Does the ownership structure matter for banks’ capital regulation and risk-taking behavior? Empirical evidence from a developing country

Accepted Manuscript Title: The Effects of Ownership Structure on Banks’ Capital and Risk-taking Behavior: Empirical Evidence from Developing Country Authors: Changjun Zheng, Syed Moudud-Ul-Huq, Mohammad Morshedur Rahman, Badar Nadeem Ashraf PII: DOI: Reference:

S0275-5319(16)30187-8 http://dx.doi.org/doi:10.1016/j.ribaf.2017.07.035 RIBAF 725

To appear in:

Research in International Business and Finance

Received date: Revised date: Accepted date:

19-7-2016 11-5-2017 3-7-2017

Please cite this article as: Zheng, Changjun, Moudud-Ul-Huq, Syed, Rahman, Mohammad Morshedur, Ashraf, Badar Nadeem, The Effects of Ownership Structure on Banks’ Capital and Risk-taking Behavior: Empirical Evidence from Developing Country.Research in International Business and Finance http://dx.doi.org/10.1016/j.ribaf.2017.07.035 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

The Effects of Ownership Structure on Banks’ Capital Regulation and Risk-taking Behavior: Empirical Evidence from Developing Country

The Effects of Ownership Structure on Banks’ Capital and Risk-taking Behavior: Empirical Evidence from Developing Country

List of Authors Changjun Zheng1 Syed Moudud-Ul-Huq2* Mohammad Morshedur Rahman3 Badar Nadeem Ashraf 4

Graphical abstract

School of Management, Huazhong University of Science and Technology (HUST), Wuhan, P.R. China, 430074, Phone: +86-27-87556446 and E-mail: [email protected] 1

2*School

of Management, Huazhong University of Science and Technology (HUST), Wuhan, P.R. China, 430074, Corresponding author. Phone: +86-13125100497 and Email: [email protected] 3Dept. of Accounting and Information Systems, Chittagong University, Bangladesh 4School of Economics and Management, East China Jiatong University, P. R. China

Abstract This paper applies two-stage least square (2SLS) to examine the bi-directional relationship between banks’ capital regulation and risk-taking behavior concerning the impacts of ownership structure. We have used a balanced panel dataset from a sample of developing country over the most recent period between 2006 and 2014. The empirical findings of this study suggest that higher capital regulation enhances banks’ stability when it combats with credit risk but higher credit risk often persuades abating capital ratio. Particularly, the key results are as follows: (i) the higher association of minority active shareholding in stability issues is positive; (ii) the higher contribution of active share holding promotes banks’ capital ratio; (iii) the lower ownership concentration prevents credit risk; (iv) private commercial banks are more risk averse and stable than state-owned banks and other type of banks; and (v) notably, Islamic banks show their superiority through overall performance despite their lower capital stability than conventional banks. Besides, no models show significant non-linear relationship between capital regulation and risk-taking except models of stability show a U-shaped relation in capital equation, indicating that when regulatory pressure works in a country then bank lose solvency at the initial stage. Finally, it also provides some imperative policy implications which will be very useful for a wide range of stakeholders.

Keywords: capital regulation; risk-taking; ownership structure; corporate governance; commercial banks; panel regression.

JEL: C3, C23, C33, G21, G32, G38

1. Introduction

In this paper, we empirically examine the relationship between capital regulation, ownership structure (nature and concentration basis) and risk-taking behavior of Bangladeshi commercial banks. From policy issues, this study is very crucial to decide which banks should be encouraged more and which banks need more supervision or to denationalize in an emerging economic environment. Moreover, imbalance capital regulation and risk-taking behavior of financial institutions cause economic fragility (Bernanke, 1983; Calomiris & Mason, 2003a, 2003b; Keeley, 1990). That’s why for regulatory deliberations, we have also taken these factors into account. From ownership view, our study is relevant to Laeven and Levine (2009), where, they have examined the relation between capital and risk through shareholders rights of control and cash flow rights.

However, the majority of works (e.g. H. Demsetz & Villalonga, 2001; Farooque et al., 2007; McConnell & Servaes, 1990; Pivovarsky, 2003; Welch, 2003) have done to show the relationship between ownership with firm performance. While a little evidence found working with ownership structure (nature and concentration) along with risk-taking behavior. Still, there is an ambiguity of the relationship between concentration and bank risk-taking behavior (Boyd & De Nicolo, 2005). Where Abbas et al. (2009) and Zouari & Taktak (2012) examine the effect of ownership nature and also the effects of various concentration on bank performance based on Islamic banks. Srairi (2013) also shows the influence of ownership on the risk of 10 MENA countries during 2005-2009 but didn’t show the effect of ownership on capital regulation.

From the recent literature based on commercial banks of Bangladesh, Miah & Sharmeen (2015) have investigated the relation between capital, risk, and efficiency based on conventional and Islamic banks of Bangladesh but they didn’t show the impact of other dimensions of ownership structure like private and state-owned or domestic and foreign ownership of banks. Correspondingly, Rahman et al. (2015) also ignore the various ownership patterns. In this pursuit, this paper delves to answer three main questions by considering Bangladesh as a sample of developing economy: (i) how do capital

regulation and risk-taking behavior influence each other simultaneously? (ii) how does ownership flaws capital regulation and risk? (iii) which bank moderately has more economic stability?

Therefore, this paper contributes to the contemporary empirical analyses in some ways. First, on this field, some Asian nations like China, Japan, Malaysia has paid a lot of attention where recently Bangladesh has become subtle to handle this sophisticated issue, but there is little evidence of research on this area. Thus, the drive of this paper is to investigate Bangladeshi banks with a wider range of panel data that covers 32 banks from the most recent period between 2006 and 2015. Second, some studies focused mostly on the relationship between capital, risk, and efficiency and it has also found that these three major issues altogether i.e. capital regulation, risk-taking, and ownership in the case of Bangladesh are absent. As a consequence, the investigation is expected to fill the shadow areas to the existing literature by adding new information. Finally, it enlarges its contribution by showing the effect of ownership on capital and risk-taking behavior.

The remainder of the paper is structured as follows. Section 2 displays institutional framework. Section 3 discusses the relevant literature and development of hypotheses that underlie the paper’s analysis. Section 4 presents the data and methodology. Section 5 describes the empirical results and deals with the analysis of the robustness of those results in Section 6. Finally, Section 7 concludes the paper.

2. Institutional Framework After independence, the banking system in Bangladesh started its journey with only eleven banks, including two state-owned specialized banks, six nationalized commercialized banks and three Foreign Banks. During 1980's banking industry significantly expanded due to the active entrance of private commercial banks. Currently, banks in Bangladesh are mainly of two types i.e. (i) Scheduled Banks: Those banks which get a license to operate under Bank Company Act, 1991 (Amended up to

2013) are termed as Scheduled Banks. (ii) Non-Scheduled Banks are established for particular and specific objective and operate under the acts that are enacted for meeting up those goals.4

At present 56 scheduled banks (till June’ 2016) are operating under full supervision and control of Bangladesh Bank (central bank) as per Bangladesh Bank Order, 1972 and Bank Company Act, 1991. Besides, four categories of Scheduled Banks are available in Bangladesh like:

(i)

State-owned Commercial Banks (SCBs): There are 6 SCBs which are wholly owned by the Government of Bangladesh. Recently, two of them (BASIC Bank Ltd. and Bangladesh Development Bank Ltd.) have become SCBs instead of DFIs.5

(ii)

State-owned Development Financial Institutions (DFIs): 2 specialized banks are now operating which were established for specific objectives like agricultural or industrial development. The Government of Bangladesh majorly owns these banks.

(iii)

Private Commercial Banks (PCBs): There are 39 private commercial banks which are majorly owned by outside shareholders or institutional owners. PCBs can also be categorized into two groups i.e. (a) Conventional Private Commercial Banks: now, 31 Conventional PCBs is operating in traditional manner i.e. interest-based operations. (b) Islamic Shari’ah based PCBs: There are 8 Islamic PCBs based on Islamic Shari’ah principles i.e. Profit-Loss Sharing (PLS) mode in Bangladesh, and they execute banking activities according to Islamic Principles. Among these banks, nine banks were newly incorporate in 2013.

(iv)

Parallel to the domestic banks here in Bangladesh, 9 FCBs is currently operating their banking activities in abroad.

According to Bangladesh Bank statistics as of December 2015, now 9,131 branches of scheduled banks are working in Bangladesh, and this focuses a view to forecasting a sound, efficient and stable financial system. The banking industry is emerging rapidly with an incremental change in some banks, 4 5

Financial System - Bangladesh Bank. Retrieved from https://www.bb.org.bd/fnansys/bankfi.php. Please see BB Annual Report: 2015-2016

branches, assets, deposits, policies, and strategies, etc. However, the overall assets of this industry amount to BDT (the local currency of Bangladesh) 9143 billion in 2014 which shows an overall increase in assets compared to 2013 (Table 1). On the one hand, deposits also increased from 2013 and the overall deposits in 2014 show BDT 6965.10 billion. In all respects, PCBs show incremental growth with passes of time. While SCBs show their bigger size regarding assets. Respect to the large banks, most of the large banks is state-owned banks regarding assets. Large banks often get some benefits from govt. guarantee and hence they enjoy strong protection, and these banks are politically involved and likely to be bailed-out in compare to the similar non-connected firms.

[Insert Table 1 near here]

Alongside the conventional banking system, Bangladesh entered into an Islamic banking system in 1983. Through its journey, Islamic banks show strong growth since its inception that reflected by their overwhelmed market share in the banking industry regarding assets, financing, and deposits.

[Insert Table 2 near here]

A concise scenario of the performance of Islamic banks is given in Table 2. The Islamic bank's total deposits stood at Taka 1349.7 billion at the end of December 2014 which accounted almost 20 percent of industry deposits. Full credit of the Islamic banks reached at Taka 1137.6 billion at the end of December 2014 which accounted for 22.10 percent of total credit. It clearly differentiates through credit to deposit ratio that continuously above of industry percentage and holds liquidity at marginal.

The banking sector of Bangladesh regulated by some governing bodies such as Bangladesh Bank (the Central Bank which is the supreme authority of banks), Bangladesh Securities and Exchange Commission (BSEC), 6 Ministry of Finance, Investment Corporation of Bangladesh (ICB), etc.

6

The Bangladesh Securities and Exchange Commission (BSEC) was established on 8th June, 1993. Earlier its name was Securities and Exchange Commission. Through an amendment of the Securities and Exchange

Besides, Bangladesh Bank (BB) has recognized four credit rating agencies and the primary objective of those agencies is to meet the required criteria of External Credit Assessment Institutions (ECAIs) guidelines (BRPD Circular No. 7 in 2008). The history of banking sector development is not too long. Align with the international standard; it runs into success for capital standards. But earlier the subsequent enactment of banking regulation, capital adequacy of banks was assessed by using capitalto-liabilities approach. As per Section 13 (2) of Banking Companies Act, 1991 and Circular No. 1 (January 8, 1996) of Banking Regulation and Policy Department (BRPD) of Bangladesh Bank (BB), capital adequacy of banks is to be assessed by risk-weighted assets. According to that circular, each bank has to maintain at least 9% of capital adequacy ratio (CAR) against risky assets where core capital must be at least 4.5% by the end of June 2003.

With the faster progression of the banking industry, it faces multifaceted challenges. So, a consecutive number of financial crises have demonstrated some weaknesses in the global regulatory framework and banks’ risk management practices. To adapt to the international practices and to make the bank’s capital more risk absorbent as well as more shock resilient, a Circular No. 14 from BRPD was issued (December 30, 2007) for the road map and implementation of Basel II in Bangladesh. In this consequence, guidelines on Risk-Based Capital Adequacy (RBCA) for banks have been introduced from January 01, 2009 (BRPD Circular No. 9) parallel to existing BRPD Circular No. 10, dated November 25, 2002. These guidelines are prepared based on BASEL II which has come fully into force on January 01, 2010 with its successive supplements. As per BASEL II, banks in Bangladesh maintain the Minimum Capital Requirement (MCR) or Capital Adequacy Ratio (CAR) at 10% of the Risk Weighted Assets (RWA)7 or Taka 4,000 million in capitals whichever is higher. According to

Commission Act, 1993, on 10 December 2012, its name has been changed as Bangladesh Securities and Exchange Commission. 7 Risk-weighted assets comprise investments involving credit, operational, and market risk. For instance, credit risk can arise from the loans provided by banks. If the counterparties default, these loans are classified as nonperforming loans (NPLs). Banks must hold adequate capital to offset the losses from these loans. Market and operational risks can result from changes in interest rates as well as changes in equity, commodity, and foreign exchange prices. If interest rates move unfavorably, resulting in losses, banks must have enough capital to absorb the losses. Consequently, banks that invest in more risky assets must hold more capital to compensate for the higher risk.

Supervisory Review Process (SRP), banks are directed to maintain sufficient level of capital which is greater than the minimum required capital and cover all possible risks in their business. Besides, ‘Guidelines on Risk-Based Capital Adequacy for Banks’ are articulated the following issues in its priority areas, such as: (i) introduction and formation of Capital, (ii) Credit Risk, (iii) Market Risk, (iv) Operational Risk, (v) Supervisory and Review Evaluation Process, (vi) Market Discipline, (vii) Reporting Formats, and (viii) Annexure.

From Fig. 1, we see that the CAR (NPLTL) of the banking industry was 11.30 (10) percent at the end of December 2014 as against 11.50 (8.90) percent of 2013.

[Insert Figure 1 near here]

The main reason for an increase of CAR in 2013 was the implementation of newly revised policy (BRPD Circular No.15 in 2013) on loan rescheduling. Besides, an increase in classified loans in 2014 resulted in the rise of the discrepancy of the capital of 2 SCBs (Sonali Bank Ltd. and BASIC Bank Ltd.), 2 DFIs (BKB, RAKUB), and 2 PCBs (BCBL, ICB Islamic Bank).

To uphold a sound, efficient and stable financial system, among the other policies, BB has given heightened interest in risk management and corporate governance in the banks. Besides, Risk Management Committee at the board level has been made mandatory to ensure proper risk management practice in the banks. As this consequence, in June 2009, BB was instructed to all scheduled banks for establishing an independent Risk Management Unit (RMU). Later, BB has introduced a Comprehensive Risk Management Report (CRMR) for banks in place of the previous format Risk Management Paper (RMP).

Bangladesh Bank issued another guideline on 15 February 2012, called Risk Management Guideline for banks. This guidance promotes an integrated, bank- comprehensive approach to monitor and control risk, adopt measures of risk and implement accordingly throughout their organization. Based

on this guideline, all banks have been rated on risk management. As per rating in December 2014, out of 56 banks, 8 banks were rated as a high-risk, 25 as moderate and the rest 23 banks as little risk category. Following the lessons of global financial crises in 2007, the Basel Committee on Banking Supervision (BCBS) upgraded the capital measurement standard and released the final document of 'Basel III: A global regulatory framework for more resilient banks and banking system' in December 2010. The Basel III has brought some financial models, tools & techniques namely, Liquidity Coverage Ratio (LCR), Net Stable Funding Ratio (NSFR) and Financial Leverage for the financial intermediaries aiming to better risk management for a sustained and sound financial system in addition to the Basel II. The level and quality of capital components are also made more stringent. Emphasis has been given to raise the Common Equity Tier 1 (CET 1) capital. A provision of creating capital conservation buffer at 2.5% of RWA with the CET 1 capital is also made. Rising of Tier 2 capital by the revaluation of fixed assets, equity and investments are discouraged and phased-out during Basel III implementation. To cope up with the internationally accepted best practices, BB conducting two Quantitative Impact Study (QIS) successively for the years 2012 and 2013. In this way, Bangladesh Bank has issued guidelines for Basel III implementation through BRPD Circular No. 7, March 2014 to boost this sector more, as well as to increase the credibility worldwide. Finally, BB issued the comprehensive guideline through BRPD Circular No. 18 dated December 21, 2014, for implementation of Basel III in Bangladesh. Where BB has set a Roadmap intending for commencement of Basel III implementation process from January 2015; with full implementation of capital ratios from beginning of 2019 as follows: (i) Common Equity Tier 1 (CET 1) of at least 4.50% of the total risk-weighted assets (RWA); (ii) Tier capital will be at least 6.0% of the total RWA; (iii) Minimum Capital to Risk-weighted Asset Ratio (CRAR) will be 10% of the total RWA; (iv) Additional Tier 1 capital can be admitted maximum up to 1.5% of the total RWA or 33.33% of CET1, whichever is higher; (v). Tier 2 capital can be recognized maximum up to 4.0% of the total RWA or 88.89% of CET 1, whichever is higher; (vi). In addition to minimum CRAR, Capital Conservation Buffer (CCB) @ 2.50% of RWA should be maintained in the form of CET 1, so, minimum total

capital plus capital conservation buffer should be 12.50%. Moreover, these latest guidelines promote banks to behave counter-cyclically in the capital buffer over the period. However, BB has taken several measures for the improvement of corporate governance in banks in line with their one of the top priority concerns. These include a "fit and proper" test for appointment of chief executive officers of PCBs, specifying the formation of the audit committee of the board, enhanced disclosure requirements, etc. In continuation of the above reforms, the roles, and functions of the board and management have been redefined and clarified to (or “intending to”) specifying the powers of the management and restricting the intervention of directors in the day- to-day administration of the bank. In this connection, related clauses of Bank Company Act 1991 have already been amended. Corporate governance mechanisms are arguably less evolved in Bangladesh than those in developed economies such as the Anglo-American countries, EU based economies or Japan (Farooque et al., 2007). As a whole, emerging economies differ considerably from developed markets in their developed institutional framework. The Mckinsey Emerging Market Investor Opinion Survey (2001) characterized the “emerging market corporate governance model” as having ownership concentration, insider boards, lack of disclosure, inadequate protection of minority shareholders, and a limited takeover market that markedly different from the developed economies. Conversely, the general features of the advanced markets model include dispersed ownership, majority non-executive members on the board, high-quality disclosure, shareholder equality, institutional investment, and an active takeover market. So, Bangladesh contentedly fits the emerging market model by Considering the above feature. The progress of corporate governance mechanisms (institutional, regulatory or legal) depends on the political, cultural and historical characteristics of a country (Prowse, 1999). Bangladesh is bearing the legacy of nearly two hundred years of British colonial rule. This has had a two-fold impact as far as corporate governance is concerned. First, it allowed Bangladesh to become heir to an English-style institutional and regulatory framework in the form of a Companies Act that originally enacted in the

British Parliament in 1913, Westminster-style parliamentary democracy and allowed a highly robust and insensitive bureaucracy. Second, the widespread economic exploitation and political domination doubled with the creation of crony elite passive to the expatriate rulers contributed to institutionalizing corruption in the bureaucracy, pausing to develop a broad-based capital market and limiting the participation of many entrepreneurs. Later of the British colonial period, the 23-years internal colonization in Pakistan period also a maxim of political suppression and economic negligence. The dearth of natural and human resources compounded by frequent natural disasters did not allow the country, with arguably the highest population density8 in the world, to build capital market institutions or carry out urgent institutional reforms even nearly five decades since independence. Despite Bangladesh inherited “British Common-law,” but it relatively weak and unsophisticated to protect investor rights. In Bangladesh, lack of transparency and accountability are common in the corporate sector and are similar to those in other developing East and South East Asian countries (Prowse, 1999). Though market-based system similar to Anglo-American firms, Bangladesh still a behind of active market for corporate control. Also, it is widely recognized that Bangladesh is suffering from the severe market anomaly and malpractices (e.g. lack of information to investors, insider ownership and conspiracy to influence stock prices). Corporate governance systems in Bangladesh are mainly based on insider-domination. In most of the bank's major shareholders are from family groups or individuals and in a few bank government is the major shareholder. Other shareholders are a financial institution or non-banking financial institutions and foreign investors. The structure of ownership is not similar to pyramid type and holding companies practically non-existent. Most banks are owned independently by family owners or sponsors and other shareholders. Family members drive the board and filling positions through inappropriate exercise. Similarly, institutional, corporate and individual block holders in Bangladesh typically sit on the boards of non-executive directors. Only rarely do block holders sit on boards. This structure opens benefits for controlling shareholders to expropriate wealth from other shareholders (Shleifer and Vishny, 1997). On this

At the time of independence in 1971, the country’s population was only 70 million. In 2015, its population was estimated to be 170 million. 8

structure, it blames for conflict of agency between large and small shareholders (Shleifer and Vishny, 1986) rather than between institutional managers and shareholders (Jensen and Meckling, 1976).

3. Review of literature and development of hypotheses

This paper is fundamentally based on mainstream corporate governance literature. However, as shown in Ardalan (2008) and Lagoarde-Segot (2016), this theory relies on a set of ad-hoc assumptions regarding the nature of knowledge and the nature of society. But, as soon as the change of mathematical assumptions, the outcomes of sophisticated models will also be changed. In that case, the scientific nature of the mainstream academic finance becomes questionable (Ardalan 2008, 2017). Social theory can indeed usefully be conceived regarding four major paradigms: functionalist, interpretive, radical humanist, and radical structuralist (see Burrel and Morgan, 1979) which are founded upon different assumptions about the nature of social science and the nature of society. It follows that claims for scientific-ness in finance reinforce the tacit paradigmatic hypothesis upon which research is based, which leads to a reification of existing social relations. Particularly, in this section, our intention is to survey key literature that reveals numerous attempts to quantify and explain the risk-taking behavior along with its influential factors of financial institutions. However, here the topics of capital regulation, risk-taking, and ownership structure are receiving heightened attention and interlinked each other that’s why we are trying here to emphasise the literature which covenant with the relation between capital regulation and risk-taking, ownership structure and risk-taking, capital regulation and ownership structure in the following way:

3.1

Capital regulation and risk-taking

Capital adequacy plays a vital role in operating banking activities (Karim et al., 2014). Regulators are always working to ensure the banks have capital stability and to keep them out of financial difficulty. This not only protects investors or depositors but also protects the large stakeholders in the economy.

Some empirical evidence (e.g. Calomiris & Mason, 2003a; Calomiris & Powell, 2001; Kim et al., 2005) find that banks with higher capital have greater incentives to attract more potential customers and investors by providing some support. Besides, higher capital adequacy will also have power to undertake higher risk (Altunbas et al., 2007; Laeven & Levine, 2009; Lin et al., 2005; Rime, 2001) and outperform significantly (Dietrich & Wanzenried, 2011). On the other hand, some studies ( e.g. Berger & DeYoung, 1997; Ho & Hsu, 2010; C.-C. Lee & Hsieh, 2013; T.-H. Lee & Chih, 2013; Zhang et al., 2008) find an inverse relationship between capital and risk. But most theories predict that higher capital intends to a higher probability of survival of banks. However, some theories predict that increasing bank capital may be counterproductive because it defiantly raises bank risk-taking (Besanko & Kanatas, 1996; Koehn & Santomero, 1980). In another stand, Hanafi & Santi (2013) find a U-shaped pattern for bank risk-taking. Apart from such definite stance, mixed and no results also have been reported by Calem & Rob (1999), Iwatsubo (2007), and Hussain & Hassan (2005) respectively. Hence, the above instance motivates us to assess the following hypotheses for developing economy: Hypothesis 1. (H1a): the higher capital ratio will be enhanced bank’s stability and lessen risk. (H1b): higher risk will be hindered for bank’s normal growth of capital ratio.

3.2 Ownership structure and bank risk-taking

Ownership structure is one of the most imperative mechanisms of corporate governance as this leads artificial or direct effects on capital regulation, incentives, risk-taking and agency issues, etc., (Iannotta et al., 2013). In this pursuit, prior studies ( e.g. Angkinand & Wihlborg, 2010; Barth et al., 2004; Yeyati & Micco, 2007) show ownership effects on bank risk-taking behavior and performance. To support our study we have categorized this part as likewise:

3.2.1 State-owned and private bank’s risk-taking

An overwhelming number of studies on bank ownership propose that govt. banks have higher insolvency risk due to poor loan quality than other types of banks (Iannotta et al., 2007) and are less efficient than private ownership (Altunbaş et al., 2001; Bonin et al., 2005; La Porta et al., 1997). In another similar stand, Berger et al. (2005), Cornett et al. (2010), and Dong et al. (2014) find that stateowned banks have inadequate core capital, inefficiency in management, inferior asset growth and poor loan quality than privately-owned banks. But in contrast, state-owned banks are less risky and more profitable in Russia (Solanko & Fungáčová, 2008). So, most of the cases, the banks which have a direct connection to the government they have greater tendency to undertake high risk (Lassoued et al., 2016) and these banks are characterized as underperforming. Conversely, private banks are getting a better payoff from their good governance. But in a developing country’s view, its still requires reassessing the relationship, and hence we posit this relationship as:

Hypothesis 2. (H2): private banks will be risk averse and stable than state-owned banks. 3.2.2 Conventional and Islamic bank’s risk-taking

Due to the rapid expansion of Islamic banks, they become grander regarding capital and efficiency to that of conventional banks (Iqbal, 2001; Brown et al., 2007). Beyond these, a few papers ( e.g. Abedifar et al., 2013; Farook et al., 2012; Gamaginta, 2015; Hasan & Dridi, 2011; Khediri, Charfeddine, & Youssef, 2015) have analyzed the risk of Islamic banks. On the other hand, Baele et al. (2010), Beck et al. (2013), and Olson & Zoubi (2008) have been proposed that that Islamic banks are lower risk involved than conventional peers. Conversely, Beck et al. (2013) suggest that Islamic banks are less efficient than conventional banks. However, Miah & Sharmeen (2015) find a positive bidirectional relationship between capital and risk for Islamic banks. Moreover, Islamic banks have active Shari’ah board and corporate governance that lead them from the front for being competitive in global economy. Therefore, we test the following hypothesis:

Hypothesis 3.

(H3):

Islamic banks will substantially be lessened risk and improved stability than conventional banks.

3.2.3 Ownership concentration and bank risk-taking

A large number of studies (e.g. Abbas et al., 2009; Hu & Izumida, 2008; Kiruri, 2013; Zouari & Taktak, 2012) have focused ownership concentration with bank’s performance but in the banking standpoint, a few studies test risk-taking behavior on ownership concentration.

From the spotlight of ownership concentration, there is the diverse effect on bank risk-taking. Some researchers (e.g. Chalermchatvichien et al., 2014a; Hanafi & Santi, 2013; Haw et al., 2010; Ho & Hsu, 2010; Laeven & Levine, 2009; Saunders et al., 1990) show that ownership concentration is positively allied on risk. Besides, diversified owners have spurs to increase bank risk (Esty, 1998; Galai & Masulis, 1976). Conversely, Gomes & Novaes (2005); Novaes (1999) find substantial ownership concentration as threatening issue to the minority shareholders and causes agency costs. This case happens if the control rights exceed over shareholding rights (Claessens et al., 2002) and mostly this scenario is available in developing and Asian countries with weak legal investor protection (Chalermchatvichien et al., 2014b; La Porta et al., 1997). Moreover, significant ownership concentration has the freedom to access in the managerial decision or controlling function. Therefore agency cost may also be reduced (Iannotta et al., 2007; Porta et al., 1999; Shleifer & Vishny, 1986). Despite, several papers find a significant effect of ownership concentration on risk-taking, but yet to explore the sign of this relationship in developing countries like Bangladesh. Therefore, we design the following hypothesis:

Hypothesis 4.

(H4):

Different ownership concentration will have different attitudes of bank risk-taking.

3.3 Ownership structure and capital regulation

As per Basel II and Basel III, banks should maintain minimum required capital against credit, market, and operational risks; as a result, it plays a central role in banking regulation system. But, this is a hard task to determine capital stability, and the amount of capital should be to absorb a risk (Posner,

2014). While Laeven & Levine (2009) show the significant dependency of capital regulation on ownership structure.

However, Nier & Baumann (2006) mention that shareholders are likely to influence the capital ratio. But we do not have strong prior literature about the sign of this coefficient and coefficient may vary with different nature and concentration of ownership. On the other hand, bank managers that are better controlled by shareholders can build higher capital buffers. Conversely, if the corporate governance systems support the interests of managers and shareholders, then managers will avoid raising capital as this dilutes the stakes of existing shareholders (Myers & Majluf, 1984). So, to minimize the agency cost corporate governance act as a hedge between ownership and management and ultimately improve the capital ratio. But subject to enough protection rights of shareholders (Shehzad et al., 2010). From the view of ownership structure by nature, state-owned banks are less capitalized (Cornett et al., 2010; Iannotta et al., 2013). Moreover, state-owned banks often tend to increase capital adequacy ratio to hedge against a high level of risk (Lassoued et al., 2016). Some other studies (e.g. Brown et al., 2007; Iqbal, 2001) compare between conventional and Islamic banks and discover that Islamic banks have capital stability than that of conventional banks.

As per Basel accord, today’s banks are virtually subject to follow minimum regulatory capital requirements and in this consequence; all European banks have already maintained uniform regulatory capital (i.e. at least 8% of total risk-weighted assets) as a buffer of future uncertainty or loss Schaeck and Cihák (2007). Where, under Basel-II, banks in Bangladesh are followed to maintain the Minimum Capital Requirement (MCR) at 10.0 percent of total Risk Weighted Assets (RWA) or Taka 4.0 billion as capital, whichever is higher.9 Banks in a particular country follow an identical capital regulation though over and above of the ratio of capital adequacy vary with different banks due to their size, ownership or efficiency. In this pursuit, this is more interesting to see how the capital regulation responds with the different ownership style, and hence we hypothesize above relation as follows: 9

See Bangladesh Bank Annual Report: 2014-15, also available at www.bb.org.bd

Hypothesis 5.

(H5):

under uniform regulation different ownership styles will have a diverse impact on capital.

4. Data and Methodology

This part comprises four sections where Section 4.1 discusses sample selection and time frame; Section 4.2 focuses on variables definition: by dividing into three categories namely (i) main variables; (ii) bank level control variables; and (iii) macroeconomic control variables. Section 4.3 reports summary statistics and correlation analysis, and finally, Section 4.4 emphasizes on empirical model development.

4.1 Sample selection and time frame

Our data on macro-economic are collected from World Bank’s economic indicators database10 and banks’ characteristics are derived from audited annual published reports from Dhaka Stock Exchange (DSE) and Bureau Van Dijk’s Bankscope database of 28 private and 4 state-owned commercial banks for 2006 to 2014. At present, 56 scheduled banks are working in Bangladesh. We have excluded 10 banks as they have been formed very recently. We have also excluded 14 banks for unavailability and irrelevancy in data. Thus our sample comprises a balanced panel of 252 observations for private commercial banks and 36 observations for state-owned commercial banks. Again, we cluster full observations into 234 observations for conventional banks and 54 observations for Islamic banks combining a total of 288 bank-year observations.

10

See more at http://data.worldbank.org/indicator

4.2 Variables definition

4.2.1 Main variables

According to our objective, we have selected three main variables i.e. risk-taking, capital regulation, and ownership structure. We have used two variables for risk such as (i) credit risk as a measure nonperforming loan to total loans (NPLTL); and (ii) stability as an inverse proxy for insolvency risk measured by Z-score (LNZ). Both these variables are widely used by Olson & Zoubi (2008), Baele et al. (2010), Abedifar et al. (2013), and Beck et al. (2013) in their empirical literature. The higher NPLTL indicates higher credit risk (Barth et al., 2004; Berger et al., 2005; ElBannan, 2015; Gonzalez, 2005). On the other hand, Z-score measures the distance from insolvency, and a higher value indicates greater stability (Blaško & Sinkey, 2006; Čihák & Hesse, 2008; ElBannan, 2015; Laeven & Levine, 2009; Lepetit et al., 2008; Nash & Sinkey, 1997). We use capital adequacy ratio (CAR) as a proxy measure of capital regulation.

Moreover, to see the influence of ownership structure on the

relationship between capital and risk-taking of banks in Bangladesh, we employ ownership structure (OS) as a most important variable. As evidence of section 3.2, we classify ownership structure by two categories: nature of ownership and ownership concentration. Ownership by nature is proxied by two dummy variables such as PRIVATE (Dummy) variable equals one, if the bank is privately owned and zero for otherwise; and ISLAMIC (Dummy) equals one if it is Islamic Shari’ah based bank and zero for otherwise.

By following International Financial Reporting Standards (IFRS) and Generally Accepted Accounting Principles (GAAP), we classify general public ownership as (i) passive shareholding (PS) if general shareholders hold below 20% of ownership; (ii) minority active shareholding (MAS) if they hold below 50% but more than 20% of ownership; and finally (iii) active and controlling shareholding (AS) if they hold 50% or above of ownership stake. In our study concern, all these variables are used as continuous and proxies of ownership concentration. However, these classifications are unique from other studies such as Chalermchatvichien et al. (2014a), Chalermchatvichien, et al. (2014b), Hu &

Izumida (2008), López-Iturriaga & Rodríguez-Sanz (2001) and extension of Laeven & Levine (2009)11 and Srairi (2013)12 though we have emphasized on single country analysis.

4.2.2 Bank-level variables

To measure the influence of risk and capital, we also employ some bank and macro level control variables along with their descriptions and possible signs which are displayed in Table 3.

[Insert Table 3 here]

In our study, bank size (SIZE) is used as a significant determinant of capital and risk-taking of banks. We also incorporate another most important variable is corporate governance (CG)13 as it works as a control mechanism for limiting excessive risks and agency costs (Arouri et al., 2014) to protect shareholders’ benefits as documented in the agency theory literature. There are quite a few studies (e.g. Iannotta et al., 2007; Laeven & Levine, 2009; Barry, Lepetit, & Tarazi, 2011) focused on connection to the corporate governance as a part of ownership or board influence on bank risk-taking and those studies mostly have based on developed economies.

Financial leverage ratio (LEVERAGE) is measured by total debt to total assets ratio; higher ratio indicates a higher dependency on debt and consequently higher bank risk and vice-versa. By following the logic of Louzis et al. (2012), we use return on total assets (ROTA) as an instrument for capital. Also, as per Basel II, risk-weighted assets to total assets (RWATA) are also an important determinant of capital adequacy ratio where risk-weighted assets calculated as total assets minus loans and advances to banks, government securities at market value, and cash. A Higher ratio indicates the

11

Laeven & Levine (2009) consider two ownership stakes of 10% and 20%, while we show ownership stakes from below 20% to above 50%. 12 Srairi (2013) only considers the largest shareholder of the bank as ownership concentration. 13 See Moudud-Ul-Huq (2015) for detailed calculation of corporate governance score.

higher requirement of CAR as increasing the overall risk (Avery & Berger, 1991; Gropp & Heider, 2007). To see the response of capital ratios to the volume of bank’s business we employ another control variable known as assets growth (AG).

4.2.3 Macroeconomic variables

By following Chaibi & Ftiti (2015), we also include two macroeconomic variables such as the growth of gross domestic product (GGDP) and rate of inflation (INFR) which may have an influence on the endogenous variables.

4.3 Summary statistics and correlation analysis

Table 4 articulates the descriptive statistics of main variables, bank-level variables and macroeconomic variables for the full sample and the various types of banks. Table 5 shows the correlation matrix by using Pearson’s correlation coefficient. Where it exhibits the highest correlation is between ROTA and Leverage (Pearson’s correlation = 0.58). So, the issue of multicollinearity does not a challenge for our study. 14

[Insert Table 4 & 5 near here]

4.4 Empirical model development

A number of literatures such as Aggarwal & Jacques (2001), Altunbas et al. (2007), Cho (1998), Hu & Izumida (2008), Rime (2001), Suhartono (2012) among others; show that the banks have simultaneous relationship either between capital adequacy ratio and risk-taking or between performance and risk-taking or ownership and risk-taking. There is no such evidence found which

14

Barako and Tower (2007) and Gujarati (2003) indicate that multicollinearity is a serious problem if correlation coefficient between two independent variables is above 0.80, which is not the case here.

focusing three things together in a regression baseline. While based on cross-country data, only Laeven & Levine (2009) apply OLS and 2SLS to show the joint effect of ownership structure and national bank regulations (capital requirements and stringent capital) on risk-taking behavior of banks. So, it is more intuitive to see the effect of capital regulation and risk-taking behavior of banks with distinct ownership pattern on the single country database. Hence, to seal this gap, we employ a simultaneous equations model for this study and apply panel two-stage least square (2SLS) to test the empirical relationship between capital regulation and risk-taking along with the various effect of ownership structure including the bank level control variables and macroeconomic variables. As capital and risk are correlated, they are endogenous in nature, and they are explanatory variables to one another in the simultaneous equation15. Also, today’s banking practice is influenced by the trend of the previous period. As this consequence, banks are adjusted their risk and capital based on last year risk and capital levels (Zhang et al., 2008). Because banks with a low degree of capital have a tendency to increase their capital, hence the relationship between capital and lagged capital is expected to be negative. In the same way, banks are also changed their portfolio risk in the current period. Banks is having higher risk level push them to decrease their portfolio risk, therefore a negative relationship between risk and lagged risk is expected. Hence, the independent variables with lagged periods are included in equation (1), and (2) which are as follows:

RISK 𝑖,𝑡 = α0 + α1 RISK 𝑖,𝑡−1 + + α2 CAP 𝑖,𝑡 + α3 OS 𝑖,𝑡 + α4 SIZE 𝑖,𝑡 + α5 CG 𝑖,𝑡 + α6 LEVERAGE 𝑖,𝑡 + α7 GGDP 𝑡 + α8 INFR 𝑡 + ε𝑖,𝑡

eq. (1)

CAP𝑖,𝑡 = β0 + β1 CAP 𝑖,𝑡−1 + + β2 RISK 𝑖,𝑡 + β3 OS 𝑖,𝑡 + β4 SIZE 𝑖,𝑡 + β5 ROTA 𝑖,𝑡 + β6 RWATA 𝑖,𝑡 + β7 AG 𝑖,𝑡 + β8 GGDP 𝑡 + β9 INFR 𝑡 + ε𝑖,𝑡

eq. (2)

In these equations, ownership variable regressed on risk and capital proxies in the presence of control variables. Where, in both equations subscripts i indicates commercial banks (i = 1, 2… 32), and t period (t = 2006, 2007… 2014), α and β are the series of parameters to be estimated and ε𝑖,𝑡 is the 15

See also Shrieves & Dahl (1992), Jacques & Nigro (1997), Rime (2001) and Altunbas et al. (2007).

error term. To account for endogeneity and simultaneity between capital and risk, RISK and CAP are included in the capital and risk equations, consecutively. Where, bank risk is dependent variable proxied by non-performing loans to total loans (NPLTL) or Z-score (LNZ) in equation (1), and bank capital (CAP) is dependent variable proxied of capital adequacy ratio (CAR) is a measure of capital regulation (CR) in equation (2). Ownership structure (OS) is measured by two variables: ownership by nature (Private dummy and Islamic dummy) and ownership concentration (PS, MAS, and AS). Bank level control variables for risk models (M1, M2…M10) are the size (SIZE), corporate governance (CG), leverage ratio (LEVERAGE). Bank level control variables for capital models (M11, M12…M20) are bank size (SIZE), return on total assets (ROTA), risk-weighted to total assets (RWATA), asset growth (AG). The growth of gross domestic product (GGDP) and rate of inflation (INFR) are two country-level control includes in both risk and capital models. Besides, we exclude ROTA from the instrument list when we run a regression for risk equation as this variable may have an endogenous effect.

5. Empirical results

This section derives results from the simultaneous model described above where risk and capital are the endogenous variables. Two stage least squares with cross-section random effect estimation have been used. 16 The random effect specification for balanced panel observations is supported by the Breusch-Godfrey (Breusch, 1978; Godfrey, 1978) Lagrange Multiplier test (LM test), which reject the null hypothesis that errors are independent within banks. A White test (White, 1980) is also applied to examine cross-sectional heteroskedasticity, and the null hypothesis of homoscedasticity is rejected at 5% level of significance. For this reason, we do not run regression through ordinary least square (OLS) estimations. We also carry out a Hausman test of endogeneity for risk and capital (results reported in Table 6 & 7). Here, we divide this section into three for the ease of discussion. Firstly, it shows the effect of capital regulation and ownership structure on risk-taking behavior of commercial

16

The fixed effect model is not appropriate for this study. As Hausman test supports the use of the random effects over fixed effects models.

banks. Secondly, it demonstrates the influence of risk and ownership structure on capital regulation. Finally, it traces non-linear relationship.

5.1 The impact of capital regulation and ownership structure on bank risk-taking

Concerning the impact of capital regulation and ownership structure on risk-taking behavior; Table 6 reveals the regression results through 10 models. First five models (M1-M5) reflect the effects of capital regulation and different ownership structure on credit risk (NPLTL) along with bank and country-level control variables. In the same way, next five models (M6-M10) have arranged with Zscore (LNZ) as the dependent variable. All models show the persistence results of risk. Model 1 carries a significantly negative coefficient among the credit risk models which convey the results of C.-C. Lee & Hsieh (2013), T.-H. Lee & Chih (2013), and Zhang et al. (2008) but opposite to the results of Altunbas et al. (2007), Rime (2001), Shrieves & Dahl (1992). The relation is positive in all models (M6-M10) when Z-score (LNZ) is used as dependent variable instead of NPLTL. The result reports that a 1% increase in CAR would decrease credit risk by 0.27% for Model 1, and increase Zscore (LNZ) by 0.12%, 0.10%, 0.10%, 0.10% and 0.11% for Model 6 to Model 10 respectively and increase stability. This result is consistent with our initial hypothesis (H1a) that the growth of capital ratio enhances the stability of banks’ and reduces credit risk.

From the ownership context; Islamic and privately owned banks are negatively (positively) associated with banks’ credit risk-taking (stability), and it means a 1% increase of Islamic (private) banks would cause credit risk decreasing by 0.94% (0.16) and consequently enhancing stability over conventional and state-owned banks respectively. So, in line with our hypothesis (H2), private banks are more risk averse than state-owned banks and have better stabilization with risk than any other banks.17 As stateowned bank have a direct liaison to the government, and they have greater tendency to undertake high risk (Lassoued et al., 2016). Hence, they are characterized as underperform as their increased credit

17

See Model 5 & 6 in Table 6, where it displays the strong position of private banks despite Islamic banks shown a superior form to reduce credit risk over all banks.

risk, insolvency risk, inefficiency in management, political pressure, etc. While the results of Model 2 also comply the next hypothesis (H3) that Islamic banks often tend to have lower credit risk than that of conventional banks which also identical to the results of Baele et al. (2010), Beck et al. (2013), and Olson & Zoubi (2008). From ownership concentration view, concentration from lower stakes (PS) experiences less risk-taking that is plausible with the results of Chalermchatvichien et al. (2014b) and ownership concentration from minority active shareholding can raise stability notably and no other promising relationship have been found from active shareholding. So, possibly risk vary within lower ownership and middle ownership stakes (H4).

In regard to bank-level control variables, bank size is insignificantly associated with insolvency risk in all models except Model 6, but credit risk models have displayed a strong positive coefficient except Model 1. So, large banks have tended to take more credit risk which is incoherent results of Stern & Feldman (2004), and this results also supported by “too-big-to-fail (TBTF)” argument.

In credit risk models corporate governance (CG) has a significantly negative association with credit risk except Model 1. As better corporate governance makes the bank cautious and lessens impulsive to take more risk (Arouri et al., 2014; De Jonghe et al., 2012). Despite there is a positive coefficient in all models of insolvency risks, but there has no such significant relation with overall risk. Apart from Model 1, in all models, leverage is positively significant. This implies more uncontrolled bank behavior and more interestingly leverage reduces insolvency a bit but generates more credit risk. The results of macroeconomic variables are also impressive. In all models, higher levels of GGDP increase bank risk-taking as banks invest more during expansion of economy which causes more risk in line with the result of Haq and Heaney (2012) but opposite from the findings of Laeven & Levine (2009). This would also cause an adverse impact on Z-score. For all models of credit risk, the INFR is significantly and negatively related to bank credit risk due to the availability of money to the hands of debtors. As a result, inflation causes to reduce the risk of Bangladeshi commercial banks and shows a greater solvency to all the models applied in the overall risk model.

5.2 The impact of risk and ownership structure on bank capital regulations

In this section, we now consider the role of risk and ownership structure where CAR is a dependent variable for all 10 models (Table 7).

All the models show the positive persistence results of capital. It means regarding capital adequacy ratio, Bangladeshi commercials banks take decisions to maintain capital by following the previous year’s trend. We find a significantly negative relationship between capital and credit risk in models (M12-M15), which validate the hypothesis (H1b) and results of Jacques & Nigro (1997), and Rahman et al. (2015). The negative relationship indicates that if the bank increases risk by 1%, then the capital balance will be deteriorated by 0.13% for Model 12, 0.13% for Model 13, 0.12% for Model 14 and 0.13% for Model 15 respectively. Conversely, higher stability of bank also enhances capital ratio (M16-M20) which also complementary to the results of (Laeven & Levine, 2009) and inverse from Hamza & Saadaoui (2013). From ownership view; a rise in ownership of private banks by 1% results in an improvement of CAR by 1.67%, 0.43% (M11, M16) and which is much higher than state-owned bank’s CAR.

[Insert Table 6 & 7 here]

The reason for this deviation is that government supports state-owned banks during financial turmoil while private banks have to keep sound capital for their safeguard. While, ownerships of Islamic bank are also positively aligned with capital regulation taking and a 1% increase of Islamic banks would cause capital raise by 0.59%, 0.45% (M12, M17). Unfortunately, in all models, no promising relations are found between capital regulation and ownership concentration from PS and MAS. Where the coefficient of AS is significantly positive in M15 and M20. Hence, higher ownership concentration exhibits a higher level of contribution to boosting capital ratio. This finding is consistent with the

corporate control hypothesis. In a nutshell, under uniform banking regulation, capital ratio influences through different ownership structure.

The results on bank-level and macroeconomic variables are also impressive. The coefficients of bank size, ROTA and GGDP are positively significant in all models except Model 16; there is no evidence of a relation between bank size and capital. On the other hand, the coefficient of RWATA is significantly negative in all models resulting improvement of capital. Where asset growth (AG) and rate of inflation (INFR) display poor coefficients with capital.

5.3 Resolving non-linearity 18

A few kinds of literature show a non-linear relationship between capital regulation and risk. Hence, we discover this opportunity by including a square term of capital regulation and risk in the regressions. After considering non-linearity, no models show significant association except models of Z-score show a significantly negative association between capital and risk when capital is the dependent variable. So, this U-shaped relation indicates when regulatory pressure works in a country then banks lose solvency at the initial stage to hold minimum capital. It is also conceivable that ownership structure may demonstrate a non-linear relationship with capital regulation and risk-taking. We thus introduce the square of all ownership variables consecutively in capital and risk equation, but the results of models are not significant and similar to the result of Chalermchatvichien et al. (2014a).

6. Robustness checks and analysis

To check robustness of regression results, we (i) introduced loans to deposits ratio (LTDR) as another risk measure in place of credit risk which is also a proxy of liquidity risk, and (ii) used shareholders’ equity to total assets (EQTTA) as another measure of capital regulation instead of CAR. 18

The non-linear regression results are available from authors upon request.

By following Chalermchatvichien et al. (2014b), we have used LTDR in place of credit risk, and LTDR shows the persistence result in all models like credit risk or overall risk of Table 6.19 But no models show significant alignment between CAR and LTDR in those tables. We also replace CAR with EQTTA to showing the prudent association between capital and risk. Ownership variables are also plausible to the previous results with very few exceptions, for example, private banks tend to have more liquidity risk over state-owned banks while there is no such relation in case of credit risk. The valid reason is private banks fueled by depositors, and they have to generate more revenue over its costs through maximum utilization of investor’s fund. As a result, the extension of investment causes liquidity risk. Besides, private banks also support the previous regression base result in capital equation (Table 7).

Similarly, the use of EQTTA also displays the conceivable result in all models. After using this variable as independent, credit risk and overall risk models show the persistence effect. Resembling Table 6, ownership variables preserve almost the same coefficient here. While the coefficient of EQTTA for overall risk models differs from primary regression results. But this is consistent with the capital equation, and there is no strong relation between capital and NPLTL when we used EQTTA as the dependent variable. From the evidence, one macroeconomic variable (INFR) has no significant connection with capital and shows robust result in all models. Almost, all control variables retain their signs and higher R-squared signify the explanatory power of the model.

7. Concluding remarks and policy implications

This paper suggests that different ownership styles have different effect on risk-taking i.e. private and Islamic banks tend to have lower risk-taking and equally stable than state-owned and conventional banks respectively. This result aligns with Srairi (2013). But these banks have higher inclinations to undertake high liquidity risk. On the other hand, banks with lower ownership concentration have 19

To conserve space, we only report main results.

fewer propensities to take the risk (Chalermchatvichien et al., 2014a; Laeven & Levine, 2009) and conversely, higher ownership concentration improves banks’ capital ratio. The existence of minority active shareholding has no evidence of generating risk but ensuring greater solvency in banks while active shareholding promotes banks to undertake more risk regarding liquidity. Besides, no ownership concentration variable has shown encouraging interaction effects (except ownership concentration of AS) on capital regulation that shows disparity from the findings of Shehzad et al. (2010). Particularly, private and Islamic banks have enough capital stability than state-owned and conventional banks respectively. Moreover, we also examine the effects of portfolio risk on capital regulation. In this case, lower level of credit risk ensures bank’s stability and promotes private and Islamic banks to improve capital adequacy ratio which also the prime objective of Basel II and Basel III. However, state-owned banks with a higher burden of credit risk and lower capital adequacy cause a matter of stun and awe. To get better control of ownership structure, we also employ corporate governance as instrument variable. Better corporate governance mechanism may lessen the aggressiveness of bank risk-taking that aligns with our expectation. In Bangladesh, it has also pointed out that large banks have greater tendency to undertake high risk (Rahman et al., 2015). Finally, we also document quadratic relationship among risk, capital regulation, and ownership structure. We found no materialistic relationship except when Z-score is performed in the capital equation as an exogenous variable.

Our contributions have very useful implications for stakeholders such as policy makers, regulators, shareholders, financial analysts, researchers, etc. The findings have some distinct insights from the results of Chalermchatvichien et al. (2014a), Laeven & Levine (2009), Miah & Sharmeen (2015), Rahman et al. 2015; and Srairi (2013).We have shown here the dual impact of a wide range of ownership styles on capital and risk. First, by following Dong et al. (2014), we can suggest that it is high time to restructure state-owned banks into private banks as state-owned banks in Bangladesh have high non-performing loans, limited capital stability resulting them losing concern in consecutive years. Alternatively, the government can reduce its ownership through issuing more shares to the public and ensure strong corporate governance including the active contribution of risk surveillance

committee. Second, Islamic banks can be encouraged more as their less risk-taking attitude, higher capital stability, asset growth and return with powerful Islamic Shari’ah board and corporate governance. Third, banks should consider various ownership stakes as they have the power of influencing bank’s internal management policies as well as market determinants. Fourth, large banks should be given priority as they hold lower capital adequacy and enforce them to follow Basel II and Basel III guidelines. Finally, the regulators show weak supervisory control on banks risk-taking behavior as the results do not find the obvious effect of capital regulation on risk regardless the insolvency risk. This result aligns with Shehzad et al. (2010) and La Porta et al. (1997). So, the regulatory bodies should strengthen the influence of capital regulation on banks’ risk-taking behaviors in Bangladesh. In this study, we didn’t consider other shareholding influence on risk and capital such as sponsors shareholding, institutions shareholding, etc. If we separately run the regression with a particular type of bank’s observation, then the results might be different. Moreover, we have limited observations as our study based on Bangladeshi banks. Therefore, these issues will be addressed in the future by considering cross-country analysis and developed guidelines under Basel III standards.

Acknowledgments: We are grateful to editors and anonymous referees for their valuable comments to improve the paper. All remaining errors are ours.

Funding: This work was supported by the project of National Natural Science Foundation of China (NSFC) Grant No. [71173077].

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Appendices

Table 1. Banking scenario of Bangladesh a

Year

Types of bank

Number of branches

Number of banks

Total Assets (in billion Taka)

Percent of industry assets

Deposits (in billion Taka)

Percent of deposits

61.8 26.4 6.1 5.7 100 63.3 27.5 5.5 3.7 100

3939.3 1631.2 359.5 343 6273 4449.4 1952.1 326 237.6 6965.1

62.8 26 5.7 5.5 100 63.9 28 4.7 3.4 100

39 3602 4948.2 PCBs 4 3520 2108.5 SCBs 9 69 488.7 2013 FCBs 4 1494 454.8 DFIs 56 8685 8000.2 Total PCBs 39 3917 5787.1 SCBs 5 3553 2517.1 2014 FCBs 9 70 505 DFIs 3 1500 333.8 Total 56 9040 9143 a Source: Annual Reports 2014-2015, Bangladesh Bank (BB)

Table 2. Comparative position of the Islamic banking sector b Year

2013

2014 b

Number of banks

Deposits(in billion Taka)

Credits (in billion Taka)

Credit deposit ratio

Liquidity: excess(+)/shortfall (-) (in billion Taka)

8 56

1117.9 6273

951.3 4638.7

85.10 73.95

91.2 955.8

Islamic

8

1349.7

1137.6

84.29

127.5

All

56

6965.1

5147.2

73.90

1142.2

Types of bank

Islamic All

Source: Annual Reports 2013-2014, Bangladesh Bank (BB)

Table 3. Variables' definition and sources Variables

Symbol

Definition and measure

Impact on CR Expected Sign

Data source

Risk Measures Credit Risk

NPLTL

Ratio of non-performing loans to total loans.

+/-

Z-score (LNZ)

An inverse proxy of bank default risk, measured as the means of return on assets ratio (ROA) plus the capital asset ratio (CAR) divided by the standard deviation of return on assets ratio σ (ROA).

+

CAR

Regulatory capital to risk weighted assets, i.e. Capital Adequacy Ratio (CAR).

-

(Barth et al., 2004; Berger, Bouwman, Kick, & Schaeck, 2014; ElBannan, 2015; Gonzalez, 2005). (Cihak & Hesse, 2008; ElBannan, 2015; Laeven & Levine, 2009; Lepetit et al., 2008). (Altunbas et al., 2007; Laeven & Levine, 2009; Lin et al., 2005; Rime, 2001).

Stability

PRIVATE (Dummy) ISLAMIC (Dummy) PS MAS AS

1 if bank is privately owned and 0 otherwise. 1 if it is Islamic Shari’ah based bank and 0 otherwise. 1 if shareholders are passive and 0 otherwise. 1 if shareholders are minority active and 0 otherwise. 1 if shareholders are active and controlling and 0 otherwise.

+/-

+/+/+/+/+

Bank size

SIZE

Natural logarithm of total assets.

+/-

-

Corporate Governance

CG

Value of CG determine by weighted scoring model.

+/-

Leverage Return on total assets Risk weighted assets Assets growth Macro-economic variables Growth of gross domestic product Rate of Inflation

LEVERAGE ROTA RWATA AG

Total debt to total assets. Net income to total assets. Ratio of risk assets to total assets. Percentage change of assets by considering 2006 as base year.

+ +

+ + + +

GGDP

Annual growth in real gross domestic product.

-

+/-

INFR

Annual inflation rate.

+/-

-

Main Variables

Capital Regulation

Impact on Risk Expected Sign

Ownership Structure Nature Concentration

(Baele et al., 2010; Beck et al., 2013; Berger et al., 2005; Chalermchatvichien, et al., 2014a; Chalermchatvichien et al., 2014b; Cornett et al., 2010; Haw et al., 2010; Laeven & Levine, 2009; Olson & Zoubi, 2008; Shehzad et al., 2010).

Bank-level variables (Drakos, Kouretas, & Tsoumas, 2014; Hussain & Hassan, 2005; Laeven & Levine, 2009; Uzun & Webb, 2007; Zribi & Boujelbène, 2011). (Arouri et al., 2014; De Jonghe et al., 2012; Laeven & Levine, 2009). (Chalermchatvichien et al., 2014b). (Gropp & Heider, 2007; Louzis et al., 2012). (Avery & Berger, 1991; Gropp & Heider, 2007). (Schaeck & Čihák, 2007).

(Chaibi & Ftiti, 2015; Jokipii & Milne, 2008; Stolz & Wedow, 2011). (Chaibi & Ftiti, 2015; Hussain & Hassan, 2005).

Table 4. Summary statistics of variables c Variables

Full sample

Private banks

State-owned banks

Conventional banks

Islamic banks

Mean

Max

Min

S.D.

Mean

Max

Min

S.D.

Mean

Max

Min

S.D.

Mean

Max

Min

S.D.

Mean

Max

Min

S.D.

CAR (%)

10.8

18.6

-29.67

4.58

11.7

18.6

6.31

1.68

4.98

14.6

-29.7

10.6

10.6

18.6

-29.7

4.98

11.7

16.5

7.19

1.91

NPLTL (%)

5.93

44.6

0.19

6.5

3.93

15

0.19

2.03

20

44.6

5.236

9.17

6.58

44.6

0.658

7

3.15

9.75

0.19

1.84

Z-score (LNZ)

2.78

4.03

-2.41

1.04

3.10

4.03

1.87

0.40

0.54

1.89

-2.41

1.38

2.70

3.85

-2.41

1.13

3.12

4.03

2.32

0.40

Private (Dummy)

0.88

1

0

0.33

1

1

1

0

0

0

0

0

0.85

1

0

0.36

1

1

1

0

Islamic (Dummy)

0.19

1

0

0.39

0.21

1

0

0.41

0

0

0

0

0

0

0

0

1

1

1

0

PS (%)

1.02

19

0

3.49

0.88

19

0

3.45

2.01

9.81

0

3.63

1.26

19

0

3.83

0

0

0

0

MAS (%)

16.8

49.8

0

18.2

19.2

49.8

0

18.2

0

0

0

0

15.8

49.8

0

18

21.1

48.1

0

18.5

AS (%) Bank Level Variables:

19.8

96.8

0

29.6

22.7

96.8

0

30.6

0

0

0

0

19.4

96.8

0

30.1

21.7

62.7

0

27.6

SIZE

11.5

13.7

9.733

0.8

11.4

13.4

9.733

0.69

12.6

13.7

11.24

0.7

11.5

13.7

9.733

0.78

11.4

13.4

9.89

0.9

Main Variables:

CG

0.95

1

0.73

0.07

0.96

1

0.73

0.06

0.92

1

0.74

0.09

0.95

1

0.73

0.07

0.96

1

0.75

0.07

Leverage (%)

92.43

112.94

84.57

3.19

91.84

96.35

84.57

2.05

96.60

112.94

88.63

5.74

92.50

112.94

84.57

3.42

92.15

96.02

86.77

1.91

ROTA (%)

1.31

6.05

-13.52

1.51

1.56

6.05

0.21

0.79

-0.42

2.04

-13.5

3.29

1.25

6.05

-13.5

1.64

1.57

3.54

0.35

0.71

RWATA (%)

75.75

127.21

35.29

17.64

78.51

127.21

49.52

15.82

56.43

121.28

35.29

17.86

76.06

127.21

35.29

18.35

74.39

124.04

51.1

14.22

AG (%) Macro-economic Variables:

182

900

0

173

196

900

0

179

85.3

252

0

72.2

165

611

0

148

257

900

0

242

GGDP (%)

6.19

6.63

5.57

0.35

6.19

6.63

5.57

0.35

6.19

6.63

5.57

0.35

6.19

6.63

5.57

0.35

6.19

6.63

5.57

0.35

INFR (%)

7.74

10.7

5.4

1.55

7.74

10.7

5.4

1.55

7.74

10.7

5.4

1.56

7.74

10.7

5.4

1.55

7.74

10.7

5.4

1.56

Obs. 288 252 36 234 54 c Note: The table shows the descriptive statistics of variables which have been used in the regression. Where, capital adequacy ratio (CAR), non-performing loan to total loans (NPLTL); the return on assets ratio (ROA) plus the capital asset ratio (CAR) divided by the standard deviation of return on assets ratio σ (ROA) defined as Z-score and are main endogenous variables; PRIVATE (DUMMY), ISLAMIC (DUMMY), passive shareholding

(PS), minority active shareholding (MAS) and active shareholding (AS) are the main explanatory ownership variables; bank size (SIZE), corporate governance (CG), financial leverage (LEVERAGE), return on average assets (ROTA), risk weighted assets to total assets (RWATA), growth of assets (AG) are bank level control variables; and growth of gross domestic product (GGDP), rate of inflation (INFR) are two macroeconomic control variables. Max = Maximum Value, Min = Minimum Value, S.D. = Standard Deviation, Obs. = Observations.

Table 5. Correlation matrix d 1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

1

CAR

2

NPLTL

-0.53***

1.0

3

Z-score (LNZ)

0.74***

-0.76***

1.0

4

0.48***

-0.82***

0.81***

1.0

0.09

-0.21***

0.16***

0.18***

1.0

6

Private (Dummy) Islamic (Dummy) PS

-0.12**

0.06

-0.07

-0.11*

-0.14**

1.0

7

MAS

0.15**

-0.32***

0.27***

0.35***

0.11*

-0.27***

1.0

8

AS

0.17***

-0.13**

0.21***

0.25***

0.03

-0.20***

-0.62***

1.0

9

SIZE

-0.10*

0.43***

-0.32***

-0.51***

-0.06

0.01

-0.25***

-0.03

1.0

10

CG

0.35***

-0.23***

0.30***

0.20***

0.02

-0.09

0.07

0.10*

0.23***

1.0

11

Leverage

-0.76***

0.56***

-0.60***

-0.49***

-0.04

0.21***

-0.13**

-0.28***

-0.02

-0.33***

1.0

12

ROTA

0.60***

-0.53***

0.56***

0.43***

0.08

-0.11*

0.15**

0.17***

-0.26***

0.16***

0.58***

1.0

13

RWATA

0.08

-0.44***

0.24***

0.42***

-0.04

-0.03

0.09

0.19***

-0.02

0.14**

0.50***

0.28***

1.0

14

AG

0.18***

-0.18***

0.18***

0.21***

0.21***

0.01

0.09

0.05

0.43***

0.40***

0.25***

0.01

0.22***

1.0

15

GGDP

-0.09

0.07

-0.09

0.02

0.01

-0.01

0.02

-0.04

-0.17***

-0.21***

-0.20***

-0.25***

-0.28***

-0.13**

1.0

16

INFR

0.02

-0.06

0.05

0.05

0.07

0.05

-0.02

0.03

-0.07

-0.04

0.09

0.08

0.12**

-0.12**

0.27***

5

d

16

1.0

1.0

Note: The table displays the Pearson’s correlation coefficients of variables. Where, capital adequacy ratio (CAR), non-performing loan to total loans (NPLTL); the return on assets ratio (ROA) plus the capital asset ratio (CAR) divided by the standard deviation of return on assets ratio σ (ROA) defined as Z-score and are main endogenous variables; PRIVATE (DUMMY), ISLAMIC (DUMMY), passive shareholding (PS), minority active shareholding (MAS) and active shareholding (AS) are the main explanatory ownership variables; bank size (SIZE), corporate governance (CG), financial leverage (LEVERAGE), return on average assets (ROTA), risk weighted assets to total assets (RWATA), growth of assets (AG) are bank level control variables; and growth of gross domestic product (GGDP), rate of inflation (INFR) are two macro-economic control variables. Total number of observations is 288. *, **, *** indicate significance at p< .10, p< .05 and p< .01 (2-tailed) respectively.

Table 6. Impact of capital regulation and ownership structure on bank risk-taking e Variables

M1

M2

M3

M4

M5

NPLTL(-1)

0.60*** (5.74)

0.67*** (11.20)

0.69*** (11.48)

0.68*** (11.86)

0.69*** (11.87)

LNZ(-1) CAR PRIVATE (Dummy)

-0.27*** (-2.48) -0.16** (-1.20)

ISLAMIC (Dummy)

0.07 (0.82)

0.03 (0.32)

0.04 (0.48)

GGDP INFR Endogeneity test t (p-value) White test , p-value LM test, p-value Adjusted R2 No. of observations

M9

M10

0.23** (2.36) 0.12*** (6.93) 1.50*** (4.46)

0.51*** (5.93) 0.10*** (4.17)

0.52*** (6.01) 0.10*** (4.14)

0.51*** (5.94) 0.10*** (4.26)

0.51*** (5.93) 0.11*** (4.14)

-0.06* (-1.63)

0.00 (0.22) -0.01 (-1.04)

AS

LEVERAGE

M8

0.06** (2.33)

MAS

CG

M7

-0.94** (-1.89)

PS

SIZE

0.05 (0.55)

M6

0.33 (0.52) 1.95 (0.09) -0.02 (-0.19) 3.40*** (6.57) -0.51*** (-3.41) -0.85 (0.00) 0.00 0.00 82.92% 288

1.59*** (2.90) -20.35* (-1.83) 0.34** (2.22) 2.59*** (3.51) -0.40** (-2.43) 1.78 (0.08) 0.00 0.00 79.14% 288

1.55*** (2.82) -21.25* (-1.72) 0.30** (2.18) 2.66*** (3.79) -0.41*** (-2.47) 2.10 (0.04) 0.00 0.00 79.19% 288

1.51*** (2.98) -21.04* (-1.79) 0.29** (2.07) 2.69*** (3.72) -0.43*** (-2.50) -6.68 (0.00) 0.00 0.00 79.07% 288

0.05** (2.02) 0.01 (1.22) 1.60*** (2.99) -22.38* (-1.82) 0.31** (2.15) 2.64*** (3.69) -0.42*** (-2.49) 1.93 (0.06) 0.00 0.00 78.70% 288

0.11*** (3.05) 0.01 (0.02) 0.06*** (6.57) -0.34*** (-8.51) 0.07*** (6.79) -2.93 (0.00) 0.00 0.00 82.21% 288

-0.12 (-1.36) 0.37 (0.32) 0.02* (1.79) -0.20*** (-2.56) 0.05*** (3.42) -1.13 (0.04) 0.00 0.00 75.88% 288

-0.12 (-1.35) 0.35 (0.31) 0.02* (1.76) -0.20*** (-2.54) 0.05*** (3.36) -1.39 (0.00) 0.00 0.00 75.82% 288

-0.11 (-1.28) 0.33 (0.29) 0.02** (2.00) -0.21*** (-2.68) 0.05*** (3.53) -1.00 (0.00) 0.00 0.00 76.00% 288

0.00 (1.61) -0.12 (-1.33) 0.34 (0.30) 0.02** (1.96) -0.21*** (-2.67) 0.05*** (3.48) -1.08 (0.00) 0.00 0.00 75.86% 288

e

Note: Table shows the 2SLS estimation results of Eq. (1). Where non-performing loans to total loans (NPLTL), and Z-score (LNZ) are the endogenous variables for bank i and year t. The NPLTL (1) and LNZ (-1) are lagged dependent variables. CAR is the independent variable and PRIVATE (DUMMY), ISLAMIC (DUMMY), passive shareholding (PS), minority active shareholding

(MAS) and active shareholding (AS) are the main explanatory ownership variables. Bank size (SIZE), corporate governance (CG), financial leverage (LEVERAGE) are bank level control variables; and growth of gross domestic product (GGDP), rate of inflation (INFR) are two macro-economic control variables. Model 1-Model 5 (Model 6-Model 10) explains the influence of capital regulation and ownership structure on credit risk (stability an inverse measures of default risk). The values in parentheses are t-statistics. *Significance at 10 percent; ** 5 percent; and *** 1 percent level.

Table 7. Impact of bank risk and ownership structure on capital regulation f Variables

M11

M12

M13

M14

M15

M16

M17

M18

M19

M20

CAR(-1)

0.37*** (3.18) -0.05 (-0.85)

0.37*** (3.17) -0.13*** (-3.55)

0.37*** (3.18) -0.13*** (-3.01)

0.38*** (3.21) -0.12*** (-2.74)

0.37*** (3.13) -0.13*** (-2.97)

0.34*** (3.39)

0.34*** (2.82)

0.33*** (2.81)

0.34*** (2.83)

0.34*** (2.81)

2.51*** (2.51) 0.43* (1.63)

1.32*** (3.37)

1.33*** (3.32)

1.32*** (3.44)

1.30*** (3.18)

NPLTL LNZ PRIVATE (Dummy)

1.67** (2.30)

ISLAMIC (Dummy)

0.59*** (2.54)

PS

0.45** (2.23) -0.01 (-0.37)

MAS

-0.01 (-0.27) -0.01 (-0.55)

AS SIZE ROTA RWATA AG GGDP INFR Endogeneity test t (p-value) White test , p-value LM test, p-value Adjusted R2 No. of observations

1.13*** (4.28) 1.97*** (6.28) -0.08*** (-5.36) 0.00 (0.61) 1.71*** (3.66) -0.04 (-0.43) 9.90 (0.00) 0.00 0.00 67.73 288

0.94*** (3.03) 1.94*** (6.40) -0.08*** (-5.26) 0.00* (1.77) 1.82*** (4.25) -0.06 (-0.72) 7.31 (0.00) 0.00 0.00 67.74 288

0.96*** (3.06) 1.93*** (6.48) -0.08*** (-4.74) 0.00 (1.16) 1.88*** (4.32) -0.07 (-0.80) 7.00 (0.00) 0.00 0.00 67.47 288

0.92*** (3.10) 1.95*** (6.30) -0.08*** (-4.62) 0.00 (1.48) 1.90*** (4.27) -0.08 (-0.86) 7.49 (0.00) 0.00 0.00 67.51 288

-0.01 (-0.97) 0.01** (0.85) 0.96*** (2.93) 1.92*** (6.28) -0.08*** (-4.58) 0.00 (1.21) 1.86*** (4.25) -0.07 (-0.81) 6.93 (0.00) 0.00 0.00 67.57 288

0.34 (0.90) 1.54*** (4.47) -0.04*** (-2.74) 0.00 (1.51) 2.31*** (3.07) -0.18 (-1.31) -8.68 (0.00) 0.00 0.00 73.18 288

0.96*** (4.36) 1.73*** (5.17) -0.07*** (-6.06) 0.00 (0.65) 1.76*** (4.59) -0.07 (-0.94) -4.82 (0.00) 0.00 0.00 72.36 288

0.99*** (4.62) 1.71*** (5.15) -0.06*** (-5.51) 0.00 (0.14) 1.80*** (4.71) -0.08 (-1.01) -4.53 (0.00) 0.00 0.00 72.19 288

0.95*** (4.54) 1.72*** (5.00) -0.06*** (-5.40) 0.00 (0.33) 1.82*** (4.65) -0.08 (-1.07) -5.04 (0.00) 0.00 0.00 72.26 288

0.02** (0.81) 0.99*** (4.48) 1.72*** (5.05) -0.06*** (-5.38) 0.00 (0.17) 1.80*** (4.52) -0.08 (-1.01) -4.37 (0.00) 0.00 0.00 72.16 288

f

Note: Table shows the 2SLS estimation results of Eq. (2). Where capital adequacy ratio (CAR) is the endogenous variable for bank i and year t. The CAR (-1) is a lagged dependent variable. The non-performing loans to total loans (NPLTL), and Z-score (LNZ) are the independent variables and PRIVATE (DUMMY), ISLAMIC (DUMMY), passive shareholding (PS), minority active

shareholding (MAS) and active shareholding (AS) are the main explanatory ownership variables. Bank size (SIZE), return on average assets (ROTA), risk weighted assets to total assets (RWATA), growth of assets (AG) are bank level control variables; and growth of gross domestic product (GGDP), rate of inflation (INFR) are two macro-economic control variables. Model 11-Model 15 (Model 16-Model 20) explains the influence of NPLTL (LNZ) and ownership structure on capital regulation. The values in parentheses are t-statistics. *Significance at 10 percent; ** 5 percent; and *** 1 percent level.

Scenerio of credit risk and capital adequacy ratio 14

Percentage, %

12 10 8 6

CAR, %

4

NPLTL, %

2 0 2006 2007 2008 2009 2010 2011 2012 2013 2014 Year

Fig.1 Capital adequacy ratio (CAR) and Non-performing loan to total loan (NPLTL)