Bank valuation in new EU member countries

Economic Systems 38 (2014) 55–72

Contents lists available at ScienceDirect

Economic Systems

journal homepage: www.elsevier.com/locate/ecosys

Bank valuation in new EU member countries

Yiwei Fang a, Iftekhar Hasan b,c,*, Katherin Marton b,Maya Waisman b

a Stuart School of Business, Illinois Institute of Technology, 565 West Adams Street, 4th Floor, Chicago, IL60661, United Statesb Fordham University, 113 West 60th Street, New York, NY 10023, United Statesc Bank of Finland, Finland

A R T I C L E I N F O

Article history:

Received 18 April 2013

Received in revised form 11 July 2013

Accepted 11 July 2013

Available online 9 October 2013

JEL classification:

G21

P30

P34

P52

Keywords:

Bank charter value

Foreign ownership

Diversification

Institutional development

Market power

Transition economies

A B S T R A C T

This paper studies the role of institutional reforms in affecting bank

valuation in new European Union (EU) member countries. It takes

advantage of the dynamic nature of institutional reforms in

transition economies and explores the causal effects of those

reforms on banks’ Tobin’s Q over the period of 1997–2008. Using a

difference-in-difference approach, the paper shows that Tobin’s Q

increases substantially after these countries reform their legal

institutions and liberalize banking. However, it decreases after

stock market reforms. After further examination of the interactive

relationships between different reforms and bank valuation, it is

observed that when the banking reform is well implemented, legal

reform can have a stronger impact on banks’ Tobin’s Q. On the other

hand, banking reform and security market reform has a substitutive

relationship. The analysis also suggests that foreign ownership,

market power, and asset diversification significantly affect Tobin’s

Q. These results are robust even after simultaneously controlling for

equity risk.

� 2013 Elsevier B.V. All rights reserved.

* Corresponding author at: Fordham University, 113 West 60th Street, New York, NY 10023, United States.

Tel.: +1 646 312 8278; fax: +1 646 312 8290.

E-mail addresses: [email protected] (Y. Fang), [email protected], [email protected] (I. Hasan),

[email protected] (K. Marton), [email protected] (M. Waisman).

0939-3625/$ – see front matter � 2013 Elsevier B.V. All rights reserved.

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Y. Fang et al. / Economic Systems 38 (2014) 55–7256

1. Introduction

The development of a sound banking system is vital to a country’s economic stability and long-term growth (Allen and Gale, 2000; Levine, 2005). This is especially true for transition economies,where capital markets are underdeveloped and the financial needs of enterprises are mostly metthrough banking sectors. Most importantly, the recent 20 years have witnessed substantialinstitutional reforms in both the financial and the enterprise sector. How these reforms in transitioneconomies affect bank market development has attracted considerable interest from academia as wellas policymakers.1

Prior studies examining the relationships between institutional reforms and bank performancehave traditionally used accounting and efficiency measures (e.g. Bonin et al., 2005a,b; Brissimis et al.,2008; Poghosyan and Poghosyan, 2010; Fang et al., 2011b). In this paper, we pay special attention tothe valuation of publicly traded banks as measured by the market-to-book value of equity (Furlongand Kwan, 2005; Caprio et al., 2007). In particular, we examine how substantial changes ininstitutional environments are transmitted to the banking sector and affect bank valuation and,secondly, how different reforms interact with each other to exercise an impact on bank valuation. Inaddition, we analyze bank-specific factors that are related to bank valuation, including market power,foreign ownership, and asset diversification.

The examination of bank valuation is motivated by three considerations. First, the structuralchanges of banking regulation, financial market structure, and competition environment in transitioneconomies are likely to alter the valuation of banks in a significant way. Second, with the developmentof security markets, more transition banks are traded publicly in the local stock market. This makesbank valuation a timely and important issue to examine. Especially, Tobin’s Q could capture thefurther growth opportunities of a bank, which is crucial for shareholders (Laeven and Levine, 2009).Third, under the Basel Capital Accord, greater supervisory efforts have been focused on riskmanagement and enhancing the capital ratio. Having a sound charter value has been documented as akey contribution to reduce risk-taking incentives of shareholders, since they would risk all their valuein the event of a downside (Keeley, 1990; Hellmann et al., 2000; Repullo, 2004).

In examining the role of institutional reforms, we look at banking reform, security market reform,and legal reform. Banking reform refers to a series of deregulation activities that took place in thebanking sectors of major transition economies. In order to establish efficient market-oriented bankingsectors, governments liberalized interest rates and decentralized central banks’ commercial bankingactivities to state banks. To foster competition, they also privatized a large number of domestic banksand allowed foreign banks to enter the market. Legal reform refers to government efforts in reforminglegislation and financial laws to create an investor-friendly, transparent and predictable legalenvironment. In particular, collateral and bankruptcy laws were revised following the standard ofWestern model laws (Dahan, 2000). It has been documented that the overall quality of the legalenvironment of transition countries has substantially improved over the past decade (Pistor, 2000).

We apply a difference-in-difference framework to explore the exogenous changes of bankingreform, legal reform, and security market reform over time across countries.2 Specifically, we obtainyearly measures of legal reforms, banking liberalization, and security market reform for thesetransition countries from 1997 to 2008. For each year, countries that experienced reforms belong tothe treatment group and countries with no changes belong to the control group. Given that thereforms in transition countries took place at different time periods in different countries, we apply theDID approach in a multiple groups and multiple time periods framework (Bertrand and Mullainathan,

1 Since the break-up of the former Soviet Union and the fall of the Berlin Wall, a large number of countries in Central and

Eastern Europe and the Baltic regions as well as the Euro-Asian Caucasus started their transition toward more democratic and

market-oriented economies. Researchers analyzing these transition countries typically divide them into two groups. One

consists of the Former Soviet Union (FSU) countries and the other of the non-FSU countries. The countries considered in this

paper are Central and Eastern European countries from the non-FSU group. It should be noted here that in recent years some

researchers have also included China, Mongolia, and Vietnam in defining economies or countries in transition.2 Arguably, institutional reforms can be seen as exogenous because they are motivated and supervised by external

organizations such as the European Union (EU), the European Bank for Reconstruction and Development (EBRD), and USAID

(Giannetti and Ongena, 2009; Haselmann et al., 2010).

Y. Fang et al. / Economic Systems 38 (2014) 55–72 57

2003; Hansen, 2007; Haselmann et al., 2010). This empirical strategy allows us to address manythreats concerning validity. For example, comparing Tobin’s Q between the treatment and controlgroups in the post-reform periods removes biases due to the common economic trend of the twogroups. Moreover, it also allows a comparison between the pre-reform and post-reform periods withinthe treatment group, which removes biases that could be due to other omitted time invariant factorsrather than reform events.

Our main findings show that legal reform and banking reform significantly enhance banks’ Tobin’sQ while security market reform decreases banks’ Tobin’s Q. We also observe that banking reform andlegal reform complement each other in the sense that when a banking reform is well implemented, thelegal reform can have a stronger impact on banks’ Tobin’s Q. On the other hand, banking reform andsecurity market reform appears to have a substitutive relationship. Our analysis also shows thatcompared to domestic ownership, foreign ownership is associated with a significantly higher chartervalue. This is in line with former research findings that foreign banks in developing countries obtainhigher returns on their investment (Claessens et al., 2001). There is no significant difference betweendomestic private banks and government-owned banks in terms of Tobin’s Q. Regarding thediversification strategy, we find that banks with higher degrees of asset diversification have higherTobin’s Q, which supports the argument that diversification creates an economy of scope which opensup opportunities for future growth.

The structure of this paper is as follows. In Section 2, we present a brief literature review anddevelop our hypotheses. Section 3 describes our sample on transition banks and introduces ourmeasures. Section 4 presents the empirical results, and Section 5 concludes.

2. Literature review

2.1. Institutional reforms in transition economies

Over the past 20 years, transition economies have undertaken substantial structural changes andinstitutional reforms. Banking sectors, for example, had quite a different background compared withother parts of the world. Before the economic transformation started, central banks directed all theallocation of credit based on a government plan and commercial banks were specialized in servingcertain economic sectors rather than diversified (Bonin et al., 2009). Therefore, banks under thesocialist system faced no pressure of competition and had no incentive to maximize profits in lending.However, during the past two decades, these banking systems went through a fundamental process ofrestructuring. To transform them into efficient and market-oriented banking sectors, governmentsliberalized interest rates and decentralized central banks’ commercial banking activities to statebanks. To foster a competitive banking industry, state banks were privatized and a large number offoreign banks entered the market. More recently, governments put more effort into the establishmentof prudential regulation and supervision guidelines. Significant progress has been made with theimplementation of the core principles of the Basel Committee on Banking Supervision.

Legal institutions had very weak shareholder and creditor protection (Pistor, 2000) at thebeginning of the reforms. However, as the transition process advanced, governments establishedproject groups working on legislation and the implementation of commercial and financial laws. Forexample, the focus of reforms was on remodeling secured transactions laws, company laws andinsolvency laws by looking at their dissemination and judicial and administrative enforcement. In2003, individual countries’ legal reform, e.g. the extent to which legal rules comply with internationalstandards, the extent to which the legal regime provides an efficient result in a given practicalsituation, and how legislation, together with the local institutional framework, creates a functional (ordysfunctional) insolvency legal regime was evaluated by the EBRD.

Securities markets were effectively non-existent at the beginning of transition. During thetransition period, securities exchanges were formed and a rudimentary legal and regulatoryframework for the issuance and trading of securities was established. In order to build well-functioning securities markets and help promote stock market performance, over the yearsgovernments have focused on the establishment of independent securities commissions, secureclearance and settlement procedures, and also on remodeling securities laws and regulations to


protect monitory shareholders (Pistor et al., 2000). Nevertheless, the progress of these reforms has notbeen as successful as expected. Lessons were learned and more reforms continued to take place aftersome failure of stock markets (Coffee, 1999).

2.2. The impacts of institutional reform on bank performance

In the literature, researchers have examined the effects of banking reform on various bankingissues. Studies generally find that banking reform, in particular the liberalization of interest rates andopening up to foreign ownership, has a positive influence on bank efficiency. For example, Bonin et al.(2005b) show that the method and timing of privatization influence bank efficiency significantly.Poghosyan and De Haan (2010) find that institutional conditions can be crucial in determining theperformance of cross-border bank acquisitions in transition countries. In analysing the impact ofbanking reforms on cost efficiency, Fries and Taci (2005) show that costs decrease during the earlystages of the transition, but rise over time and with the implementation of reforms. A study byBrissimis et al. (2008) looks at transition economies that joined the European Union and finds thatbanking reforms exert a positive impact on profitability.

Bank lending activities can also be greatly influenced by how banks perceive insolvency laws,contracting enforcement and creditor protection (Djankov et al., 2007; Haselmann et al., 2010).Similarly, Qian and Strahan (2007) contribute on the relationship between institutions and loancharacteristics and find that borrowers in countries with strong creditor-protection environmentsenjoy loans with more concentrated ownership, lower interest rates, and longer maturities.

In the context of transition economies, the literature suggests that institutional improvements,such as an effective legal environment and efficient judicial systems, are important to foster theconfidence of banks to lend to enterprises. For example, Haselmann and Wachtel (2007) show thatbanks tend to lend more to large enterprises in a weak legal system and more to SMEs when the legalsystem is sound and effective. Haselmann et al. (2010) investigate the impact of legal changes on banklending. An interesting conclusion is that banks increase their credit supply subsequent to theimprovement of the legal environment, especially for foreign banks. It is also found that highercreditor rights and enforcement reduce banks’ risk of expropriation by borrowers (Fang et al., 2011a).

Cole and Turk-Ariss (2008) look at how the legal origins and creditor protection affect bank lending,finding that banks allocate a higher proportion of assets in risky loans in English legal origin and withweaker creditor rights. Weill (2011) reports on how corruption affects bank lending in Russia.

2.3. Market power, ownership, and diversification

There are two different approaches in researching the role of market power on bank performance intransition economies. Based on the quiet life hypothesis, when a bank has monopoly power, managersreduce their efforts and gain monopoly rents through discretionary expenses (Hicks, 1935). Under thisassumption market power affects performance negatively. The structure–conduct–performanceparadigm, on the other hand, postulates that strong market power allows banks to extract monopolyrents through offering low deposit rates and charging high borrowing rates (Bain, 1956). Strongmarket power is also found to allow banks to take advantage of economies of scale to monitorborrowers and operate at higher cost efficiency (Diamond, 1984). Under this argument, market powerand performance are related positively. The empirical research on the role of banking competition andmarket power on efficiency in transition economies presents conflicting findings. This may partly berelated to differences among countries and the various approaches that were used to measurecompetition, for example industry level concentration measures, number of firms in the industry, andindividual bank market power (Yildirim and Philippatos, 2007; Brissimis et al., 2008; Kosak et al.,2009; Pruteanu-Podpiera et al., 2008).

The findings in the literature on the relationship of bank ownership and performance in transitioneconomies differ study by study. Most early single country case studies find that foreign banksperform better, followed by domestic private and state-owned banks (e.g. Hasan and Marton, 2003;Kraft et al., 2006; Jemric and Vujcic, 2002; Weill, 2003). Similar findings are also supported by anumber of cross-country studies (e.g. Bonin et al., 2005a,b; Kasman and Yildirim, 2006). These studies


are consistent with former research findings that foreign banks in developing countries obtain higherreturns on their investment (Claessens et al., 2001). The superior performance of foreign-owned bankscan be attributed to their management skills, advanced technology, access to lower cost funds fromthe parent company, lack of legacy costs (e.g. non-performing loans from former periods), anddifferences in clientele, such as larger shares of foreign-owned companies. Though foreign banks mayhave some advantages, they could also experience disadvantages, such as informational asymmetriesin new markets, inadequate knowledge of local conditions, and difficulties in establishing relationalnetworks. These factors tend to increase the costs of foreign banks and reduce their inherentadvantages vis-a-vis domestic banks (Buch, 2003; Berger et al., 2000; Green et al., 2004; Zajc, 2006;Mamatzakis et al., 2008).

Diversification is an important option for banks to grow. The literature has presented differenttheoretical predictions and conflicting outcomes on the impact of diversification on bankperformance. One stream of literature has found a positive impact of bank diversification onperformance. The arguments highlight that by lending to different industries and engaging in multiplebusiness activities banks can acquire better-quality information about clients and achieve moreefficient capital allocation (Diamond, 1984; Rajan, 1992; Saunders and Walter, 1994; Stein, 2002).They are also able to spread fixed costs and leverage management skills across product lines, therebycreating economic synergies and better performance (Williamson, 1975; Boot and Schmeits, 2000;Iskandar-Datta and McLaughlin, 2005). Hence, they advocate bank diversification. Another stream oftheories, however, postulates that diversification does not necessarily result in improvedperformance. Klein and Saidenberg (1998), for example, argue that expanding into multiple marketsegments might go beyond existing expertise and dilute banks’ comparative advantages. Furthermore,agency theories assume that by expanding the scope of activities, bank managers may extract privatebenefits, e.g. reduce their personal risk, even if the additional business lines lower the value of the firm(Jensen, 1986; Jensen and Meckling, 1976; Amihud and Lev, 1981; Acharya et al., 2006).

In transition economies, bank diversification activities were only made possible after the reform ofbanking sectors. Before that, banks were mainly lending to one particular industry and their lendingactivities were determined by the central banks’ plans. Liberalization provided banks withunprecedented opportunities to reach beyond the traditional lending business, removing the barrierof regulatory restrictions on various other banking activities. For publicly traded banks, corporategovernance reforms in transition economies strengthened the confidence of banks’ shareholders toallow managers to purse value-increasing diversification. Claessens and Klingebiel (2000) argue that ifbanks were given greater freedom, they would use the opportunity to pursue economies of scale andscope, e.g. by diversifying into multiple income streams and thus reducing risk. Recent surveys byBarth et al. (2001, 2004) also provide evidence that strict diversification guidelines and loanclassification stringency are associated negatively with banking sector development, efficiency, andfinancial stability. Whether diversification can help banks to better exploit economies of scale andscope and thereby provide higher growth opportunities is an empirical issue.

3. Sample and data

3.1. Sample selection

Our sample consists of publicly traded banks in Central and Eastern European (CEE) countries overthe period of 1997–2008. The balance sheet financial variables are obtained from BankScope and stockdata is mainly obtained from DataStream and completed with BankScope. Due to some reportedshortcomings of the BankScope database (Bonin et al., 2005a) we make a careful examination ofmultiple entries for the same bank because they are not completely duplicate observations. First of all,we choose the unconsolidated financial reports of commercial banks, since this gives the financial datafor the bank rather than the holding company. Then we check the accounting standards. InternationalAccounting Standards (IAS) data are used wherever available; otherwise, inflation-adjusted localaccounting standards data are used. All bank-level data are inflation-adjusted and reported in USD. Fora bank to be included in our sample, market capitalization information for the bank must also beavailable. We allow failures, mergers, and de novo entry of banks, but banks in our sample must have a


minimum of three years of continuous data to obtain reliable estimates. The selection process yieldsan unbalanced panel with 60 banks in three SEE countries (Bulgaria, Croatia and Romania) and eightCEE countries (Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Slovakia and Slovenia).

3.2. Measuring market power

The Lerner index is a well-established indicator of market power at the individual bank level. Thisindex is defined as the mark-up of the price over marginal cost, divided by the price (Lerner, 1934). Itcaptures the power of individual banks to set prices above marginal cost. A higher value of the Lernerindex denotes higher market power of the bank. The Lerner index is calculated as Lerner=(pit�mcit)/pit, where pit indicates the price, and mcit indicates the marginal cost. We calculate the price (pit) astotal revenue (REV) divided by total earning assets (Y), and marginal cost (mcit) is calculated from theestimation of a translog cost function and is specified as follows:

lnTOC

w2

� �¼ a0 þ a1ln

w1

w2

� �þ 1

2a2ln

w1

w2

� �ln

w1

w2

� �þ b1lnðYÞ þ b2

1

2lnðYÞlnðYÞ

þ 1

2lnðYÞln w1

w2

� �þ 1

2

X2

l¼1

lnðYÞlnðzlÞ þ 1

2

X2

l¼1

hllnw1

w2

� �lnðzlÞ þ year dummies

þ region dummy þ GDP growth þ inflation þ n þ m

Note that this specification is not the same as a cost frontier. Instead of using individual outputs(e.g. loans, securities, and other earning assets) which are usually specified in the cost frontierfunction, here we use Y(total earning assets) as the total output. Specifically, Y equals the sum of loans(y1), securities (y2), and other earning assets (y3). Marginal cost follows directly from the estimation bytaking derivatives with respect to Y. In the estimation, total equity (z1) is used as fixed inputs in theestimation to account for the banks’ endogenous choices of risk. The two input prices are the price ofborrowed funds (w1 =interest expense divided by total borrowed funds) and the price of capital perfixed asset (w2 =non-interest expense divided by fixed asset). We normalize the equation by one inputprice (w2) to impose linear homogeneity of input prices (Kuenzle, 2005). Finally, n represents therandom noise, which incorporates both measurement error and luck, and m is the inefficiency termthat increases banks’ costs and is assumed to have a half-normal distribution with a positive value.

This equation is widely used in estimating the Lerner index in the banking industry (Brissimis et al.,2008; Koetter et al., 2012; Maudos and de Guevara, 2007). We use the stochastic frontier analysis toestimate this equation and obtain the coefficients. Since the Lerner index is the mark-up of the priceover marginal cost divided by the price, it has an upper bound of 1 when the bank has monopoly powerand operates with zero marginal cost. It has a value of zero when the price is equal to the marginal costand the bank operates in a perfectly competitive market. The Lerner index can also be negative. Thishappens when the price is below marginal cost and the bank is in serious trouble. Table 4 (Column 4)reports the Lerner index of CEE banks from 1998 to 2008.

3.3. Bank ownership

The data on bank ownership is drawn from BankScope. Since many banks in transition economieschanged ownership several times over the past two decades, it is important to have yearly ownershipdata so that all ownership changes in our sample period are identified (De Haas and Van Lelyveld,2010). A limitation of BankScope is, however, that it only provides shareholder information for theyear when the database was last updated. Therefore, we take separate editions of the database (1999,2001, 2003, 2005 and 2007) and fill in the years in between with data from the previous year, ifavailable. We also return to 1997 and 1998 using the same ownership as in 1999. To achieve higheraccuracy we also search bank homepages and business publications. We group shareholders into threecategories: foreign, domestic private, and government. We then calculate the aggregated shares heldby each group and construct three ownership dummy variables for each bank in each year according tothe type of majority shareholders.


3.4. Institutional development

Our indicator of banking reform is obtained from the EBRD (European Bank for Reconstruction andDevelopment). The EBRD measures banking reform progress in the following three areas: (i) creationof a two-tier banking sector and interest rate liberalization, (ii) establishment of regulatory norms forprudential regulation and supervision and full liberalization of credit and interest rates, (iii) significantprogress toward the implementation of the core principles of the Basle Committee (EBRD, 2006). Toassess the progress of banking reform, the EBRD research group compiles an indicator ranging from 1to 4.3, with higher numbers indicating higher stages of development in the liberalization of interestrates and credit allocation; substantial progress in the establishment of bank solvency and aframework for prudential supervision and regulation; significant lending to private enterprises andsignificant presence of private banks.

The security market reform indicator also comes from the EBRD report. The indicator reflects theprogress of reforms in the securities market and nonbank financial institutions. The measure rangesfrom 1 to 4.3. ‘‘1’’ means little progress. ‘‘2’’ means the formation of securities markets and regulatoryagencies, including securities exchanges, market-makers and brokers, some trading in governmentpaper and/or securities, and rudimentary legal and regulatory framework for the issuance and tradingof securities. ‘‘3’’ means substantial issuance of securities by private enterprises; establishment ofindependent share registries, secure clearance and settlement procedures, and some protection ofminority shareholders; emergence of non-bank financial institutions (for example, investment funds,private insurance and pension funds, leasing companies) and associated regulatory framework. ‘‘4’’means that securities laws and regulations approach IOSCO standards; substantial market liquidityand capitalisation; well-functioning non-bank financial institutions and effective regulation. Thehigher the score of the indicator, the more progress, and the closer the securities markets are to theperformance norms of advanced industrial economies.

Regarding legal reforms, we borrow the creditor-rights indicator provided by Pistor (2000), Pistoret al. (2000) and Haselmann et al. (2010). Their creditor-rights indicator evaluates the progress of legalreforms in two areas: individual enforcement regimes (collateral laws) and collective enforcementregimes (bankruptcy laws). The collateral laws specify the type and scope of security interests a lendermay require (e.g. whether mortgaged land or personal assets can be used as collateral). Bankruptcylaws ensure an orderly procedure for conflicting claims so that creditors can control the liquidationprocess and avoid a wasteful run on the assets of firms. Table 1 provides the definitions and datasources for the variables used in our study, including bank characteristics, institutional indicators, aswell as country-level macro variables. The summary statistics and correlation matrices for thevariables are provided in Tables 2 and 3. All the variable statistics are consistent with existingempirical studies, and there is no multicollinearity problem. Table 4 describes the statistics of reformindicators in each country.

4. Results

4.1. Difference-in-difference estimations on the role of institutional reforms

We examine the effects of institutional reforms on banks’ Tobin’ Q using a DID approach followingBertrand and Mullainathan (2003) and Haselmann et al. (2010). The estimation is at the individualbank level and is specified as:

Qi;t ¼ a0 þ at þ a j þX

b � ðReform indicatorsÞ j;t þX

g � ðControlsÞi;t þ ei;t (1)

where i indexes individual banks, j indexes countries, and t indexes years. The model includes a full setof time effects (at), country fixed effects (aj), a constant term (a0), and various bank-specific andcountry macro controls. The dependent variable is individual banks’ Tobin’s Q, measured by the ratioof market value of equity to book value of equity at year t. Independent variables of interest are thethree types of institutional reforms, namely banking reform, security market reform, and legal reform.We are interested in estimating the coefficients of each reform indicator (b) which captures thesensitivity of Tobin’s Q to institutional reforms. Considering that the reform indicators represent

Table 1Variable definitions.

Variable name Definition Data source

Bank variables/controls

ROA Net profit divided by total assets Bankscope

Equity return volatility Standard deviation of stock weekly returns of each bank

computed over the year

Bankscope

Loan to asset ratio Net loans divided by total assets Bankscope

Deposit to asset ratio Total deposits divided by total assets Bankscope

Equity to asset ratio Total equity divided by total assets Bankscope

Size Logarithm of total assets

Loan growth Annual growth rate of loans

Asset growth Annual growth rate of assets

Z-score Calculated as the sum of ROA and equity-to-assets divided

by the standard deviation of ROA of each bank over past

three years.

Bankscope

Domestic private =1 if more than 50% ownership is domestic private entities Bankscope

Foreign majority =1 if more than 50% ownership is foreign entities

Lerner index This index is defined as the mark-up of the price over

marginal cost, divided by the price (Lerner, 1934). It

captures the degree of market power of a bank

Income_HHI The degree of concentration across two types of income:

interest income and non interest income, measured by

Herfindahl–Hirschman Index approach following Acharya

et al. (2006)

Asset_HHI The degree of concentration across two types of assets:

loans and other earning assets, measured by Herfindahl-

Hirschman Index approach following Acharya et al. (2006)

Institutional variables Bankscope

Legal_reform An index that evaluates the progress of legal reforms in

collateral laws and bankruptcy laws

Pistor (2000) and

Haselmann et al. (2010)

Banking reform An index that measures the degree of liberalization of

interest rates, the allocation of bank credit, whether there is

significant lending to private enterprises, whether there is a

significant presence of private banks, and whether bank

supervision and regulation are prudential. The indicator

goes from 1 to 4.3, with higher numbers indicating higher

stages of development

EBRD

Security market reform An index that measures the extent of security market

development, regulations, security laws, and issuance of

securities by private enterprises. The values increase from

1.0 to 4.3, with higher values implying a higher level of

progress

EBRD

Country macro controls

SEE =1 if the country is in South-Eastern Europe (Romania,

Bulgaria, and Croatia in our sample)

GDP per capita GDP per capita in thousand dollars WDI 2010

Inflation Annual growth rate of the consumer price index WDI 2010

Deposit insurance =1 both when the country has explicit deposit insurance and

when depositors were fully compensated the last time a

bank failed if the country did not have formal deposit

insurance

Demirguc-Kunt et al. (2007)

Bank crisis =1 if this country is going through a situation where the

banking sector becomes insolvent and cannot continue to

operate without special assistance from supervisory

authorities

Laeven and Valenci (2010)


year-end status, we use one-year lag values of the reform indicators in the analysis. We control forvarious bank-specific characteristics, including logarithm of total assets (Size), total loans (Loan to

Assets), total deposit (Deposit to Assets), equity (Equity to Assets), financial stability Z-score (ln_Z),profitability (ROA), and two growth variables (loan growth and asset growth). Growth rates are

Table 3Correlation matrices.

Size Loan to

assets

Deposit to

assets

Equity to

assets

Loan

growth

Asset

growth

ln_Z ROA

Panel A. Correlations among bank specific variables

Size 1

Loan to assets 0.10 1

Deposit to assets 0.01 �0.09 1

Equity to assets �0.51* �0.08 �0.49* 1

Loan growth �0.01 0.10 0.05 0.02 1

Asset growth �0.05 0.02 0.13 �0.09 0.77* 1

ln_Z 0.14* 0.21* �0.07 �0.03 0.10 0.10 1

ROA 0.15* �0.04 �0.42* 0.39* �0.03 �0.13 0.07 1

Panel B. Correlations among country variables

GDP growth

rate

Inflation Banking

crisis

DI SEE8 Banking

reform

Security

market reform

Legal

reform

GDP growth rate 1

Inflation �0.03 1

Banking crisis �0.32* 0.18* 1

DI 0.05 �0.14* 0.04 1

SEE �0.34* �0.12 0.21* 0.09 1

Banking reform 0.22* �0.04 �0.29* 0.07 0.09 1

Security market reform 0.12 0.05 �0.32* 0.11 �0.63* 0.35* 1

Legal reform �0.19* 0.37* 0.01 �0.16* �0.27* �0.29* 0.22* 1

* Significance level at least at the 10% significance level.

Table 2Summary statistics.

Variable name N Mean Median Std. dev. 5 percentile 95 percentile

Bank specific variables

Size 204 14.59 14.86 1.36 12.24 16.40

Loan to assets 204 0.56 0.56 0.14 0.33 0.81

Deposit to assets 204 0.79 0.83 0.09 0.62 0.91

Equity to assets 204 0.10 0.09 0.04 0.05 0.19

Loan growth 204 0.21 0.12 0.33 �0.04 0.77

Asset growth 204 0.16 0.09 0.22 0.00 0.54

ln_Z 204 3.73 3.73 0.87 2.23 5.08

ROA 204 0.01 0.01 0.01 0.01 0.03

Lerner 204 0.31 0.31 0.15 0.11 0.51

Income_HHI 204 0.64 0.63 0.08 0.51 0.78

Asset_HHI 204 0.55 0.52 0.07 0.50 0.71

Equity return volatility 147 0.07 0.05 0.07 0.03 0.15

Foreign_majority 149 0.68 1.00 0.47 0.00 1.00

domestic_private 136 0.28 0.00 0.45 0.00 1.00

Country level variables

Gdp growth 204 5.36 4.98 2.32 1.50 9.98

Inflation 204 4.72 3.74 3.53 0.98 11.72

Banking crisis 204 0.07 0.00 0.27 0.00 1.00

DI 204 0.98 1.00 0.12 1.00 1.00

SEE 204 0.33 0.00 0.47 0.00 1.00

Banking_reform 204 3.53 3.67 0.36 3.00 4.00

Security_market_reform 204 3.04 3.00 0.46 2.33 3.67

Legal_reform 204 3.02 3.00 0.53 2.23 3.85

This table reports summary statistics for the main analysis variables.


Table 4Description of Institutional Reforms by Country.

Country Banking reform index Security market reform index Legal reform index

Mean Median Min Max Mean Median Min Max Mean Median Min Max

BULGARIA 3.67 3.67 3.67 3.67 2.78 2.67 2.67 3.00 3.04 3.01 3.01 3.10

CROATIA 3.53 3.67 2.67 4.00 2.61 2.67 2.33 3.00 2.86 2.77 2.24 3.50

CZECH REPUBLIC 4.00 4.00 4.00 4.00 3.67 3.67 3.67 3.67 3.25 3.27 3.12 3.35

ESTONIA 3.84 3.84 3.67 4.00 3.33 3.33 3.33 3.33 3.04 2.91 2.63 3.70

HUNGARY 4.00 4.00 4.00 4.00 3.76 3.67 3.67 4.00 3.12 2.97 2.15 3.85

LATVIA 3.76 3.67 3.67 4.00 3.00 3.00 3.00 3.00 2.55 2.45 1.51 3.50

LITHUANIA 3.28 3.17 3.00 3.67 2.92 3.00 2.33 3.33 2.88 2.85 1.67 3.70

POLAND 3.42 3.33 3.00 3.67 3.59 3.67 3.33 3.67 3.32 3.48 2.32 3.85

ROMANIA 3.00 3.00 3.00 3.00 2.33 2.33 2.33 2.33 2.77 2.77 2.45 3.10

SLOVAKIA 3.67 3.67 3.67 3.67 2.92 3.00 2.67 3.00 2.95 3.01 2.49 3.27

SLOVENIA 3.33 3.33 3.33 3.33 2.75 2.67 2.67 3.00 3.49 3.48 3.15 3.85

This table shows the summary statistics of three institutional reform indices for individual countries over the sample period

from 1998 to 2008.


computed using the annual percentage change of total loans and total assets, respectively. Thedetailed definitions of these variables can be found in Table 1. As for country-level controls, we includecountry fixed effects. The significance of our results remains unchanged when adding additionalcountry-level variables such as inflation and GDP growth rate.

Table 5 reports the estimation results of Eq. (1). Column 1 examines the effect of banking reform onTobin’s Q. The coefficient is 0.5638 (statistical significance is at the 5% level), which implies that

Table 5Difference-in-difference estimations relating institutional reforms and Tobin’s Q.

Variables Q

(1) (2) (3) (4)

Reform indicators

Banking reform 0.56** (2.50) 0.85** (2.40)

Security market reform �1.57*** (�3.20) �1.74*** (�3.43)

Legal reform 0.08* (1.95) 0.05* (1.77)

Controls

Size �0.05 (�0.53) �0.03(�0.39) �0.04 (�0.40) �0.05 (�0.54)

Loan to assets �1.99** (�2.26) �1.78** (�2.25) �1.99** (�2.27) �1.73**(�2.23)

Deposit to assets �2.89* (�1.75) �3.66** (�2.33) �2.59(�1.61) �4.15*** (�2.60)

Equity to assets �4.83 (�1.54) �5.66* (�1.89) �4.41 (�1.40) �6.17* (�1.95)

Loan growth 0.13 (0.35) 0.19 (0.55) 0.18 (0.47) 0.11 (0.33)

Asset growth �0.04 (�0.07) �0.21 (�0.40) �0.10 (�0.19) �0.11 (�0.22)

ln_Z 0.03 (0.33) 0.08 (0.83) 0.02 (0.22) 0.10 (1.05)

ROA �0.63 (�0.03) �1.87 (�0.11) 1.91 (0.10) �6.54 (�0.37)

Constant 4.38 (1.47) 11.86*** (2.89) 5.22* (1.71) 10.21** (2.57)

Year fixed effects Yes Yes Yes Yes

Country fixed effects Yes Yes Yes Yes

Observations 204 204 204 204

Adjusted R-squared 0.63 0.65 0.63 0.66

This table presents difference-in-difference estimations relating institutional reforms and bank Tobin’s Q. The dependent

variable is the Tobin’s Q, measured by the ratio of market to book value of equity. The main independent variables are the three

institutional reforms, namely banking reform, security market reform, and legal reform. Control variables include various bank

characteristics. Variable definitions are reported in Table 1. The first three columns regress the individual reform indicator on

Tobin’s Q and the last column includes all reform indicators in one regression. All the regressions control for year and country

fixed effects. Difference-in-difference estimations are implemented. Robust standard errors are applied. T-statistics are

presented in brackets.* Significance at 10% level.** Significance at 5% level.*** Significance at 1% level.


Tobin’s Q would increase by 0.5638 when banking reform indicators increase by 1. It also indicatesthat with one standard deviation increase in banking reform (Std. dev. of banking reform is 0.364)banks enjoy an increase of 0.2 in Tobin’s Q (0.2=0.5638�0.364). The impact of banking reforms onTobin’s Q is economically significant. In Column 3 we find that legal reform also exerts a positive effecton Tobin’s Q, with a coefficient of 0.0869. The statistical significance and economic impact arerelatively smaller compared with banking reform. In Column 2 we find that security market reformhas a negative impact on banks’ Tobin’s Q. The coefficient is �2.5759, which is highly significant interms of both economic and statistical meaning. Specifically, one standard deviation increase ofsecurity market reform could reduce Tobin’s Q by 0.84 (0.84=1.5759�0.531). In the last column, weinclude all three types of reforms in the regression to control for each other. The results are consistentwith the estimation results in the first three columns, meaning that the simultaneous control for otherreforms does not affect our main findings.

The findings are generally consistent with the literature. In particular, liberalization leads to anincrease of operating efficiency and future growth opportunity of banks (Fries and Taci, 2005). Bankingreform is also found to enhance bank stability (Fang et al., 2011a). Legal institutional development hasbeen documented as an important factor affecting banking market development. In particular,Haselmann et al. (2010) show that banks significantly increased lending after bankruptcy laws andcollateral laws were reformed in former socialist countries. Fang et al. (2011a) find that stronger legalreforms reduce banks’ earnings’ volatility, equity risk, as well as non-performing loans. The findings inour paper are consistent with these studies. There have not been many studies looking into the impactof security market reform on the banking industry of transition economies. According to the EBRD,security reforms are aimed to build and improve the functioning of stock markets, give shareholdersmore rights and protection, and provide better monitoring and governance of the security listingprocess. Hence, as a security market is established, there are more companies seeking financing viasecurities exchanges and shareholders are empowered with more rights compared with creditors likebanks. From these perspectives, the strengthening of the security market could inherently reducebank profitability and increase the risk of expropriation by shareholders. We find that security marketdevelopment hurts the growth opportunities of banks. These findings are consistent with substitutingrelations between stock market and bank market as two alternative financing sources.

4.2. The interplay among institutional reforms and their effects on Tobin’s Q

After analyzing the individual effects of three institutional reforms on banks’ Tobin’s Q, we furtherexplore if there are any complementary or substitute effects among the reforms. The argument is thatdifferent types of reforms could be potentially dependent on each other to effectively reduce/increaseTobin’s Q. For example, when the security market is well developed, the impact of banking reform onbanks’ Tobin’s Q might be not as strong due to the increased competition among two financialmarkets. Or, when the banking reform is well implemented, the legal reform could have a strongerimpact on banks’ Tobin’s Q. When one reform shows a positive effect depending on the gooddevelopment of another reform, it is an indication of a complementary effect. When a reform shows anegative effect depending on the good development of another reform, this is an indication of asubstitute effect. If the effect of one reform does not vary with the development of another reform, thissuggests no interacting effects between these two reforms. In other words, the effect of this reform isindependent upon other reforms. Or this reform plays a more dominant and direct role on banks’Tobin’s Q.

We test the interacting effects using OLS regression with a year fixed effect. We control for the sameset of bank specific variables as the regression in Table 5. In addition, since we do not have a countryfixed effect in the OLS model, we add a set of country macro variables to control for country effects. Inparticular, we have Inflation, GDP growth rate, an indicator of deposit insurance (DI), an indicator ofBank Crisis, and a dummy variable of SEE indicating whether the country is in Southeastern Europe(Bulgaria, Croatia, Romania) or Central Eastern Europe (Czech Republic, Estonia, Hungary, Latvia,Lithuania, Poland, Slovakia, and Slovenia). We use Inflation to control for macroeconomic stability andGDP growth rate to capture the economic development of a country. Deposit Insurance is used to proxyfor market discipline, which influences bank stability (Demirguc-Kunt and Detragiache, 2002; Barth

Table 6OLS regressions on the interactions among institutional reforms and Tobin’s Q.

Dependent

variable

Q

High bank

reform (1)

Low bank

reform (2)

High security

market

reform (3)

Low security

market

reform (4)

High legal

reform (5)

Low legal

reform (6)

Banking reform �4.63 (�1.12) 2.40** (2.17) 4.27* (1.68) 2.05* (1.89)

Legal reform 5.19* (2.01) 1.08* (1.67) 0.80* (1.86) 0.51* (1.71)

Security Market

reform

�1.82* (�1.91) �0.46 (�0.58) �3.88* (�1.90) 0.73 (1.30)

Controls

Size 0.04 (0.30) 0.01 (0.07) �0.17 (�0.68) 0.19 (1.65) 0.10 (0.23) 0.11 (1.36)

Loan to assets �0.42 (�0.29) �1.16 (�0.92) �4.99** (�2.66) 1.05 (1.12) �1.56 (�0.52) �0.58 (�0.76)

Deposit to assets �2.52 (�1.34) 3.15 (0.81) �10.75*** (�3.95) 4.70** (2.48) �9.83* (�1.76) 2.86 (1.49)

Equity to assets �13.59 (�1.61) 6.46 (0.99) �10.63 (�1.58) 9.17** (2.25) �20.08 (�1.63) 5.52 (1.39)

Loan growth �1.59 (�0.81) �0.02 (�0.04) �0.17 (�0.10) 0.33 (0.81) 1.04 (0.36) �0.20 (�0.73)

Asset growth 4.00 (1.38) 0.19 (0.24) 0.60 (0.30) �0.38 (�0.53) �2.26 (�0.47) 0.18 (0.33)

ln_Z 0.18 (0.96) �0.27* (�1.85) 0.23 (1.06) �0.41*** (�2.65) �0.21 (�0.62) �0.20* (�1.77)

ROA 52.21 (1.17) 33.92 (1.37) 6.05 (0.19) 18.15 (0.75) 89.47* (1.76) 29.50* (1.77)

GDP growth rate �0.28 (�0.53) �0.05 (�0.65) �0.11 (�0.86) �0.13 (�1.20) 0.17 (0.38) �0.17* (�1.96)

Inflation �0.53* (�1.97) 0.04 (0.57) �0.46*** (�2.78) 0.06 (1.04) 0.69 (1.48) 0.08 (0.81)

Banking crisis 1.99 (1.65) 0.18 (0.27) 0.00 (.) �0.27 (�0.46) �1.24 (�0.92) �0.48 (�0.93)

DI 0.00 (.) �0.45 (�1.11) 0.00 (.) �1.66** (�2.41) 0.00 (.) �0.95*** (�2.77)

SEE �0.50 (�0.15) 1.30** (2.60) 0.00 (.) 1.68*** (2.68) 3.44 (1.60) 1.24** (2.16)

Constant �3.92 (�0.30) �6.37 (�1.02) 18.17** (2.59) 11.05*** (2.90) �3.36 (�0.32) 2.73 (0.86)

Year fixed effects Yes Yes Yes Yes Yes Yes

Observations 58 146 76 128 74 130

Adjusted R-squared 0.57 0.25 0.53 0.55 0.34 0.43

This table presents OLS estimations on the interplay between different types of reforms. The dependent variable is Tobin’s Q,

measured by the ratio of market value to book value of equity. Columns (1)–(2) examine the effects of Legal Reform and Security

Market Reform on Q, depending on the level of Banking Reform. Columns (3)–(4) examine the effects of Legal Reform and Banking

Reform on Q, depending on the level of Security Market Reform. Columns (5)–(6) examine the effects of Security Market Reform

and Banking Reform on Q, depending on the level of Legal reform. Control variables include various bank characteristics and

country macro factors. All estimations have a year fixed effect with robust standard errors. T-statistics are presented in brackets.* Significance at 10% level.** Significance at 5% level.*** Significance at 1% level.


et al., 2006). Bank Crisis is a dummy variable that equals 1 if the country is going through a systemiccrisis in a given year and 0 otherwise. We include it in the model to control for the negative impact ofbank crises on the stability of banking sectors. The detailed definitions of these variables can be foundin Table 1.

As shown in Table 6, Columns 1 and 2, we divide our sample into two groups: high bank reformmeans that the value of the banking reform indicator is higher than median; low bank reform meansthat the value of the banking reform indicator is lower than the median value of the sample. Note thata bank may belong to one group in a certain year while moving to the other group in another when thecountry-level banking reform changes. The findings suggest that legal reform has a stronger andpositive effect on Tobin’s Q when the banking reform is well executed, while the effect is much smallerwhen the banking reform is poor. This result implies that banking reform plays an importantcomplementary role with legal reforms. The effect of security market reform, however, is negativewhen the bank reform is good, while it is insignificant when the bank reform is poor. These findingssupport the competition argument – that is, there is tension between the banking market and thesecurity market, and hence, when the bank reform is good, the strengthening of security marketdevelopment reduces banks’ further growth opportunities in providing financing to enterprises. InColumns 3 and 4 we examine the effects of banking reform and legal reform depending on high versus


low security market reform. When the security market is poorly reformed, banking reform exerts asignificant and strong impact on Tobin’s Q, and similarly legal reform also positively affects Tobin’s Q.However, when the security market is well reformed, the positive impact of bank reform on Tobin’s Qis significantly reduced. The coefficient of banking reform on Tobin’s Q when the security market ishigh is not statistically significant. Again, this implies a substitute effect between these two reforms.Lastly, we look at what role legal reform plays with the other two reforms in Columns 5 and 6. Ourresults indicate that when legal reform is good, banking reform has a strong effect on Tobin’s Q,supporting the complementary effect. However, security market reform still negatively affects Tobin’sQ when the legal reform is good, indicating a substitute effect. When legal reform is poor, we find thatbanking reform has a weaker impact on Tobin’s Q and security market reform does not have asignificant impact.

4.3. The role of market power, ownership, and diversification on Tobin’s Q

In Tables 7–9, we analyze the relationship between banks’ Tobin’s Q and a set of independentvariables. In particular, we examine the role of market power, ownership structure, and diversificationat individual bank level. The estimations employ OLS regressions with a year fixed effect. The modelspecifications are as follows:

Qi;t ¼ a0 þ a1 � Lerner indexi;t þ a2 �X

b � ðControlsÞi; t þ ei;t; (2)

X
Qi;t ¼ a0 þ a1 � foreigni;t þ a2 � domestic privatei;t þ a3 � b � controlsi;t þ ei;t ; (3)
X
Qi;t ¼ a0 þ a1 � income divi;t þ a2 � asset divi;t þ a3 � b � controlsi;t þ ei;t; (4)
where i indexes individual banks, j indexes countries, and t indexes years.

Table 7Regressions relating market power and Tobin’s Q.

Variables OLS SUR

(1) Q (2) Q (3) Equity return volatility

Lerner 0.94** (2.56) 3.36** (2.52) �0.21* (�1.94)

Controls

Size �0.01 (�0.19) 0.18 (1.16) �0.03*** (�2.62)

Loan to assets �1.73* (�1.76) �3.88*** (�4.56) �0.01 (�0.08)

Deposit to assets �5.01** (�2.24) �5.29*** (�3.56) �0.17 (�1.34)

Equity to assets �10.02** (�2.09) �10.99** (�2.20) �0.54 (�1.25)

Loan growth 0.14 (0.49) 0.21 (0.57) 0.01 (0.43)

Asset growth 0.01 (0.01) �0.28 (�0.31) �0.028 (�0.35)

ln_Z 0.15 (1.54) 0.18 (1.43) �0.01 (�0.75)

ROA 18.58 (0.66) �14.17 (�0.37) �1.46 (�0.45)

GDP growth rate �0.044 (�0.73) �0.12 (�1.59) �0.01 (�0.68)

Inflation �0.05 (�0.76) �0.16** (�2.18) 0.002 (0.33)

Banking crisis �0.18 (�0.53) �0.44 (�0.91) �0.01 (�0.14)

SEE 0.39 (0.56) �0.71 (�0.51) 0.019 (0.15)

Constant 6.23 (1.64) 0.0000 (.) 0.00 (.)

Year fixed effects Yes Yes Yes

Observations 129 90 90

Adjusted R-squared 0.74 0.85 0.28

This table reports the regressions relating market power and Tobin’s Q. Market power is measured by the Lerner index. Column

(1) applies OLS regressions with bank specific variables and country variables as controls. Columns (2) and (3) implement the

SUR regression on Tobin’s Q and equity return volatility simultaneously. In all estimations, a year fixed effect is included. T-

statistics are presented in brackets.

Robust t-statistics in parentheses. ***p<0.01, **p<0.05, *p<0.1.* Significance level at 10%.** Significance level at 5%.*** Significance level at 1%.

Table 8Regression relating ownership structure and Tobin’s Q.

Variables OLS SUR

(1) Q (2) Q (3) Equity return volatility

Foreign_majority 0.44* (1.72) 0.40* �0.02 (�0.20)

Domestic_private �0.37 (�0.67) �0.21 (�0.24) 0.12 (1.44)

Controls

Size �0.01 (�0.02) 0.59** (2.46) �0.08*** (�3.34)

Loan to assets �1.54 (�1.38) �5.50*** (�5.70) 0.15* (1.67)

Deposit to assets �5.37* (�1.93) �3.91** (�2.45) �0.53*** (�3.37)

Equity to assets �8.62 (�1.64) 1.43 (0.17) �3.60*** (�4.40)

Loan growth �0.28 (�0.53) 0.07 (0.15) �0.05 (�0.98)

Asset growth 0.33 (0.32) 0.47 (0.59) 0.02 (0.31)

ln_Z 0.07 (0.54) �0.086 (�0.49) 0.01 (1.07)

ROA 34.08 (1.39) 27.61 (0.93) 4.04 (1.37)

GDP growth rate 0.02 (0.24) �0.03 (�0.31) �0.01 (�0.35)

Inflation �0.03 (�0.54) �0.10 (�1.31) 0.01 (1.28)

Banking crisis 0.13 (0.31) �0.41 (�0.81) �0.03 (�0.71)

SEE 0.66 (0.75) �0.82 (�0.19) �0.22* (�1.82)

Constant 5.51 (1.29) 0.00 (.) 1.86*** (4.31)




This table reports the regressions relating bank ownership structure and Tobin’s Q. Foreign majority is an indicator which equals

1 if more than 50% of the bank’s shares are under foreign ownership. Domestic private equals 1 if more than 50% of the bank’s

shares are under domestic private ownership. Column (1) applies OLS regressions with bank specific variables and country

variables as controls. Columns (2) and (3) implement the SUR regression on Tobin’s Q and equity return volatility

simultaneously. In all estimations, a year fixed effect is included. T-statistics are presented in brackets.* Significance level at 10%.** Significance level at 5%.*** Significance level at 1%.


Our dependent variables (Qi,t) represent the Tobin’s Q of bank i at time t. To measure the marketpower of a bank, we employ the Lerner index, a well-established indicator of market power at theindividual bank level. It is defined as the mark-up of the price over marginal cost, divided by the price(Lerner, 1934). It captures the power of individual banks to set prices above marginal cost. A highervalue of the Lerner index denotes higher market power of the bank.

To measure ownership structure, we group shareholders into three categories: foreign, domesticprivate, and government. We then calculate the aggregated shares held by each group and constructthree ownership dummy variables for each bank in each year according to the type of majorityshareholders. foreign_dummy indicates the banks whose majority owners are foreign, and domestic

private dummy indicates the banks whose majority owners are domestic private investors (companies).We capture diversification in two dimensions: assets and loans. Total assets (T) are decomposed

into total loans (A1) and assets in financial investment (A2). Total loans (L) are decomposed intocorporate loans (L1) and loans to non-corporations (L2), which includes mortgages, government loans,interbank loans, and other lending. We construct the focus index based on the above decompositionusing a Herfindahl–Hirschman Index approach following Acharya et al. (2006). The focus index iscalculated as the sum of squares of the proportions of portfolios in each classification. Specifically,

Loan focus index ¼X2

i¼1

Li

Q

� �2

; where Q ¼X2

j¼1

L j;

Asset focus index ¼X2 Ai

� �2

where T ¼X2

A j:
i¼1
Tj¼1

By definition, the focus index ranges from 1/n (here ½) in this case to 1, higher values indicating ahigher degree of focus and a lower degree of diversification. Table 7 reports the regression results

Table 9Regression relating diversification strategy and Tobin’s Q.

Variables OLS SUR

(1) Q (2) Q (3)Equity return volatility

Loan_HHI �2.92** (�2.46) 1.28 (0.71) �0.05 (�0.36)

Asset_HHI �2.81** (�2.13) �2.29* (�1.86) 0.17 (1.04)

Controls

Size 0.001 (0.11) 0.20 (1.24) �0.03** (�2.37)

Loan to assets �2.22** (�2.44) �3.51*** (�3.99) 0.01 (0.01)

Deposit to assets �4.83** (�2.08) �5.38*** (�3.61) �0.18 (�1.41)

Equity to assets �8.45* (�1.73) �11.31** (�2.25) �0.48 (�1.11)

Loan growth 0.01 (0.01) 0.18 (0.48) 0.02 (0.75)

Asset growth 0.33 (0.59) 0.34 (0.39) �0.01 (�0.19)

ln_Z 0.17* (1.92) 0.23* (1.72) �0.01 (�0.97)

ROA 37.47*** (2.69) 35.47 (1.53) 1.55 (0.78)

GDP growth rate �0.02 (�0.35) �0.08 (�1.03) �0.01 (�0.56)

Inflation �0.08 (�1.61) �0.15** (�2.05) 0.01 (1.08)

Banking crisis �0.07 (�0.21) �0.46 (�0.91) �0.01 (�0.37)

SEE 0.28 (0.55) 6.77** (2.37) �0.05 (�0.51)

Constant 5.42 (1.49) 0.00 (.) 0.77*** (3.06)




This table reports the regressions relating diversification and Tobin’s Q. Income HHI is a measure of income portfolio

diversification. Higher income HHI means a higher degree of concentration of income in interest and non-interest income. Asset

HHI is a measure of asset portfolio diversification. A higher value of asset HHI means a higher degree of asset concentration in

traditional banking businesses and investing activities. Column (1) applies OLS regressions with bank specific variables and

country variables as controls. Columns (2) and (3) implement the SUR regression on Tobin’s Q and equity return volatility

simultaneously. In all estimations, a year fixed effect is included. T-statistics are presented in brackets.* Significance level at 10%.** Significance level at 5%.*** Significance level at 1%.


relating market power to bank Tobin’s Q. In the OLS regression (Column 1) we find that the Lernerindex has a positive effect on banks’ Tobin’s Q. The effect is significant at 10% and translates into anincrease of 0.14 in Tobin’s Q when the Lerner index increases by one standard deviation(0.14=0.947�0.15). To take into consideration the effect of equity risk on Tobin’s Q, we runsimultaneous equations on both Tobin’s Q and equity risk using seemingly unrelated regressions. Theresults in Columns 2 and 3 suggest that the effect of market power as proxied by the Lerner index onTobin’s Q becomes even stronger when we simultaneously control for equity risk. Market power,however, has a negative equity risk. Overall, our findings on market power suggest that the marketpower of banks plays a significant and positive role in enhancing banks’ value and growthopportunities. In particular, this is consistent with the argument that banks with greater marketpower gain monopolistic profit and enjoy higher interest margins. Therefore, they have a betteroperating performance.

Table 8 reports the regression results relating ownership structure to bank Tobin’s Q. We firstconsider the results from the OLS regressions. As shown in Column 1, foreign ownership is associatedwith higher Tobin’s Q. The coefficient is statistically significant and economically meaningful. Onestandard deviation increase of foreign ownership increases Tobin’s Q by 0.2 (0.2=0.366�0.4383).However, domestic ownership is not significantly associated with Tobin’s Q. The positive effect offoreign ownership on banks’ Tobin’s Q could be mostly related to superior management skills, easyaccess to international markets, and the introduction of new products with premium pricing. It is alsoconsistent with previous findings regarding the superior bank efficiency of foreign banks comparedwith domestic and government banks. In Columns 2 and 3 we run simultaneous equations on bothTobin’s Q and equity risk. The results do not change materially. The ownership structure does notappear to affect equity risk in a significant way.


Table 9 examines the effects of loan and asset diversification on banks’ Tobin’s Q. As shown inColumn 1, both loan focus index (loan_HHI) and asset focus index (asset_HHI) are negativelyassociated with Tobin’s Q. Both coefficients are statistically significant at the 5% level. Since the focusindex is an inverse measure of diversification, this result suggests that a higher degree ofdiversification increases banks’ growth opportunities. In Columns 2 and 3, we simultaneously controlfor equity risk and find that the effect of the loan focus index loses its statistical significance, while theasset focus index still shows a significant and positive impact on Tobin’s Q. These findings areconsistent with the argument that diversification creates an economy of scope, opening upopportunities for future growth. In particular, our results are more robust for asset diversification.They suggest that asset diversification tends to produce a premium for bank value, which is consistentwith previous studies on bank diversification in transition economies (Fang et al., 2011b).

5. Conclusions

During the past 20 years, transition economies have undergone significant economic andinstitutional reforms. The banking sectors were liberalized and privatized with a large number offoreign banks involved. Securities markets were formed in most countries and reforms took place toimprove the functioning of stock markets, strengthen shareholders rights, and provide bettermonitoring and governance of the security listing process. At the same time, to better protect investorsand especially creditors’ rights, the government also put great efforts into reforming legislations andfinancial laws to create an investor-friendly, transparent, and predictable legal environment. Inparticular, collateral and bankruptcy laws were revised following the standard of Western model laws(Dahan, 2000). It has been documented that the overall quality of the legal environment of transitioncountries has sustainably improved over the past decade (Pistor, 2000).

Our findings suggest that bank valuation increases substantially after transition countries reformtheir legal institutions and liberalize the banking system. However, it decreases after stock marketreforms. After further examination of the interactive relationships between different reforms andbank valuation, we find that when the banking reform is well implemented, the legal reform can havea stronger impact on banks’ Tobin’s Q. On the other hand, banking reforms and security marketreforms appear to have a substitutive relationship. When the security market is well developed, thepositive impact of banking reform on banks’ Tobin’s Q becomes smaller, and when the banking reformis good, the negative impact of the security market on Tobin’s Q is larger. When the banking reform ispoor, the negative effect of the security market on Tobin’s Q becomes insignificant. All things equal,foreign ownership, market power, and a higher degree of asset diversification increase banks’ chartervalue and thus shareholder wealth. These results are robust after we simultaneously control for thepotential linkage between valuation and equity risk.

The establishment of a relatively efficient, privately-owned banking system marks a major step forthese transition countries as they have been moving toward integration in the EU. Our study takes afurther step to look at the issue of bank valuation, and in particular the role of institutional reforms ininfluencing bank valuation. We also identify key bank characteristics that could affect it. Thesefindings provide additional evidence of bank valuation, which adds to the transition bankingliterature. Moreover, they provide policy implications for these countries regarding the ongoingdebate over how to enhance the capital ratio and bank charter value. Government policies towardbanking liberalization and creditor right reforms exert a strong and positive impact on theenhancement of bank valuation. However, reforms of the securities markets and non-bank financialinstitutions need to be formulated carefully and take into account that they might inherentlynegatively affect bank growth and shareholder wealth.

Acknowledgements

The authors thank the editors of the symposium and the two anonymous reviewers for insightfulsuggestions. The usual caveats apply.


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Bank valuation in new EU member countries