Corporate governance, political connections, and bank performance

Haris, Muhammad; Yao, Hongxing; Tariq, Gulzara; Javaid, Hafiz Mustansar; Ul Ain, Qurat Article Corporate governance, political connections, and bank performance International Journal of Financial Studies Provided in Cooperation with: MDPI – Multidisciplinary Digital Publishing Institute, Basel Suggested Citation: Haris, Muhammad; Yao, Hongxing; Tariq, Gulzara; Javaid, Hafiz Mustansar; Ul Ain, Qurat (2019) : Corporate governance, political connections, and bank performance, International Journal of Financial Studies, ISSN 2227-7072, MDPI, Basel, Vol. 7, Iss. 4, pp. 1-37, https://doi.org/10.3390/ijfs7040062 This Version is available at: https://hdl.handle.net/10419/257660 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ International Journal of Financial Studies Article Corporate Governance, Political Connections, and Bank Performance Muhammad Haris 1,* , Hongxing Yao 1, Gulzara Tariq 1, Hafiz Mustansar Javaid 2and Qurat Ul Ain 3 1School of Finance and Economics, Jiangsu University, Zhenjiang 212013, China; [email protected] (H.Y.); [email protected] (G.T.) 2School of Economics, Sapienza Universitàdi Roma, 00161 Roma, Italy; [email protected] 3School of Economics and Finance, Xi’an Jiaotong University, Xi’an 710049, China; [email protected] *Correspondence: [email protected] Received: 8 May 2019; Accepted: 8 October 2019; Published: 15 October 2019   Abstract: This study investigates the impact of corporate governance characteristics and political connections of directors on the profitability of banks in Pakistan. The study uses the data of 26 domestic banks over the latest and large period of 2007–2016. Our findings firstly affirm that bank profitability is negatively affected by the presence of politically connected directors on the board, reporting significantly lower return on assets, return on equity, net interest margin, and profit margin. Secondly, our findings also affirm the negative political influence on the sustainability of the banking industry, reporting significantly lower return on assets, return on equity, net interest margin, and profit margin during the government transition of banks having politically connected directors sitting on their board. Our findings further report an inverted U-shaped relationship between board size and bank profitability, suggesting that a board size beyond 8–9 members decreases the profitability. The study further finds a positive impact of board composition, board independence, and director compensation on bank profitability, while also finding a negative impact of frequent board meetings, presence of foreign directors, and audit committee independence. Keywords: Pakistan; banks; profitability; corporate governance; political connections JEL Classification: G21; G28; G34 1. Introduction Sustainable profitability is vitally important for the stability of banks (Garc í a-Herrero et al. 2009) and the economic growth of any country (Sinha and Sharma 2016). The banking sector is regarded as the most vital component of the financial industry, which itself is a key pillar of the economy of a country. The economic growth is positively related to growth in banks and other financial intermediaries (Haris et al. 2019a) . Thus, the sustainable growth of banks in Pakistan is essential, as it enables them to continue their supporting role in economic growth. Many studies from non-financial firms claimed that political connections benefit the firms in accessing higher loans at a lower cost from political banks. Because firms appoint politically connected directors (PCDs) to obtain political benefits (Jackowicz et al. 2014), those appointed directors use their political relations to access easy loans from political banks to finance the electoral campaigns of ruling parties and/or their associated political parties. Pakistan is a political economy, and many firms in Pakistan are aligned with political connections. The firms use their political connections to gain monetary and nonmonetary benefits such as licensing, tax subsidies, contracting, and, most importantly, easy access to higher loans from political banks (Cheema et al. 2016). The political Int. J. Financial Stud. 2019,7, 62; doi:10.3390/ijfs7040062 www.mdpi.com/journal/ijfs Int. J. Financial Stud. 2019,7, 62 2 of 37 connections of banks can also be beneficial for them with regard to accessing tax advantages, financial bailouts, etc. Nevertheless, political connections (PCs) may affect the corporate governance mechanism of banks; for instance, PCs might affect audit independence and accounting information. PCs may increase the risk of agency problems, because PCDs prefer achieving political goals that could damage the interest of shareholders; PCs can also raise conflicts of interest among PCDs and non-PCDs because of their exclusive interests. On the one hand, politically connected firms face low risk through their access to higher credit and financial bailouts during times of distress. On the other hand, politically connected banks face higher risk by injecting higher credit to politically connected firms at a lower cost with easy terms. Therefore, the advantages of political connections are different for financial and non-financial firms. Recently, Chen et al. (2018) reported the lower performance of politically connected banks than non-political banks. They also reported a higher default ratio of those banks having politically connected chief executive officers (CEOs). They further suggested that politically connected directors use their political power and influence lending decisions by interfering in lending standards and, thus, raise their bank’s sensitivity to lower performance and risk, especially during crises. Theoretically, this indicates that the government is likely to direct state-owned banks to finance certain projects for political expediency, especially during election years, even if such projects are of less significance to the public interest. The ruling government parties, specifically in Pakistan, gain monetary advantages (e.g., preferential loans) by putting pressure on political connected directors during election years. Thus, it is important to examine the empirical work with regard to the impact of political connections on bank performance during government transitions. The studies from the perspective of political connections in banks are still limited and scarce. Therefore, it would be more interesting to see the role of corporate governance and political connections in the context of Pakistani financial institutions in relation to their financial performance. Corporate governance practices aid to build an effective relationship between shareholders (referred to as principals) and the management (referred to as agents) for the sustainability of banks (Adams and Mehran 2012). Different corporate governance theories also emphasize the importance of corporate governance in the improved performance of banks, such as the agency theory (Jensen and Meckling 1976) , transaction cost theory (Williamson 1985), resource-dependent theory (Pfeffer and Salancik 1978), and stewardship theory (Donaldson and Davis 1991). Corporate governance provides structure and an effective framework to set and monitor the performance of banks by establishing a strong principal–agent relationship (Mehran 2003). Given the importance of deregulation, globalization, increasing risk, and investor protection, as well as the positive role of the banking sector in economic growth, corporate governance has significant importance for the sustainability of the banking industry, because corporate governance practices help to build sustainable value for the banking industry (Yatim and Yusoff2014). Both the Organization for Economic Co-operation and Development (OECD 1999) and Basel Committee on Banking Supervision (BCBS 1999;BCBS 2006) produced and made recommendations regarding the best corporate governance practices for a sound financial system, which is important for sustained economic growth (de Andres and Vallelado 2008; Ferdous et al. 2014). Following the OECD and Basel committee recommendations, many countries, including Pakistan 1 , developed their own guidelines for the best corporate governance practices in order to monitor and enhance the performance of their banking system and to protect shareholder 1 Initially, in 2002, the Security and Exchange Commission of Pakistan (SECP), in collaboration with United Nation Development Program (UNDP), started a project which involved developing, designing, and implementing the code of corporate governance in order to improve best corporate governance practices in the country (SECP 2004) for the sustainable growth of industry. The focus of the project was to develop codes for the banking industry, but mainly for non-banking sector. Later, based on the OECD principles (OECD 1999) and Basel committee recommendations (BCBS 1999;BCBS 2006), the State Bank of Pakistan (SBP—the central bank of the country) issued a “Handbook of Corporate Governance” in 2003 particularly for the banking industry, containing guidelines for the board of directors, auditor, audit committee, disclosure, and management. Furthermore, the Banking Companies Ordinance (1962) and Prudential Regulations for banks issued by the SBP also direct governance requirements. Additionally, the SECP and SBP as major shareholders initiated a “Pakistan Institute of Corporate Governance” in order to promote governance education in the country. Apart from that, both the Int. J. Financial Stud. 2019,7, 62 3 of 37 wealth. Because of the idiosyncratic nature of financial institutions, banks are considered as highly leveraged and vulnerable to risky exposures, which require prudent lending decisions to avoid the higher risk of loan losses, which is possible through the developed mechanism of sound corporate governance practices such as the formation of risk and audit committees. The adoption of sound corporate governance practices ensures the implementation of all prudential regulations and prevents the financial institutions from penalties, thus mitigating the regulatory risk and enhancing performance. Therefore, it is equally important to examine whether these corporate governance practices made a substantial contribution in achieving the improved performance of banks, which has vital importance for the sustainability of the whole financial system (Yatim and Yusoff2014). Corporate governance studies regarding the financial sector are still limited and scarce. The unique nature of the banking business and its relevance in the economic system result in problems being very specific, based on their corporate governance mechanism. The complex nature of banking operations squeezes the stakeholders’ power to monitor the decisions of bank managers and enhances asymmetric information. Banks are highly leveraged because of taking deposits, which requires a more intense regulatory control for reducing payment and systematic risk, as well as safeguarding the deposits, thereby ensuring a stable payment system and prudent lending mechanism. Therefore, regulations for the corporate governance of banks are somehow different from non-financial firms. Excessive regulatory measures, e.g., bank ownership restrictions, credit restrictions, reduced operations, and deposit insurance, tend to reduce the risk. However, these excessive measures may cause agency problems because they are not aligned with the profit maximization goal of shareholders. Thus, the developed mechanism of corporate governance of banks, e.g., bank board, board independence, and board committees, helps in the framework of higher informational asymmetries and intense regulations, thereby controlling the behavior of managers. Due to the complexity of banking operations, the knowledge possessed by board members enables them to monitor the efficiency of business. The board creates a link with regulators by ensuring regulatory compliances, and reduces the conflict between regulators and banks, thus raising the performance. Therefore, examining the role of corporate governance in the improved performance of banks is an important research area for academics and policy-makers. Our study contributes to the existing literature in several ways. The issue of political connections of bank directors gained much attention during recent years. Pakistan is a political country, where the performance of the banking industry is always influenced by high political interference. Previously, Khwaja and Mian (2005) found that the performance of Pakistani banks is influenced by higher preferential bank loans. They argued that these loans are injected by banks into politically connected firms during election years because of political influence in the banking industry. Liang et al. (2013) also argued that politically connected boards have structure-oriented incentive behaviors toward government objectives and allow political interference in internal decisions, which harms bank performance through pursuing political concerns at the expense of banks. Political connections make banks more open to risk-taking by lowering interest rates and leveraging lending terms, which damages the performance. Thus, politically connected firms access easy loans more frequently from government banks. Therefore, for the first time, we intend to study the political connections of directors and examine their impact on bank profitability in Pakistan. Moreover, Yao et al. (2018) found a lower profitability of the Pakistani banking industry during government transitions and argued that the lower profitability could be because of political connections. Haris et al. (2019a) also reported a lower profitability of Pakistani government banks during the period of government elections. They argued that this negative growth was due to the high political influence. Therefore, we also contribute to analyzing the profitability of banks having the presence of politically connected directors (PCDs) SECP and SBP revise and update the corporate governance guidelines from time to time through circulars (for further details, visit https://www.secp.gov.pk and http://www.sbp.org.pk/). Int. J. Financial Stud. 2019,7, 62 4 of 37 during the period of government transitions 2 . Because, in Pakistan, nine out of 29 domestic banks are government-owned and politically dominant, some privately owned banks also suffer from political influence. Both government- and private-owned banks disburse a higher amount of lending to government projects, departments, and personnel because of political connections, which leads to lower profitability due to loan defaulting upon government change (Yao et al. 2018). Consequently, government change negatively affects the sustainable growth in the profitability of Pakistani banks (Yao et al. 2018). Furthermore, our study, for the first time, intends to examine the impact of internal corporate governance characteristics (board size, board composition, board independence, director compensation, presence of foreign directors, board meetings, audit committee meetings, and audit committee independence) on the profitability of Pakistani banks by considering four accounting measures of profitability, i.e., return on assets (ROA), return on equity (ROE), net interest margin (NIM), and profit margin (PM), taken from Haris et al. (2019b), Yao et al. (2018), and Tan (2016). Our study further extends the evidence to support the findings of Yeung (2018), Yulia (2016), Grove et al. (2011), and de Andres and Vallelado (2008), by examining the nonlinear (inverted U-shaped) relationship between board size and profitability. Furthermore, the endogeneity issue also remains unaddressed in the few available studies of corporate governance in the Pakistani banking industry. Our baseline methodology is the generalized method of moments (GMM), which draws more robust and consistent findings by eradicating the problem of endogeneity in corporate governance characteristics. Our study also makes a substantial contribution by examining, for the first time, the corporate governance of the whole domestic banking industry of Pakistan during the period of 2007–2016, which is the most recent ten-year period representative of free market operation and the revival of the democratic process in the country, based on two government transition periods (Yao et al. 2018). The robust results report the lower profitability of banks having politically connected directors (PCDs) sitting on their board than those who do not. This affirms the political influence on the banking industry due to the existence of political connections. In addition, the results also report the lower profitability, during government transitions, of banks having PCDs sitting on their board. This suggests that the PCDs sitting on the board adversely affect sustainable profitability during government transitions. It also indicates the negative political influence on banking decisions, specifically during the period of government transitions, because of the sustained political connections of the directors (Hung et al. 2017). The results related to the political connections of the directors also support the arguments of Yao et al. (2018), stating that the Pakistani banking industry suffers from political connections. The results also affirm an inverted U-shaped relationship between board size and bank profitability in Pakistan. This supports the findings of Yeung (2018), Yulia (2016), Grove et al. (2011) , and de Andres and Vallelado (2008); a board size up to 8–9 members is suggested to improve the profitability, after which a further increase in board members reduces profitability. Furthermore, the results report that, on the one hand, the profitability of Pakistani banks increases due to the presence of non-executive directors and independent directors, as well as the higher compensation paid to the directors. On the other hand, the profitability weakens due to the frequent board meetings and the audit committee independence. Moreover, the study finds a lower profitability of banks having foreign directors sitting on their boards than those who do not, indicating the negative effect of the presence of foreign directors. The rest of the paper is structured as follows: Section 2reviews the Pakistani banking system. Section 3presents the hypothesis development based on the existing literature. Section 4discusses 2 In the past, some researchers studied the periods of election years (Jackowicz et al. 2013;Liang et al. 2013; Micco et al. 2007 ), but our study considered electoral cycles referred to as government transitions, consistent with Haris et al. (2019b), Yao et al. (2018) ,Cole (2009), and Baum et al. (2010). Government elections took place in the country during 2008 and 2013; therefore, a value of 1 was assigned to 2008–2009 (transition period) and 2013–2014 (transition period); otherwise, a value of 0 was used (Yao et al. 2018). Int. J. Financial Stud. 2019,7, 62 5 of 37 the data and the methodology used in this study. Section 5provides the main findings of the study. Section 6concludes and discusses the paper. 2. Review of Pakistani Banking System There is always a requirement for a healthy, sound, and stable financial system to ensure a functioning economy. However, the Pakistani financial sector (PFS) faces several regimes and daunting challenges mainly because of an unstable political system. Since its independence in 1947 until today, Pakistan’s economy experienced almost 25 governments, including elected, interim, and military governments. If we exclude the military and interim governments, the average life span of a politically elected government is around 2.5 years. Therefore, the PFS suffered due to the different economic policies and higher political interference as a response of authoritarian and democratic regimes. At the time of independence, Pakistan inherited a financial system dominated by foreign banks (Haris et al. 2019b) . However, the State Bank of Pakistan (SBP), i.e., the Central Bank, was incorporated by the political government in July 1948 to establish a financial system and to regulate the monetary and credit system of the country. As a result, five banks operated with 97 branches until 1951 (Haris et al. 2019a) . However, in February 1953, the first martial law was imposed, and the first military government assumed full control of the country in 1958. Consequently, during this period, reforms were implemented vigorously with impressive results in the financial system and economic growth until 1970 (Yao et al. 2019). Later, in 1971, the military government transited into a civil government, and the PFS suffered a setback in 1974, when the elected government introduced another set of reforms to nationalize all banks (Haris et al. 2019a). In the aftermath of the nationalization, the supervisory role of the SBP was distorted due to the incorporation of the Pakistan Banking Council (PBC). The purpose of the PBC was to monitor and inspect the banks and to oversee the objectives of nationalization. However, a second military government again assumed command of the state in 1977, and, once again, the democratic regime transited into an authoritarian one (Yao et al. 2019). Because of reforms, realizing the adverse effect of nationalization, in 1980, licenses were issued to private banks allowing them to operate side by side (Haris et al. 2019a). However, after the end of the authoritarian regime, as part of the federal government policy of privatization and deregulation of the financial sector, the PFS was opened to the private sector in 1989. The broader macroeconomic structural adjustment programs initiated financial sector deregulation and liberalization during the 1990s. The SBP was awarded partial autonomy in 1994 and declared a completely autonomous body in May 1997, when the PBC was dissolved during the same year. Since the 1980s, there were a series of reforms initiated to counter the adverse effects of nationalization and to streamline the financial sector on modern lines with the intention of making it conducive to economic growth and stability. A number of studies were conducted to study the aftermath of these reforms, and most of them converged to the same conclusion that sector performance remains a question mark (Haris et al. 2019a). The lack of human and financial resources, in addition to political interference and political instability, hindered industry growth in the past. However, significant improvement was noted in recent years. The financial sector and stock market development are likely to continue, given the growth of Pakistan’s gross domestic product (GDP), which hit an average growth of 5.2% over the past decade. The tremendous performance of the Pakistani financial sector contributed to establishing Pakistan as one of the most renowned stock markets around the globe (Yao et al. 2018). The contribution of the financial sector to the GDP of Pakistan was raised to 3.39% by the end of 2018 from 3% (2011), and the sector itself achieved a growth of 6.13% in 2018, which was negative ( − 4.22%) by the end of 2011 (Yao et al. 2019). Despite this, Figure 1reports a lower profitability (ROA, ROE, NIM, and PM) of Pakistani banks during the periods of government transition (2008 and 2013), which shows the negative impact of government transitions on Pakistani bank profitability due to political interference (Yao et al. 2018). Therefore, this study intends to measure the political influence on the PFS by empirically examining the impact of political connections on the profitability of banks in Pakistan. Int. J. Financial Stud. 2019,7, 62 6 of 37 Int. J. Financial Stud. 2019, 7, 62 6 of 38 Figure 1. Trend in the profitability of Pakistani banks (2007–2016). PB, private banks; GB, government banks; TB, total banks. 3. Related Literature and Hypothesis Development Considering the purpose of our study, which was to evaluate the impact of corporate governance characteristics and political connections of directors on the profitability of Pakistani banks, this section extends the development of hypotheses based on the related literature. Politically Connected Directors: In a politicized economy, banks tend to lend more money at a lower cost and offer favorable terms to firms linked to politicians. These preferential bank loans fund the electoral campaigns of politicians and suppress the management’s ability to achieve sustainable business growth. Politically connected directors (PCDs) influence board decisions by allowing more political interference to pursue political objectives at the expense of banks, which adversely affects the performance (Liang et al. 2013). The political connectedness was first found in the influential studies conducted by Tullock (1967), Stigler (1971), and Krueger (1974). Later, it was extensively studied in the body of literature related to the performance of non-financial firms (Boubakri et al. 2008; Domadenik et al. 2016; Faccio 2006; Fan et al. 2007; Fonseka et al. 2015; Hasan et al. 2017; Khwaja and Mian 2005; Kroszner and Stratmann 1998; Muttakin et al. 2015; Wu et al. 2012; Xu et al. 2013; Yeh et al. 2013) and financial institutions (Berger et al. 2009; Charumilind et al. 2006; Chen and Liu 2013; Dinç 2005; Firth et al. 2009; Hung et al. 2017; Jackowicz et al. 2013; Khwaja and Mian 2005; Liang et al. 2013; Micco et al. 2007). Baum et al. (2010) provided evidence and argued that the government forces politically connected banks (especially state-owned banks) to extend funding to government projects and political cronies at lower interest rates, resulting in the misallocation of resources and lower profitability. They reported that government banks underperform during election years. Fan et al. (2007) argued that bank lending decisions are affected by the political connections of directors, which negatively affect bank performance. PCDs tend to lend more to those firms linked with politicians at lower interest rates with easy collateral terms to support the electoral campaigns of associated politicians (so-called preferential banks loans), which suppress the management’s ability to achieve a desired profitability. Previously, Micco et al. (2007) also supported the political view that, during the period of government elections, the higher amount of lending by state-owned banks (Dinç 2005) relates to lower interest charges, which reduces the profitability of banks. The resource-based theory postulates that firms may have higher competitive advantages because of accessing many benefits due to their political connections (Cheema et al. 2016). Thus, PCDs sitting on bank boards may have political goals to achieve, which lead the bank to perform poorly. The grabbing hand theory argues that directors appointed by politicians pursue political objectives rather than social welfare. Figure 1. Trend in the profitability of Pakistani banks (2007–2016). PB, private banks; GB, government banks; TB, total banks. 3. Related Literature and Hypothesis Development Considering the purpose of our study, which was to evaluate the impact of corporate governance characteristics and political connections of directors on the profitability of Pakistani banks, this section extends the development of hypotheses based on the related literature. Politically Connected Directors: In a politicized economy, banks tend to lend more money at a lower cost and offer favorable terms to firms linked to politicians. These preferential bank loans fund the electoral campaigns of politicians and suppress the management’s ability to achieve sustainable business growth. Politically connected directors (PCDs) influence board decisions by allowing more political interference to pursue political objectives at the expense of banks, which adversely affects the performance (Liang et al. 2013). The political connectedness was first found in the influential studies conducted by Tullock (1967), Stigler (1971), and Krueger (1974). Later, it was extensively studied in the body of literature related to the performance of non-financial firms ( Boubakri et al. 2008 ; Domadenik et al. 2016 ;Faccio 2006;Fan et al. 2007; Fonseka et al. 2015 ; Hasan et al. 2017 ; Khwaja and Mian 2005 ;Kroszner and Stratmann 1998;Muttakin et al. 2015; Wu et al. 2012 ; Xu et al. 2013 ;Yeh et al. 2013) and financial institutions (Berger et al. 2009;Charumilind et al. 2006;Chen and Liu 2013;Dinç 2005;Firth et al. 2009;Hung et al. 2017;Jackowicz et al. 2013; Khwaja and Mian 2005;Liang et al. 2013;Micco et al. 2007). Baum et al. (2010) provided evidence and argued that the government forces politically connected banks (especially state-owned banks) to extend funding to government projects and political cronies at lower interest rates, resulting in the misallocation of resources and lower profitability. They reported that government banks underperform during election years. Fan et al. (2007) argued that bank lending decisions are affected by the political connections of directors, which negatively affect bank performance. PCDs tend to lend more to those firms linked with politicians at lower interest rates with easy collateral terms to support the electoral campaigns of associated politicians (so-called preferential banks loans), which suppress the management’s ability to achieve a desired profitability. Previously, Micco et al. (2007) also supported the political view that, during the period of government elections, the higher amount of lending by state-owned banks (Dinç 2005) relates to lower interest charges, which reduces the profitability of banks. The resource-based theory postulates that firms may have higher competitive advantages because of accessing many benefits due to their political connections (Cheema et al. 2016). Thus, PCDs Int. J. Financial Stud. 2019,7, 62 7 of 37 sitting on bank boards may have political goals to achieve, which lead the bank to perform poorly. The grabbing hand theory argues that directors appointed by politicians pursue political objectives rather than social welfare. Similarly, the network theory states that financial resources are directed to fund unviable government projects with the help of networks between the government and institutions. This theory can be supported in the context of Pakistan. In Pakistan, the connections between bank directors and ruling parties were disclosed as a result of a criminal investigation with regard to money laundering and fake bank accounts 3 . Thus, the political connections of the bank directors damaged the reputation of banks among stakeholders and investors, which affected their performance negatively. Another main theory of corporate governance also explains the negative effect of political connections on bank performance via agency problems. Politically connected directors always seek to meet the needs of associated politicians (e.g., favorable loans, relaxation in loan repayments, and job provisions), which causes a conflict between the goals of shareholders and managers, thus increasing the agency cost and reducing performance. Moreover, Khwaja and Mian (2005) also specified, in the context of Pakistan, that, during elections, state-owned banks lend more to politically connected firms, which leads to a higher rate of default and, thus, deteriorates bank profitability. They further argued that politically connected firms access 40% more loans and have a 50% default rate, thereby leading the banks toward lower profitability. Additionally, government change affects the economy overall, because elections may influence the monetary instruments and outcomes through injecting money to support the needs of an expensive election campaign due to political manipulation. Many studies reported a lower profitability of financial institutions during election years because of the political connectedness of banks. Cole (2009) extended the evidence of political interference and found a higher injection of agricultural credit by state-owned banks during elections years. Jackowicz et al. (2013) stated that state-owned banks serve as a tool to fund political goals and found a lower profitability of banks in 11 central European countries during election years due to political connections. Chen and Liu (2013) also found a lower profitability of state-owned financial institutions than privately owned institutions during election years. Liang et al. (2013) found a negative relationship between the proportion of PCDs and the profitability of 52 Chinese banks. Other recent studies by Haris et al. (2019b) and Yao et al. (2018) also extended the evidence of political interference and found a lower profitability of 28 banks in Pakistan during periods of government transition. Furthermore, Haris et al. (2019a) also reported a lower profitability of nine Pakistani government banks during the period of government election (2013). We, thus, pose our first hypothesis. Hypothesis 1a (H1a). The profitability of Pakistani banks deteriorates due to the presence of politically connected directors on the board. Hypothesis 1b (H1b). Banks in Pakistan earn lower profitability during government transitions because of the presence of politically connected directors. 3 During the last decade, one former Prime Minister and one former President were sentenced to prison in cases of money laundering and fake bank accounts. The regulatory authorities also arrested the president of a provincial government-owned bank in relation to the fake bank accounts. Furthermore, the Supreme Court of Pakistan directed the Federal Investigation Agency to put the names of the heads of three Pakistani banks on the exit control list, as they were alleged to open fake bank accounts to launder money. Moreover, the appointment of a president of another state-owned bank was also challenged, as it was claimed that his appointment was based on nepotism and political interest, which was illegal. In addition, some private banks were also found guilty with regard to opening fake bank accounts to launder money. Information can be accessed from http://www.msn.com/en-xl/asia/pakistan/nab-arrests-sindh-bank-chief-in-fake-accounts-case/ar-AAEciNy, https://en.dailypakistan.com.pk/business/president-nbp-saeed-ahmeds-appointment-challenged/, and https://gulfnews. com/world/asia/pakistan/former-pakistan-president-asif-ali-zardari-arrested-in-fake-bank-accounts-case-1.64511834;https: //www.pakistantoday.com.pk/2018/07/08/sc-orders-to-place-heads-of-ubl-sindh-bank-summit-bank-on-ecl/. Int. J. Financial Stud. 2019,7, 62 8 of 37 Board Size: The board of directors (BODs) protects bank interests and provides strategic directions to monitor the achievement of the banking system’s strategic objectives. The duties and responsibilities of BODs are important aspects of corporate governance practices, which lead to achieving sustainable growth for banks (Yatim and Yusoff2014). The addition of many directors to the board brings more knowledge, expertise, and experience, which lead to a sustained competitive advantage, raising the performance of the banking industry (Barroso et al. 2011). However, in the literature, there is no single consensus with regard to the relationship between board size and the performance of banks. On the one hand, some studies suggested that an adequately sized board performs relatively better than a very small board. Large boards carry a wide range of expertise for decision-making, effectively monitoring management activities (Isaac 2017) and dealing with the complexity of the financial system ( Adams and Mehran 2003 ,2012;Yermack 1996), thereby raising bank performance. Some previous studies, for instance, Farag et al. (2017), Nawaz (2017), and Isaac (2017), found a positive relationship between board size and profitability. On the other hand, both Jensen (1993) and Lipton and Lorsch (1992) stated a certain limit for board size and suggested that a board size beyond 7–8 members functions ineffectively and, thus, deteriorates profitability. Previously, some studies also found a negative relationship between profitability and boards with a large number of members ( Ghosh 2006 ; Liang et al. 2013;Masulis et al. 2012;Mollah and Zaman 2015; Pathan et al. 2007 ; Tanna et al. 2011 ). In addition to the above positive and negative relationships, some studies found a nonlinear relationship (inverted U-shaped) between board size and profitability ( de Andres and Vallelado 2008 ; Grove et al. 2011 ;Yeung 2018;Yulia 2016). These studies suggested that the addition of too many directors decreases the performance due to problems of coordination and communication, thereby prolonging the process of decision-making, and leading to agency cost outweighing the benefits (Coles et al. 2008;Janis 1983;Yermack 1996). Therefore, in light of the above findings, we construct a second hypothesis. Hypothesis 2 (H2). There is an inverted U-shaped relationship between board size and the profitability of Pakistani banks. Board Composition: The OECD principles clearly regulate board composition and suggest that every company must ensure the presence of non-executive directors (NEDs) on the board in sufficient number (OECD 1999). A balanced board composed of non-executive and executive directors brings an objective view, aligns the interests of different parties, and acts to enhance shareholder wealth (Luo 2016). Previously, Jensen and Meckling (1976) suggested that the agency problem between shareholders and directors can be minimized through the addition of NEDs, which translates into sustained performance. Fama and Jensen (1983) also suggested that the presence of more NEDs on a bank’s board helps minimize conflicts of interest, which increases value for shareholders through disciplining and monitoring of the managers (Salim et al. 2016). de Andres and Vallelado (2008) also argued that bank performance can be increased through the advisory and monitoring role of NEDs. Although, there is a vast body of literature available on board composition, we could not find conclusive evidence regarding the impact of appointing more NEDs on profitability. Some studies found a positive impact (Cornett et al. 2009;Dahya et al. 2008;Liang et al. 2013;Pathan et al. 2007; Tanna et al. 2011) and some found a negative impact (Awadh and Azhar 2015;Erkens et al. 2012; Isaac 2017;Pathan and Faff2013) of NEDs on performance. de Andres and Vallelado (2008) found an inverted U-shaped impact indicating both a positive and negative relationship between a higher ratio of NEDs and the profitability of 69 banks in six countries. In addition to that, some studies did not find any association between appointing NEDs and bank performance ( Manas and Palanisamy 2017 ; Nawaz 2017;Salim et al. 2016). However, considering the above findings, our third hypothesis is as follows: Hypothesis 3 (H3). There could be a significant association between board composition and the profitability of banks in Pakistan. Int. J. Financial Stud. 2019,7, 62 15 of 37 errors can be downward biased in the case of small samples when using an efficient two-step GMM. Since we did not have a large sample, to avoid any potential bias in the estimation of asymptotic standard errors, we applied Windmeijer (2005) corrections to the standard errors that produced robust and corrected inference, consistent with Haris et al. (2019b), Yao et al. (2019,2018). Following Haris et al. (2019b), Yao et al. (2019,2018), since the GMM allows the use of instruments, the validity of these instruments is crucial for the consistency of the GMM. The GMM calculates Hansen-J statistics for over-identifying restrictions under the null hypothesis of joint validity of the instruments. It indicates that the residuals and instruments are not correlated. Furthermore, for the validity of instrument subsets, GMM also calculates the difference-in-Hansen test (also called C-statistic) under the null hypothesis of exogeneity of instrument subsets (Roodman 2009). The problems of Arellano and Bond (1991) with regard to serial correlations, i.e., first-order autocorrelation (AR-1) and second-order autocorrelation (AR-2), are also addressed by GMM under the null hypothesis of no serial correlations. However, the absence of AR-2 indicates the validity of GMM even in the presence of AR-1. Furthermore, our study applied “orthogonal deviation” because, in unbalanced panel data, it subtracts the average of future available observations of a variable in the transformed data and reduces the gap, while the use of first-difference transformations magnifies the gap (Arellano and Bover 1995). 4.4. Econometric Specification Considering the time persistence of profitability, following past studies (for instance, Haris et al. (2019b ), Yao et al. (2018), Farag et al. (2017), Saona (2016), Tan (2016), and Trujillo-Ponce (2013) ), we added a one-year lag of each profitability indicator on the left side as an independent variable, making our model dynamic. Previously, some studies concluded that bank-specific, industry-specific, and country-specific variables have a strong influence on bank profitability (see, for instance, Yao et al. (2018), Zhang et al. (2018), Haris et al. (2019a), Shahab et al. (2017) ,Tan (2016), Trujillo-Ponce (2013), and Athanasoglou et al. (2008)). Therefore, in order to get more consistent and robust results, we controlled the impact of bank-specific, industry-specific, and country-specific variables, taken from Haris et al. (2019b) and Yao et al. (2018) . Furthermore, Dinç (2005) and Micco et al. (2007) also suggested that government transitions, especially during election periods, influence bank performance. A recent study by Yao et al. (2018) found a lower profitability of the Pakistani banking industry during government transitions; therefore, we also controlled the impact of government transitions in order to offer robust results. To analyze the impact of political connections and corporate governance characteristics on the profitability of banks in Pakistan, the first dynamic model of our study is given below. Pit =α0+δPit−1+βiPCDsit + J P j=1 βjCGj it + K P k=1 βkBSVk it +βlISVt+βmCSVt +βnGOVt+ϕoTDt+vit +µit, (1) where irepresents each bank, and trepresents the time considered as years; Pit indicates the profitability of ibank at time t, which is expressed as return on assets (ROA), return on equity (ROE), net interest margin (NIM), and profit margin (PM); δPit−1 is the one-year lag of each profitability indicator to deal with time persistence, and δ refers to the adjustment speed; PCDsit refers to politically connected directors; CGj it indicates the corporate governance variables expressed as board size, board composition, board independence, board meetings, directors compensation, board ownership, audit committee meetings, and audit committee independence; BSVk it controls the impact of bank-specific variables expressed as bank size, capitalization, and credit quality; ISVt controls the impact of industry-specific variables expressed as industry concentration; CSVt controls the impact of country-specific variables expressed as the annual growth rate of gross domestic product of the country; GOVt is a dummy variable which controls the impact of government transitions (for details, see Table 1); α is a constant, Int. J. Financial Stud. 2019,7, 62 16 of 37 and β is a coefficient; TDt represents the time dummies (year effect), vit is the unobserved bank individual effect, and µit is the residual. We further interacted politically connected directors (PCDs) with each explanatory indicator (except for ISV and CSV) and checked the impact on profitability. For that, we applied the following dynamic panel model: Pit =α0+δPit−1+ J P j=1 βjCGj it ×PCDsit + K P k=1 βkBSVk it ×PCDsit +βlISVt+βmCSVt +βnGOVt×PCDsit +ϕoTDt+vit +µit. (2) 5. Findings Before using the data, we applied some pre-estimation tests to ensure the validity of our unbalanced dynamic panel data. For that, firstly, a Fisher-type root test (augmented Dickey–Fuller (ADF)) was performed to check the stationarity of the data. The ADF unit root results are presented in Table 2. The significant p-values of each variable rejected the presence of a unit root, making the data stationary. Secondly, a variance inflation factor (VIF) test was performed to address the multicollinearity problem among all explanatory variables. The VIF values of each variable along with mean VIF (1.87) are presented in Table 2, rejecting the existence of multicollinearity among variables at the cut-offvalue of 10 (Netter et al. 1989). Table 2. Unit root and multicollinearity results. Coef p-Value VIF Coef p-Value VIF Profitability Indicators Control ROA 206.263 0.000 BSIZE 135.865 0.000 2.60 ROE 169.514 0.000 SOLV 151.657 0.000 1.35 NIM 120.894 0.000 RISK 129.823 0.000 1.37 PM 153.756 0.000 IC5 134.501 0.000 1.16 Corporate Governance GDPR 108.527 0.000 1.25 PCDs 212.040 0.000 1.59 GOV 187.168 0.000 1.05 BOSIZE 143.097 0.000 1.40 Mean VIF 1.87 BCOMP 134.510 0.000 2.55 BINDP 126.862 0.000 3.33 BOWN 115.533 0.000 1.80 BMEETs 174.405 0.000 1.43 DCOMP 226.546 0.000 2.29 AUDMEETs 198.334 0.000 1.79 AUDIND 142.853 0.000 3.10 Note: We applied the augmented Dickey–Fuller (ADF) test to address the unit root and the variance inflation factor (VIF) to address the multicollinearity problem. Coef—coefficient. We also performed correlation analysis, as presented in Table 3. The correlation matrix shows the relationship among independent variables and also addresses the problem of multicollinearity; however, a correlation coefficient <0.8 rejects the presence of multicollinearity (Kennedy 2008). Int. J. Financial Stud. 2019,7, 62 17 of 37 Table 3. Correlation matrix. PCDs BOSIZE BCOMP BINDP BOWN BMEETs DCOMP AUDMEETs AUDIND BSIZE SOLV RISK IC5GDPR GOV PCDs 1.000 BOSIZE −0.191 1.000 BCOMP 0.079 0.084 1.000 BINDP 0.079 −0.202 −0.638 1.000 BOWN −0.495 0.076 0.119 −0.187 1.000 BMEETs 0.368 −0.166 −0.085 0.292 −0.338 1.000 DCOMP −0.248 0.241 −0.223 0.143 0.342 −0.020 1.000 AUDMEETs 0.267 −0.099 0.053 0.375 −0.247 0.353 0.072 1.000 AUDIND −0.035 −0.138 −0.679 0.725 −0.144 0.228 0.298 0.198 1.000 BSIZE −0.057 0.357 −0.004 0.087 0.007 0.139 0.595 0.346 0.169 1.000 SOLV 0.055 −0.077 −0.070 0.210 0.001 −0.024 −0.255 0.004 −0.018 −0.341 1.000 RISK 0.185 −0.351 −0.019 0.022 −0.079 −0.021 −0.202 −0.030 0.075 −0.358 −0.039 1.000 IC5−0.001 0.013 0.187 −0.168 0.028 −0.054 −0.220 −0.074 −0.275 −0.174 0.066 −0.070 1.000 GDPR 0.007 −0.013 −0.230 0.210 −0.122 −0.012 0.196 0.058 0.347 0.200 −0.052 0.077 −0.219 1.000 GOV 0.045 −0.047 −0.014 0.012 0.019 −0.045 −0.063 0.019 −0.070 −0.076 0.071 −0.003 0.147 −0.121 1.000 Int. J. Financial Stud. 2019,7, 62 18 of 37 5.1. Descriptive Statistics The results of descriptive statistics are presented in Table 4, showing a total of 251 bank–year observations. Some variables had lower observations due to missing values; however, out of a total of 4769 values of 19 variables (251 × 19), our data reported only 60 missing values for six variables (1.26%). Therefore, orthogonal deviation was used for the unbalanced dynamic panel data to generate consistent results (Arellano and Bover 1995). Table 4shows that the average ROA of banks in Pakistan was 0.5%, the average ROE was 4.8%, the average NIM was 4.3%, and the average PM was 0.9%. A mean value of 0.378 PCDs indicates that, on average, 38% banks in Pakistan had PCDs represented on their boards. The value ranged from 0 to 1 as it was a dummy variable indicating the presence (1) or absence (0) of a political director on the board. Turning to the corporate governance variables, Table 4shows that the average board size of Pakistani banks comprised approximately 8–9 (average 8.45) members, which is almost equivalent to the average board size of Islamic banks (8.88) of 13 countries including 11 Asian countries (Farag et al. 2017) and less than the average board size (10.97) of United States (US) commercial banks (Yulia 2016). The board size of banks in Pakistan ranged from four to 13 members, where SME bank limited (SMEBL) had the smallest board size at the end of 2016 and MCB bank limited (MCBL) had the largest board size. The 0.586 mean value of board composition (BCOMP) indicates that boards of Pakistani banks constituted on average 58.6% non-executive directors, which shows that bank boards were highly dominated by outside directors. The BCOMP ranged from 11.1% to 92.3% for different banks during different years. The board independence (BIND) ratio was 26.9%, which shows that banks in Pakistan, on average, had at least two independent directors on their board. The average BIND ratio was higher than the minimum required ratio of 25% by the SBP 10 . It ranged from 0% to 87.5%, where 0 indicates that banks had no representation of independent directors on their boards during some years. The average frequency of board meetings (BMEETs) was 6.466, which shows that the boards of Pakistani banks met, on average, six times a year, which is higher than the regulatory requirement of a minimum of four meetings a year 11 . This frequency of board meetings was less than the average of eight board meetings a year in 13 countries (Farag et al. 2017) and the average of 11.67 board meetings a year for US commercial banks (Yulia 2016), but higher than the average of 3.47 board meetings for non-banking financial institutions in Ghana (Isaac 2017). The frequency of BMEETs ranged from two to 17 meetings a year, where the boards of SME bank limited (SMEBL) and Zarai Tarakiati Bank limited (ZTBL) met only twice in 2009, and the board of the Bank of Punjab (BOP) met 17 times in 2013. The provincial government of the country owns the BOP; therefore, the 2013 government elections in the country could explain the frequent meetings to support the political campaigns of associated politicians. 10 As per the prudential regulations by the SBP, every bank operating in Pakistan must constitute 25% independent directors (available at www.sbp.org.pk). 11 As per prudential regulations issued by the SECP and SBP, both the boards and audit committees of banks are directed to meet at least once every quarter (available at http://www.secp.org.gov.pk and http://www.sbp.org.pk). Int. J. Financial Stud. 2019,7, 62 19 of 37 Table 4. Descriptive statistics. Obs—observed; Min—minimum; Max—maximum. Obs. Mean SD Min Max Obs. Mean SD Min Max Profitability Indicators Control Variables ROA 251 0.005 0.019 −0.092 0.044 BSIZE 251 19.023 1.306 15.483 21.596 ROE 251 0.048 0.248 −2.030 0.334 CAP 251 0.111 0.079 0.002 0.762 NIM 251 0.043 0.019 −0.020 0.100 RISK 247 0.137 0.259 0.000 2.005 PM 251 0.009 0.025 −0.095 0.060 IC5251 0.540 0.012 0.525 0.562 Corporate Governance GDPR 251 3.709 1.335 1.607 5.741 PCDs 251 0.378 0.486 0 1 GOV 251 0.398 0.491 0 1 BOSIZE 242 8.446 1.662 4 13 BCOMP 236 0.586 0.214 0.111 0.923 BINDP 239 0.269 0.213 0.000 0.875 BOWN 251 0.434 0.497 0 1 BMEETs 236 6.466 2.264 2 17 DCOMP 247 10.807 0.832 8.045 12.840 AUDMEETs 250 5.156 2.855 3 28 AUDIND 251 0.681 0.467 0 1 Int. J. Financial Stud. 2019,7, 62 20 of 37 Turning to the audit committee meetings (AUDMEETs), on average, the frequency of AUDMEETs was 5.16, which is higher than the minimum regulatory requirement of four meetings a year. This frequency of AUDMEETs is less than the 7.88 average audit committee meetings of US banks (Yulia 2016), which shows the strict board control of US banks in the auditing role. The frequency of AUDMEETs ranged from three to 28 meetings a year, where ZTBL and BOP had the lowest frequency and the National Bank of Pakistan had the highest frequency of AUDMEETs in 2009, following the 2008 period of sub-prime crises and government elections in the country. Finally, a 0.434 mean value of board ownership (BOWN) indicates that almost 43% of banks in Pakistan had a representation of foreign directors on their board. This value ranged from 0 to 1, as it was a dummy variable indicating the presence (1) or absence (0) of a foreign director on the board. 5.2. Empirical Findings Our study used a generalized method of moments (GMM) two-step system estimator to examine the relationship among corporate governance characteristics, political connections of directors, and bank profitability. Our results are robust to Windmeijer (2005) estimated asymptotic standard errors and also robust to the four profitability indicators and sets of control variables categorized into bank-specific, industry-specific, and country-specific variables. The results are reported in Tables 5–7. The results of the impact of political connections of directors on profitability are reported in Table 5. Table 6reports the interaction effect of political connections of directors and their impact on profitability during government transitions. Table 7reports the relationship between corporate governance and bank profitability expressed as return on assets (ROA), return on equity (ROE), net interest margin (NIM), and profit margin (PM). In Tables 5–7, the significant coefficients of lagged profitability prove the dynamic nature of the models. The 1% p-values of the F-statistics indicate the joint significance of our models. The results report the problem of AR-1 in some models, but the insignificant p-values of AR-2 in all estimated models indicate the absence of AR-2 and lead to acceptance of the null hypothesis of no serial correlation. The insignificant p-values of Hansen-J and C-statistics in all models also prove the validity of the instruments and the exogeneity of instrument subsets utilized to address the endogeneity. 5.2.1. Political Connections of Directors and Bank Profitability In Table 5, there are four models; each model examines one profitability indicator, i.e., ROA, ROE, NIM, and PM. We found significant negative coefficients of PCDs in each model, indicating the lower ROA, ROE, NIM, and PM of banks having PCDs sitting on their board than those who do not. This is consistent with the findings of Chen and Liu (2013), Jackowicz et al. (2013), and Liang et al. (2013). It indicates the significant negative impact of PCDs on the board, thus leading our hypothesis being accepted. This is because of the fact that Pakistani commercial banks with the presence of PCDs tend to lend more to those firms linked with politicians, resulting in lower interest rates and leveraging in collateral to support their electoral campaigns (so-called preferential banks loans), which reduces their profitability (Dinç 2005;Micco et al. 2007). We argued that the loan quality of politically connected banks in Pakistan is lower because of sustained political connections, resulting in lower profitability. Moreover, the performance of politically connected banks in Pakistan is also affected by conflicts of interest between PCDs and non-political directors and even among PCDs associated with different political parties. PCDs sitting on the boards of Pakistani commercial banks are more likely to pursue political interests to gain political advantages. Furthermore, our findings are also supported by the view that a bank’s board having politically connected directors may act in favor of politicians instead of maximizing shareholder value, thus leading to a deterioration in the performance of Pakistani banks due to policy loans injected for political purposes (Berger et al. 2009;Hung et al. 2017). Int. J. Financial Stud. 2019,7, 62 21 of 37 Table 5. Politically connected directors (PCDs) and bank profitability. ROA ROE NIM PM DEPt−10.684 ** (0.303) 0.405 *** (0.108) 0.420 ** (0.202) 0.243 ** (0.114) Corporate Governance PCDs −0.007 ** (0.004) −0.075 * (0.041) −0.009 ** (0.004) −0.010 * (0.005) BOSIZE −0.017 (0.030) −0.201 (0.204) −0.007 (0.032) −0.024 (0.027) BCOMP 0.035 (0.033) 0.779 ** (0.360) 0.047 ** (0.020) 0.069 * (0.041) BINDP −0.004 (0.027) 0.232 (0.304) 0.009 (0.026) 0.019 (0.028) BOWN −0.030 * (0.017) −0.425 ** (0.196) −0.034 ** (0.015) −0.048 ** (0.023) BMEETs −0.010 * (0.006) −0.148 * (0.081) −0.009 (0.006) −0.027 *** (0.007) DCOMP 0.010 (0.007) 0.160 ** (0.066) 0.009 ** (0.004) 0.009 ** (0.005) AUDMEETs −0.000 (0.011) −0.302 * (0.172) −0.013 (0.019) −0.019 (0.020) AUDIND 0.013 (0.014) 0.209 (0.258) 0.006 (0.016) 0.014 (0.024) Control Variables BSIZE −0.000 (0.004) 0.018 (0.020) 0.002 (0.002) 0.009 *** (0.003) SOLV 0.027 (0.025) 0.387 (0.264) 0.082 ** (0.040) 0.070 ** (0.031) RISK −0.010 (0.012) −0.256 *** (0.084) 0.004 (0.008) −0.020 * (0.010) IC5 −0.330 (0.236) −1.055 (1.176) −0.332 (0.276) 0.238 (0.319) GDPR −0.005 *** (0.001) −0.040 ** (0.018) −0.006 * (0.003) −0.001 (0.003) GOV 0.005 (0.008) 0.029 (0.043) 0.011 (0.010) 0.000 (0.009) Constant 0.126 (0.130) −0.635 (0.919) 0.102 (0.246) −0.283 * (0.167) Obs. 210 210 210 210 Banks 26 26 26 26 Instrument 26 26 26 25 F-statistics 24.43 *** 141.17 *** 26.89 *** 140.73 *** AR-1 (p-value) −1.37 (0.171) −2.83 (0.005) −2.01 (0.045) −2.36 (0.018) AR-2 (p-value) 1.05 (0.296) −0.19 (0.851) −0.13 (0.893) 0.60 (0.546) Hansen-J (p-value) 9.60 (0.384) 3.49 (0.942) 7.38 (0.598) 3.37 (0.909) C-statistics (p-value) 6.13 (0.105) 0.98 (0.805) 1.12 (0.773) 1.34 (0.719) Notes: This study applied a generalized method of moments (GMM) two-step system estimator with orthogonal deviation. The Windmeijer (2005) robust standard errors are in parentheses. ***, **, and * represent the significance level at 1%, 5%, and 10%, respectively. Following Farag et al. (2017) and de Andres and Vallelado (2008), BOSIZE and BCOMP were treated as endogenous variables and implemented with a lag level (3–5). The significant p-values of F-statistics indicate the joint significance of the model. AR-1 denotes the results of the Arellano–Bond first-order autocorrelation, while AR-2 denotes the second-order autocorrelation. The insignificant p-values of AR-2 led to acceptance of the null hypothesis of no autocorrelation. The insignificant p-values of Hansen-J statistics address the over-identifying restrictions under the null hypothesis of joint validity of exogenous instruments. The insignificant p-values of the difference-in-Hansen test (C-statistics) led to acceptance of the null hypothesis of exogeneity of the full instrument subset. Int. J. Financial Stud. 2019,7, 62 22 of 37 Table 6. Interaction effect of politically connected directors (PCDs). ROA ROE NIM PM DEPt−10.887 *** (0.132) 0.622 *** (0.091) 0.471 *** (0.161) 0.957 *** (0.143) Corporate Governance BOSIZE ×PCDs −0.097 *** (0.030) −1.281 *** (0.485) −0.058 *** (0.020) −0.175 *** (0.064) BCOMP ×PCDs −0.015 (0.031) 0.101 (0.438) 0.058 * (0.031) 0.005 (0.042) BINDP ×PCDs −0.001 (0.015) 0.449 (0.284) 0.045 * (0.027) 0.030 (0.039) BOWN ×PCDs −0.012 (0.011) 0.047 (0.376) 0.021 (0.027) −0.025 (0.020) BMEETs ×PCDs −0.010 * (0.005) −0.035 (0.148) −0.002 (0.008) −0.010 (0.010) DCOMP ×PCDs 0.000 (0.004) −0.093 (0.088) −0.006 (0.006) −0.008 (0.010) AUDMEETs ×PCDs −0.004 (0.013) −0.327 * (0.185) −0.027 ** (0.013) −0.026 (0.041) AUDIND ×PCDs −0.015 (0.011) −0.339 * (0.176) −0.001 (0.016) −0.024 (0.013) Control Variables BSIZE ×PCDs 0.013 *** (0.005) 0.027 *** (0.062) 0.009 *** (0.003) 0.028 *** (0.008) SOLV ×PCDs 0.017 (0.018) −0.047 (0.258) 0.084 *** (0.028) 0.029 (0.041) RISK ×PCDs 0.001 (0.007) −0.151 * (0.84) −0.002 (0.005) 0.003 (0.014) IC5 −0.135 (0.110) −2.220 (0.854) −0.250 *** (0.064) −0.203 (0.219) GDPR −0.002 * (0.001) −0.003 (0.006) −0.002 *** (0.001) −0.003 (0.002) GOV ×PCDs −0.009 *** (0.003) −0.100 ** (0.048) −0.002 (0.004) −0.017 ** (0.007) Constant 0.079 (0.061) 1.351 (0.463) 0.164 *** (0.034) 0.120 (0.122) Obs. 211 211 211 211 Banks 26 26 26 26 Instrument 26 26 26 26 F-statistics 170.67 *** 184.66 *** 135.76 *** 369.21 *** AR-1 (p-value) −1.59 (0.112) −1.82 (0.069) −2.51 (0.012) −1.57 (0.117) AR-2 (p-value) 0.22 (0.825) −1.57 (0.116) −0.49 (0.625) −0.63 (0.527) Hansen-J (p-value) 4.42 (0.926) 3.11 (0.979) 4.93 (0.896) 3.82 (0.955) C-statistics (p-value) 1.27 (0.736) 0.18 (0.980) 1.03 (0.793) 2.17 (0.538) Notes: The study applied a GMM two-step system estimator with orthogonal deviation. The Windmeijer (2005) robust standard errors are in parentheses. ***, **, and * represent the significance level at 1%, 5%, and 10%, respectively. Following Farag et al. (2017) and de Andres and Vallelado (2008), BOSIZE and BCOMP were treated as endogenous variables and implemented with a lag level (3–5). The significant p-values of F-statistics indicate the joint significance of the model. AR-1 denotes the results of the Arellano–Bond first-order autocorrelation, while AR-2 denotes the second-order autocorrelation. The insignificant p-values of AR-2 led to acceptance of the null hypothesis of no autocorrelation. The insignificant p-values of Hansen-J statistics address the over-identifying restrictions under the null hypothesis of joint validity of exogenous instruments. The insignificant p-values of the difference-in-Hansen test (C-statistics) led to acceptance of the null hypothesis of exogeneity of the full instrument subset. Int. J. Financial Stud. 2019,7, 62 23 of 37 Table 7. Corporate governance characteristics and banks profitability. ROA ROE NIM PM 12121212 DEPt−10.464 *** (0.153) 0.958 *** (0.312) 0.332 *** (0.086) 0.550 *** (0.137) 0.724 *** (0.102) 0.701 *** (0.158) 0.368 ** (0.141) 0.791 *** (0.175) Corporate Governance BOSIZE 0.354 *** (0.099) 0.907 * (0.456) 6.663 *** (1.944) 20.903 *** (7.094) 0.329 *** (0.057) 0.275 *** (0.081) 0.453 ** (0.192) 0.617 *** (0.208) BOSIZE-SQ −0.080 *** (0.025) −0.232 ** (0.112) −1.511 *** (0.480) −5.232 *** (1.759) −0.082 *** (0.014) −0.073 *** (0.020) −0.099 ** (0.047) −0.166 *** (0.055) BCOMP −0.005 (0.020) 0.009 (0.016) 0.586 ** (0.229) 1.277 *** (0.456) −0.001 (0.013) 0.014 (0.016) 0.069 ** (0.033) 0.002 (0.019) BINDP −0.001 (0.011) −0.009 (0.013) 0.195 (0.346) −0.207 (0.193) 0.027 ** (0.011) 0.001 (0.012) 0.024 (0.023) 0.029 ** (0.014) BOWN −0.019 *** (0.007) −0.011 * (0.006) −0.165 ** (0.079) −0.465 * (0.260) −0.006 *** (0.002) −0.001 (0.004) −0.021 * (0.011) −0.022 ** (0.011) BMEETs −0.012 *** (0.003) −0.028 *** (0.009) −0.169 ** (0.069) −0.352 *** (0.123) −0.005 ** (0.003) 0.011 (0.014) −0.022 ** (0.008) −0.022 ** (0.010) DCOMP 0.007 *** (0.002) 0.010 * (0.006) 0.087 *** (0.023) 0.001 (0.145) 0.007 *** (0.003) 0.004 ** (0.002) 0.008 *** (0.003) −0.007 (0.013) AUDMEETs 0.005 (0.004) 0.007 (0.015) 0.012 (0.071) −0.223 * (0.132) −0.002 (0.005) −0.008 (0.007) 0.009 (0.015) −0.040 ** (0.015) AUDIND −0.009 (0.007) −0.001 (0.005) 0.074 (0.116) 0.452 (0.243) −0.023 *** (0.003) 0.002 (0.006) 0.008 (0.007) −0.017 *** (0.006) Control Variables BSIZE −0.002 (0.004) 0.124 ** (0.059) 0.001 (0.002) 0.014 ** (0.007) SOLV −0.004 (0.019) 0.837 (0.746) 0.054 *** (0.016) 0.054 * (0.030) RISK 0.020 (0.023) 0.181 (0.239) −0.002 (0.014) 0.009 (0.014) IC5 −0.288 ** (0.121) −3.680 ** (1.634) −0.312 * (0.176) 0.308 (0.251) GDPR −0.002 (0.001) −0.027 (0.020) −0.003 ** (0.001) 0.001 (0.002) GOV 0.004 (0.007) 0.037 (0.073) 0.002 (0.002) −0.013 *** (0.004) Constant −0.425 *** (0.102) −0.722 * (0.426) −8.262 ** (1.959) −20.856 ** (7.661) −0.369 *** (0.084) −0.142 (0.100) −0.613 *** (0.218) −0.813 *** (0.263) Int. J. Financial Stud. 2019,7, 62 24 of 37 Table 7. Cont. ROA ROE NIM PM 12121212 DEPt−10.464 *** (0.153) 0.958 *** (0.312) 0.332 *** (0.086) 0.550 *** (0.137) 0.724 *** (0.102) 0.701 *** (0.158) 0.368 ** (0.141) 0.791 *** (0.175) Obs. 210 210 210 210 210 210 211 210 Banks 26 26 26 26 26 26 26 26 Instrument 26 26 26 26 26 26 26 26 F-statistics 16.98 *** 29.91 *** 17.66 *** 152.28 *** 51.98 *** 59.66 *** 20.31 *** 195.45 *** AR-1 (p-value) −1.62 (0.105) −1.70 (0.089) −2.50 (0.012) −2.39 (0.017) −3.25 (0.001) −2.26 (0.024) −1.95 (0.051) −2.08 (0.037) AR-2 (p-value) 0.81 (0.420) 0.75 (0.452) −0.91 (0.363) −0.38 (0.707) −1.15 (0.251) 0.05 (0.961) −0.12 (0.906) 0.52 (0.605) Hansen-J (p-value) 7.81 (0.931) 3.33 (0.950) 8.85 (0.885) 2.81 (0.971) 12.66 (0.628) 4.55 (0.872) 14.58 (0.482) 4.64 (0.865) C-statistics (p-value) 0.26 (0.967) 1.26 (0.739) 1.53 (0.674) 0.85 (0.838) 4.21 (0.240) 0.56 (0.905) 0.98 (0.806) 0.02 (0.999) Notes: The study applied a GMM two-step system estimator with orthogonal deviation. The Windmeijer (2005) robust standard errors are in parentheses. ***, **, and * represent the significance level at 1%, 5%, and 10%, respectively. Following Farag et al. (2017) and de Andres and Vallelado (2008), BOSIZE and BCOMP were treated as endogenous variables and implemented with a lag level (3–5). The significant p-values of F-statistics indicate the joint significance of the model. AR-1 denotes the results of the Arellano–Bond first-order autocorrelation, while AR-2 denotes the second-order autocorrelation. The insignificant p-values of AR-2 led to acceptance of the null hypothesis of no autocorrelation. The insignificant p-values of Hansen-J statistics address the over-identifying restrictions under the null hypothesis of joint validity of exogenous instruments. The insignificant p-values of the difference-in-Hansen test (C-statistics) led to acceptance of the null hypothesis of exogeneity of the full instrument subset. Int. J. 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