plus central bank domestic assets.Central bank is the ratio of central bank domestic assets to GDP. Besides the financial development indicators, the regressions include the logarithm of initial real per capita GDP, the logarithm of initial secondary school enrollment, the ratio of government consumption expenditure to GDP, inflation rate, ratio of exports plus imports to GDP, the real interest rate, dunimy variables for 5-year periods. White's heteroscedasticity-consistent standard errors are given in parantheses. *, ** and *** indicate significance levels of 10, 5 and I percent respectively. 2 The dependent variable is the financial development indicator listed in the column header. Regressions include a constant. 48 APPENDIX Definitions and Data Sources for Variables Included in the Logit Regressions Variable Name Defnition Source Growth Rate of growth of real GDP IFS where available. Otherwise, WEO. Tot change Change in the terms of trade WEO Real interest rate Nominal interest rate minus 1FS. Where available, nominal rate on the contemporaneous rate short-term government securities. of inflation Otherwise, a rate charged by the Central Bank to domestic banks such as the discount rate; otherwise, the commercial bank deposit interest rate hiflation Rate of change of the GDP IFS deflator M2Jreserves Ratio of M2 to foreign M2 is money plus quasi-money (lines 34 + exchange reserves of the 35 from the IFS) converted into US$. Central Bank Reserves are line ldd of the IFS. Private/GDP Ratio of domestic credit to Domestic credit to the private sector is line the private sector to GDP 32d from the IFS. Cash/bank Ratio of bank liquid Bank reserves are line 20 of the IFS. Bank reserves to bank assets assets are lines 21 + lines 22a to 22f of the IFS. Credit growth Rate of growth of real IFS line 32d divided by the GDP deflator. domestic credit to private sector GDP/CAP Real GDP per capita GDP data are from the World Bank National Accounts data base. Population is IFS line 99z. Law and order Index ranging from 0 to 6 hiternational Country Risk Guide (ICRG), published by Political Risk Service, Syracuse, NY. Bureaucratic delay Index ranging from 0 to 4 Business Environmental Risk Intelligence (BERI), Washington DC Contract enforcement Index ranging from 0 to 4 BERI Quality of bureaucracy Index ranging from 0 to 6 ICRG Corruption Index ranging from 0 to 6 ICRO Policy Research Working Paper Series Contact Title Author Date for paper WPS1897 Development of Natural Gas and Andrej Juris March 1998 S. Vivas Pipeline Capacity Markets in the 82809 United States WPS1898 Does Membership in a Regional Faezeh Foroutan March 1998 L. Tabada Preferential Trade Arrangement Make 36896 a Country More or Less Protectionist? WPS1899 Determinants of Emerging Market Hong G. Min March 1998 E. Oh Bond Spread: Do Economic 33410 Fundamentals Matter? WPS1900 Determinants of Commercial Asli Demirg0,-Kunt March 1998 P. Sintim-Aboagye Bank Interest Margins and Harry Huizinga 37656 Profitability: Some International Evidence WPS1901 Reaching Poor Areas in a Federal Martin Ravallion March 1998 P. Sader System 33902 WPS1902 When Economric Reform is Faster Martin Ravallion March 1998 P. Sader than Statistical Reform: Measuring Shaohua Chen 33902 and Explaining Inequality in Rural China WPS1903 Taxing Capital Income in Hungary Jean-Jacques Dethier March 1998 J. Smith and the European Union Christoph John 87215 WPS1904 Ecuador's Rural Nonfarm Sector Peter Lanjouw March 1998 P. Lanjouw as a Route Out of Poverty 34529 WPS1905 Child Labor in C6te d'lvoire: Christiaan Grootaert March 1998 G. Ochieng Incidence and Determinants 31123 WPS1906 Developing Countries' Participation Constantine Michalopoulos March 1998 L. Tabada in the World Trade Organization 36896 WPS1907 Development Expenditures and the Albert D. K. Agbonyitor April 1998 L. James Local Financing Constraint 35621 WPS1908 How Dirty Are "Quick and Dirty" Dominique van de Walle April 1998 C. Bernardo Methods of Project Appraisal? Dileni Gunewardena 31148 WPS1909 Capital Market Responses to Susmita Dasgupta April 1998 R. Yazigi Environmental Performance in Benoit Laplante 37176 Developing Countries Nlandu Mamingi WPS1910 Capital Outflow from the Agriculture Junichi Yamada April 1998 E. Khine Sector in Thailand 37471 Policy Research Working Paper Series Contact Title Author Date for paper WPS1911 The intemationalization of Financial Stijn Claessens April 1998 R. Va Services in Asia Tom Glaessner 33722 WPS1912 Pay and Grade Diffe.entials at the Deon Filmer April 1998 C. 8ernardo World Bank Margaret Grosh 31148 Elizabeth King Dominique van de Walle WPS1913 The 1994 Currency Crisis in Turkey Oya Celasun April 1998 K. Labrie 31001 WPS1914 Distinguishing between Types of Jesko Hentschel April 1998 PREM Advisory Data and Methods of Collecting Them 87736 WPS1915 Distortionary Effects of State Trading Merlinda Ingco April 1998 M. Fernandez in Agriculture: Issues for the Next Francis Ng 33766 Round of Multilateral Trade Negotiations WPS1916 The Size, Origins, and Character James H. Anderson May 1998 P. Sintim-Aboagye of Mongolia's Informal Sector 37656 during the Transition