The soft budget constraint of banks

Journal of Comparative Economics 35 (2007) 108–135 www.elsevier.com/locate/jce

The soft budget constraint of banks Julan Du a , David D. Li b,∗ a Department of Economics, Chinese University of Hong Kong, Shatin, N.T. Hong Kong SAR, China b School of Economics and Management, Tsinghua University, Beijing 100084, China

Received 27 January 2005; revised 1 November 2006

Du, Julan, and Li, David D.—The soft budget constraint of banks Since the source of funds for banks is mainly deposits, banks have difficulty raising funds to refinance their balance sheets when a substantial portion of their loan portfolio is in default. Intrinsically, banks face hard budget constraints and are subject to market discipline. However, governments with both the resources and the incentives to bail out failing banks may lead to soft budget constraints for banks. Consequently, banking regulation, especially bank capital adequacy regulation, becomes an important institutional solution to the resulting instabilities. Our theory predicts that countries having a larger fiscal capacity are more prone to applying soft budget constraints to failing banks; thus, these governments impose tighter bank capital adequacy regulations to minimize the adverse impact of moral hazard arising from the soft budget constraint on banks. We provide cross-country empirical evidence to support this prediction. Journal of Comparative Economics 35 (1) (2007) 108–135. Department of Economics, Chinese University of Hong Kong, Shatin, N.T. Hong Kong SAR, China; School of Economics and Management, Tsinghua University, Beijing 100084, China. © 2006 Association for Comparative Economic Studies. Published by Elsevier Inc. All rights reserved. JEL classification: G2; D2; H1; N2; P5 Keywords: Soft budget constraint; Capital structure of banks; Banking regulation

1. Introduction The growing literature on the soft budget constraint (SBC), including Goldfeld and Quandt (1988), Dewatripont and Maskin (1995) and Berglof and Roland (1998), focuses on enterprises * Corresponding author. Fax: +86 10 6279 6902.

E-mail address: [email protected] (D.D. Li). 0147-5967/$ – see front matter © 2006 Association for Comparative Economic Studies. Published by Elsevier Inc. All rights reserved. doi:10.1016/j.jce.2006.11.001

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and assumes that banks rescue enterprises that are on the verge of bankruptcy. To conduct frequent and massive rescues of failing businesses, banks must also face SBCs; otherwise, they would not be financially viable. As Maskin and Xu (2001) and Kornai et al. (2003) show, banks are frequently observed to have SBCs. Because banks are the most important sources of external finance for corporate investment in most economies, we expect that SBCs of enterprises stem largely from SBCs on banks. Thus, analyzing the SBC on banks enhances our understanding of the entire SBC syndrome. We argue that, intrinsically, banks face hard budget constraint under free or laissez-faire banking in the early days of capitalism. In modern capitalism, social-welfare-minded governments with expanding fiscal capacities cannot commit to not rescuing banks in financial distress. This government failure leads to the SBC on banks, which in turn gives rise to moral hazard. Consequently, banking regulation becomes an important institutional response to the SBC in the banking system. The unique financial structure of banks generates hard budget constraints. For banks, a significant source of funding comes from demandable deposits that enjoy first-come, first-served sequential service arrangements. Hence, refinancing is difficult for a bank in financial distress. Because weak banks often do not have sufficient funds for refinancing, a new investor is necessary and the existing investors must collectively give up part of their initial claims. Once a bank is acknowledged to be in financial distress, the depositors cannot be convinced to give up their initial claims to accommodate a new investor. This impossibility of refinancing in laissez-faire banking is often socially inefficient because it rules out the ex post efficiency of refinancing socially worthwhile projects. However, it does constitute a credible commitment device for banks to manage risk carefully. Thus, absent non-market forces, bankers behave in a conservative way, which we call the beauty of banking. Modern governments destroy the beauty of banking. In comparison with hereditary monarchies, modern governments run by professional politicians must be much more responsive to short-term social welfare concerns. In addition, these governments are stronger fiscally and financially than their predecessors. Consequently, a modern government finds it almost impossible not to use its fiscal and financial prowess to refinance or to bail out a bank in financial distress. Although bailing out banks may be ex post efficient in many cases, it is always ex ante inefficient because it makes both the depositors and the bankers more reckless in their decisions. We treat the lack of government commitment to no bailout and the resulting SBC on banks as a type of government failure. Banking regulation is an institutional response to the SBC on banks. To address moral hazard, governments impose regulatory requirements on banks, e.g., bank capital adequacy ratio. The objective is to constrain bankers’ opportunistic behavior and to align private bankers’ investment decisions closer to social optimality. Although banking regulations cannot harden budget constraints, they can minimize the efficiency losses from moral hazard under the SBC on banks.1 In this theory of banking regulation, capital adequacy regulation is a social-welfare-enhancing institutional solution to government failure, i.e., SBC on banks, rather than a correction of market failure.2 Our theory predicts a positive relationship between fiscal capacity and the stringency of 1 Dowd (1996) makes a similar argument that laissez-faire banking can be efficient and stable. However, he proposes to return to the free banking regime without proper regard to the existence of instantaneous-welfare-minded modern governments that makes such a move virtually impossible. 2 Benston and Kaufman (1996) argue that banking regulation can be justified only on the ground that it can deal with the negative externality of moral hazard generated by a poorly structured deposit insurance scheme. Our approach

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bank capital adequacy regulation. Because the government is always tempted to bail out insolvent banks, its ability to execute bailout is constrained only by its fiscal capacity. Countries having abundant fiscal resources will be more likely to acquiesce to the SBC on banks than those with scarcer fiscal capacity. As a result, the former will impose stricter regulations and supervision on banks. We present cross-country evidence to support this hypothesis.3 In addition, our theory also generates predictions regarding the relationship between the strength of capital regulations and the real deposit rate or the salvage value from refinancing banks. Our evidence suggests that the real deposit rate and bank salvage value are positively and negatively related to the strictness of capital regulations, respectively. The literature on the SBC on banks includes Berglof and Roland (1995) and Mitchell (1998).4 These authors discuss bankers’ misbehavior under the SBC and governments’ attempts to mitigate the consequences of the SBC on banks. In contrast, we probe the financial structure of banks to establish the genesis of the SBC and the institutional solutions available to modern governments. In terms of modeling, our theory is related specifically to two recent lines of literature, namely the theoretical literature on SBC and the role of banks’ capital structure in enabling them to create liquidity. In the former tradition, Dewatripont and Maskin (1995) show that, if the financiers are large, commitment not to refinance investment projects ex post is impossible. One implication of their analysis is that financiers should be small to gain efficiency through commitment. We apply this logic to the relations between governments and banks and provide another solution to the SBC, namely, regulations to restrict ex ante actions of bankers. In the other literature, Calomiris and Kahn (1991) show that demandable deposits attract funds by giving depositors an option to force liquidation so as to prevent informed bankers from acting against the interests of uninformed depositors. Diamond and Rajan (2001) argue that the fragility of banks’ financial structure is a good commitment device. Similarly, Diamond and Rajan (2000) analyze the optimal bank capital structure that trades off the benefit of commitment against the cost of instability. These authors consider the potential for managerial expropriation of investors and borrowers. Our theory is fundamentally different from the argument that justifies banking regulation based on explicit deposit insurance as described in Dewatripont and Tirole (1995) or implicit deposit insurance.5 First, the phenomenon of government bailout of banks is much more prevalent than pure bailout of depositors. As reported by Business Week (1998), the Japanese government argues that the inevitability of government failure, of which deposit insurance is one aspect, makes banking regulation necessary. In our view, even if the deposit insurance system were structured better, government failure would still arise and necessitate banking regulation. 3 We collected much historical evidence on the general stability of the banking sector in the laissez-faire banking era, bank instability generated by moral hazard following government protection of banks, and the emergence or strengthening of banking regulation as an institutional solution to government failure. To save space, we do not report this evidence in the paper but will provide them upon request. 4 Other studies focus on the optimal design of bank bailout policies to harden budget constraints. Aghion et al. (1999) consider the optimal design of bank bailouts in transition economies to minimize the negative effects of the SBC on banks. Goodhart and Huang (2005) study the government’s role as lender of last resort. They suggest that one way to limit the SBC problem on banks is to restrict bailouts to very large banks. Freixas (1999) argues for a creative ambiguity approach, i.e., bailing out banks randomly. In our view, the social-welfare-minded modern governments may not even be able to commit to these optimal bailout policies. Thus, ex ante banking regulation is a more feasible institutional cure for the SBC syndrome. 5 Dewatripont and Tirole (1995) also point out that deposit insurance could be provided by the private sector in the same way as are most forms of insurance, e.g., life insurance and health insurance. In their scheme, the unique position of deposit insurance in justifying banking regulations is not clear.

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injected capital into ailing banks to prevent them from closing down and to allow them to continue to operate in addition to covering depositors in the late 1990s and early 2000s. Second, our SBC-based theory explains banking regulation directly while deposit insurance is, at best, an indirect explanation. Deposit insurance prevents bank runs, so that it reduces indirectly depositors’ incentives in monitoring banks’ risk-taking behavior. Hence, deposit insurance contributes to moral hazard, which in turn necessitates banking regulation. Our SBC-based theory is consistent with the literature that explains how the SBC alters significantly a firm manager’s behavior. Thus, bank bailout plays a more instrumental role in giving rise to banking regulation than does depositor bailout. Finally, empirical tests in Section 4 indicate that our theory is more relevant than deposit insurance for justifying banking regulation. The next section presents the model of the SBC on banks and analyzes a few benchmark cases. Section 3 investigates in detail banking regulation as a solution to the SBC on banks. Section 4 contains some cross-country econometric analysis on the relationship between fiscal capacity and the strength of capital regulation. In Section 5, we test several other predictions from our theory. Section 6 concludes with a summary and policy implications. 2. A model of the soft budget constraint on banks We consider an economy that consists of n banks and three types of active players, namely, bank managers, depositors, and the government. Each bank is run by a manager whose payoff is the monetary value from holding equity shares in the bank plus a nonpecuniary private benefit of control. Depositors are concerned about the expected rate of return on their deposits in each bank. The government is controlled by politicians whose objective is to enhance social welfare at any moment. Maximizing social welfare at any moment is often achieved at the expense of not reaching the highest expected overall social welfare. We consider a typical operation cycle of a bank. At time 1, depositors put their savings into the bank in response to the expected rate of return that they calculate from observed parameters of the bank, including the nominal interest rate. At time 2, the bank manager decides on the investment portfolio by balancing risk and mean return, and investment becomes sunk once made. At time 3, the uncertainty of the return to the investment is resolved in one of two ways. In the first case, the return is high enough to cover the deposit and the promised interest payment so that the operation cycle ends. In the second case, the investment projects do not generate any positive cash flow unless additional investments are made so that negotiations between the bank and other parties take place regarding whether and how to refinance the additional investment. When pertinent, we add a time 0 in which the government decides on the configuration of banking regulation. For simplicity, we assume that the feasible investment projects from which the manager of a bank, denoted i (i = 1, . . . , n), chooses all exhibit constant returns to scale, that is, the return will increase proportionately with total investment. We index the continuum of feasible investment projects by y in the following way. For bank i, with probability pi , the gross rate of return is ky(pi ), where k is a parameter. With probability 1 − pi , the gross rate of return is 0 unless an extra investment of x is made, in which case the gross rate of return becomes z − x. To finish up the project, the manager having indispensable knowledge for the project must be retained, and he receives private benefits of control. The manager’s choices of investment projects are assumed to be independent of each other. Given constant returns to scale, we can scale down all of the bank’s operational variables by fixing one of them at a preset value. If we increase this variable, all others will change proportionately. We choose to fix total initial equity for each bank at e. Let the manager of each bank

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hold proportion α of equity shares and enjoy private benefits of control B for one unit of finished investment. Given one unit of total bank equity, depositors are willing to supply d = βs(r e ) + s0 to the bank, where s0 is a positive constant, β is a parameter, and r e is the depositors’ expected rate of return to one unit of deposit. In this formulation, we assume a fixed supply of deposits (s0 ) to banks regardless of the rate of return for various reasons, e.g., for transactional convenience. Another part of deposits (s(r e )) is sensitive to the expected return to deposits. We use parameter β to indicate the degree of this sensitivity. We make a few explicit assumptions; the first concerns the quality of the set of investment projects. Assumption 1. (1) ∃p: kpy(p) > 1 + r; (2) limp→0 py(p) = 0; (3)y  (p) < 0; (4) [py(p)] < 0. Part (1) of Assumption 1 ensures the existence of investment projects that can make the bank profitable. Even if refinancing is impossible, the expected return of some projects is sufficient to pay the principal plus interest. Part (2) indicates that it is not socially worthwhile to choose projects with a very small p. Part (3) states that the return in the good state decreases in p, implying that high returns are associated with high risks. Part (4) is a technical assumption implying that the response of the expected return to a change in p is decreasing if p is sufficiently small. Assumption 2. z − x + B < c < 1, but z > 1 + r, where c is a constant. Assumption 2 indicates that refinancing is ex ante inefficient in that a social-welfare-minded decision maker who knows initially that a project will need refinancing at a later stage will not invest in the project. Furthermore, if z − x + B > 0, bank bailout is ex post efficient in that a project needing refinancing will be funded by a social-welfare-conscious investor. Moreover, once refinancing occurs, the gross return covers the repayment of principal and interest to the depositors because ze(1 + d) > (1 + r)ed from z > 1 + r. Assumption 2 links our model to two benchmark models. In models of the Diamond–Dybvig (1983) type, z − x > 1 is assumed implicitly so that refinancing is socially efficient not only ex post but also ex ante. In contrast, Dewatripont and Maskin (1995) make an assumption similar to Assumption 2 in that refinancing is ex post efficient but ex ante inefficient. Assumption 3. Depositors cannot collectively agree to lower the terms of their existing claim rights. This is a key behavior assumption of the model in that the possibility of a bank run is due to the unique financial structure of banks. Assumption 4. [py(p)] < 0. This is a nonessential technical assumption made for ease of exposition and states that py(p) becomes more concave with higher p. The most important conclusions do not depend on this assumption. Assumption 5. For technical convenience, we restrict our analysis to a symmetric equilibrium in which each bank manager chooses p optimally given that p is chosen by all other banks.

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Given that each bank is identical in e, x, z, a single Nash equilibrium in which each bank manager chooses the same p is reasonable to consider and does not cost any significant insight. Three important benchmark cases follow from the model structure. The first-best banking arrangement (FBB) is a hypothetical situation in which a social-welfare-maximizing planner acts in the capacity of the bank manager to choose investment projects and, when necessary, decides whether to fund those projects that require refinancing. Following the principle of backward induction, we consider the decision of the social planner at date 3. If the investment project needs refinancing, the social planner should decide to fund the project if the social welfare of refinancing is larger than that of no refinancing, i.e., z − x + b > 0. To support refinancing, the depositors must be paid the full amount of principal plus interest. Otherwise, a bank run will occur. Normally, such refinancing may induce risky investment decisions at date 1. However, in FBB, the decision at date 1 is also made by the social planner so that this negative consequence is avoided. Given that refinancing is always provided by the social planner at date 3 if it is necessary, the expected social welfare at date 1 associated with an investment decision indexed by p for a bank is S = e(1 + d)[pky(p) + (1 − p)(z − x) + B − 1]. Note that the interest rate r does not enter this expression for social welfare because it affects only the amount of transfer from one group of agents, i.e., investors of the bank, to another group, i.e., depositors. The social planner maximizes social welfare S by choosing an optimal p. Therefore, we have the following proposition.6 Proposition 1. If z − x + B > 0, the first-best arrangement is the following: (1) Choose an investment project pFBB such that [kp FBB y(p FBB )] = z − x. (2) If the investment project is unsuccessful, provide investment funds x and pay all depositors their principal and interest. If we consider the contagion risk or systemic risk, i.e., the risk that the financial difficulties at one bank spill over to a large number of other banks or to the financial system as a whole, the case for the social planner to refinance the unsuccessful investment project is reinforced because it precludes a bank run. The second benchmark case, laissez-faire banking (LFB), refers to the situation in which the government is not involved in any decision relevant to the bank. Specifically, the government imposes no banking regulation and makes no decision to refinance investment if necessary. The most important feature of LFB is that refinancing of investment projects may not be possible at date 3 and this is ex post inefficient. Lemma 1. If c < (1 +r)d/(1 + d), no refinancing is possible for unsuccessful investment projects in LFB. To show this result, note that the depositors cannot be persuaded collectively to lower their claims on the bank. Suppose that refinancing is provided. For each bank, the original equity holder will obtain at most e(1 + d)(z − x) minus the total payment to the depositors (1 + r)ed, i.e., e(1 + d)(z − x) − (1 + r)ed. According to Assumption 2 and the condition in Lemma 1, 6 To save space, we omit the proofs of all propositions and lemmas except Proposition 6, but will provide them upon request.

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e(1 + d)(z − x) − (1 + r)ed < ce(1 + d) − (1 + r)ed < 0. Therefore, refinancing cannot be provided by a profit-maximizing new investor. Lemma 1 illustrates the concept of the beauty of banking. Because of the unique financial structure of banks, no ex post refinancing is possible without government intervention. This forces the bank manager to be cautious in making investment decisions ex ante. Given Lemma 1, we calculate the bank manager’s payoff as W B (d) = αep[(1 + d)ky(p) − d(1 + r)] + pB − αe, which is maximized by choosing a proper p. The optimal p is the best response to the total amount of deposits that the bank can attract, i.e., ed. Furthermore, the depositors anticipate the bank manager’s decision on p and decide on their aggregate supply of deposits. The supply function is d = βs(r e ) + s0 , where r e is the expected rate of return. In our context, there is no refinancing so that r e = p(1 + r) − 1. In an equilibrium of LFB, r e is consistent with the bank manager’s actual choice of p so that we have the following proposition. Proposition 2. In the case of LFB, if c < (1 + r)d/(1 + d), the unique equilibrium consists of p LFB and d LFB satisfying [kpy(p LFB )] = (1 + r)d LFB /(1 + d LFB ) − B/α and d LFB = βs[p LFB (1 + r) − 1] + s0 . In addition, we examine the sensitivity of the equilibrium to changes in the exogenous variables. Proposition 3. The equilibrium of LFB has the following properties: (1) p LFB decreases in r, α, β and increases in k and B; (2) d LFB decreases in α and increases in k, B, and β. A higher r makes the banker gamble with a lower p because the upside of his gamble is smaller. However, a lower p and higher y(p) compensate for this effect. Moreover, a higher B or α makes the case of 1 − p more costly and therefore induces a higher p. Our model is similar to the one of Bolton and Scharfstein (1996) in that a large number of creditors can harden the budget constraint. However, our model differs in several important respects. First, the hard budget constraint from free banking can be regarded as an extreme case of their model because the number of creditors approaches infinity so that renegotiation for refinancing is ruled out. We consider this characterization of bank capital structure to be the natural one. Second, their theory emphasizes how a larger number of existing creditors makes renegotiation on no liquidation more difficult. In our model, renegotiation is impossible not only among existing depositors but also between the existing depositors and any potential new investor willing to refinance the project, as Assumption 3 indicates. Third, unlike in their model, we do not distinguish between liquidity default and moral-hazard-based strategic default. Our central concern is the ex post efficiency of refinancing. If an undesirable investment outcome occurs, we do not consider it important to detect whether the investment failure results from bad luck or erroneous investment decision. Fourth, unlike in their model, our model does not rely on the complementarities of collateral assets to generate a hard budget constraint. Rather, our mechanism to induce a hard budget constraint is more closely related to the unique capital structure of banks. The final benchmark is the case of banking with government intervention (BGI), i.e., the SBC case. Unlike LFB, the government decides to refinance the bank’s investment if doing so enhances the ex post social welfare, which has three important implications. First, the government must bail out depositors; otherwise, individual depositors anticipate that the bank has insufficient

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funds to pay interest and principal in full so that they run on the bank before the refinancing can be implemented. Second, the bank manager must be retained because, by our assumption, he has indispensable knowledge for finishing the project. Thus, anticipating refinancing, the manager faces no risk of losing his position. Third, refinancing the bank’s investment projects and bailing out the depositors may be inefficient ex ante because this policy makes both the depositors and the bank manager less prudent in their deposit and investment decisions. Formally, we have the following lemma. Lemma 2. If and only if z − x + B > 0, an ex post social-welfare-maximizing government with no budgetary constraint rationally chooses to refinance the bank’s unsuccessful investment projects and pay the depositors principal and interest. In this case, the expected payoff to each bank manager is W B (d) = αp[e(1 + d)ky(p) − (1 + r)ed] + B − αe. Maximizing the expected payoff, the bank manager chooses his optimal project indexed by p according to the following first-order condition: [kpy(p)] = (1 + r)d/ (1 + d), which gives p as a function of d. Furthermore, given the possibility of government bailout, the depositors’ expected rate of return is the same as the announced interest rate of the bank, r. Consequently, the deposit supply schedule is given by d = βs(r). The intersection of the two curves, p = p(d) and d = βs(r), describes the equilibrium of the case of BGI. Proposition 4. If z − x + B > 0, in the case of government intervention without ex ante regulation, the unique equilibrium consists of p BGI and d BGI satisfying the following conditions: [kpy(p)] = (1 + r)d/(1 + d), and d = βs(r) + s0 . In the case of unsuccessful investment projects, the government will provide refinancing and pay the depositors principal and interest. We can compare the efficiency of these three benchmark cases. By definition, FBB in which a social planner makes decisions on both p and refinancing is optimal. Relative to the scenario of BGI, LFB effectively constrains the moral hazard problem of choosing high risk projects so that it generates higher social welfare. Proposition 5. Suppose z − x + B > 0 and c is sufficiently small: (1) p BGI < p FBB , p BGI < p LFB ; (2) the ranking of social welfare per unit of total investment is sw BGI < sw LFB < sw FBB . If 0 < z − x + B < c and c is small, bailout is not socially beneficial because the benefit of bailout is dominated by the loss of p. If contagion risk is taken into consideration, the social welfare gain from bank bailout increases substantially so that the welfare comparison between the latter two benchmark cases may be altered. However, we do not consider contagion risk in our analysis. First, many studies already address contagion risk and justify banking regulation from the perspective of preventing bank contagion. Second, the importance of contagion risk is controversial. Dowd (1992) and Hasan and Dwyer (1994) show that bank failures even in LFB episodes did not appear to have involved severe contagion risk. They argue that external factors exogenous to the banking system and government intervention of some sort were mainly responsible for banking crises. Moreover,

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the very possibility of bank contagion made bank managers more cautious in free banking periods, which enhanced the overall stability of the banking system in LFB. Next, we turn to analyze how banking regulation emerges as an institutional solution to the problems of SBC on banks. 3. The soft budget constraint and banking regulation In our analysis, the SBC on banks results from the ex post efficiency in terms of social welfare in refinancing and the government’s concern for social welfare. Because no profit-maximizing investor is willing to refinance the bank, a government having access to fiscal and financial resources chooses rationally to conduct refinancing. Thus, we utilize the ex post efficient refinancing in Dewatripont and Maskin (1995) and the social welfare concern of modern governments to generate the SBC on banks. In this section, we fit our theory better to the real world by introducing two new elements. First, the government has limited financial resources so that its ability to bail out banks is restricted by its fiscal capacity. We assume that the government has fiscal resources, denoted by f , with which it can refinance the banks. Second, the government can regulate banks to minimize the harmful effects of moral hazard arising from the SBC on banks. Therefore, banking regulation is an institutional solution to the problem and is often needed to enhance social welfare. Among many types of banking regulations, capital adequacy requirements, which force banks to maintain a minimum ratio of equity to total assets, are implemented frequently. Capital adequacy is indexed inversely by d in our model. A higher level of capital, i.e., a lower d, induces the bank manager to be more cautious in his investment decisions. At time 3, if the investment project turns out to be unprofitable, government bailout is needed. For a bank, the required amount of refinancing is xe(1 + d), i.e., the product of refinance required per unit of bank assets and the total bank assets. After refinancing, each bank generates a revenue z per unit of bank assets, which will be sufficient to repay the principal and interest to depositors, according to Assumption 2. Therefore, forward-looking depositors do not run on the bank. For each bank i, the amount of bailout required bi satisfies 0  bi  xe(1 + d). From  the perspective of the government, the total amount of required funds for bank bailout is ni=1 bi . Hence, we have the following distribution function:  0, if t < 0; m v (1 − p)v p (n−v) v[xe(1 + d)], if m  t < m + 1  n; G(t) = C v=0 n 1, if t > n. As a result, the expected amount of bailout for bank i is E(bi ) = + d), and the (1 − p)xe(1 expected amount of bailout for all domestic banks becomes E( ni=1 bi ) = ni=1 (1 − p) × xe(1 + d) = n(1 − p)xe(1 + d). The government always  wants to bail out all insolvent banks. If fiscal resources are sufficient to bailout ex post, i.e., f  i bi , where i = 1, . . . , n, all the insolvent banks are bailed out with probability one. However, if fiscal capacity falls short of the required amount for bank bailout, the government freezes the assets of insolvent banks and distributes the rescue funds across insolvent banks according to the proportion of each insolvent bank’s assets to the total assets of all insolvent banks. Because banks have the same size of assets in our model, each insolvent bank will receive an equal share of government bailout funds. Hence, for each bank, the ex post percentage of investment refinanced by the government, denoted Q, is determined by:   1,  if f  i bi , Qi = f/ i bi , if f < i bi ,

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where i = 1, . . . , n. Before the investment projects are chosen, managers form an expectation about the percentage of bank assets that the government will bail out in case of bank insolvency. With perfect foresight, the ex ante probability of bank bailout or ex ante percentage of bank assets getting bailed out, denoted q, is equal to the conditional expectation of Q, that is, q = E(Q | e, d, p, n). The choice of p by  each manager plays an important role in determining the total amount of bailout refinance, i.e., i bi , i = 1, . . . , n, and thus Q. For technical convenience, we consider a myopic equilibrium case in which each manager is assumed to be myopic in choosing investment projects without taking into account the impact of his actions on the probability of government bailout. In choosing p, each manager takes the ex ante percentage of bank assets being bailed out q and the investment project choice of other banks p−i as given. In other words, each manager does not realize that his choice of investment projects may affect the probability or percentage of bank bailout and thus in turn the project choice by other banks. This simplifying assumption is plausible if the number of banks is sufficiently large and the impact of any individual bank on the whole banking industry is rather small. Thus, we restrict our analysis to a myopic symmetric equilibrium in which each manager chooses the same p taking q as given. Then, q is determined by p as well as the other parameters, but each manager takes no account of the impact of his choice of p on q. We focus on two key issues so as to relate our theory to observations about capital regulation across countries. First, when and under what conditions is capital adequacy regulation needed. Second, when and under what conditions should capital adequacy regulation be stricter. We proceed in the following order of analysis. First, we consider the case of no prudential regulation of bank capital. In such an equilibrium, the supply of deposits, which is determined in anticipation of the manager’s decision, may provide some discipline. Let the associated level of deposits be d E . Second, suppose that the government can dictate the amount of deposits each bank obtains. Let the government’s optimal choice be d G . If d E  d G , capital adequacy regulation is not needed because depositors cannot be forced to put more deposits into the bank. If d E > d G , capital regulation is useful because the unregulated level of deposits is too high in that it encourages risky investment choices. As a result, the bank must reduce the amount of its deposits or increase its own capital. First, we analyze the equilibrium without banking regulation. Since all banks behave in the same way in the symmetric equilibrium, we focus on a representative bank. Given the amount of deposits d, the bank manager chooses p to maximize his expected payoff, which is W B (d) = αp[e(1+d)ky(p)−(1+r)d]+e(1+d)pB +e(1+d)(1−p)qb. Hence, we derive the first-order condition for the manager’s investment choice p as:   kpy(p) = (1 + r)d/e(1 + d) + (q − 1)B/α. (1) Equation (1) defines the reaction function of the bank manager, p = p(d). Meanwhile, the depositors expect the bank manager to choose investment project p and the resulting expected rate of return to be p(1 + r) + (1 − p)q(1 + r) − 1. Thus, the depositors’ supply function is given by d = d[p(1 + r) + (1 − p)q(1 + r) − 1]. The two reaction functions define a banking equilibrium in the absence of government regulation, (pE , d E ), satisfying Eq. (1) and d = d[p(1 + r) + (1 − p)q(1 + r) − 1]. Depositors are indifferent to different banks in making their deposit investment because each bank provides the same expected return.7 7 After deciding on the amount of deposit investment, each depositor will randomly choose one or more bank in which to deposit his money. However, in the banking equilibrium, the flow of deposits ensures that each bank ultimately ends

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To determine the optimal level of bank deposits d G , the government maximizes the expected social welfare associated with the bank given by:   SW = e(1 + d) pky(p) + pB + (1 − p)q(z − x) + (1 − p)qB = e(1 + d)U,

(2)

where U is defined as the social welfare per unit of bank assets and p is chosen by the bank manager according to Eq. (1).8 Hence, p is a function of d. Taking the first derivative of the social welfare function with respect to d, we have: ∂SW = U + (1 + d)Up pd ∂d

 (1 + r)d 1 = U + (1 + d) + 1− (1 − q)B − q(z − x) pd , 1+d α

(3)

where we use Eq. (1), which should be satisfied after the government announces d G , to calculate Up . We examine how d G varies with exogenous variables, e.g., f, n, e, and r, and do the same with d E . This sensitivity analysis characterizes situations in which banking regulation is more likely to emerge and how regulation varies across different economic environments. Among the most important exogenous variables are f , n, and e. Fiscal capacity, denoted f , determines the government’s ability to bail out banks, while n and e influence total bank asset size. If the government has larger fiscal capacity, the government has less ability to commit itself not to bail out banks, holding bank assets constant. As a result, the government should be more inclined to impose tight capital adequacy regulation. Thus, we have the central proposition of the paper. Proposition 6. There exist h, m, and β such that (1) if c < h, k/B < m, and β < β, if f is higher, it is more likely that capital adequacy regulation will be necessary for social welfare maximization; (2) if c < h, k/B < m, and β < β, if n or e or both are higher, it is less likely that capital adequacy regulation will be necessary for social welfare maximization; (3) if c < h, if banking regulation is necessary, the higher f , or the lower n or e or both, the tighter should be the capital adequacy requirement. The interpretation of Proposition 6 is simple and the proof is provided in an appendix. The upper limit on the ex post social welfare benefits of bank bailout is c. If c is sufficiently small, bank bailout decreases social welfare and does so increasingly with increasing fiscal capacity. In addition, k must be sufficiently small relative to B. A small k indicates that profitable banking projects are not numerous so that the bank manager’s decision is likely to be socially inefficient. As a measure of the manager’s personal stake in the success of the project, a large B reduces the tendency of bank managers to choose risky projects. Hence, k/B is a relative index of the quality up holding an equilibrium amount of deposits d. Too large a d for any bank would only raise bank risks, which is unappealing to depositors. 8 To be more precise, for n banks, suppose that the individual bank’s own assets are a , a , . . . , a , respectively. Under n 1 2 our assumption of constant return to scale, total social welfare is (1 + d)a1 U + (1 + d)a2 U + · · · + (1 + d)an U = (a1 + a2 + · · · + an )(1 + d)U so that the government’s objective is to maximize (1 + d)U .

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of the project pool and the manager’s tendency to choose socially inefficient projects. Under these conditions, a higher fiscal capacity and a higher probability of bailout must be counteracted by a lower d. In addition, if β is low, the supply of deposits is not sensitive to the expected rate of return. Therefore, if the bank is left unregulated, as fiscal capacity gets higher, the quality of bank investments gets lower because depositors are not lowering d enough to counteract the effect of a higher f or l. In this case, regulation of d is required. Proposition 6 states that, if fiscal capacity is large relative to the size of bank bailout or bank bailout size is small relative to fiscal capacity, the problem of an SBC on banks is more likely. To minimize the negative effects of the SBC, capital adequacy regulation should be strengthened. In what follows, we explore further the predictions of our theory. First, we examine the impact of a higher deposit rate on capital regulation. The deposit rate r is often fixed or regulated by monetary policies so that a common consequence of tighter monetary policy is an increase in r. A higher r is equivalent to reducing the payoff of a successful project without changing that of an unsuccessful one, inducing the manager to take on riskier projects. Thus, one effect of a higher r is that a lower d G is needed to counteract the manager’s tendency to choose riskier projects. In addition, a higher r lowers the expected rate of return to depositors so that the unregulated equilibrium d E decreases. However, whether the reduction in d G is lower than that in d E is not clear. However, if β is low, d E is not very sensitive to the expected rate of return so that the latter effect will be dominated by the former effect. We summarize this discussion in the following proposition. Proposition 7. There exists a β such that, ceteris paribus, if β < β, and r is higher, (1) it is more likely for capital adequacy regulation to be necessary; (2) if capital adequacy regulation is necessary, it is stricter. We continue by analyzing the impact of changes in the salvage value of the bank’s investment project that needs refinancing, z − x, and the overall average rate of return on all investment projects, k, on bank capital adequacy regulation. The value of a bank’s investment after refinancing without incorporating the initial investment cost is given by z − x. Intuitively, if z − x is lower, the manager’s imprudent investment decisions become more socially costly so that improving investment quality is increasingly beneficial. Moreover, the equilibrium under no banking regulation is unchanged because the manager’s payoff is independent of z − x, which goes to depositors and the government. Thus, a lower z − x requires tighter capital regulation. The profitability of investment projects also matters. In our model, changes in the overall average rate of return of projects are captured by changes in k. As in the analysis of an increase in r, we find two effects. First, the regulator prefers a lower d G to induce better quality investment projects, which is necessary to compensate for a decrease in k. Second, the unregulated equilibrium d E also decreases because the success rate of the bank’s investment projects falls so that the supply of deposits decreases. Again, if β is small, the equilibrium d does not decrease much because the former effect dominates the latter one. Proposition 8. Ceteris paribus, a higher value of z − x makes it less likely for capital adequacy regulation to be necessary and, if the regulation is in place, it becomes less strict. In addition, there exists a β such that, ceteris paribus, if β < β, then

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(1) if k is higher, it is less likely for capital adequacy regulation to be necessary for social welfare maximization; (2) if capital adequacy regulation is necessary, the regulation is less strict. After deriving the main predictions of our theory, we turn to empirical analysis to test these predictions. 4. Cross-country econometric evidence for the relationship between fiscal capacity and banking regulation Our theory links the cross-country variation in the adequacy of banking regulation with that in fiscal capacity. We argue that, if instantaneous-social-welfare-minded governments have stronger fiscal capacity, it will be harder and less credible for them to commit to a hard budget constraint for banks. As a result, these governments will implement stricter capital adequacy regulation to preclude massive bank fraud. In short, countries with more abundant fiscal resources are expected to establish more stringent capital adequacy regulations. To measure the cross-country differential in the adequacy and stringency of capital regulation, we employ the data set of the project on “Banking Regulation and Supervision” of the World Bank Group, which contains comprehensive information on commercial bank regulatory practices for a large sample of countries. The data were collected in the year of 1999 and reflect the recent practices of banking regulation across countries. Barth et al. (2001, 2004) provide a detailed description of the survey questions and the data collection process. Capital adequacy regulation has various dimensions. The most frequently mentioned is the minimum capital adequacy ratio required by bank regulatory agencies in each country. However, this instrument does not exhibit substantial variation across countries; almost all countries set it at 8% or a little above. Perhaps most countries follow the Basle agreement in setting the de jure minimum capital adequacy ratio. However, enforcement of this requirement varies considerably across countries and the strength of enforcement determines ultimately whether the requirement is fulfilled. The overarching issue in capital adequacy enforcement is the types of funds that qualify to be counted as bank capital. We focus on two major aspects, namely, regulation of funding sources of bank capital and regulation of capital risk adjustments. Regulation of funding sources for bank capital deals with the types of funds that can be considered to be bank capital. To ensure the liquidity and safety of bank capital, assets other than cash or government securities cannot be counted. In addition, to make sure that bank capital is truly the bank’s own assets, borrowed funds are not allowed to be used as bank capital. We combine these two features to form an index of bank capital funding regulation. Regulation of capital risk adjustment requires that the minimum bank capital level be adjusted in accordance with changes in banking risks. Bank regulators may require the capital adequacy ratio to be riskweighted in line with Basle guidelines, to vary with a bank’s credit risk, and to vary with market risk. To protect the capital adequacy ratio against operational risks, bank regulators may demand that some potential operational losses, e.g., the market value of loan losses, unrealized securities losses, and unrealized foreign exchange losses, be deducted from bank capital before the minimum capital adequacy ratio is calculated. We synthesize these aspects to form an index of bank capital risk adjustment regulation. In constructing these two indices of banking regulation, we follow Barth et al. (2004) by using the first-principal-component method. By simply summing all the numerical values of individual components to form a new index, we would be assigning equal weight to all components. In

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contrast, the first-principal-component method seeks and applies the optimal weight to avoid arbitrariness in assigning weights to each component. These indices are constructed so that a higher value indicates more adequate and more stringent regulation. In addition, we must choose an appropriate measure of fiscal capacity. Because we are dealing with government bailout of failing banks, the measure of fiscal capacity must reflect the government’s capability to meet the emergency funding needs of ailing banks. Some popular measures of fiscal power, e.g., tax revenue or government subsidies and transfers to GDP, provide a general picture of fiscal activity but they do not measure surplus revenue at the discretion of a government wishing to rescue insolvent or illiquid banks on short notice. The overall budget balance exactly reflects surplus fiscal revenue and, thus, the government’s capability to meet emergency funding needs. To control for the size of economy, we scale the overall budget balance by GDP or total bank assets. Scaling by GDP is a popular approach in cross-country empirical analysis because it measures the magnitude of the budget surplus relative to total economic activities. In contrast, scaling by total bank assets provides a better indication of whether the government has the fiscal capacity to satisfy the emergency funding needs for bank bailout. This ratio also fits the prediction of Proposition 6 well because it reflects the relative magnitude of fiscal capacity and potential bank bailout size. We use the average value of these two ratios in the period 1985 to 1997, a period before the year in which the data on banking regulation strength were collected. For brevity, we report only the regression results for overall budget balance as a percentage of bank assets. The results for the ratio of overall budget balance to GDP are qualitatively equivalent. Other factors may be important in explaining cross-country variation in the strength of bank capital regulation. We consider two sets of variables. The first set consists of development level, i.e., per capita GDP, legal origins, religious composition, latitude, and ethnolinguistic fractionalization. These variables are potential determinants of institutional quality and, thus, the strength of banking regulation. We discuss the expected impact of each of these in turn on the strength of banking regulation. Regarding the level of economic development, Pigou (1920) and Stiglitz (1989) argue that, if banking regulation is created to overcome market failures, less developed economies with presumably higher chances of experiencing market failures will need tighter capital regulations. Similarly, Shleifer and Vishny (1994) point out that, if capital regulations are instruments of politicians to control social resources for their own benefits, developing economies with less total social wealth will tend to have stricter bank capital regulation. However, economic underdevelopment may preclude incurring the costs of establishing good institutions for regulation. Overall, the impact of per capita GDP on banking regulations is ambiguous. Legal origins are presumably a fundamental determinant of the quality of banking regulations. Legal origins differ in the priority attached to the protection of the rights of private investors, including bank depositors and shareholders, relative to the rights of the State. La Porta et al. (1999) and Beck et al. (2003) argue that common law provides better property rights protection and creates better institutions than civil law, especially the French civil law, and than socialist law. Hence, we predict that capital regulations will be more stringent in common law countries than countries having civil law or socialist law. The cultural theory of institutional development argues that religious beliefs play a central role in shaping institutional quality. According to Landes (1998) and La Porta et al. (1999), the Protestant religion fosters a strong work ethic and interpersonal trust that contribute to institutional development, whereas the Catholic and Muslim religions are associated with intolerance and closed-mindedness, which deters institutional development. Applied to banking regulation,

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the cultural theory predicts that strong institutions in Protestant countries will promote more adequate capital regulations than in Catholic and Muslim countries. Landes (1998) and La Porta et al. (1999) also show that a country’s latitude affects the quality of public institutions. Countries located in temperate zones have more productive agriculture and healthier climates, which enable them to develop economies and institutions, whereas countries located close to the equator are subject to epidemic diseases and weak agriculture. According to this view, countries in higher latitudes may have better institutions and thus exhibit better banking regulation. A second set of possible determinants of capital adequacy regulation recognizes that the strength of banking regulation may differ between large and small economies. Thus, we include the logarithm of GDP to measure the size of an economy. In addition, the strength of capital regulation may increase with the importance of the banking sector to the national economy. If the size of bank deposits is large, the banking sector is more important to social welfare. In this situation, political demand for strengthening capital regulations to ensure the safety of people’s wealth may be forthcoming. We use the ratio of bank deposits to GDP to gauge the importance of the banking industry to the economy. If an economy is vulnerable to various adverse aggregate shocks, the soundness of banks’ balance sheets is jeopardized due to the financial difficulties of the corporate and household sectors. To prevent bank failures, capital regulations may well need to be strengthened. We employ the volatility of GDP growth rate to measure the susceptibility of the national economy to aggregate shocks and, thus, the vulnerability of the banking system to failures. In addition, market contestability in the banking industry may be relevant. In a contestable banking sector, the entry of new banks is easy and market discipline is stronger. If market discipline can replace government regulation, we should find a negative relationship between market contestability and the stringency of banking regulation. If a contestable banking sector mitigates some pure market failures and moral hazard problems are due largely to government failure as suggested by our theory, market discipline may be complementary to government regulation. Moreover, a contestable banking sector may indicate the absence of strict entry regulations. In this case, stringent capital requirements may be a substitute for slack regulation of bank entry. These latter two possible factors suggest a positive correlation between market contestability and bank regulation. We use the number of banks per thousand people to measure the contestability of the banking industry. Summary statistics of all variables are reported in Table A.1 in the appendix. Table 1 presents regressions in which the dependent variable is one of the two bank capital regulation indices. If the ratio of overall budget balance to total bank assets is the sole independent variable, we find positive and statistically significant effects. After we control for these two sets of potential determinants of bank regulation quality, the results show that a higher ratio of overall budget balance to total bank assets has a consistently and statistically significantly positive association with the two bank capital adequacy regulation indices. Moreover, GDP per capita does not exhibit statistically significant effects on bank regulation indices suggesting that the economic development level is not particularly relevant. Furthermore, legal origins do not have much explanatory power. We find that only countries of Scandinavian legal family register a lower score in the index of bank capital funding regulation than do the common law countries, which is the excluded category. Similarly, our results do not lend strong support for the impact of religious composition and latitude in shaping bank regulation strength. Turning to the second set of control variables, we find no strong evidence for the impact of these variables on bank capital regulations, with one exception. The number of banks per thousand people has a significant positive correlation with the bank capital risk adjustment index.

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Table 1 Fiscal capacity and other determinants of capital adequacy regulation Dependent variable

A

A

A

B

B

B

Overall budget balance/Total bank assets Log of GDP per capita

1.38*** (0.24)

1.46*** (0.32)

1.70*** (0.42)

2.13*** (0.74)

1.46 (1.07)

2.36*** (0.88)

French legal origin German legal origin

−0.22 (0.14) 0.015 (0.32) 0.72 (0.66)

−0.095 (0.25) −0.22 (0.70) 0.23 (0.96)

0.13 (0.23) 0.36 (0.70) 0.89 (0.81)

−0.0078 (0.27) 0.37 (0.79) 0.93 (0.92)

Scandinavian legal origin Socialist legal origin

−1.98** (0.96) 0.0099 (0.67)

−1.73 (1.54) 0.72 (1.11)

−1.17 (1.86) −0.13 (1.05)

−1.24 (1.99) −0.97 (1.43)

Protestant fraction

1.46 (0.89)

1.51 (1.69)

0.95 (1.57)

1.11 (1.69)

Catholics fraction Muslim fraction Latitude

0.93* (0.51) 0.50 (0.55) 1.23 (1.30)

1.01 (0.71) 0.55 (0.91) −0.38 (1.96)

0.96 (0.85) −0.20 (0.90) −0.091 (2.33)

0.86 (0.90) −0.56 (0.88) 0.12 (2.70)

Log of GDP Bank deposits/GDP Volatility of GDP growth rate Number of banks per thousand people Constant # of obs. Adjusted R 2

0.20 (0.15) 67 0.10

0.93 (0.96) 65 0.091

−0.0072 (0.14) 0.15 (1.24) 0.0069 (0.14)

0.20 (0.13) −0.58 (0.69) 0.088 (0.12)

2.90 (4.21)

1.95* (1.01)

0.44 (3.46) 39 0.087

0.30 (0.24) 84 0.040

−1.34 (1.51) 83 0.034

−4.85 (3.06) 79 0.028

Notes. (1) The dependent variable of these OLS regressions is the index of bank capital funding regulation (A) and the index of bank capital risk adjustment regulation (B), respectively. (2) Robust standard errors are presented in brackets. * Statistical significance at the 10% level. ** Idem, 5%. *** Idem, 1%.

This suggests that market contestability is only a complement to government regulation of capital adequacy. In unreported results, we take a broader view of the strength of banking regulation across countries by constructing the index of preconditions for banking regulation covering the

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extent of the independence and flexibility of regulatory agencies, the index of ex ante banking regulation focusing on the ownership structure of banks, the initial bank capital stringency and the ownership of non-financial firms by banks, and the index of ongoing banking regulation encompassing overall capital stringency, credit risk management, and prompt corrective power of regulatory agencies. We detect significant positive relations between these indices and the fiscal capacity measure, which suggests that the impact of fiscal capacity on the strength of banking regulation extends beyond capital adequacy regulations. A potential concern about our empirical results is the possible endogeneity of this fiscal capacity measure. Some countries may have stronger banking regulation for reasons unrelated to fiscal capacity. However, stricter banking regulation minimizes the likelihood of bank insolvency and thus bank bailouts, which may lead to a higher level of fiscal reserves. In general, we do not think that endogeneity is a serious concern. Our fiscal capacity measure is predetermined relative to the dependent variable. Furthermore, the bulk of government expenditure is for government consumption, transfers and subsidies, public enterprises, and various social welfare programs. Fiscal outlays for bank bailouts do not affect fiscal balances significantly for long periods. Nonetheless, we adopt an instrumental variable approach to deal with the possible endogeneity of the fiscal capacity variable. We consider two potential instrumental variables, namely, the Gini coefficient of the income distribution and the percentage of population having access to improved water source. On an ex ante basis, we expect to find a negative correlation between the Gini coefficient and fiscal capacity and a positive correlation between the percentage of population having access to improved water source and fiscal capacity. A more unequal income distribution implies a larger portion of low-income people in the population, which reduces the tax base and raises the demand for government transfer payments. Both of these lead to a lower level of fiscal reserves. Alternatively, a modern government with larger fiscal reserves may offer more transfer payments to reduce inequality in income distribution. Furthermore, income inequality is not likely to have a direct impact on banking regulation strength. Access to improved water source may be an even better instrumental variable because it is less likely to have a direct impact on banking regulation. The quality of water supply is typically a public good. Hence, a government having more abundant fiscal resources will be more capable of providing improved water source.9 To investigate whether the two potential instrumental variables are correlated with fiscal capacity, we report in Panel 1 of Table 2 the regressions of overall budget balance to total bank assets on the Gini coefficient and the percentage of population with access to improved water source, respectively. We observe statistically significant correlation in both cases. Countries having larger inequality in income distribution are likely to have a lower level of budget balance; in contrast, countries having a higher level of budget balance are likely to provide improved water source to a larger proportion of their people. The results of the two-stage least squares estimations are reported in Panels 2 and 3 of Table 2.10 In Panel 2, the Gini coefficient is used as the instrumental variable and the estimated coefficients of the fiscal capacity measure are positive and statistically significant. If the percentage of population having access to improved water source is adopted as the instrumental variable in Panel 3, the estimated coefficients of the fiscal capac9 As shown in Table 1, legal origins and religious composition do not have a significant impact on the strength of capital regulation. Thus, both improved water source and bank capital regulation are unlikely to be determined by the same underlying fundamental determinants of institutional quality. 10 Because the data on the Gini coefficient and the percentage of population with access to improved water source are not available for some countries, the sample size in the two stage least squares regressions is reduced.

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Table 2 Fiscal capacity and other determinants of capital adequacy regulation Panel 1: Explaining Overall Budget Balance/Total Bank Assets Gini coefficient Overall budget balance/ Total bank assets Overall budget balance/ Total bank assets

Access to improved water source

−0.0041* (0.0023) 0.0091** (0.0044)

Constant term

Number of observations

Adjusted R 2

0.011 (0.083) −0.90** (0.40)

90

0.019

89

0.098

Panel 2: IV Regressions with Gini Coefficient as IV Dependent variable

A (1)

A (2)

A (3)

B (4)

B (5)

B (6)

Overall budget balance/Total bank assets # of observations First stage adjusted R 2 p-value of first stage F -test p-value of Hausmann test

4.47** (1.79)

5.37** (2.63)

8.00** (3.65)

24.36*** (8.11)

19.03* (9.67)

23.71** (10.29)

49 0.070

47 0.042

27 0.15

65 0.0043

62 0.041

55 0.15

0.038

0.076

0.0001

0.17

0.054

0.0001

0.77

0.091

0.85

0.50

0.38

0.26

Panel 3: IV Regressions with Percentage of Population Having Access to Improved Water Source as IV Dependent variable

A (1)

A (2)

A (3)

B (4)

B (5)

B (6)

Overall budget balance/Total bank assets # of observations

2.36** (1.08)

3.58 (2.39)

11.59 (8.92)

6.16** (2.44)

2.91 (4.84)

7.78* (4.08)

53

49

21

60

56

50

0.19

0.18

0.091

0.20

0.18

0.091

0.0033

0.0004

0.0007

0.0001

0.0003

0.0007

0.74

0.89

0.96

0.89

0.22

0.71

First stage adjusted R 2 p-value of first stage F -test p-value of Hausmann test

Notes for Panel 1. (1) The dependent variable is the ratio of overall budget balance to total bank assets (2) Robust standard errors are presented in brackets. Notes for Panels 2 and 3. (1) The dependent variable is the index of bank capital funding regulation (A) and the index of bank capital risk adjustment regulation (B), respectively. (2) The regressions in columns (1) and (4) include a constant term; the regressions in columns (2) and (5) contain a constant term and a simple conditioning information set consisting of the log of GDP per capita, French, German, Scandinavian, and socialist legal origins, Protestant, Catholic and Muslim fraction, and latitude; the regressions in columns (3) and (6) contain a constant term and a full conditioning information set consisting of the simple set plus the log of GDP, bank deposits/GDP, volatility of GDP growth rate, and number of banks per thousand people. (3) Robust standard errors are presented in brackets. * Statistical significance at the 10% level. ** Idem, 5%. *** Idem, 1%.

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ity variable are often significant. However, the results are not as consistent as those in Panel 2. We also perform a Hausmann test for the null hypothesis that the differences in the coefficients between the instrumental variable regressions and the corresponding ordinary least squares regressions are not systematic. This null hypothesis cannot be rejected at the conventional statistical significance levels in all cases. In other words, from a purely statistical perspective, we cannot say that instrumental variable regressions are necessary. Hence, the potential concern about the endogeneity of the fiscal capacity variable is mitigated by these results. So far, we have used the ratio of overall budget balance to bank assets to gauge fiscal capacity. To test the robustness of our findings, we adopt alternative measures of fiscal capacity. In addition to using surplus revenue to finance bank bailouts, the government can also raise funds by borrowing through sovereign debt. We employ two measures of the borrowing capacity of governments in different countries. We first utilize the ratio of central government debt to GDP. The implicit assumption is that, if a government already has a large amount of borrowing, it is more likely to be close to the upper limit of its capacity to repay sovereign debt. Thus, such a government is less likely to borrow additional funds. Hence, we treat the ratio of central government debt to GDP as an inverse measure of a government’s ability to borrow to add to its fiscal capacity. In Panel 1 of Table 3, we present regressions of the two bank regulation indices on the ratio of central government debt to GDP and other control variables. Only the regressions for the bank capital funding regulation index produce negative estimated coefficients on the sovereign debt measure, but these are not consistently statistically significant. Perhaps financing bank bailout by raising sovereign debt is not an appealing option because the general public does not expect it to be a profitable undertaking. Next, we consider the gross private capital flow, i.e., the size of private capital flow into and out of a country, scaled by GDP to measure the government’s borrowing capacity indirectly. In a country in which private capital flow is large and active, domestic residents have many investment opportunities abroad; at the same time, foreign investors have considerable opportunities to invest in domestic assets. If a government borrows for bank bailout, the expected return on government debt will be affected adversely. Hence, both domestic and foreign investors are less likely to buy government bonds. Thus, we expect more active private capital flow to diminish the fiscal capacity for bank rescue and to lower the stringency of capital regulation. In addition, a great volume of private capital flow may impose market discipline on banks. If domestic banks are operated recklessly, depositors both at home and abroad can withdraw their money from domestic banks and invest in alternative assets. Such market discipline could substitute partially for government regulation of banks and, thus, reduce the strictness of capital adequacy regulation. Panel 2 in Table 3 presents cross-country regressions of bank capital adequacy regulation indices on the ratio of gross private capital flow to GDP. The results show that a more active capital flow is consistently and statistically significantly correlated negatively with the bank capital risk adjustment index and the bank capital funding regulation index. These results provide support for our theoretical prediction using alternative measures of fiscal capacity.11 As mentioned in Section 1, one argument justifies banking regulation based on explicit deposit insurance. To investigate the importance of our theory relative to that argument, we rerun 11 Reverse causality, i.e., weak bank capital regulation causes capital flight so that gross private capital flows increase, is unlikely to be a major concern. If weak bank capital regulation prompts domestic and foreign residents to withdraw deposits, they can invest in other domestic assets. Even if the domestic and foreign investors choose to invest abroad, the increase in private capital outflow will be offset by the decrease in private capital inflow. Thus, the gross capital flow should not exhibit any appreciable change.

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Table 3 Additional regressions on capital adequacy regulation Panel 1 Dependent variable

A (1)

A (2)

A (3)

B (4)

B (5)

B (6)

Central gov’t debt/GDP # of obs. Adjusted R 2

−0.0075** (0.0036) 66 0.031

−0.0059 (0.0049) 64 0.072

−0.0063 (0.0066) 37 −0.11

0.0015 (0.0051) 84 −0.011

0.0011 (0.0045) 81 0.065

0.0031 (0.0050) 74 0.047

Panel 2

Gross private capital flow/GDP # of observations Adjusted R 2

A (1)

A (2)

A (3)

B (7)

B (8)

B (9)

−0.47* (0.27) 84 0.069

−0.65** (0.32) 79 0.12

−0.36 (6.31) 40 −0.33

−0.86* (0.46) 97 0.0019

−1.25*** (0.43) 93 0.029

−1.04** (0.43) 82 0.16

Panel 3

Overall budget balance/Total bank assets Explicit deposit Insurance dummy # of observations Adjusted R 2

A (1)

A (2)

A (3)

B (4)

B (5)

B (6)

1.54*** (0.29)

1.61*** (0.36)

1.65*** (0.41)

2.18*** (0.72)

1.47 (0.97)

2.15** (0.93)

0.033 (0.35) 42 0.087

−0.039 (0.46) 41 0.0083

−0.24 (0.59) 38 0.15

−0.15 (0.43) 81 0.029

−0.63 (0.50) 79 0.051

−1.06 (0.64) 77 0.049

0.75*** (0.28) 1.41*** (0.23)

0.79*** (0.29) 1.44*** (0.38)

−0.42 (3.01) 1.37** (0.59)

1.30*** (0.39) 2.64*** (0.73)

1.29*** (0.48) 1.65 (1.10)

1.12* (0.60) 2.50*** (0.90)

57 0.12

56 0.16

33 −0.14

76 0.098

75 0.10

71 0.11

Panel 4 Real deposit Interest rate Overall budget balance/Total bank assets # of observations Adjusted R 2

Notes. (1) The dependent variable is the index of bank capital funding regulation (A) and the index of bank capital risk adjustment regulation (B), respectively. (2) The main independent variable is the ratio of central government debt to GDP in Panel 1, gross private capital flow to GDP in Panel 2, overall budget balance to total bank assets and explicit deposit insurance dummy in Panel 3, and the real deposit rate and overall budget balance to total bank assets in Panel 4. The regressions in columns (1) and (4) include a constant term; the regressions in columns (2) and (5) contain a constant term and a simple conditioning information set consisting of the log of GDP per capita, French, German, Scandinavian, and socialist legal origins, Protestant, Catholic and Muslim fraction, and latitude; the regressions in columns (3) and (6) contain a constant term and a full conditioning information set consisting of the simple set plus the log of GDP, bank deposits/GDP, volatility of GDP growth rate, and number of banks per thousand people. The regressions are estimated using Ordinary Least Squares. (3) Robust standard errors are presented in brackets. * Statistical significance at the 10% level. ** Idem, 5%. *** Idem, 1%.

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the regressions of Table 1 by adding a dummy variable for an explicit deposit insurance scheme in Panel 3 of Table 3. If deposit insurance is the primary justification for banking regulation, the estimated coefficient of the dummy should be statistically significant, while the coefficient of fiscal capacity should lose statistical significance. The regressions demonstrate that the ratio of overall budget balance to total bank assets remains consistently statistically significant, while the deposit insurance scheme dummy produces no statistically significant effects. In unreported results, we add a deposit insurance dummy to regressions using alternative government borrowing capacity measures and obtain qualitatively equivalent results. 5. Empirical tests of additional predictions of the model Our theory suggests a positive relationship between the deposit rate and the stringency of banking regulation. In view of the substantial variation in inflation rates across countries over years, we use real deposit rates calculated by subtracting the inflation rate from the nominal deposit rate. In Panel 4 of Table 3, we use the average real deposit rate over the period from 1980 to 1997 as our main independent variable. To investigate whether the deposit rate has an independent effect on bank regulation beyond that of fiscal capacity, we control for the ratio of the overall budget balance to total bank assets. We find that a higher real deposit rate is associated with more rigorous bank capital risk adjustment regulations and bank capital funding regulations in support of our theoretical prediction. Proposition 8 links the salvage value of the bank’s investment projects that need refinancing and the overall average rate of return on all investment projects to banking regulation. Exact data for these variables are difficult to obtain in cross-country analysis. Thus, we use macroeconomic conditions as a proxy. In a booming economy, banks have numerous profitable projects so that the above two variables are likely to be large. Obviously, the reverse situation applies in an economic recession. We took the average GDP growth rate in the period from 1980 to 1997 or from 1990 to 1997 as a measure of macroeconomic conditions and did not find any statistically significant impact on capital regulation indices. However, the time-series changes in the stringency of capital regulation in some countries provide suggestive evidence. Wells (2002) and Vietor and Evans (2005) give a vivid description of how the stringency of banking regulation varies with macroeconomic conditions in Japan. In Japan’s economic miracle in the post-war era up to the early 1990s, banks played a central role in financing corporations but they were also subject to serious SBC. Because banks’ investment projects remained profitable during periods of high GDP growth, the capital adequacy regulation was not stringent. However, the bursting of the bubble economy in the early 1990s slowed GDP growth and led to a massive bad-debt problem to banks. Nonetheless, the Japanese government still committed to rescuing most of the banks in financial distress. In January 1998, the government announced a 30 trillion Yen stabilization package to support weak banks. Thus, the SBC on banks coexisted with declining profitability of banks and firms. In response, Japan tightened banking regulations. In April 1998, “prompt corrective action” measures were introduced to protect a bank’s capital adequacy ratio. Banks operating solely within Japan were forced to have at least a 4% ratio and internationally active banks were required to have a ratio of 8%. Failure to meet these standards would require a management improvement plan or, in more severe cases, bank restructuring. As Huang (2002) documents, Korea has similar experience. In the high-growth period from 1993 to 1997, the Korean government granted more autonomy to banks and maintained lax restrictions. Prominent among the latter was the inadequate provisioning for loan losses, which led to insufficient capital adequacy. Compared with other OECD countries, the non-performing loan

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classification standard in Korea was lax. For example, the Korean tax code discourages prudential practices. Adequate provisioning for losses is penalized by the tax code; loan loss reserves over 2% of total loans are not tax deductible. In 1995, the government loosened provisioning requirement by lowering the amount required for doubtful loans from 100 to 75%. The onset of the Asian financial crisis caused profitability in the corporate and banking sectors to drop. However, the Korean government did not allow banks to go bankrupt. The recession and the SBC on banks prompted the Korean government to strengthen banking regulations. Specifically, reporting of consolidated financial statements was made mandatory, capital adequacy requirements were enforced strictly, and adequate provisions for loan losses were encouraged. These two examples suggest that banking regulation tends to be strengthened during periods of economic slowdown. 6. Conclusion In this paper, we attempt to identify the fundamental cause of and investigate possible institutional solutions to the SBC on banks. We argue that banks faced a hard budget constraint in the laissez-faire banking era. However, the rise of modern governments led to the imposition of an SBC, which in turn resulted in a moral hazard problem for banks. We illustrate that prudential banking regulations serve as an institutional remedy for the symptoms of banks’ SBC. Our theory and empirical evidence suggest that when the SBC problem is more severe, banking regulation is more likely to be imposed and, when in place, is likely to be stricter. In a cross-country empirical analysis, we show that when the government has a larger fiscal capacity and, thus, is more likely to bail out banks, bank capital regulation is more stringent. Our theory also has policy implications for regulating different types of bank. Typically, state-owned domestic banks, nonstate-owned domestic banks and foreign banks coexist in an economy, especially in a transition country. State-owned domestic banks often bear the social responsibility of supporting government-administered projects. They enjoy the top priority in receiving bailout subsidy from their owner, i.e., the domestic government, and, thus, they face the most severe SBC problem. Relative to state-owned banks, nonstate-owned domestic banks are less related to the domestic government and have lower priority in obtaining government rescue in case of insolvency. Although foreign banks take domestic deposits, their bank capital is owned by foreigners, and their parent banks may rescue them if they fall into financial distress. Hence, foreign banks are a less concern than domestic banks to the domestic government. Based on the different severity of the SBC problem that different types of bank face, the domestic government is advised to impose the strictest prudential regulations on domestic state-owned banks, less strict regulations on domestic nonstate-owned banks, and the most lax regulations on foreign banks. Furthermore, our study suggests that it is beneficial to open domestic banking industry to foreign capital by allowing foreign banks, especially those large-scale multinational banks, to enter transition economies. The obvious benefits already widely discussed include that domestic banks can acquire managerial techniques from multinational banks by either direct information flow or luring senior executives of the latter to work for the former. In addition, the entry of foreign banks increases the banking industry competition, improving the operational efficiency of domestic banks. More importantly, implied by our analysis, attracting multinational banks can enhance social welfare at low regulatory costs. Multinational bank headquarters typically cannot expect their foreign subsidiaries to be bailed out by foreign governments and therefore have strong commitments to the solvency of their foreign subsidiaries. As a result, domestic governments can channel most of their regulatory resources into domestic banks to improve their efficiency. Hence, encouraging foreign bank entry allows transition economies to

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achieve a higher social welfare level through an expanding banking industry at a low regulatory cost. Acknowledgments We are deeply indebted to John P. Bonin and three anonymous referees for their comments that helped improve the paper substantially. We would also like to thank Chun Chang, Tie Su, Tim Zhu and seminar and conference participants at the CCER of Peking University, City University of Hong Kong, HKUST, the Chinese Academy of Social Sciences (CASS), Stockholm School of Economics, Tsinghua University, the American Economic Association annual meeting 2004, the 2005 Summer Workshop on Industrial Organization and Management Strategy at Beijing, and China International Conference in Finance 2005 for comments and suggestions. Excellent research assistance by David Yuen, Iris Pang, Li Tao, and Wang Lanfang and financial support from the Research Grant Council of Hong Kong SAR (RGC HKUST6224/02H, RGC HKUST6072/01, and RGC CUHK4203/02H) are gratefully acknowledged. Appendix A. Mathematical appendix Proof of Proposition 6. Changes in f , n, and e affect d G and d E through their impact on q. We know that q = E(Q | e, d, p, n) = Q dG(t). As f increases, ceteris paribus, i.e., given that p, e, and n remain unchanged, Q increases. With perfect foresight, q also increases. As n increases, given that f , e and p remain unchanged, Q decreases because more banks are likely to require refinancing and given fiscal resources must accommodate the needs of more banks. Thus, ex ante, q decreases as well. Alternatively, as e increases, the amount of refinancing required for each bank increases. With given f , p and n, the given fiscal resources can bail out a smaller percentage of total bank assets. As a result, q and Q decrease. We next examine the impact of changes in q on capital adequacy regulation. Given a myopic equilibrium, the changes in f , n, and e affect those in d G and d E through q. From the bank manager’s objective function, we obtain the first order condition for his optimal choice of p as: (kpy)p =

(1 + r)d B + (q − 1) . 1+d α

(A.1)

From the social welfare function associated with a bank of e(1 + d) unit of capital, we derive the following condition: ∂SW = U + (1 + d)Up pd ∂d

 (1 + r)d 1 = U + (1 + d) + 1− (1 − q)B − q(z − x) pd , 1+d α

(A.2)

where we use (A.1) to simplify in (A.2). Furthermore, we have: ∂ 2 SW = Uq + Up pq + (1 + d)Upq pd + (1 + d)Up pdq . ∂d∂q

(A.3)

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From (A.1), we can obtain: (1 + r) < 0; (1 + d)2 (kpy)pp B < 0; pq = α(kpy)pp pd =

(A.4) (A.5)

and pdq = −

(1 + r) B B (kpy)ppp pd = − (kpy)ppp < 0. α[(kpy)pp ]2 α[(kpy)pp ]3 (1 + d)2

Also, from the expression for U , we can write:

 (1 + r)d 1 Up = + 1− (1 − q)B − q(z − x); 1+d α   Uq = (1 − p) (z − x) + B > 0; and Upq

 1 = 1− B − (z − x) < 0. α

(A.6)

(A.7) (A.8)

(A.9)

Thus, if B + (z − x) is small enough and B/k is large enough, (A.7) is positive and bounded below from 0 and the term (1 + d)Up ppq will be negative and dominate all other terms in the right-hand side of (A.3), which will become negative. Hence, if q is higher, the social-welfaremaximizing d G decreases. Intuitively, Uq can be either positive or negative due to two effects. On the one hand, an increase in q may increase U because it is more likely that ex post profitable projects are refinanced. On the other hand, an increase in q may decrease U because it makes the bank manager less fearful of losing the private benefits of control, B, so that he may choose riskier investments with lower p. If the salvage value, z − x, is not very high, the second effect dominates the first and Uq is negative. Clearly, Up is positive because an increase in p indicates better quality investment projects, which increases social welfare. Moreover, pq is negative because a higher q encourages more reckless investment. The last two terms in Eq. (A.3) are shown to be negative later under our technical assumptions. Thus, we show that, if q is higher, the government’s optimal d, d G , should be smaller, which implies a more stringent capital regulation. This makes intuitive sense because a higher q indicates a higher likelihood of bailout and promotes more reckless investments. Furthermore, the impact of higher q on the unregulated equilibrium d E is ambiguous because E d may change either way due to two opposing effects. On the one hand, a higher q makes the bank manager more reckless, lowers p, and, other things being equal, lowers the supply of deposits. On the other hand, if q is higher, the chances of government bailout of depositors are higher, which increases the supply of deposits. In sum, if q is higher, the p = p(d) curve shifts downward due to a softer budget constraint and the supply curve d = d(p) shifts outward. However, if the deposit supply schedule is relatively flat, i.e., insensitive to the real deposit rate, the second effect is small and dominated by the first. In other words, if β is small enough, the change in d E is limited. Thus, the effect on d G dominates. As a result, if f is higher, or if n or e or both are lower, q is higher and d G is lower, which implies that capital regulations are more likely and more stringent.

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To summarize our proof, we find that there exist h, m, and β such that (1) if c < h, k/B < m, and β < β, if f is higher, it is more likely that capital adequacy regulation will be necessary for social welfare maximization; (2) if c < h, k/B < m, and β < β, if n or e or both are higher, it is less likely that capital adequacy regulation will be necessary for social welfare maximization; (3) if c < h, if banking regulation is necessary, the higher f , or the lower n or e or both, the tighter should be the capital adequacy requirement. Appendix B. Data appendix Index of Bank Capital Funding Sources Regulation Constructed on the basis of the following questions: Can assets other than cash or government securities be used to increase bank capital (no = 1, yes = 0)? Can borrowed funds be used for bank capital (no = 1, yes = 0)? The raw data are from the World Bank data set of “Bank Regulation and Supervision.” We use the first principal component of this index in statistical analysis. Index of Bank Capital Risks Adjustment Regulation Constructed on the basis of the following questions: Is capital adequacy ratio risk-weighted in line with Basle guidelines (yes = 1, no = 0)? Does the ratio vary with a bank’s credit risk (yes = 1, no = 0)? Does the ratio vary with market risk (yes = 1, no = 0)? Before minimum capital adequacy is determined, is the market value of loan losses deducted from capital (yes = 1, no = 0)? Before minimum capital adequacy is determined, is the unrealized securities losses deducted from capital (yes = 1, no = 0)? Before minimum capital adequacy is determined, are the unrealized foreign exchange losses deducted from capital (yes = 1, no = 0)? The data are from the World Bank data set of “Bank Regulation and Supervision.” We use the first principal component of this index in statistical analysis. Overall Budget Balance/Total Bank Assets Constructed as the ratio of the overall budget balance/GDP to total bank assets/GDP, averaged over 1985–1997. Data on total bank assets/GDP are from the World Bank data set of “Bank Regulation and Supervision,” while data on overall budget balance/GDP are from the World Bank data set of World Development Indicators CD ROM. Log of GDP per capita Logarithm of GDP per capita in constant US dollars, average over the period 1970–1995. The data are from World Bank data set of World Development Indicators CD ROM. Legal Origins The legal origin or legal tradition of the company law or commercial law of each country is identified. There are five categories of legal origins: (1) English common law legal origin; (2) French civil law legal origin; (3) German civil law legal origin; (4) Scandinavian civil law legal origin; and (5) Socialist legal origin. The data are from La Porta et al. (1999). Religious Composition The percentage of the population of each country that followed the three most widely spread

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religions in the world, i.e. Protestant, Catholic and Muslim. The numbers are in percentage terms. The data are from La Porta et al. (1999). Latitude The absolute value of the latitude of the country, scaled to take values between 0 and 1. The data are from La Porta et al. (1999). Log of GDP Logarithm of GDP in constant US dollars, average over the period 1970–1995. The data are from World Bank data set of World Development Indicators CD ROM. Bank Deposits/GDP The ratio of total bank deposits to GDP, averaged over 1985–1997; data are from the World Bank data set of “Bank Regulation and Supervision.” Volatility of GDP Growth Rate The standard deviation of yearly real GDP growth rate over the period 1970–1997; the data on real GDP (GDP in constant US dollars) are from the World Bank data set of World Development Indicators CD ROM. Number of Banks per Thousand People The number of banks divided by population; the data on the number of banks are from the World Bank data set of “Bank Regulation and Supervision,” while the data on the population are from the World Bank data set of World Development Indicators CD ROM. Explicit Deposit Insurance Dummy A dummy variable that takes value one when a country has deposit insurance scheme and zero if otherwise. The data are from the World Bank data set of “Bank Regulation and Supervision.” Percentage of Population having Access to Improved Water Source: The data are from the World Bank data set of World Development Indicators CD ROM. The data are for year 1990. Gini Coefficient Average of the data from Barro–Lee data set and those from World Development Report (1998/1999 issue). Gross Private Capital Flow/GDP Gross capital flow as fraction of GDP, averaged over the period 1980–1997; data are from the World Bank data set of World Development Indicators CD ROM. Real Deposit Interest Rate Calculated as the difference between deposit interest rate and inflation rate. The inflation rate is calculated as the year-on-year growth rate in the consumer price index. Data on (nominal) deposit interest rate and consumer price index are from the World Bank data set of World Development Indicators CD ROM.

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Table A.1 Summary statistics Variable name

Number of obs.

Mean

Standard deviation

Minimum

Maximum

Index of bank capital funding sources regulation Index of bank capital risks adjustment regulation Overall budget balance/Total bank assets French legal origin German legal origin Scandinavian legal origin Socialist legal origin Protestant fraction (%) Catholics fraction (%) Muslim fraction (%) Latitude Bank deposits/GDP Volatility of GDP growth Number of banks per thousand people % of people having access to improved water source Gini coefficient Ethnolinguistic fractionalization Deposit insurance scheme dummy

104

−0.052

1.06

−1.12

1.80

109

0.0082

1.96

−2.88

3.50

129

−0.21

0.68

−5.37

0.89

95 95 95 95 95 95 95 95 150 187 111

0.33 0.053 0.042 0.22 15.11 32.27 16.19 0.35 0.36 5.58 0.21

0.47 0.22 0.20 0.42 23.64 35.75 30.71 0.20 0.35 4.05 1.05

0 0 0 0 0 0 0 0.011 0.014 0.21 0.002

1 1 1 1 96.6 97.3 99.9 0.72 2.88 33.73 10.50

125

77.65

21.76

20

100

103 78

38.19 0.26

8.97 0.26

20.50 0

62 0.86

92

0.55

0.50

0

1

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