Bank valuation in new EU member countries

Economic Systems 38 (2014) 55–72

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Economic Systems jo urnal home page : www.elsevier.com/loc ate/ecos ys

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, IL 60661, United States Fordham University, 113 West 60th Street, New York, NY 10023, United States c Bank of Finland, Finland b

A R T I C L E I N F O

A B S T R A C T

Article history: Received 18 April 2013 Received in revised form 11 July 2013 Accepted 11 July 2013 Available online 9 October 2013

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. ß 2013 Elsevier B.V. All rights reserved.

JEL classification: G21 P30 P34 P52 Keywords: Bank charter value Foreign ownership Diversification Institutional development Market power Transition economies

* 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 ß 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.ecosys.2013.07.002

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1. Introduction The development of a sound banking system is vital to a country’s economic stability and longterm 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 met through banking sectors. Most importantly, the recent 20 years have witnessed substantial institutional reforms in both the financial and the enterprise sector. How these reforms in transition economies affect bank market development has attracted considerable interest from academia as well as policymakers.1 Prior studies examining the relationships between institutional reforms and bank performance have 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 to the valuation of publicly traded banks as measured by the market-to-book value of equity (Furlong and Kwan, 2005; Caprio et al., 2007). In particular, we examine how substantial changes in institutional 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. In addition, 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 structural changes of banking regulation, financial market structure, and competition environment in transition economies are likely to alter the valuation of banks in a significant way. Second, with the development of security markets, more transition banks are traded publicly in the local stock market. This makes bank valuation a timely and important issue to examine. Especially, Tobin’s Q could capture the further 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 risk management and enhancing the capital ratio. Having a sound charter value has been documented as a key contribution to reduce risk-taking incentives of shareholders, since they would risk all their value in 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 the banking sectors of major transition economies. In order to establish efficient market-oriented banking sectors, governments liberalized interest rates and decentralized central banks’ commercial banking activities to state banks. To foster competition, they also privatized a large number of domestic banks and allowed foreign banks to enter the market. Legal reform refers to government efforts in reforming legislation and financial laws to create an investor-friendly, transparent and predictable legal environment. In particular, 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 transition countries has substantially improved over the past decade (Pistor, 2000). We apply a difference-in-difference framework to explore the exogenous changes of banking reform, legal reform, and security market reform over time across countries.2 Specifically, we obtain yearly measures of legal reforms, banking liberalization, and security market reform for these transition countries from 1997 to 2008. For each year, countries that experienced reforms belong to the treatment group and countries with no changes belong to the control group. Given that the reforms in transition countries took place at different time periods in different countries, we apply the DID 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).

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2003; Hansen, 2007; Haselmann et al., 2010). This empirical strategy allows us to address many threats concerning validity. For example, comparing Tobin’s Q between the treatment and control groups in the post-reform periods removes biases due to the common economic trend of the two groups. Moreover, it also allows a comparison between the pre-reform and post-reform periods within the treatment group, which removes biases that could be due to other omitted time invariant factors rather than reform events. Our main findings show that legal reform and banking reform significantly enhance banks’ Tobin’s Q while security market reform decreases banks’ Tobin’s Q. We also observe that banking reform and legal reform complement each other in the sense that when a banking reform is well implemented, the legal reform can have a stronger impact on banks’ Tobin’s Q. On the other hand, banking reform and security market reform appears to have a substitutive relationship. Our analysis also shows that compared to domestic ownership, foreign ownership is associated with a significantly higher charter value. This is in line with former research findings that foreign banks in developing countries obtain higher returns on their investment (Claessens et al., 2001). There is no significant difference between domestic private banks and government-owned banks in terms of Tobin’s Q. Regarding the diversification strategy, we find that banks with higher degrees of asset diversification have higher Tobin’s Q, which supports the argument that diversification creates an economy of scope which opens up opportunities for future growth. The structure of this paper is as follows. In Section 2, we present a brief literature review and develop our hypotheses. Section 3 describes our sample on transition banks and introduces our measures. 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 and institutional reforms. Banking sectors, for example, had quite a different background compared with other parts of the world. Before the economic transformation started, central banks directed all the allocation of credit based on a government plan and commercial banks were specialized in serving certain economic sectors rather than diversified (Bonin et al., 2009). Therefore, banks under the socialist 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 of restructuring. To transform them into efficient and market-oriented banking sectors, governments liberalized interest rates and decentralized central banks’ commercial banking activities to state banks. To foster a competitive banking industry, state banks were privatized and a large number of foreign banks entered the market. More recently, governments put more effort into the establishment of prudential regulation and supervision guidelines. Significant progress has been made with the implementation of the core principles of the Basel Committee on Banking Supervision. Legal institutions had very weak shareholder and creditor protection (Pistor, 2000) at the beginning of the reforms. However, as the transition process advanced, governments established project groups working on legislation and the implementation of commercial and financial laws. For example, the focus of reforms was on remodeling secured transactions laws, company laws and insolvency laws by looking at their dissemination and judicial and administrative enforcement. In 2003, individual countries’ legal reform, e.g. the extent to which legal rules comply with international standards, the extent to which the legal regime provides an efficient result in a given practical situation, and how legislation, together with the local institutional framework, creates a functional (or dysfunctional) insolvency legal regime was evaluated by the EBRD. Securities markets were effectively non-existent at the beginning of transition. During the transition period, securities exchanges were formed and a rudimentary legal and regulatory framework for the issuance and trading of securities was established. In order to build wellfunctioning securities markets and help promote stock market performance, over the years governments have focused on the establishment of independent securities commissions, secure clearance and settlement procedures, and also on remodeling securities laws and regulations to

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protect monitory shareholders (Pistor et al., 2000). Nevertheless, the progress of these reforms has not been as successful as expected. Lessons were learned and more reforms continued to take place after some 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 banking issues. Studies generally find that banking reform, in particular the liberalization of interest rates and opening 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 the performance of cross-border bank acquisitions in transition countries. In analysing the impact of banking reforms on cost efficiency, Fries and Taci (2005) show that costs decrease during the early stages of the transition, but rise over time and with the implementation of reforms. A study by Brissimis et al. (2008) looks at transition economies that joined the European Union and finds that banking 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 loan characteristics and find that borrowers in countries with strong creditor-protection environments enjoy 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 the confidence of banks to lend to enterprises. For example, Haselmann and Wachtel (2007) show that banks tend to lend more to large enterprises in a weak legal system and more to SMEs when the legal system is sound and effective. Haselmann et al. (2010) investigate the impact of legal changes on bank lending. An interesting conclusion is that banks increase their credit supply subsequent to the improvement of the legal environment, especially for foreign banks. It is also found that higher creditor 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 with weaker 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 in transition economies. Based on the quiet life hypothesis, when a bank has monopoly power, managers reduce their efforts and gain monopoly rents through discretionary expenses (Hicks, 1935). Under this assumption market power affects performance negatively. The structure–conduct–performance paradigm, on the other hand, postulates that strong market power allows banks to extract monopoly rents through offering low deposit rates and charging high borrowing rates (Bain, 1956). Strong market power is also found to allow banks to take advantage of economies of scale to monitor borrowers and operate at higher cost efficiency (Diamond, 1984). Under this argument, market power and performance are related positively. The empirical research on the role of banking competition and market power on efficiency in transition economies presents conflicting findings. This may partly be related to differences among countries and the various approaches that were used to measure competition, for example industry level concentration measures, number of firms in the industry, and individual 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 transition economies differ study by study. Most early single country case studies find that foreign banks perform 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 a number of cross-country studies (e.g. Bonin et al., 2005a,b; Kasman and Yildirim, 2006). These studies

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are consistent with former research findings that foreign banks in developing countries obtain higher returns on their investment (Claessens et al., 2001). The superior performance of foreign-owned banks can be attributed to their management skills, advanced technology, access to lower cost funds from the parent company, lack of legacy costs (e.g. non-performing loans from former periods), and differences in clientele, such as larger shares of foreign-owned companies. Though foreign banks may have some advantages, they could also experience disadvantages, such as informational asymmetries in new markets, inadequate knowledge of local conditions, and difficulties in establishing relational networks. These factors tend to increase the costs of foreign banks and reduce their inherent advantages 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 different theoretical predictions and conflicting outcomes on the impact of diversification on bank performance. One stream of literature has found a positive impact of bank diversification on performance. The arguments highlight that by lending to different industries and engaging in multiple business activities banks can acquire better-quality information about clients and achieve more efficient 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, thereby creating economic synergies and better performance (Williamson, 1975; Boot and Schmeits, 2000; Iskandar-Datta and McLaughlin, 2005). Hence, they advocate bank diversification. Another stream of theories, however, postulates that diversification does not necessarily result in improved performance. Klein and Saidenberg (1998), for example, argue that expanding into multiple market segments 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 private benefits, 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 of banking sectors. Before that, banks were mainly lending to one particular industry and their lending activities were determined by the central banks’ plans. Liberalization provided banks with unprecedented opportunities to reach beyond the traditional lending business, removing the barrier of regulatory restrictions on various other banking activities. For publicly traded banks, corporate governance reforms in transition economies strengthened the confidence of banks’ shareholders to allow managers to purse value-increasing diversification. Claessens and Klingebiel (2000) argue that if banks were given greater freedom, they would use the opportunity to pursue economies of scale and scope, e.g. by diversifying into multiple income streams and thus reducing risk. Recent surveys by Barth et al. (2001, 2004) also provide evidence that strict diversification guidelines and loan classification stringency are associated negatively with banking sector development, efficiency, and financial stability. Whether diversification can help banks to better exploit economies of scale and scope 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 over the period of 1997–2008. The balance sheet financial variables are obtained from BankScope and stock data is mainly obtained from DataStream and completed with BankScope. Due to some reported shortcomings of the BankScope database (Bonin et al., 2005a) we make a careful examination of multiple 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 data for the bank rather than the holding company. Then we check the accounting standards. International Accounting Standards (IAS) data are used wherever available; otherwise, inflation-adjusted local accounting standards data are used. All bank-level data are inflation-adjusted and reported in USD. For a bank to be included in our sample, market capitalization information for the bank must also be available. We allow failures, mergers, and de novo entry of banks, but banks in our sample must have a

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minimum of three years of continuous data to obtain reliable estimates. The selection process yields an unbalanced panel with 60 banks in three SEE countries (Bulgaria, Croatia and Romania) and eight CEE 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. This index 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 higher value of the Lerner index 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) as total revenue (REV) divided by total earning assets (Y), and marginal cost (mcit) is calculated from the estimation of a translog cost function and is specified as follows:         TOC w1 1 w1 w1 1 ln ¼ a0 þ a1 ln þ a2 ln ln þ b1 lnðYÞ þ b2 lnðYÞlnðYÞ w2 2 2 w2 w2 w2     2 2 X X 1 w1 1 1 w þ lnðYÞln lnðYÞlnðzl Þ þ h ln 1 lnðzl Þ þ year dummies þ 2 2 l¼1 2 l¼1 l w2 w2 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 frontier function, 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 by taking derivatives with respect to Y. In the estimation, total equity (z1) is used as fixed inputs in the estimation to account for the banks’ endogenous choices of risk. The two input prices are the price of borrowed funds (w1 = interest expense divided by total borrowed funds) and the price of capital per fixed asset (w2 = non-interest expense divided by fixed asset). We normalize the equation by one input price (w2) to impose linear homogeneity of input prices (Kuenzle, 2005). Finally, n represents the random noise, which incorporates both measurement error and luck, and m is the inefficiency term that 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 to estimate this equation and obtain the coefficients. Since the Lerner index is the mark-up of the price over marginal cost divided by the price, it has an upper bound of 1 when the bank has monopoly power and operates with zero marginal cost. It has a value of zero when the price is equal to the marginal cost and the bank operates in a perfectly competitive market. The Lerner index can also be negative. This happens 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 economies changed ownership several times over the past two decades, it is important to have yearly ownership data 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 the year 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, if available. We also return to 1997 and 1998 using the same ownership as in 1999. To achieve higher accuracy we also search bank homepages and business publications. We group shareholders into three categories: foreign, domestic private, and government. We then calculate the aggregated shares held by each group and construct three ownership dummy variables for each bank in each year according to the type of majority shareholders.

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3.4. Institutional development Our indicator of banking reform is obtained from the EBRD (European Bank for Reconstruction and Development). The EBRD measures banking reform progress in the following three areas: (i) creation of a two-tier banking sector and interest rate liberalization, (ii) establishment of regulatory norms for prudential regulation and supervision and full liberalization of credit and interest rates, (iii) significant progress toward the implementation of the core principles of the Basle Committee (EBRD, 2006). To assess the progress of banking reform, the EBRD research group compiles an indicator ranging from 1 to 4.3, with higher numbers indicating higher stages of development in the liberalization of interest rates and credit allocation; substantial progress in the establishment of bank solvency and a framework for prudential supervision and regulation; significant lending to private enterprises and significant presence of private banks. The security market reform indicator also comes from the EBRD report. The indicator reflects the progress of reforms in the securities market and nonbank financial institutions. The measure ranges from 1 to 4.3. ‘‘1’’ means little progress. ‘‘2’’ means the formation of securities markets and regulatory agencies, including securities exchanges, market-makers and brokers, some trading in government paper and/or securities, and rudimentary legal and regulatory framework for the issuance and trading of securities. ‘‘3’’ means substantial issuance of securities by private enterprises; establishment of independent share registries, secure clearance and settlement procedures, and some protection of minority 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 liquidity and capitalisation; well-functioning non-bank financial institutions and effective regulation. The higher the score of the indicator, the more progress, and the closer the securities markets are to the performance norms of advanced industrial economies. Regarding legal reforms, we borrow the creditor-rights indicator provided by Pistor (2000), Pistor et al. (2000) and Haselmann et al. (2010). Their creditor-rights indicator evaluates the progress of legal reforms in two areas: individual enforcement regimes (collateral laws) and collective enforcement regimes (bankruptcy laws). The collateral laws specify the type and scope of security interests a lender may require (e.g. whether mortgaged land or personal assets can be used as collateral). Bankruptcy laws ensure an orderly procedure for conflicting claims so that creditors can control the liquidation process and avoid a wasteful run on the assets of firms. Table 1 provides the definitions and data sources for the variables used in our study, including bank characteristics, institutional indicators, as well as country-level macro variables. The summary statistics and correlation matrices for the variables are provided in Tables 2 and 3. All the variable statistics are consistent with existing empirical studies, and there is no multicollinearity problem. Table 4 describes the statistics of reform indicators 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 following Bertrand and Mullainathan (2003) and Haselmann et al. (2010). The estimation is at the individual bank level and is specified as: X X Q i;t ¼ a0 þ at þ a j þ b  ðReform indicatorsÞ j;t þ g  ðControlsÞi;t þ ei;t (1) where i indexes individual banks, j indexes countries, and t indexes years. The model includes a full set of time effects (at), country fixed effects (aj), a constant term (a0), and various bank-specific and country macro controls. The dependent variable is individual banks’ Tobin’s Q, measured by the ratio of market value of equity to book value of equity at year t. Independent variables of interest are the three 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 the sensitivity of Tobin’s Q to institutional reforms. Considering that the reform indicators represent

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Table 1 Variable definitions. Variable name Bank variables/controls ROA Equity return volatility Loan to asset ratio Deposit to asset ratio Equity to asset ratio Size Loan growth Asset growth Z-score

Domestic private Foreign majority Lerner index

Income_HHI

Asset_HHI

Institutional variables Legal_reform Banking reform

Security market reform

Country macro controls SEE GDP per capita Inflation Deposit insurance

Bank crisis

Definition

Data source

Net profit divided by total assets Standard deviation of stock weekly returns of each bank computed over the year Net loans divided by total assets Total deposits divided by total assets Total equity divided by total assets Logarithm of total assets Annual growth rate of loans Annual growth rate of assets Calculated as the sum of ROA and equity-to-assets divided by the standard deviation of ROA of each bank over past three years. =1 if more than 50% ownership is domestic private entities =1 if more than 50% ownership is foreign entities 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 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) The degree of concentration across two types of assets: loans and other earning assets, measured by HerfindahlHirschman Index approach following Acharya et al. (2006)

Bankscope Bankscope

An index that evaluates the progress of legal reforms in collateral laws and bankruptcy laws 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 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

=1 if the country is in South-Eastern Europe (Romania, Bulgaria, and Croatia in our sample) GDP per capita in thousand dollars Annual growth rate of the consumer price index =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 =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

Bankscope Bankscope Bankscope

Bankscope

Bankscope

Bankscope Pistor (2000) and Haselmann et al. (2010) EBRD

EBRD

WDI 2010 WDI 2010 Demirgu¨c¸-Kunt et al. (2007)

Laeven and Valenci (2010)

year-end status, we use one-year lag values of the reform indicators in the analysis. We control for various 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

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Table 2 Summary statistics. Variable name

N

Mean

Median

Std. dev.

5 percentile

95 percentile

Bank specific variables Size Loan to assets Deposit to assets Equity to assets Loan growth Asset growth ln_Z ROA Lerner Income_HHI Asset_HHI Equity return volatility Foreign_majority domestic_private

204 204 204 204 204 204 204 204 204 204 204 147 149 136

14.59 0.56 0.79 0.10 0.21 0.16 3.73 0.01 0.31 0.64 0.55 0.07 0.68 0.28

14.86 0.56 0.83 0.09 0.12 0.09 3.73 0.01 0.31 0.63 0.52 0.05 1.00 0.00

1.36 0.14 0.09 0.04 0.33 0.22 0.87 0.01 0.15 0.08 0.07 0.07 0.47 0.45

12.24 0.33 0.62 0.05 0.04 0.00 2.23 0.01 0.11 0.51 0.50 0.03 0.00 0.00

16.40 0.81 0.91 0.19 0.77 0.54 5.08 0.03 0.51 0.78 0.71 0.15 1.00 1.00

Country level variables Gdp growth Inflation Banking crisis DI SEE Banking_reform Security_market_reform Legal_reform

204 204 204 204 204 204 204 204

5.36 4.72 0.07 0.98 0.33 3.53 3.04 3.02

4.98 3.74 0.00 1.00 0.00 3.67 3.00 3.00

2.32 3.53 0.27 0.12 0.47 0.36 0.46 0.53

1.50 0.98 0.00 1.00 0.00 3.00 2.33 2.23

9.98 11.72 1.00 1.00 1.00 4.00 3.67 3.85

This table reports summary statistics for the main analysis variables.

Table 3 Correlation matrices. Size

Loan to assets

Deposit to assets

Equity to assets

Loan growth

Asset growth

1 0.02 0.09 0.03 0.39*

1 0.77* 0.10 0.03

1 0.10 0.13

ln_Z

ROA

1 0.07

1

Panel A. Correlations among bank specific variables Size Loan to assets Deposit to assets Equity to assets Loan growth Asset growth ln_Z ROA

1 0.10 0.01 0.51* 0.01 0.05 0.14* 0.15*

1 0.09 0.08 0.10 0.02 0.21* 0.04

1 0.49* 0.05 0.13 0.07 0.42*

Panel B. Correlations among country variables GDP growth rate GDP growth rate Inflation Banking crisis DI SEE Banking reform Security market reform Legal reform *

1 0.03 0.32* 0.05 0.34* 0.22* 0.12 0.19*

Inflation

1 0.18* 0.14* 0.12 0.04 0.05 0.37*

Significance level at least at the 10% significance level.

Banking crisis

1 0.04 0.21* 0.29* 0.32* 0.01

DI

SEE8

1 0.09 0.07 0.11 0.16*

1 0.09 0.63* 0.27*

Banking reform

Security market reform

Legal reform

1 0.35* 0.29*

1 0.22*

1

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Table 4 Description of Institutional Reforms by Country. Country

BULGARIA CROATIA CZECH REPUBLIC ESTONIA HUNGARY LATVIA LITHUANIA POLAND ROMANIA SLOVAKIA SLOVENIA

Banking reform index

Security market reform index

Legal reform index

Mean

Median

Min

Max

Mean

Median

Min

Max

Mean

Median

Min

Max

3.67 3.53 4.00 3.84 4.00 3.76 3.28 3.42 3.00 3.67 3.33

3.67 3.67 4.00 3.84 4.00 3.67 3.17 3.33 3.00 3.67 3.33

3.67 2.67 4.00 3.67 4.00 3.67 3.00 3.00 3.00 3.67 3.33

3.67 4.00 4.00 4.00 4.00 4.00 3.67 3.67 3.00 3.67 3.33

2.78 2.61 3.67 3.33 3.76 3.00 2.92 3.59 2.33 2.92 2.75

2.67 2.67 3.67 3.33 3.67 3.00 3.00 3.67 2.33 3.00 2.67

2.67 2.33 3.67 3.33 3.67 3.00 2.33 3.33 2.33 2.67 2.67

3.00 3.00 3.67 3.33 4.00 3.00 3.33 3.67 2.33 3.00 3.00

3.04 2.86 3.25 3.04 3.12 2.55 2.88 3.32 2.77 2.95 3.49

3.01 2.77 3.27 2.91 2.97 2.45 2.85 3.48 2.77 3.01 3.48

3.01 2.24 3.12 2.63 2.15 1.51 1.67 2.32 2.45 2.49 3.15

3.10 3.50 3.35 3.70 3.85 3.50 3.70 3.85 3.10 3.27 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. The detailed definitions of these variables can be found in Table 1. As for country-level controls, we include country fixed effects. The significance of our results remains unchanged when adding additional country-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 on Tobin’s Q. The coefficient is 0.5638 (statistical significance is at the 5% level), which implies that Table 5 Difference-in-difference estimations relating institutional reforms and Tobin’s Q. Variables

Q (1)

Reform indicators Banking reform Security market reform Legal reform Controls Size Loan to assets Deposit to assets Equity to assets Loan growth Asset growth ln_Z ROA Constant Year fixed effects Country fixed effects Observations Adjusted R-squared

(2)

(3)

0.56** (2.50) 0.08* (1.95)

0.85** (2.40) 1.74*** (3.43) 0.05* (1.77)

0.04 (0.40) 1.99** (2.27) 2.59(1.61) 4.41 (1.40) 0.18 (0.47) 0.10 (0.19) 0.02 (0.22) 1.91 (0.10) 5.22* (1.71)

0.05 (0.54) 1.73**(2.23) 4.15*** (2.60) 6.17* (1.95) 0.11 (0.33) 0.11 (0.22) 0.10 (1.05) 6.54 (0.37) 10.21** (2.57)

1.57*** (3.20)

0.05 (0.53) 1.99** (2.26) 2.89* (1.75) 4.83 (1.54) 0.13 (0.35) 0.04 (0.07) 0.03 (0.33) 0.63 (0.03) 4.38 (1.47) Yes Yes 204 0.63

0.03(0.39) 1.78** (2.25) 3.66** (2.33) 5.66* (1.89) 0.19 (0.55) 0.21 (0.40) 0.08 (0.83) 1.87 (0.11) 11.86*** (2.89) Yes Yes 204 0.65

(4)

Yes Yes 204 0.63

Yes Yes 204 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.

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Tobin’s Q would increase by 0.5638 when banking reform indicators increase by 1. It also indicates that 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 on Tobin’s Q is economically significant. In Column 3 we find that legal reform also exerts a positive effect on Tobin’s Q, with a coefficient of 0.0869. The statistical significance and economic impact are relatively smaller compared with banking reform. In Column 2 we find that security market reform has a negative impact on banks’ Tobin’s Q. The coefficient is 2.5759, which is highly significant in terms of both economic and statistical meaning. Specifically, one standard deviation increase of security market reform could reduce Tobin’s Q by 0.84 (0.84 = 1.5759  0.531). In the last column, we include all three types of reforms in the regression to control for each other. The results are consistent with the estimation results in the first three columns, meaning that the simultaneous control for other reforms does not affect our main findings. The findings are generally consistent with the literature. In particular, liberalization leads to an increase of operating efficiency and future growth opportunity of banks (Fries and Taci, 2005). Banking reform is also found to enhance bank stability (Fang et al., 2011a). Legal institutional development has been documented as an important factor affecting banking market development. In particular, Haselmann et al. (2010) show that banks significantly increased lending after bankruptcy laws and collateral laws were reformed in former socialist countries. Fang et al. (2011a) find that stronger legal reforms reduce banks’ earnings’ volatility, equity risk, as well as non-performing loans. The findings in our paper are consistent with these studies. There have not been many studies looking into the impact of 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 shareholders more rights and protection, and provide better monitoring and governance of the security listing process. Hence, as a security market is established, there are more companies seeking financing via securities exchanges and shareholders are empowered with more rights compared with creditors like banks. From these perspectives, the strengthening of the security market could inherently reduce bank profitability and increase the risk of expropriation by shareholders. We find that security market development hurts the growth opportunities of banks. These findings are consistent with substituting relations 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 further explore if there are any complementary or substitute effects among the reforms. The argument is that different types of reforms could be potentially dependent on each other to effectively reduce/increase Tobin’s Q. For example, when the security market is well developed, the impact of banking reform on banks’ Tobin’s Q might be not as strong due to the increased competition among two financial markets. Or, when the banking reform is well implemented, the legal reform could have a stronger impact on banks’ Tobin’s Q. When one reform shows a positive effect depending on the good development of another reform, it is an indication of a complementary effect. When a reform shows a negative effect depending on the good development of another reform, this is an indication of a substitute effect. If the effect of one reform does not vary with the development of another reform, this suggests no interacting effects between these two reforms. In other words, the effect of this reform is independent 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 same set of bank specific variables as the regression in Table 5. In addition, since we do not have a country fixed effect in the OLS model, we add a set of country macro variables to control for country effects. In particular, we have Inflation, GDP growth rate, an indicator of deposit insurance (DI), an indicator of Bank 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 and GDP growth rate to capture the economic development of a country. Deposit Insurance is used to proxy for market discipline, which influences bank stability (Demirgu¨c¸-Kunt and Detragiache, 2002; Barth

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

Q High bank reform (1)

Banking reform Legal reform Security Market reform Controls Size Loan to assets Deposit to assets Equity to assets Loan growth Asset growth ln_Z ROA GDP growth rate Inflation Banking crisis DI SEE Constant

Low bank reform (2)

5.19* (2.01) 1.08* (1.67) 1.82* (1.91) 0.46 (0.58)

0.04 (0.30) 0.42 (0.29) 2.52 (1.34) 13.59 (1.61) 1.59 (0.81) 4.00 (1.38) 0.18 (0.96) 52.21 (1.17) 0.28 (0.53) 0.53* (1.97) 1.99 (1.65) 0.00 (.) 0.50 (0.15) 3.92 (0.30)

Year fixed effects Yes Observations 58 Adjusted R-squared 0.57

High security market reform (3) 4.63 (1.12) 0.80* (1.86)

0.01 (0.07) 0.17 (0.68) 1.16 (0.92) 4.99** (2.66) 3.15 (0.81) 10.75*** (3.95) 6.46 (0.99) 10.63 (1.58) 0.02 (0.04) 0.17 (0.10) 0.19 (0.24) 0.60 (0.30) 0.27* (1.85) 0.23 (1.06) 33.92 (1.37) 6.05 (0.19) 0.05 (0.65) 0.11 (0.86) 0.04 (0.57) 0.46*** (2.78) 0.18 (0.27) 0.00 (.) 0.45 (1.11) 0.00 (.) 1.30** (2.60) 0.00 (.) 6.37 (1.02) 18.17** (2.59) Yes 146 0.25

Yes 76 0.53

Low security market reform (4) 2.40** (2.17) 0.51* (1.71)

High legal reform (5) 4.27* (1.68)

2.05* (1.89)

3.88* (1.90)

0.73 (1.30)

0.19 (1.65) 0.10 (0.23) 1.05 (1.12) 1.56 (0.52) ** 4.70 (2.48) 9.83* (1.76) 9.17** (2.25) 20.08 (1.63) 0.33 (0.81) 1.04 (0.36) 0.38 (0.53) 2.26 (0.47) 0.41*** (2.65) 0.21 (0.62) 18.15 (0.75) 89.47* (1.76) 0.13 (1.20) 0.17 (0.38) 0.06 (1.04) 0.69 (1.48) 0.27 (0.46) 1.24 (0.92) ** 1.66 (2.41) 0.00 (.) 1.68*** (2.68) 3.44 (1.60) 11.05*** (2.90) 3.36 (0.32) Yes 128 0.55

Low legal reform (6)

Yes 74 0.34

0.11 (1.36) 0.58 (0.76) 2.86 (1.49) 5.52 (1.39) 0.20 (0.73) 0.18 (0.33) 0.20* (1.77) 29.50* (1.77) 0.17* (1.96) 0.08 (0.81) 0.48 (0.93) 0.95*** (2.77) 1.24** (2.16) 2.73 (0.86) Yes 130 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 systemic crisis in a given year and 0 otherwise. We include it in the model to control for the negative impact of bank crises on the stability of banking sectors. The detailed definitions of these variables can be found in Table 1. As shown in Table 6, Columns 1 and 2, we divide our sample into two groups: high bank reform means that the value of the banking reform indicator is higher than median; low bank reform means that the value of the banking reform indicator is lower than the median value of the sample. Note that a bank may belong to one group in a certain year while moving to the other group in another when the country-level banking reform changes. The findings suggest that legal reform has a stronger and positive effect on Tobin’s Q when the banking reform is well executed, while the effect is much smaller when the banking reform is poor. This result implies that banking reform plays an important complementary role with legal reforms. The effect of security market reform, however, is negative when the bank reform is good, while it is insignificant when the bank reform is poor. These findings support the competition argument – that is, there is tension between the banking market and the security market, and hence, when the bank reform is good, the strengthening of security market development reduces banks’ further growth opportunities in providing financing to enterprises. In Columns 3 and 4 we examine the effects of banking reform and legal reform depending on high versus

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low security market reform. When the security market is poorly reformed, banking reform exerts a significant 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 Q is significantly reduced. The coefficient of banking reform on Tobin’s Q when the security market is high 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. Our results 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’s Q when the legal reform is good, indicating a substitute effect. When legal reform is poor, we find that banking reform has a weaker impact on Tobin’s Q and security market reform does not have a significant 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 independent variables. In particular, we examine the role of market power, ownership structure, and diversification at individual bank level. The estimations employ OLS regressions with a year fixed effect. The model specifications are as follows: X b  ðControlsÞi; t þ ei;t ; (2) Q i;t ¼ a0 þ a1  Lerner indexi;t þ a2  Q i;t ¼ a0 þ a1  foreigni;t þ a2  domestic privatei;t þ a3  Q i;t ¼ a0 þ a1  income divi;t þ a2  asset divi;t þ a3 

X

X

b  controlsi;t þ ei;t ;

b  controlsi;t þ ei;t ;

(3) (4)

where i indexes individual banks, j indexes countries, and t indexes years. Table 7 Regressions relating market power and Tobin’s Q. Variables

OLS

SUR

(1) Q Lerner Controls Size Loan to assets Deposit to assets Equity to assets Loan growth Asset growth ln_Z ROA GDP growth rate Inflation Banking crisis SEE Constant Year fixed effects Observations Adjusted R-squared

(2) Q **

0.94 (2.56) 0.01 (0.19) 1.73* (1.76) 5.01** (2.24) 10.02** (2.09) 0.14 (0.49) 0.01 (0.01) 0.15 (1.54) 18.58 (0.66) 0.044 (0.73) 0.05 (0.76) 0.18 (0.53) 0.39 (0.56) 6.23 (1.64) Yes 129 0.74

3.36

(3) Equity return volatility **

(2.52)

0.18 (1.16) 3.88*** (4.56) 5.29*** (3.56) 10.99** (2.20) 0.21 (0.57) 0.28 (0.31) 0.18 (1.43) 14.17 (0.37) 0.12 (1.59) 0.16** (2.18) 0.44 (0.91) 0.71 (0.51) 0.0000 (.) Yes 90 0.85

0.21* (1.94) 0.03*** (2.62) 0.01 (0.08) 0.17 (1.34) 0.54 (1.25) 0.01 (0.43) 0.028 (0.35) 0.01 (0.75) 1.46 (0.45) 0.01 (0.68) 0.002 (0.33) 0.01 (0.14) 0.019 (0.15) 0.00 (.) Yes 90 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. Tstatistics 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%.

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

OLS

SUR

(1) Q

(2) Q *

(3) Equity return volatility *

Foreign_majority Domestic_private

0.44 (1.72) 0.37 (0.67)

0.40 0.21 (0.24)

0.02 (0.20) 0.12 (1.44)

Controls Size Loan to assets Deposit to assets Equity to assets Loan growth Asset growth ln_Z ROA GDP growth rate Inflation Banking crisis SEE Constant Year fixed effects Observations Adjusted R-squared

0.01 (0.02) 1.54 (1.38) 5.37* (1.93) 8.62 (1.64) 0.28 (0.53) 0.33 (0.32) 0.07 (0.54) 34.08 (1.39) 0.02 (0.24) 0.03 (0.54) 0.13 (0.31) 0.66 (0.75) 5.51 (1.29) Yes 94 0.78

0.59** (2.46) 5.50*** (5.70) 3.91** (2.45) 1.43 (0.17) 0.07 (0.15) 0.47 (0.59) 0.086 (0.49) 27.61 (0.93) 0.03 (0.31) 0.10 (1.31) 0.41 (0.81) 0.82 (0.19) 0.00 (.) Yes 62 0.91

0.08*** (3.34) 0.15* (1.67) 0.53*** (3.37) 3.60*** (4.40) 0.05 (0.98) 0.02 (0.31) 0.01 (1.07) 4.04 (1.37) 0.01 (0.35) 0.01 (1.28) 0.03 (0.71) 0.22* (1.82) 1.86*** (4.31) Yes 62 0.56

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 market power of a bank, we employ the Lerner index, a well-established indicator of market power at the individual 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 higher value of the Lerner index denotes higher market power of the bank. To measure ownership structure, we group shareholders into three categories: foreign, domestic private, and government. We then calculate the aggregated shares held by each group and construct three ownership dummy variables for each bank in each year according to the type of majority shareholders. 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 into corporate 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 decomposition using a Herfindahl–Hirschman Index approach following Acharya et al. (2006). The focus index is calculated as the sum of squares of the proportions of portfolios in each classification. Specifically, 2  2 2 X X Li ; where Q ¼ L j; Loan focus index ¼ Q i¼1 j¼1 2  2 2 X X Ai where T ¼ A j: Asset focus index ¼ T i¼1 j¼1 By definition, the focus index ranges from 1/n (here ½) in this case to 1, higher values indicating a higher degree of focus and a lower degree of diversification. Table 7 reports the regression results

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

OLS

SUR

(1) Q Loan_HHI Asset_HHI Controls Size Loan to assets Deposit to assets Equity to assets Loan growth Asset growth ln_Z ROA GDP growth rate Inflation Banking crisis SEE Constant Year fixed effects Observations Adjusted R-squared

(2) Q **

2.92 (2.46) 2.81** (2.13)

1.28 (0.71) 2.29* (1.86)

0.001 (0.11) 2.22** (2.44) 4.83** (2.08) 8.45* (1.73) 0.01 (0.01) 0.33 (0.59) 0.17* (1.92) 37.47*** (2.69) 0.02 (0.35) 0.08 (1.61) 0.07 (0.21) 0.28 (0.55) 5.42 (1.49) Yes 129 0.76

0.20 (1.24) 3.51*** (3.99) 5.38*** (3.61) 11.31** (2.25) 0.18 (0.48) 0.34 (0.39) 0.23* (1.72) 35.47 (1.53) 0.08 (1.03) 0.15** (2.05) 0.46 (0.91) 6.77** (2.37) 0.00 (.) Yes 90 0.85

(3)Equity return volatility 0.05 (0.36) 0.17 (1.04) 0.03** (2.37) 0.01 (0.01) 0.18 (1.41) 0.48 (1.11) 0.02 (0.75) 0.01 (0.19) 0.01 (0.97) 1.55 (0.78) 0.01 (0.56) 0.01 (1.08) 0.01 (0.37) 0.05 (0.51) 0.77*** (3.06) Yes 90 0.28

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 Lerner index has a positive effect on banks’ Tobin’s Q. The effect is significant at 10% and translates into an increase 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 run simultaneous equations on both Tobin’s Q and equity risk using seemingly unrelated regressions. The results in Columns 2 and 3 suggest that the effect of market power as proxied by the Lerner index on Tobin’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 market power of banks plays a significant and positive role in enhancing banks’ value and growth opportunities. In particular, this is consistent with the argument that banks with greater market power gain monopolistic profit and enjoy higher interest margins. Therefore, they have a better operating performance. Table 8 reports the regression results relating ownership structure to bank Tobin’s Q. We first consider the results from the OLS regressions. As shown in Column 1, foreign ownership is associated with higher Tobin’s Q. The coefficient is statistically significant and economically meaningful. One standard 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 of foreign ownership on banks’ Tobin’s Q could be mostly related to superior management skills, easy access to international markets, and the introduction of new products with premium pricing. It is also consistent with previous findings regarding the superior bank efficiency of foreign banks compared with domestic and government banks. In Columns 2 and 3 we run simultaneous equations on both Tobin’s Q and equity risk. The results do not change materially. The ownership structure does not appear to affect equity risk in a significant way.

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Table 9 examines the effects of loan and asset diversification on banks’ Tobin’s Q. As shown in Column 1, both loan focus index (loan_HHI) and asset focus index (asset_HHI) are negatively associated with Tobin’s Q. Both coefficients are statistically significant at the 5% level. Since the focus index is an inverse measure of diversification, this result suggests that a higher degree of diversification increases banks’ growth opportunities. In Columns 2 and 3, we simultaneously control for equity risk and find that the effect of the loan focus index loses its statistical significance, while the asset focus index still shows a significant and positive impact on Tobin’s Q. These findings are consistent with the argument that diversification creates an economy of scope, opening up opportunities 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 consistent with 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 and institutional reforms. The banking sectors were liberalized and privatized with a large number of foreign banks involved. Securities markets were formed in most countries and reforms took place to improve the functioning of stock markets, strengthen shareholders rights, and provide better monitoring and governance of the security listing process. At the same time, to better protect investors and especially creditors’ rights, the government also put great efforts into reforming legislations and financial laws to create an investor-friendly, transparent, and predictable legal environment. In particular, 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 transition countries has sustainably improved over the past decade (Pistor, 2000). Our findings suggest that bank valuation increases substantially after transition countries reform their legal institutions and liberalize the banking system. However, it decreases after stock market reforms. After further examination of the interactive relationships between different reforms and bank valuation, we find that when the banking reform is well implemented, the legal reform can have a stronger impact on banks’ Tobin’s Q. On the other hand, banking reforms and security market reforms appear to have a substitutive relationship. When the security market is well developed, the positive impact of banking reform on banks’ Tobin’s Q becomes smaller, and when the banking reform is good, the negative impact of the security market on Tobin’s Q is larger. When the banking reform is poor, 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’ charter value and thus shareholder wealth. These results are robust after we simultaneously control for the potential linkage between valuation and equity risk. The establishment of a relatively efficient, privately-owned banking system marks a major step for these transition countries as they have been moving toward integration in the EU. Our study takes a further step to look at the issue of bank valuation, and in particular the role of institutional reforms in influencing bank valuation. We also identify key bank characteristics that could affect it. These findings provide additional evidence of bank valuation, which adds to the transition banking literature. Moreover, they provide policy implications for these countries regarding the ongoing debate over how to enhance the capital ratio and bank charter value. Government policies toward banking liberalization and creditor right reforms exert a strong and positive impact on the enhancement of bank valuation. However, reforms of the securities markets and non-bank financial institutions need to be formulated carefully and take into account that they might inherently negatively affect bank growth and shareholder wealth. Acknowledgements The authors thank the editors of the symposium and the two anonymous reviewers for insightful suggestions. The usual caveats apply.

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