Financial stability and risk allocation under varying levels of competition

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(1)PONTIFICIA UNIVERSIDAD CATOLICA DE CHILE INSTITUTO MAGISTER EN. DE ECONOMIA ECONOMIA. TESIS DE GRADO MAGISTER EN ECONOMIA Wander, Paul Johnson Julio, 2013.

(2) PONTIFICIA UNIVERSIDAD CATOLICA DE CHILE INSTITUTO MAGISTER EN. DE ECONOMIA ECONOMIA. Financial stability and risk allocation under varying levels of competition. Paul Johnson Wander. Comisión Prof. Rodrigo Fuentes Prof. Francisco Rosende Prof. Matías Tapia. Santiago, julio de 2013.

(3) Financial stability and risk allocation under varying levels of competition Paul J. Wander November 21, 2013. Abstract Developed countries vary widely in terms of levels of competition exhibited within the banking sector. This paper measures the empirical eects of competition on nancial stability using the Lerner index as a proxy for competition.. Theoretically, competition may. inuence the probability of a banking crisis via the charter value channel or the risk allocation channel, the latter of which provides an ambiguous result. Logit probability models show that competition may decrease stability, especially when deposits are guaranteed by government insurance programs, and when the non-bank nancial sector is large. Risk allocation is shown to be negatively correlated with competition, a fact that supports the conclusion that the risk allocation channel is dominated by the notion that increased competition encourages risk taking at the bank level. Nonetheless, the results should be tempered by the fact that the competition-stability relationship appears to depend greatly on other factors, including the regulatory system and non-bank competitors.. 1.

(4) Introduction Financial markets are considered imperative to long term growth (Levine 2004), but are also a key source of volatility. Bank failures tend to have outsize real eects relative to failures in other industries.. Bank sector regulators, there-. fore, face a distinct challenge, and must consider stability as well as competition.. The literature on whether or not these two policy goals are distinct is. divided between a competition-stability view, which holds that increasing competition increases stability, and the competition-volatility view, which holds that increased competition yields increased volatility.. Theoretical models, ranging. from the watershed bank-run model of Diamond and Dybvig (1983) to the more recent work of Allen and Gale (2004) yield a broad range of conclusions on the eects of competition on stability. Empirical work, at the bank level as well as at the country level, is equally inconclusive across a wide range of sample periods. This paper adds to the literature by considering the fact that the eect of bank sector competition on stability depends on interactions with several other characteristics of a countries banking sector, including the existence of deposit insurance and the extent to which the banking sector competes with non-bank nancial sector. An important part of this paper is the construction of a crisis database and the empirical methodology. Reinhart & Rogo (2010) provide a historical crisis database for 70 countries from 1800-2010.. I use their classication of. banking crisis, which includes two types of events, either 1) bank runs that lead to the closure, merging, or takeover by the public sector of one or more nancial institutions; or 2) if there are no runs, the closure, merging, takeover, or large-scale government assistance of an important nancial institution (or group of institutions) that marks the start of a string of similar outcomes for other nancial institutions. I use variants on this data for robustness checks. I use logistical regression analysis, including variations with xed and random eects. These models use macroeconomic parameters, nance market conditions, and bank structure to calculate the probability of country crisis in year. t.. i. experiencing a banking. I control for other relevant banking structure elements, use lags. to assuage concerns for reverse causality, and test several relevant interactions. The key variables is the Lerner index, which measures market power. The analysis suggests that competition, sua sponte, is neither denitively stability-inducing nor stability-reducing, but instead tests the hypothesis that other policies and outcomes may combine with competition to deleterious eect. First, consider briey why the subject warrants further study: banking crisis are a frequent and costly phenomenon that over the last 30 years have occurred with approximately equal frequency in rich and poor countries alike.. Motivation The data show that banking crises are frequent occurrences across all country groups. The following gure shows a count per year of countries with banking. 2.

(5) crisis, as dened by Reinhart and Rogo (2010), for a group of 70 countries (listed in Figure 1 of the Appendix).. The countries studied comprise a wide. range of developed and developing states, and a signicant percentage of world GDP. Notably, only one country analyzed by Reinhart & Rogo has not experienced a banking crisis in recent decades: Mauritius. The gure alludes to an additional point: if ination was the chief economic problem of the pre-1984 period, nancial crises. 1 seem to be the dening problem of the subsequent decades.. Indeed, in the period dened as the Great Moderation, dened as the post-1984 period in which key macroeconomic variables such as output and ination experienced diminished volatility across much of the developed world, the number of banking crises increased signicantly.. Such crises represent a signicant cost, both in terms of a negative deviation from output trends and government balances. The eects of banking crises also often spread beyond the nancial sector. For example, the scal cost of the Thai crisis of 1997-98 was reportedly 35 percent of that nation´s GDP. Additionally, the government balance sheet is hit on both ends, with revenues contracting and expenditures expanding.. The response to such crisis are wide-ranging,. but typically involve a costly bailout of the banking sector. Bailouts occur in many forms, through the purchase of bad loans, forced or facilitated mergers, or government takeovers. Reinhart and Rogo (2008) estimate that government debt increases by 86 percent, on average, after a banking crisis Haldane and Alessandri (2009) report that the sub-prime crisis in the US cost 73 percent of GDP in terms of government response, and the IMF reports the total costs at $1.4 trillion USD. While these actions are costly in terms of scal impact, the actions also have signicant aects on banking incentive structures. An important cost associated with banking crises that is often overlooked are the policy responses.. Market structure and regulatory policy have signicant. impact on the incentives to take on risk in the banking industry.. While a. detailed analysis of the pros and cons of regulatory responses to crisis is not the objective of this paper, the particular case of deposit insurance is addressed below.. Other response, such as a government bailout of a failing bank, for. example, entail both scal costs and costs to the incentive structure of the. 1 Throughout. the paper the phrases nancial crisis and banking crisis are used inter-. changeably. This is an oversimplication, as all banking crisis belong to the set of nancial crises but not vice versa. However, in both the literature on the subject and in popular media in general the terms are used interchangeably.. 3.

(6) entire banking sector. Bank managers may choose dierent risk levels for loans if they have information that the government will bail them out in event of failure. The policy-response cost suggests an alternative way of thinking - that banking crises are a part of nancial development and any attempt to avoid them would be necessarily inecient. The theoretical argument to be made in defense of banking crises, or more specically, that banking crises are ecient and maybe even necessary despite their costs. Allen & Gale (2003 & 2004) show that bank default is optimal in the case of complete contracts and perfect competition. In practice the argument that nancial crisis are a natural part of nancial development has weight amongst economists and policy makers alike, as bank bailouts typically rile sects of both sides of the political spectrum. For the purposes of this paper, however, banking crises are considered costly, and measures to avoid them may include more or less regulation. Indeed, the study of nancial market regulation leaves much to be desired given the frequency and costs of banking crises in recent decades. Despite signicant cost incentives nd viable policy solutions to bank-sector instability, there appears to be no clear state-of-the-art policy in terms of nancial sector regulation. In fact, banking sectors tend to be quite diverse in terms of regulation and outcomes show a wide degree of variation in terms of sector concentration and competition across time and countries. Even amongst industrialized countries, there is a wide degree of variation in terms of banking sector concentration and competition.. In the late 1980s and early 1990s, the. concentration of the top three banks (measured in terms of assets and referred to as C3) was high, hovering around 80 percent in the sample of 66 countries used in this paper. However, in the last decade that average has fallen to around 50 percent. The United States is an example of a country with traditionally low concentration levels, maintaining a top-3 concentration of below 20 percent on average over the last 20 years. New Zealand, on the other hand, has very high average concentration with C3 at over 90 percent of assets. The story is very similar for several dierent measures of competition. While industrialized countries may claim to have better institutions for monetary and scal policy development and implementation, policies related to nancial markets have lagged behind in terms of results. In their broad study of world nancial systems, Cihak, Demirguc-Kunt, Feyen and Levine (2012) show that high-income countries have nancial systems and institutions that outperform their lower-income counterparts in terms of depth, access, and eciency. Nonetheless, nancial sectors in high-income countries are no more stable (and oftentimes less so) than their lower-income counterparts.. In fact, the regres-. sion analysis in the subsequent sections will show that level of GDP per capita is rarely signicantly correlated with the probability that a banking crisis will occur. As Reinhart and Rogo (2008) note, banking crisis are an equal opportunity menace, meaning that nancial instability has had real eects in terms of output and employment in both the emerging and industrialized world. This fact, combined with the observation that banking crises are a relatively common modern phenomenon, makes their study of particular interest.. 4.

(7) There is an extensive literature on the eects of various nancial market characteristics on growth.. While growth and volatility may be related, this. paper will not address the question of which nancial market characteristics are best for growth. Instead, I will evaluate which characteristics seem to matter for instability and which do not. There is also a signicant debate on whether or not crises and instability produce eciency losses.. Despite the fact that. failures, bank or otherwise, may have eciency improving eects, part of the motivation of this paper is that crises are negative events. Still, an important corollary to this is the possibility that crisis-preventing regulations that may have unintended consequences on risk allocation. Historically, the idea that competition is necessary for an ecient banking system gained signicant credence in the 1970s and 1980s. In the US, for example, between 1975 and 1992 restrictions on intrastate branching were largely eliminated and in 1994 the Reigle-Neal Interstate Banking and Branching Efciency Act did away with much of the state-level protection of the banking industry. It is not clear whether this preference for competition came from a desire for increased eciency in spite of less stability, or whether competition was seen to have a direct stabilizing eect.. Regardless, the result was a sig-. nicant deregulation, which can be seen as an increase in competition in the data. The gure below shows that bank sector concentration worldwide averages have declined from high levels in the late 1980s and early 1990s and have. 2. since stabilized.. This study takes place against the backdrop of large changes in the structure of the banking industry. Within the sample period, information-technology developments have revolutionized the loaner/loanee relationship through changes in production technology, distribution channels, and many new products have become available.. Automated teller machines, which date to the 1970s, have. become ubiquitous in the developed world, and may make competition easier by allowing banks to access local markets without building a branch. Bikker and Bos (2005) suggest specically that technological change has resulted in lower prot margins even if concentration levels remain the same.. For this reason,. concentration levels are not thought to be a good measure of competition for the purposes of this study. The traditional brick-and-mortar branch bank system has been made all but obsolete by internet banking. Banks have reacted. 2 Concentration. is shown here because data for more precise indicators of competition are. only available beginning in 1996.. 5.

(8) in dierent ways to increased competition but most notably through the development of new products. Likewise, the non-bank nancial sector has grown signicantly in many countries. New policies have been instituted or proposed which may interact with the competition eect in very dierent ways. The paper continues in the following fashion. The rst section outlines the theoretical reasons why competition is relevant to a discussion on stability, and highlights previous work in this area. The second section reviews the empirical literature and the third section presents the data and methodology utilized here. Section 4 presents the empirical results and a discussion of their relevancy within the literature. In section 5 I test interactions between competition levels and other key variables using similar methodology and section 6 concludes the empirical work by testing a possible channel by which competition could aect stability.. Theoretical Considerations The Arrow-Debreu theorems of welfare economics show that competition is a socially optimal result under certain general conditions. Allen and Gale (2003) use a general equilibrium model of nancial intermediaries to show that the same conclusions apply specically to the banking sector, but with important caveats. Most importantly, perfect competition is socially optimal for nancial intermediaries in the presence of complete contracts. Because nancial market contracts are not contingent upon every possible state of the world, (contracts are incomplete) default is an option. Allen and Gale (2003) show that under certain conditions regarding the treatment of a defunct rms assets (namely that they are divided proportionally amongst stakeholders), perfect competition remains constrained-ecient.. As the model does not consider unemployment. and other bankruptcy costs, periodic bank failures can be described as ecient. The authors do note, however, that a more realistic measurement of the costs associated with bank failures may create a role for pro-stability policy measures. Certainly the above-mentioned costs of crises suggest that nancial instability is not a minor problem. This paper goes on to show that the solution to this problem may be rife with unintended consequences due to the complex way in which competition aects stability. Competition aects stability in the banking sector through two main channels, risk allocation and charter value. Charter value refers to the present value of the stream of expected prots, and the charter value paradigm holds that as competition increases, so decrease interest margins which in turn lower the charter value. This follows from the theoretical notion that in competitive markets prices are equal to marginal cost.. While there are certainly many dierences. between modern banking markets and this simplistic view, the intuition that competition decreases a rm's charter value seems to hold. Lower charter values, ceteris paribus, leave banks more exposed to shocks and therefore more vulnerable to crisis. Banks operating near the margin have fewer resources and a smaller capital cushion with which to maintain a positive balance sheet given. 6.

(9) a negative shock to bank borrowers. In practice, this conclusion may be dubious, as regulations on required assets may prove more restrictive than expected prot levels. Still, evidence suggest that, especially in the last decade, banks tend to hold more assets than required. Berger et al (2008) show that in the US banks have held stronger than necessary capital ratios, and that increased prots are a main reason for doing so. A stronger line of thinking suggests that in the absence of signicant charter value, bank leadership are more likely to take on risk as there is less to lose. The charter value channel therefore suggests a weakly negative relationship between competition and stability. However, changes in competition levels aect more than prot margins. The risk allocation channel refers to the fact that an increase or decrease in competition may cause banks to adjust loaning practices and thereby change overall levels of risk and its distribution. Many theoretical models consider the plight of a banker facing an increase in competition, and the results often depend on model specics.. The eect of competition on stability via the risk allocation. channel is therefore uncertain. The specic scenarios under which competition may improve or worsen stability are discussed in detail below.. However, if. competition leads banks to make more risky loan decisions, the risk allocation channel works in the same direction as the charter value channel, and competition should be shown to increase the probability of a banking crisis. If on the other hand, competition leads to more ecient and less risky loan decisions, the two eects work in dierent directions. In this scenario theoretical models have little to say about which eect is dominant. The theoretical and empirical literature on the eect of bank market structure on stability are best grouped by the conclusions reached. On one hand, the competition-stability view suggests that more competitive markets are associated with fewer banking crises. On the other hand, the competitionfragility view suggests that the negative eects of competition dominate and that increased competition is correlated with more unstable systems. The sheer number of contradictory studies in this elds suggests that the underlying theory is complex, and that empirical results should be accepted with great caution. In fact, the number of empirical studies which yield contradictory results suggests that competition may interact with other structural variables. This study contributes at this point in the literature by rst using previously tested methods to determine the eect of competition on the probability of a banking crisis between 1996 and 2010.. I then test specically for interactions between the. levels of competition and other key factors, including the existence of deposit insurance and the size of the non-bank nancial sector. I show that competition has destabilizing results, but only when competition from a non-bank nancial sector is high and only when deposit insurance exists as well.. Literature Previous work on the link between competition and stability in the banking sector can be divided into three categories: theoretical models, bank-level empirical studies, and country panel studies.. 7. In both theoretical and empirical.

(10) work, conclusions on the eect of competition in the banking sector on stability are mixed. Theoretical literature on the banking industry is vast, so here we focus on the intersection between competition and crisis in banking. Stability inducing incentives have long been a subject of great interest to economists and policy makers, in particular in the banking sector. Historically, bank instability has been treated in an ad hoc fashion - with a mix of deposit insurance and bank suspension policies. At the outset of the Great Depression in the United States, the Emergency Banking Act implemented a mandatory bank holiday and provided government relief to distressed banks.. In 2013, Cyprus imposed harsh. capital controls including a daily withdraw limit to prevent a bank run. Economic theory suggests some conclusions on the most eective of these possible policy responses. Deposit insurance, government guarantees of up to a certain level of qualied deposits in approved institutions, is shown to be the optimal policy response to the problem of self-fullling bank runs (Diamond & Dybvig, 1983). Bank suspension is another possible response, but is shown to leave some depositors liquidity constrained in Chari & Jagannathan (1988).. Bhat-. tacharya et al. (1998) show that insurance dominates suspension, provided that the taxes which provide for insurance are only slightly distortionary. Allen and Gale (1998) show that the optimal policy is for the central bank to extend a loan. These results apply generally to post-crisis responses, but do not directly address the long-run role played by competition. The idea that competition may aect the probability of banking crisis has its theoretical base in structure-conduct-performance models (SCP). Bikker and Bos (2005) derive the relationship between market structure and performance for several such models. Generally, they nd that competition tends to improve eciency and reduce prots and thereby charter values.. One problem with. the SCP model is the assumption that all banks react similarly to changes in market structure and therefore all benet similarly.. They also develop a. Cournot model that shows similar results without the drawback of assuming a homogenous response to increased concentration. The authors show that an increase in market share results in more collusive behavior. The conclusions reached in theoretical work tend to favor the stabilizing eect of competition in the absence of potentially moral hazard inducing policies. Demsetz et al. (1996) divide determinants of charter value into market-related and bank-related sources.. This division essentially serves to allow franchise. value to depend on competition, but also on the intrinsic quality of the bank or of the banks clients. They explain how moral hazard encourages banks with low franchise value to take increased risk under the protection of deposit insurance. However rms with high charter value have more to lose. They nd that having high charter value is related to lower risk scores (systemic and rm-level) using OLS with xed and random eects. Boyd, De Nicolo, & Smith (2004) study how monopoly versus perfectly competitive banks perform against a crisis. They nd that uncompetitive markets are more stable if interest rates are high enough.. Farias (2006) also extends. the theoretical bank-run model from Diamond & Dybvig (1983) to show that. 8.

(11) more concentrated banking markets are more susceptible to a run if long term interest rates are low. Asymmetric information causes consumers to interpret concentration levels as a signal of a healthy or unhealthy banking system. Data from 1993-2003 shows that the relationship between bank concentration and the probability of a bank runs is nonlinear. The empirical evidence is equally mixed.. Anginer et al (2012) use bank-. level data from 1997 to 2009 to show that competition in the banking sector is positively correlated with systemic stability.. They suggest that increased. competition encourages banks to take on more diversied risks, which improves the ability to withstand shocks. Schaeck & Cihák (2010) propose that increased competition improves banking eciency, which improves bank soundness. However, they explicitly avoid studying bank markets in which banks may be too big to fail , which they note is a policy that distorts competition. Their conclusions, therefore, are true only under circumstances without bank bailouts. They also use the z-score as a measure of soundness. One branch of literature, based in industrial organization theory, suggests that competition should lead to more ecient lending decisions, which thereby increase stability. Competition can improve stability through dierent channels, namely Zarutskie (2009) nds that specialization is the typical bank response to competition.. When banks focus only on cer-. tain kinds of loans, they gain information more eciently and adjust lending technologies accordingly. Furthermore, Dick & Lehnert (2010) show that competition increases lending productivity and decreases loan loss rates. Claessens & Laeven (2004) conclude that concentration is a poor proxy for competition. Demirguc-Kunt & Detragiache (2002) show that certain policies, namely deposit insurance, competition may have a destabilizing eect. Allen and Gale (2004) extend this conclusion in a theoretical model. Under their framework, if deposit insurance is present, competition tends to weaken bank soundness. In highly competitive systems, in which charter values are low, signicant moral hazard arises due to the insurance of deposits. Hoque, Khan, and Dewan (2011) also observe a relationship between banking crises and the existence of explicit deposit insurance schemes, but note that the country´s development status plays an important role. Less developed countries that use explicit deposit insurance schemes may suer from crises as a result, but this eect dissipates as nations become more developed. Demirguc-Kunt and Huizinga (2012) study the eect of bank size on performance, strategy, and market discipline. They dene absolute size and systemic size, nding that the former presents a trade-o between risk and return, while the latter presents only risk. Rose (2012) analyzes the eect of international nancial linkages on the severity of the 2008-2009 nancial crisis in 85 countries, nding that more nancially integrated economies did not seem to experience more profound recessions. However numerous studies have also found competition to produce banking instability.. Most recently, Beck, Demirguc-Kunt, & Levine (2006) nd that. concentration in the banking sector is linked to stability.. Schaeck, Cihak, &. Wolfe, (2009) on the other hand nd that competition is stability enhancing. 9.

(12) from 1980-2005. Beck, De Jonghe, & Schepens (2011) show that competition can lead to instability depending on several characteristics including activity restrictions in banking, herding in revenue structure, and more generous deposit insurance. If there is a trend in the literature, it is toward conclusions that are based on other existing policy or structural conditions in the banking sector.. This. paper extends that research in particular by testing the special cases of deposit insurance and large non-bank nancial sectors in the following sections.. Data This project benets from the 2012 release of the Global Financial Development Database at the World Bank. Developed by Martin ihák, Asl Demirgüç-Kunt, Erik Feyen, and Ross Levine, this series aggregates annual micro-level data from a variety of sources (including Bankscope, the Financial Access Survey and Financial Soundness Indicators from the International Monetary Fund, and the Findex from the World Bank) for 217 countries.. It includes 73 variables on. depth, access, eciency, and stability in the nancial sector with data ranging from 1960 - 2010.. The panel is not balanced as many observations are. missing especially in the period from 1960-1990.. Nonetheless, there are su-. cient country-year observations to provide regressions with signicant power. This large database is joined with data on crisis indicators and several other country-level databases to yield a sample of 66 countries which are observed between 1996-2010.. Measure of nancial competition Financial market competition is measured by the Lerner index, which is increasing in market power. A higher Lerner index is therefore indicative of less competition. The Lerner index is dened for country. Li,t =. (i). and year. (t)as:. Pi,t − M Ci,t Pi,t. (P ) are calculated as total bank revenue over assets, while marginal (M C)are derived from an estimation of the trans-logarithmic cost function,. Here prices costs. where the value of interest is the derivative of cost with respect to output. The estimations come from Demirguc-Kunt & Peria (2010), who use rm level data from bankscope. The extreme values for the Lerner index are zero, which implies prices are set equal to marginal cost and competition is perfect, and one, which implies full monopoly power.. Data is available between 1996 and. 2010. In estimations the Lerner Index is typically lagged one period to avoid the potential for reverse causality.. However results are fairly consistent with. lagged and contemporaneous values. The Lerner index has been found to be related to other important characteristics of bank market structure that are dicult to observe.. 10. Fang, Hasan,.

(13) & Marton (2011) nd that the Lerner index is correlated with cost and prot eciency using bank-level data. This may suggest that economies of scale are present and dominant in the banking industry.. When the data is aggregated. at the national level, however, any eciency dierences between countries is controlled for by adding a country xed eect to the regression. The Lerner index is used as the key independent variable in this study because it provides the most classic measure of competition - market power. As market power decreases, prot margins should approach zero. Demirgüç-Kunt & Martinez Peria suggest that non-structural measures of competition, like the Lerner index, may provide better information on the nature of competition because instead of inferring the data from structural characteristics like concentration, they are based on observed bank behavior. However, there are other proxies for competition, such as of banking sector concentration and the Boone indicator. Banking sector concentration is typically measured as the percent of total bank assets owned by the top 3 or top 5 banks in a given market. Beck, Demirgüç-Kunt, & Levine (2003) use top-5 concentration, averaged across all periods, to conclude that crises are less likely in more concentrated markets. Concentration is problematic in that it is often taken as a proxy for competition. At the least, it is often assumed that concentration is strictly decreasing in competition. However, Schargrodsky and Sturzenegger (2000) show that in the case of bank competition in products (a la Schumpeter), competition may not be correlated with competition in the classic fashion. Additionally, the measure of concentration is also not very informative about market structure. An example demonstrates a key weakness. Country. 1. has one bank that controls. 75% of assets and several smaller banks with very small shares. Country. 2 has 5. equally-sized banks that together control 75% of that countries banking assets. While these two structures might have very dierent levels of actual competition, their top-5 concentration gures would be equal.. For this reason, this. study does not use concentration as an explanatory variable. Boone (2004, 2008a, 2008b) develops an alternative measure of competition that is based on a relative prots measure.. This so-called Boone indicator is. decreasing in intensity of competition, with the logic being that in more competitive industries, less ecient rms are punished more severely. The Boone indicator is based on the ecient structure hypothesis, which is essentially the survival of the ttest.. Under this hypothesis, we expect that more ecient. banks, banks with lower marginal costs, achieve superior performance in the sense of higher prots at the expense of their less ecient counterparts, and this eect is monotonically increasing in the degree of competition when rms interact more aggressively and when entry barriers decline, (Schaeck & Cihák 2010). The Boone indicator has several problems which limit its use in this study. First, it is a dynamic measure. The value is essential the coecient on marginal cost from a prot regression.. As one cannot test the counter-factual case in. which all banking sectors experience identically sized changes in marginal costs, these regressions probably are not adequate out of sample, yet this is precisely what is proposed in a cross-country panel regression. Schaeck & Cihák (2010). 11.

(14) suggest that endogeneity may be a serious problem in the prot regressions that are used to derive the Boone indicator.. The Boone indicator makes the. following assumptions: 1) that eciency is one dimensional, 2) that eciency is observable, and 3) that rms compete on a level playing eld (Boone, 2008). For these reasons, and because data is limited as this is a relatively new indicator of competition, this analysis does not consider the Boone indicator as a proxy for competition. This is not to say that the Lerner index is problem free. Boone (2008) argues that the relative prot measures provide a more robust measure of competition, since some theoretical models (Amir 2002, Stiglitz 1989) show that increased competition can increase price-cost margins (as measured in the Lerner index). Berger & Mester (1997) and Vander & Vennet (1997) suggest that bank output prices are subject to severe measurement problems.. If the eciency frontier. is stochastic, not all deviations from maximum prot are due to bank-specic ineciency. Additionally, Lerner may not be able to appropriately capture the degree of product substitutability (Vives, 2008).. Still, because better data is. available, and because price margins are the classic denition of competition, this study uses the Lerner index as a proxy for competition.. Foreign and government banks Other key variables on national nancial centers are included for controls. Most importantly, the data set above provides data on the proportion of bank assets that are government and foreign owned. Later, it will be important to control for these variables to be sure the eects measured are due to national banking systems. The incentive structures that exist within state-owned banks are potentially very dierent from the private sector. I expect to observe an increase in the probability of a crisis as the percentage of bank assets in government banks increases. As the data cover a very recent period during which the internationalization of the banking industry has grown signicantly, it is important to control for the percentage of foreign owned banks in a given country. Banks with out-of-country ownership likely respond to dierent incentives than domestically owned banks vis-a-vis competition. More importantly, foreign banks may make risk allocation decisions that depend on international competition levels, rather than domestic competition. Fang, Hasan, & Marton (2011) conrm that foreign banks often operate with dierent restrictions by showing that developed country banks are often at an advantage vis-a-vis domestic banks in developing countries. As this exercise depends on the ability to isolate competition levels by country, it is very important to control for the percentage of assets owned by foreign banks.. Non-performing loans In the nal phase of the empirical analysis, the ratio of non-performing loans to total loans is used to measure the eect of competition on risk allocation. Here, instead of a dummy variable for banking crises, the non-performing loan. 12.

(15) ratio serves as a proxy for bank stability. The loan ratio is commonly used to accurately time nancial crises and presents a more detailed way to analyze the eect of competition on risk distribution. The use of the non-performing loan ratio has several distinct advantages over the crisis dummy variable, namely the fact that it is not binary and helps to isolate the eects of competition on the risk allocation channel. High non-performing loans ratios are highly correlated with crisis periods. However, the loan ratios yields information on the size of the shock to the banking sector without taking in to account the initial conditions. In other words, outside of risk distribution, the ratio of non-performing loans to total loans should not depend on the charter value of a rm, or its available capital.. Two countries may experience similar shocks to borrower ability to. pay, but have diering capital positions. A system with stronger assets held in reserve may survive the shock without a crisis while a less buered system may experience a crisis.. This data is, regrettably, only available from 2005-2010.. While the use of such a short data sample is problematic for many reasons, it is only critical to the nal exercise in this paper and further research should be in this area when more data is available. The use of this data also serves as an additional check for robustness, as the sign on the proxy for competition should be the same in regressions using the crisis dummy and those using the loans ratio.. Deposit insurance The database also provides data on deposit insurance which is a simple dummy variable that takes a value of 1 if the state guarantees a certain level of bank deposits (in approved institutions). Previous studies, including Demirguc-Kunt & Detragiache (2000) have found that contrary to the conclusions of Diamond & Dybvig (1983), explicit deposit insurance can increase the probability of a banking crisis. This is due to the moral hazard problem that exists commonly in the insurance industry. This is of particular interest when interacted with highly competitive banking systems. As mentioned above, Allen & Gale (2004) suggest that this combination should increase crisis probability but do not empirically test this conclusion.. Non-bank nance The other variable which I interact with market competition has to do with the size of the non-bank nancial sector.. There is a large literature on so-. called market-based nance, and without delving too far into this issue, this paper considers the impact of competition in the banking sector under varying degrees of market based competition. Levine (2002) provides the methodology on measuring the extent to which a country has a bank-based or market-based nancial system. His structure-size. (ss). variable is the logarithm of the market. capitalization ratio divided by the bank credit ratio. Structure-eciency. (se). is. the logarithm of the total value traded ratio times overhead costs (larger values imply a market based system).. Structure-activity(sa)is an index of nancial. 13.

(16) market structure using activity, rather than size. It is also strictly increasing in the extent to which the activity of a nancial market is dominated by non-bank nance. This data is available in the Global Financial Development Database for years between 1960 and 2010.. Measure of crisis The main dependent variable is the occurrence of a banking crisis. Crisis data comes from the database of Reinhart & Rogo (2010), which classies crisis years for 70 countries dating back to 1800. I use the series on banking crises between 1996 and 2010, to match other data limitations. The variable. crisisb. takes a value of one if either of the following conditions occur: (1) bank runs that lead to the closure, merger, or takeover by the public sector of one or more nancial institutions, (2) if there are no runs, the closure, merger, takeover, or large-scale government assistance of an important nancial institution that marks the start of a string of similar outcomes for other nancial institutions. Otherwise, the variable is a zero. Notably, if a two consecutive crisis years are shown to be related to the same root cause event, this study only considers the rst crisis year. For robustness and to help eliminate the potential for endogeneity, two other sets of independent variables are tested. The rst comes directly from Reinhart & Rogo (2010), and includes only banking crises that occurred in years with no other crisis types. This means that this set uses only crises that occurred without currency crashes, sovereign domestic or external default, ination crises, and stock market crashes. While this greatly reduces the number of crises observed in the sample, it goes a long way to eliminate potential endogeneity problems in the regression analysis that follows. Additionally, I use data from Laeven & Valencia (2008) on root-cause banking crises to provide additional robustness and to ensure that the results are not dependent on data from Reinhart & Rogo. This database also describes crises by the rst crisis year, and is restrictive in the sense that it considers crises that originated in the banking sector. For this reason, the number of crises in this set is much smaller, 75 crises in total. Laeven & Valencia consider crises that include a large number of defaults and spikes in the ratio of non-performing to performing loans. The authors also collect data on currency and sovereign debt crises, which allows us to consider only banking crises which are unique events for a given country-year. The authors also drop crises observations for concurrent crises and for banking crises which were proceeded by a currency or sovereign debt crises in the previous year.. For this reason, when included in. regressions, I drop the macro controls which are used in the main specication.. Institutional controls Finally, the literature suggests that other institutional characteristics may be important. Even as country xed eects should account for institutions, these are necessary to add due to the weaknesses of the xed eects specication. 14.

(17) mentioned below. Therefore I add indicators from the Heritage Foundation on nancial freedom, investment freedom, and monetary freedom. These values are indexed measures which proxy for general regulatory environment.. Methodology The base specication of the model is taken from Demirguc-Kunt & Detragiache (1998), which is then extended in Demirguc-Kunt & Detragiache (2002) as well as Beck, Demirguc-Kunt, & Levine (2003). The base specication posits that the probability of a banking crisis in a given country in a given year depends on shocks and the underlying market structure.. Because the dependent variable. is binary, I use a multivariate logistic probability model, based on DemirgucKunt & Detragiache (1998), to test for the impact of banking competition on the probability of banking crisis. Such models are common in the case of dichotomous independent variables, and I will not explain their use in detail here although Hilbe (2009) is helpful. The choice of a logistic probability model over a probit model is based on the facts that studies on bank data tend to use the logit form, and both models give very similar results. Since data is annual, the banking crisis dummy variable is a function. P (i , t). that labels each country(i)-. year(t ) as either normal (0) or a crisis-year (1). The probability that a crisis will occur in a given country-year is set up as a function as a vector of tory variables,. Z (i , t).. We then use. F (β ´Z (i , t))as. n. explana-. the cumulative probability. distribution function, and the log-likelihood function is:. Ln L =. X t=1....T. P. P (i, t) ln {F (β ´Z(i, t))}+[1 − P (i, t)] ln {1−F (β ´Z(i, t))}. i=1...n. (1) The resulting vector of coecients. (β ´). is subject to interpretation with. caution. While the sign of the coecient is indicative of the direction of change, as usual, the magnitude of the change depends on the slope of the cumulative distribution function at. β ´Z (i, t).. This means that the interpretation of the. magnitude by which an explanatory variable. b β´. aects the probability of a. systemic banking crisis depends on the initial values of all other explanatory variables. The main purpose of this paper is to evaluate big-picture eects, so I do not calculate individual marginal eects by country. Throughout the analysis is use three variants of the logit model: standard logit, logit with random intercepts, and logit with xed eects.. The use of. xed eects by country is preferred, as dierent countries may have institutions and other unique determinants of this eect.. However, xed eects present. some problems in logistic regressions, as there has to be sucient time variance in the other variables for necessary convergence to occur. For this reason the reported outcomes for xed eect specication report much lower numbers of observations. The xed eect results should therefore be viewed with caution, as there is an implicit self selection in not considering countries which have no variation in some variables.. Often this is because no crisis occurred in these. 15.

(18) countries. When the analysis turns to testing the risk allocation channel, the logit model is no longer useful. Instead, I use an OLS model with xed eects for year and country. The model is:. LRi,t = αRIRi,t +βCGi,t−2 +γGovBanksi,t +δF orBanksi,t +Lerneri,t−1 +ηi +t (2) Where the loan ratio (LR) is the ratio of non-performing loans to gross loans in a given country in a given year. This is said to depend on a macroeconomic indicator, here the real interest rate (RIR), and a nancial indicator, here as before the twice lagged growth in private sector credit (CG). Additionally, I control for the proportion of foreign banks and government banks in order to ensure that the eects are observed on in-country private sector banks (which are reected by the loan ratio). The lagged value of the Lerner index is used to avoid reverse causality issues. In addition to xed eects for country and year, I also add several interaction terms which are described in the results section.. Empirical Specication The empirical specication of the logit model is based on variables suggested by a long literature on banking crises beginning with Demirguc-Kunt & Detragiache (1998). The shocks are divided into two categories, macroeconomic and nancial, which constitute the control variables in my analysis. Macroeconomic shock controls include GDP growth (gdppc), terms of trade growth rency depreciation. (d .er ),. the real interest rate. (rir ),. (d .tot), cur(infdef1 ).. and ination. Financial and monetary shocks are controlled using the ratio of M2 to reserves. (m2res), and the twice lagged growth of credit to the private sector GDP (L.2d .privcredtogdp). In some regressions a measure of GDP (gdppcapconstant) is used to control for development level.. divided by per capita. We expect GDP and terms of trade growth to decrease the probability of banking crisis. Specically, we expect negative shocks to GDP and to the terms of trade to increase the likelihood of a banking crisis. Ination is expected to be positively correlated with the probability of a banking crisis as it may proxy for monetary mismanagement. The real interest rate and the ratio of private sector credit to GDP are included to proxy for the liberalization of the nancial sector, as recommended by Demirguc-Kunt & Detragiache (1998). The ratio of M2 to reserves is included to control for the possibility of sudden capital outows in economies with exchange rate pegs. It is therefore a proxy for vulnerability to balance of payment crises, as suggested by Calvo (1996). Development level, as proxied by GDP per capita, is expected to be insignicant (or possibly negative). As the motivation of this paper suggests, there are no indications that more developed countries tend to be less aected by banking crisis. In fact there is some evidence that the contrary is true. Through the use of these I hope to control for macroeconomic causes of bank failures. Because all of these variables are have potential endogeneity problems,. 16.

(19) I also run the main specication with two other sets of crisis variables described above.. The banking crisis only set, from Reinhart & Rogo (2010) and the. root cause set of systemic banking crises from Laeven & Valencia (2008). When using these variables which should be cleaned of all crises episodes that, for example, originated in a non-bank sector of the economy but later became a banking crisis.. When using the Laeven & Valencia data I do not use macro. controls, as that work has essentially been done by the authors. There are, however, other institutional variables which may convey relevant information about the likelihood of a banking crisis. Government control of the banking sector upsets many of the mechanisms by which competition aects crisis probability. Additionally, if the majority of in-country banking is managed by a foreign bank, the results maybe also be skewed, this time positively. I therefore use the proportion of banking assets in government owned banks (banks are classied as government owned if more than 50 percent of the shares are government controlled), (govb) as a control.. Similarly, the proportion of. banking assets in foreign owned banks (foreignb)are used. These two controls are available since 1999, so their inclusion signicantly limits the sample. The structural variables of interest are described in detail above. The Lerner index (lerner ) is a measure of the distance between price and marginal cost of banking services, and is therefore increasing in market power and decreasing in competition. As suggested above, theory is inconclusive on how banking sector competition should aect stability. The literature suggests that other institutional characteristics may be important.. Therefore I add indicators from the. Heritage Foundation on nancial freedom (financialfreedom),investment freedom (investmentfreedom), and monetary freedom (monetaryf reedom). The presentation of empirical results occurs in four phases. I rst test the impact of varying competition levels on crisis outcomes. This involves several tests for robustness and a wide range of controls.. I then test the interaction. between competition and various measures of the importance of the non-bank nancial sector. I then test for an interaction between the presence of deposit insurance and competition. Finally, I test a the risk allocation channel, described in the theory section above as having an ambivalent theoretical results.. Empirical Results Eect of competition on crisis probability The rst results show that high competition, as measured by the Lerner index, is robustly associated with banking crisis. The results from the main specication appear in table 1, where it is shown that the Lerner Index has a negative coefcient, robust to a variety of specications and distinct measures of crises. The Lerner Index is always lagged one period to eliminate the potential for obvious reverse causality. Indeed, it is probable that banking crises, dened by the fact that some banks exit the market, change the nature of competition in the banking sector. Additionally, I include controls for foreign and government ownership. 17.

(20) of banks to insure that the observations are not skewed by government manipulation or certain countries that may have outsourced their banking sector to international banks that may be subject to dierent levels of competition than those listed here. Columns 1-3 report the results using the full banking crisis data from Reinhart & Rogo (2010) with the full range of specications of the logit model. As this classication, dened formally above, includes observations for banking crises that were accompanied by crises in other areas (including the stock market, exchange rate, etc.), I include the full range of macroeconomic and nancial controls as suggested by Beck, Demirguc-Kunt, & Levine (2003). The results clearly show that an increase in market power is related to a decrease in crisis probability. These results hold when I restrict the Reinhart & Rogo crisis database by including only banking crises that were not accompanied by crises of any other kind (column 4). Column 5 further restricts the Reinhart & Rogo crisis database by dropping crisis observations with crises of any other kind occurring in the previous year. I therefore drop controls for changes in the exchange rate since no such crises appear in the list. This specication is very restrictive. Further robustness is checked in column 6 by using the classication of systemic banking crises proposed by Laeven & Valencia (2008). As this classication includes only crises that had a so-called root cause in the banking sector, meaning observations with concurrent and proceeding crises of other types are dropped, I eliminate the macro controls. Despite the fact that this crises classication is very restrictive and therefore includes very few actual crises, the coecient on the lagged value of the Lerner Index is still negative. Prediction is a common part of the use of logit models, so I test the predictive power of the model. The results are consistent with other studies of this kind, few crises are predicted but the accuracy ranges between 50-80%. As the intent of this exercise is not to develop a forecasting model for banking crises, I do not provide predictions for the rest of the specications. As was mentioned in the theoretical introduction, the studies on this subject seem to depend greatly on the time period considered. The biggest test to the stability of the model from 1997-2010 is the 2008-2010 period, during which many countries experienced banking crises as part of the global nancial crisis. I test that the results do not depend on the inclusion of this volatile period in table 2, which shows the results from the period 1997-2007. The results are the same for the main specication but one of the alternative crisis measures does not show signicant results for the coecient on the Lerner index. Between the two alternative sets of crisis denitions, the Laeven & Valencia set should be considered stronger, as the bank crisis only set was constructed without historical consideration. Table 3 shows that the main specication is robust to the inclusion of three institutional indicators provided by the Heritage Foundation. This specication was also tested for non-linearities in the eect of competition but the evidence did not suggest that non-linearities play a signicant role in explaining this relationship.. 18.

(21) Interaction between competition and the size of the non-bank nancial sector As suggested by Allen & Gale (2004) and others, it is important to consider competition from outside the banking sector when observing nancial market competition. There is a large literature on the pros and cons of having a large non-bank nancial sector (see Levine 2000). An important issue to consider is that banks may not only compete with other banks, but also with non-bank nancial service providers.. This possibility complicates the previously shown. analysis, because the eect of bank sector competition on the probability of a crisis may depend on relative size of the banking sector vis-a-vis the non-bank nancial sector. The main dierence between the banking sector and the nonbank nancial sector has to do with regulations on how institutions may invest funds, both in the quality and type of investment vehicle. A large and ecient non-bank nancial sector may place an opportunity cost of holding money in the banking sector as long as risk dierences are only minor. This competition from outside the banking sector may amplify or diminish the standard competition eect described above. This hypothesis is tested using an interaction between the Lerner index and three dierent indicators describing the size, activity, and eciency of the nonbank nancial sector.. The structure-size. (ss),. structure-eciency. (se),. and. structure-activity(sa)variables described above are each included alone and interacted with the Lerner index.. The results in table 4 show that the main. specication results do indeed depend on the size and eciency of the non-bank sector. In fact, the previous result that competition increases the probability of crisis can be attributed to an interaction between competition in the banking sector and the size and eciency (both could generously be considered proxies for competition) of the non-banking sector. Several parts of this result are worth noting. When the interaction between the Lerner index and either. ss. or. se. are. included in the regression, Lerner by itself has no signicant eect. The amount of activity in the non-bank nancial sector has little impact on the result. The conclusion can be made that only in the case of a large or highly ecient nonbank nancial sector do the negative eects of competition in the banking sector become apparent. This helps to some extent to explain the wide range of results from previous studies which do not account for competition from the non-bank nance sector. This line of questioning is certainly fertile for further research, as many of the suggested causes of the 2008 nancial crisis have to do with interaction between the banking sector and the non-bank nancial sector. Note that these results hold using the main specication described above, but are not run using the restricted crisis denitions that were used to limit the possibility for reverse causality in the rst section of results. Given these. 3. restricted denitions, there is not sucient data to make a conclusive results.. If and when longer series of country nancial variables become available this area in particular warrants further attention.. 3 There. may be sucient data, but there are not enough clean crisis observations.. 19.

(22) Interaction between competition and deposit insurance Another interesting test from the literature is for the eect of the interaction between competition and the presence of deposit insurance. Deposit insurance existed in the United States long before Diamond & Dybvig (1983) modeled the problem that it helps to resolve.. Many policy makes would stress that. deposit insurance, when credible, has prevented many bank runs.. Recently,. during the 2008 nancial crisis, several governments either added or augmented the insurable amount of deposits. In the US, the insurable amount was doubled from $200 thousand dollars to $400 thousand. The United Kingdom and several Eurozone countries followed suit. While deposit insurance seems to work well to prevent bank runs in the short run, a moral hazard problem exists in the long run. If deposits are insured, bankers have incentives to take risks at little cost if the rms charter value is small. Table 5 shows the results of the main specication with an interaction between competition and a dummy variable for deposit insurance added. Using the three specications of the logit model shown above, and with lagged and concurrent use of the key variables, the presence of deposit insurance never improves the eect of competition on stability.. In fact, in 4 of 6 specications. (those with random or xed eects) deposit insurance exacerbates the destabilizing eect of competition.. Competition is shown to maintain an eect that. does not depend on deposit insurance, albeit diminished.. Testing the risk allocation channel The nal empirical exercise is to test the risk allocation channel. As mentioned above, theory has shown that competition ought to inuence stability via diminished charter value and changed risk allocation preferences. Here I use the ratio of non-performing loans to gross loans to isolate the eect of the risk allocation channel. Whereas bank failure (and crisis) may depend on the size of the negative shock to loan repayment and/or the existing prot margin, the loan ratio only depends on the shock. In this way, increases in the loan ratio, which would likely increase the probability of a crisis, can be modeled and tested for a relationship with competition. This test measures risk allocation ex post by necessity, and this analysis that risk outcomes are correlated with the risk taking mentality at a given bank.. This may not be true, especially if herding is an issue.. Nonetheless,. given the uncertain theoretical relationship between competition and risk allocation, it is interesting that the results shown in table 6 are remarkably strong. Without interaction terms, market power is correlated with a decrease in the non-performing loans ratio - a stabilizing eect. In this way, the results provide some robustness to the previous results using crisis dummies. While the magnitude appears large, it should be noted that the loan ratio is a percentage, and a unitary change in the Lerner index represents a switch from full monopoly power to perfect competition. An increase in the lerner index by one standard deviation is shown here to reduce the non-performing loans ratio by 1.61%.. 20.

(23) Here, the interaction with deposit insurance dominates the solo eect of competition.. In other words, only in the presence of deposit insurance does. market power correlate with decreased non-performing loans ratios.. This is. evidence that the moral hazard issue discussed above may indeed play out in practice. The results of interaction between competition and the non-bank nancial sector are less clear. As before, the activity (SA) level of a non-bank nancial sector seems to have no eect (and in fact this regression looses signicant power due to low observations). The size (SS) of the non-bank nancial sector does seem to play a role however, with the total eect of competition depending on the size of said sector.. Conclusion The main argument of this paper is that the competition eect on stability in the banking sector is subject to other nancial conditions, which are dynamic. This paper has shown that between 1997 and 2010 competition in the banking sector, as measured by the Lerner index, is negatively correlated with stability. This eect is amplied by a large and/or ecient non-bank nancial sector. In fact, when controlling for the interaction between the size or eciency of the non-bank sector and the Lerner index, the latter has no power in the model. The results are less drastic when competition levels are interacted with deposit insurance, but the destabilizing eect of competition is increased with the incentives that come with deposit insurance. Competition is shown to have a destabilizing eect even when only risk allocation is observed. This is shown by a negative correlation between market power and the ratio of non-performing loans.. Again, both the existence of. deposit insurance and the size of the non-bank nancial sector play an important role in this relationship. Still, the result in this last section is likely to be very dependent on the data limitations. The conclusion is weakened by the fact that only 5 years of data are considered for just over 30 countries. Despite the use of xed eects for country and year, there is still a large possibility for error in this model as well. In particular, endogeneity is likely to aect the results. Further research on this topic is of signicant importance. The frequency and costs of banking crises in the developed and developing world suggest that there may be signicant gains to be made by further study. While this study shows that competition, especially in the presence of deposit insurance and a large nonbank nancial sector, may be a destabilizing force, the competition-stability relationship has been shown to depend to a great degree on regulatory and structural factors in place. In particular, deposit insurance and large non-bank nancial sectors seem to increase the likelihood that the eects of competition on stability is negative.. 21.

(24) References [1] Allen, F. & Gale, D. 2003. Financial Intermediaries and Markets. Working Paper 00-44-C, Wharton Financial Institutions Center. [2] Allen, F. and Gale, D. 2004. Competition and Financial Stability, Journal of Money, Credit, and Banking. 36(3) 453-480. [3] Anginer, D., Demirgü£-Kunt, A. & Zhu, M. 2012. How Does Bank Competition Aect Systemic Stability. Policy Research Working Paper 5981, The World Bank. [4] Amir, R. 2002. Market structure, scale economies and industry performance, mimeo. [5] Beck T, Demirguc-Kunt, A. & Levine, R. 2003. Bank Concentration and Crisis. NBER Working Paper, 9921. [6] Beck, T., De Jonghe, O., Schepens, G. 2011. Bank competition and stability: reconciling conicting empirical evidence, Working Paper. [7] Berger, A., DeYoung, R., & Flannery, M. 2008. How do large banking organizations manage their capital ratios? The Federal Reserve Bank of Kansas City, Economic Research Department. [8] Bikker, J, & Bos, J. 2005. Trends in Competition and Protability in the Banking Industry: A Basic Framework. Suerf: The European Money and Finance Forum, 2. [9] Boyd, J. & Runkle. 1993. Size and Performance of Banking Firms: Testing the Predictions of Theory. Journal of Monetary Economics, 31, 47-67. [10] Boyd, J., De Nicolo, G. & Smith, B. 2004. Crises in Competitive versus Monopolistic Banking Systems, Journal of Money, Credit and Banking, Vol 36(3), 487-506. [11] Boone, J. 2004. A New Way to Measure Competition, CEPR Discussion Paper Series No. 4334. [12] Boone, J. 2008. A New Way to Measure Competition, The Economic Journal, 188:1245-1261. [13] Boone, J. 2008. Competition: Theoretical Parameterizations and Empirical Measures, Journal of Institutional and Theoretical Economics, 164:587-611. [14] Calvo, G. 1996. Capital Flows and Macroeconomic Management: Tequilla Lessons, International Journal of Finance and Economics, 1, 207-224.. 22.

(25) [15] ihák, M, Demirgü£-Kunt, A., Feyen, E., & Levine, R. 2012. Benchmarking Financial Systems around the World. Policy Research Working Paper, 6175, The World Bank. [16] Demirguc-Kunt, A., Detragiache, E. 1998. The Determinants of Banking Crisis in Developing and Developed Countries, IMF Sta Paper, Vol. 45 (1). [17] Demirguc-Kunt, A., Detragiache, E. 2002. Does deposit insurance increase banking system stability?. An empirical investigation,. Journal of Monetary Economics. 49, 1373-1406. [18] Demirgüç-Kunt, A., & Martinez Peria, M. Forthcoming. A Framework for Analyzing Competition in the Banking Sector: An Application to the Case of Jordan. Policy Research Working Paper, World Bank, Washington, DC. [19] Demsetz, R., Saidenberg, M., & Strahan, P. 1996. Banks with Something to Lose: The Disciplinary Role of Franchise Value, Federal Reserve Bank of New York Economic Policy Review, October 1996. [20] Diamond, D. & Dybvig, P. 1983. Bank runs, deposit insurance, and liquidity. Journal of Political Economy. 91(3), 401-419. [21] Fang, Y., Hasan, I., & Marton, K. 2011. Bank eciency in transition economies: recent evidence from south-eastern Europe. Bank of Finland Research, Discussion Papers. [22] Farias, M. 2006. Market Concentration and Banking Crisis, Universidad de Chile, mimeo. [23] Haldane, G. & Alessandri, P. 2009. Banking on the State. Bank of England Mimeo. [24] Hellman, Murdock, & Stiglitz. 2000. Liberalization, Moral Hazard in Banking and Prudential Regulation: Are Capital Requirements Enough? American Economic Review, 90(1), 147-165. [25] Hilbe, J. 2009. Logistic Regression Models, Chapman and Hall. [26] Hoggarth, Reis, and Saporta. 2001. Costs of banking system instability: some empirical evidence. Bank of England Working Paper, 144. [27] Hoque Khan, A., Dewan, H. 2011. Deposit insurance scheme and banking crises: a special focus on less-developed countries, Empirical Economics, Vol. 41(2):155-182. [28] Keeney, M. 1990. Deposit Insurance, Risk, and Market Power in Banking, The American Economic Review, 60(5), 1163-1200.. 23.

(26) [29] Laeven, L. & Valencia, F. 2008. Systemic Banking Crises: A New Database, IMF Working Paper 08/224. [30] Levine. 2000. Bank-Based or Market-Based Financial Systems: Which is Better? Journal of Financial Intermediation, 11, 398428. [31] Levine. 2004. Finance and Growth: Theory and Evidence. NBER Working Paper, 10766. [32] Rabe-Hesketh, S. & Pickles, A. 1999. Generalized linear latent and mixed models, Proceedings of the Workshop on Statistical Modeling, Graz Austria, 332-339. [33] Reinhart, C. & Rogo, K. 2008. Banking Crises: An Equal Opportunity Menace. NBER Working Paper 14587. [34] Reinhart, C. & Rogo, K. 2010. From Financial Crash to Debt Crisis. NBER Working Paper 15795. [35] Schaeck, K. & Cihak, M. 2010. Competition, Eciency, and Soundness in Banking:. An Industrial Organization Perspective, Euro-. pean Banking Sector Discussion Paper, 0924-7815. [36] Schaeck, K., Cihak, M., & Wolfe, S. 2009. Are competitive banking systems more stable? Journal of Money, Credit, and Banking, 41, 711-734. [37] Stiglitz, J. 1989. Imperfect information in the product market, Handbook of Industrial Organization, Vol. 1. Amsterdam: Elsevier Science Publishers. [38] Vives, X. 2008. Innovation and competitive pressure, Journal of Industrial Economics, Vol. 56:419-469.. 24.

(27) Appendix Figure 1. Countries:. Algeria, Angola, Argentina, Australia, Austria, Belgium, Bolivia,. Brazil, Canada, Central African Republic, Chile, China, Colombia, Costa Rica, Cote d'Ivoire, Denmark, Dominican Republic, Ecuador, El Salvador, Finland, France, Germany, Ghana, Greece, Guatemala, Honduras, Hungary, Iceland, India, Indonesia, Ireland, Italy, Japan, Kenya, Korea, Rep., Malaysia, Mauritius, Mexico, Morocco, Myanmar, Netherlands, New Zealand, Nicaragua, Nigeria, Norway, Panama, Paraguay, Peru, Philippines, Poland, Portugal, Romania, Singapore, South Africa, Spain, Sri Lanka, Sweden, Switzerland, Thailand, Tunisia, Turkey, United Kingdom, United States, Uruguay, Zambia, Zimbabwe.. Table 1. 25.

(28) Table 2. 26.

(29) Table 3. 27.

(30) Table 4. 28.

(31) Table 5. 29.

(32) Table 6. 30.

(33)