1 Introduction

This paper provides new empirical evidence on how host–home differences in national governance affect foreign bank’s financial performance in Asian banking industry by addressing the role of bank competition. Foreign banks are generally recognized for prospective drivers of innovative techniques, management teams and know-how transmission from the host countries by encouraging a relative advantage on productivity (Chaffai, 2021). However, previous studies have confirmed that the distance in national institutions between home and host nations economically affect foreign banks’ financial performance in reaction to banking industry structure in a host country. Specifically, previous studies have indicated that foreign banks from home countries with cultural, economic and institutional distance to the host country experience challenges in accommodating to host macroeconomic conditions and exerting own competitive advantages in the local country (Cezar & Escobar, 2015; Dow & Karunaratna, 2006; Ghemawat, 2001; Martín Martín & Drogendijk, 2014). As Chen and Liao (2011) showed, banking market structure significantly affects foreign bank’s profits and implies that foreign banks could gauge their market power to compensate for cross-country differences and motivate them to perform better in the host country. Furthermore, Du et al. (2018) indicated that emerging countries with an institutional framework could be comparable to that of mature ones and the performance of foreign banks also reflects the level of economic development in the host country. Recently, Toh and Jia (2021) examined the impact of host–home nation differences in culture, economic performance and institutions on liquidity creation for domestic versus foreign banks in Malaysia and found that a bank’s market power should mitigate reverse influences from host–home country distance. Following this perspective, this paper empirically investigates whether host–home country differences in country governance present the critical influence of bank market power on profitability of foreign banks in comparison to domestic banks.

The presence of foreign banks significantly facilitates the banking sector in host country (Bruno & Hauswald, 2014; Buch & Goldberg, 2020; Jeon et al., 2011; Yin et al., 2020). According to Claessens et al. (2001), foreign banks could improve the quality of banking services in host countries, force domestic banks to follow them through the competition, and enhance the banking services infrastructure through stringent supervision and stronger legal requirements, as well as facilitate the country’s funding access to international banking markets. However, because foreign banks are heavily controlled by their home parent banks, they show less risk, particularly during the financial crisis, and are more likely to be subject to political pressures in host nations to make loans. Therefore, all these consequences should encourage the productiveness of banks and foster the opposition of the monetary markets in the host countries. However, the related literature asserts some different contrary views that foreign banks are viewed as a source of instability as a result from the possibility to withdraw from domestic markets more easily, in particular for higher instability due to vital political or financial crisis (Claessens & Van Horen, 2013; Chen et al., 2017). In addition, foreign banks generally acted as “follow-the-customer” for their clients in host customers, leaving the domestic banks to serve the others i.e., more riskier ones. These arguments influence the effectiveness of the banking sector as a whole. Thus, based on the dominant effects, foreign banks could also operate better or worse in contrast to home banks (Claessens & Van Horen, 2013).

Regarding the bank profitability, empirical evidence shows that, in emerging markets, foreign banks are more profitable and more efficient than domestic banks (Bonin et al., 2005; Claessens et al., 2001; Demirgüç-Kunt & Huizinga, 2000). In contrast, other studies have shown that foreign banks are disadvantaged when compared to domestic banks in developed countries (Berger et al., 2000; Claessens et al., 2001; Peek et al., 1999; Sathye, 2001). Focusing on 129 countries over 1995–2013, Yin (2019) find that foreign banks show higher risk in host countries. However, previous empirical evidence of foreign bank performance has been mainly concentrated on examples of EU or US banks operating abroad. Studies of foreign banks operating in other countries include those by Williams (1996, 1998a, 1998b, 2003) for Australia; Minh To and Tripe (2002) for New Zealand; Ursacki and Vertinsky (1992) for Japan and Korea (Jeon & Miller, 2005); Gropp (2002) demonstrated that higher bank concentrations may have resulted in less competitive pricing by banks located in the EU during 1993–1999. In addition, Bikker and Haaf (2002) applied the Panzar–Rosse model to measure banking competition in 23 countries, providing support for the conventional view that bank concentration impairs competitiveness. Similarly, Beck et al. (2003) concluded that highly concentrated banking systems were less likely to suffer from crises. As shown by Maudos and Fernández de Guevara (2004), there was a statistically significant and positive correlation between bank concentration and bank interest margins during 1993–2000 for the European banking markets. Furthermore, Maudos and Fernández de Guevara (2004) used the Lerner index as a proxy of the degree of competition in banking markets. In a recent study by Athanasoglou et al. (2008), a GMM (Generalized Method of Moments) technique was applied to a panel of Greek banks during 1985–2001, indicating that bank concentration negatively affected bank profitability, but this effect was relatively insignificant. Based on the data for 148 countries over 1987–2015, Yin (2021) recently explores the influence of foreign bank entry on bank competition in the host countries, and indicates that although on average an increase in the number of foreign banks is related to more competition in the host country, competition raises in developed but declines in developing countries.

This paper contributes to the previous literature in several aspects. Most importantly, we address two banking literature viewpoints: (1) the impact of country governance on bank performance and (2) the heterogeneous impact of bank market power and host-home difference in national governance on the profitability for domestic banks and foreign banks. Our findings disclosure the comparative advantages of domestic banks versus foreign banks in the host country of Asia. We further expand the global banking literature by shedding light on the role of host-home country distance in national governance in the impact of bank competition on the profitability for foreign banks. The results draw attention to the importance of maintaining some degree of market power for foreign banks to maintain in the host country. In addition, while the literature on foreign banks’ performance is extensive in the context of profitability and efficiency performance in host countries, very little is known for regarding the impact of host-home country distance in national governance on their financial performance, especially in Asia countries. By using hierarchical linear modeling, we are able to simultaneously model company-specific and bank-specific variables in a large bank- and country-level dataset. However, the estimated hierarchical specifications are not only allowed for the clustered heterogeneity, but also modeled the potential cross-sectional dependence among banks, particularly for country-level data. The clustered standard errors derived from the estimated hierarchical specifications are close to the Driscoll and Kraay (1998) by controlling for cross-section dependency in non-hierarchical settings.

The remaining papers proceed as follows. Section 2 presents the data source and econometric models are discussed. The construction of the empirical specification shows the details of the estimations. The main results from the estimations are then discussed in Sect. 3, and followed by a summary of the empirical findings and conclusion in Sect. 4.

2 Data and Methodology

2.1 Data Sources

Different data sources are collected and used for our empirical analysis at 375 foreign banks from 47 Asian countries between 2004 and 2019. The bank-level data on the financial statement report is mainly collected from the database of BankFocus produced by the Bureau Van Dijk Corporation. The country-level data on macroeconomic variables in each country are obtained from World Development Indicators (WDI) by World Bank (WB). Specifically, country-level data on institution quality is collected from Worldwide Governance Indicators (WGI), which have been compiled and accessed by Kaufmann et al. (2008) in excess of 50 countries available at https://info.worldbank.org/governance/wgi/.

2.2 Measuring Bank Competition: Boone Index

Based on the theoretical explanation from Boone (2008) and the current empirical evidence from van Leuvensteijn et al. (2007), both estimates present the bank level, but then change to the aggregate level. To this end, we apply the Boone (2008) index from bank level data to capture the significance of the reallocation influence at the aggregate banking system within country level. For the empirical implementation, we characterize the Boone (2008) model for bank i as \(\pi_{i,t} = \alpha + \phi \ln (c_{i,t} )\), where \(\pi_{i,t}\) stands for the bank profits i at year t, \(\phi\) is represented for the Boone (2008) index, while \(c_{i,t}\) means marginal costs. Due to the unobservability of marginal costs, this paper then follows the study of Boone et al. (2005) to utilize average costs. In particular, theoretical framework of Boone (2008) is applied to investigate how margins from loans and other earning assets change with the average costs of deposits and other borrowed funds, labor, and fixed assets (Koetter et al., 2012; Sealey & Lindley, 1977).

This paper applies the Boone (2008) index to model the linkage between profits and average cost according to the following reasons. An increment in costs decreases profits in all markets, but the same percentage rise in a more competitive market causes a larger decrease in profitabilities while inefficient banks are disciplined for their bad management. This index reflects the characteristics by measuring the extent where differences in efficiency are in response to performance changes. It is concluded that the Boone index represents the decreasing in profitabilities as a result from cost inefficiencies. Because cost inefficiencies frequently show poor lending outcomes, the index shows explicitly reasonable for measuring banking contention as a component of bank efficiency. However, the Boone index is extensively and successfully applied for the empirical banking literature (Bolt & Humphrey, 2010, 2015a, 2015b; Duygun et al., 2015; Faia, et al., 2021; Glass et al., 2020).

Bank‐specific effects are also included in our empirical model to control for the heterogeneity within banks. Moreover, empirical specification is crucial to allow for time-varying in the influence of competition on bank performance by exploring the transmission mechanism. Based on the specification of Schaeck and Cihák (2014), we estimate the Boone (2008) model as follows:

$$ \pi_{i,t} = \alpha_{i} + \sum\limits_{k = 1}^{T} {\phi_{k1} d_{k,t} \ln (c_{i,t} )} + \sum\limits_{k = 1}^{T - 1} {\phi_{k2} d_{k,t} \ln (c_{i,t} )} + u_{i,t} $$
(1)

where \(\pi_{i,t}\) are the profits of bank i at year t as a proportion of its total assets, T is the total number of years, \(d_{k,t}\) is a year dummy where \(d_{k,t} = 1\) if k = t and zero otherwise, \(c_{i,t}\) are average variable costs, and \(u_{i,t}\) is the error term. We then follow Boone’s (2008) setting on the measure of bank competition by adopting the average costs of bank i as a ratio to its total income. The cost components are composed of the sum of interest and personnel expenses, administrative, and other operating expenses. Income includes commission and trading income, interest income, fees income, and other operating income. Banks with lower marginal costs (\(\phi { < }0\)) present better profitability. Thus, incremental competition enhances profits of more efficient banks in comparison to less efficient ones. The more profound the influence (i.e., the higher \(\phi\) the absolute value) is, the stronger the competition is. Hence, we expect that the more negative the Boone index, the higher the degree of bank competition is due to the stronger influence of reallocation forward the resources.

2.3 Multilevel Mixed-Effects Panel Data Model

Based the hierarchical structure of our panel data on banking sectors nested within among nations, we use a panel data model with multilevel mixed effects to estimate the joint effect of the country-level governance and bank competition on bank-level profits. Especially, we apply a two-level random effects where the period of bank is included as level 1 while the country governance and banking competition as level 2 nested among nations. The selection of our approach presents two crucial innovations. First, potential clustered heterogeneity linked to the disaggregated panel data is controlled by the model (Rabe-Hesketh & Skrondal, 2014). Further, the explanatory variables and error terms at each level of the panel data are incorporated in the model. Second, the multilevel model eliminates the possibility of aggregated bias in which a conclusion is incorrectly included at one level but not at another (Robinson, 2009). This issue is frequently associated with data aggregation, which masks diverse behaviors of industries in the manufacturing process (Hox et al., 2010). As a result, we could loss crucial information underpinning economic linkages among sectors and also could decrease the statistical strength of the estimation, potentially leading to inaccurate results. Following the specification of Chen and Liao (2011), our empirical model is set up as follows:

Bank-Level

$$ \Phi_{i,j,t} = \alpha_{0,j} + \alpha_{1} ForeignBank_{i,j,t} + \sum\limits_{q = 1}^{{}} {\gamma_{q,j} } BankControls_{i,j,t} + \tau_{t} + \varphi_{j} + \xi_{i,j,t} $$
(2)

where \(\Phi_{i,j,t}\) stands for bank profit after tax for bank i in country j in year t. \(\tau_{t}\) and \(\varphi_{j}\) denotes the time effect and country-specific effects, respectively. \(\xi_{i,j,t}\) represents the error term.

Country-Level

$$ \begin{aligned} \alpha_{0,j} & = \beta_{0,0} + \beta_{0,1} Competition_{1,j} + \beta_{0,1} Macroeconomics_{1,j} \\ & \quad + \beta_{0,1} \left| {Governance_{1,j}^{Host} - Governance_{1,j}^{Home} } \right| + \mu_{0,j} \\ \end{aligned} $$
(3)
$$ \begin{aligned} \alpha_{1,j} & = \beta_{1,0} + \beta_{1,1} Competition_{1,j} + \beta_{1,1} Macroeconomics_{1,j} \\ &\quad + \beta_{1,1} \left| {Governance_{1,j}^{Host} - Governance_{1,j}^{Home} } \right|\mu_{1,j} \\ \end{aligned} $$
(4)
$$ \begin{aligned} \alpha_{0,j} & = \beta_{0,0} + \beta_{0,1} Competition_{1,j} + \beta_{0,1} Macroeconomics_{1,j} \\ & \quad + \beta_{0,1} \left| {Governance_{1,j}^{Host} - Governance_{1,j}^{Home} } \right| \\ & \quad+ \beta_{0,1} \times Competition_{1,j} \times \left| {Governance_{1,j}^{Host} - Governance_{1,j}^{Home} } \right| + \mu_{0,j} \\ \end{aligned} $$
(5)
$$ \begin{aligned} \alpha_{1,j} & = \beta_{1,0} + \beta_{1,1} Competition_{1,j} + \beta_{1,1} Macroeconomics_{1,j} \\ & \quad+ \beta_{1,1} \left| {Governance_{1,j}^{Host} - Governance_{1,j}^{Home} } \right| \\ & \quad+ \beta_{1,1} \times Competition_{1,j} \times \left| {Governance_{1,j}^{Host} - Governance_{1,j}^{Home} } \right| + \mu_{1,j} \\ \end{aligned} $$
(6)

where \(Competition_{1,j}\) denotes the degree of bank competition measured by Boone Index. \(\left| {Governance_{1,j}^{Host} - Governance_{1,j}^{Home} } \right|\) defines the absolute value on differences in national governances between home and host country with respect to overall scores, voice and accountability, political stability and absence of violence/terrorism, government effectiveness, regulatory quality, rule of law, and control of corruption. We shows the mean value of seven measures from 2004 to 2019 in Appendix A. Based on Kaufmann et al. (2008), the definition and explanation for the six indicators are described as follows: (1) Voice and Accountability (VA), which is defined as the extent to which citizens in a country are able to participate in selecting their government, as well as freedom of expression, freedom of association, and free media; (2) Political Instability and Violence (PV), which is defined as perceptions of the likelihood that the government may be destabilized or overthrown by unconstitutional or violent means, including political violence and terrorism; (3) Government Effectiveness (GE), which is defined as the quality of public services, the quality of civil services and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of government commitment to such policies; (4) Regulatory Quality (RQ), which is defined as the ability of the government to formulate and implement sound policies and regulations that permit and promote private sector development; (5) Rule of Law (RL), which is defined as the extent to which agents have confidence in and abide by the rules of society, in particular the quality of contract enforcement, the police, and the courts, as well as the likelihood of crime and violence; and (6) Control of Corruption (CC), which is defined as the extent to which public power is exercised for private gain, including both petty and grand forms of corruption, as well as “capture” of the state by elites and private interests.

The three measures of bank profitability are used alternatively for the dependent variables of NIM, ROA, and ROE. NIM is the net interest margin generated by the net interest income (= interest income – interest expense) divided by current assets. This ratio means that higher net interest margins show better profitability. ROA is defined as the net profit divided by total assets and stands the earning performance of the bank based on the total assets. ROE is calculated as the return on equity that is the net profit after tax divided by shareholder equity, and reflects the earning performance of the bank according to the share of the stakeholders. Our series of independent variables for the empirical analysis, we consider bank financial characteristics, foreign bank ownership, banking competition, macroeconomic variables in host country, and differences in national governances between home and host country. \(ForeignBank_{i,j,t}\) is the foreignership-specific variable and is a proxy of the dummy variable, which is equal to one for foreign-owned banks defined as foreign-owned if their shareholding is up to 50% or more; otherwise; 0 for domestic-owned banks. The list of 375 foreign banks included for empirical analysis in our dataset is shown in the Appendix B. With respect to control variables (\(BankControls_{i,j,t}\)) for bank characteristics as internal determinants of performance, we include the following variables in the empirical specification: Ln(Total Assets) = The natural logarithm of the total assets, Ln(Liquidity) = Total Loans divided by customers and short-term funding, Ln(Opportunity) = The ratio of liquid reserves/total assets, Credit Risk = The loan-loss provisions to loans ratio, Ln(Cost) = The natural logarithm of total operation expenses, Ln(Noninterest Revenues) = Non-interest revenues/total revenue, Ln(Interest Payments) = Operating expenses minus non-Interest income to total assets, and Ln(Other Operating Incomes) = Other operating income/total assets. In addition, three macroeconomic variables in host country also included with the growth rate of GDP per capita, inflation rate, and real interest rate.

3 Empirical Results

3.1 Descriptive Statistics

We use a bank panel data including 375 foreign banks from 47 Asian countries during 2004–2019, Table 1 provides a summary statistics report of the variables used with respect to all banks (Panel A), domestic banks (Panel B), and foreign banks (Panel C). Mean value of all sample on Panel A presets an ROA of 0.714, ROE of 7.127, and NIM of 5.895. Regarding the macroeconomic performance, the mean inflation rate is 2.060 lower than real interest rate of 2.232. The mean value of Boone Index is − 0.019 which means the higher competitiveness in banking competition. We find the mean value of the difference in overall national governance aggregated by six measures is 0.606, implicating the better quality of country governance for foreign banks. Besides, as shown in Panel A and Panel B, we advocate clearly significant that foreign banks perform more profitable than domestic banks when considering the mean of the three measures, with an ROA of 1.198 (0.643), ROE of 9.738 (6.747), NIM of 3.673 (2.357), respectively. Compared to domestic banks, foreign banks exhibit a lower ratio of noninterest revenues and smaller total assets, but also have a higher ratio of liquidity, opportunity cost, credit risk, operating costs, interest payments, and other operating incomes.

Table 1 Descriptive Statistics of Variables
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3.2 Are Foreign Banks Perform Better than Domestic Banks in Asia?

We apply the panel data model with multilevel mixed-effects to estimate Eqs. (2) to (6) since banks within a country might interact both correlated and corresponding. Based on the result of correlation coefficient matrix shown in Table 2, we find our bank profit measures (NIM, ROA, and ROE) present significant monotonic association with the number of bank financial characteristics, bank competition, macroeconomic environment, and the difference in national governance between host and home country.

Table 2 Correlation coefficient matrix
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In Table 3, we respectively use ROA, ROE, and NIM as the profitability variables by controlling for bank financial characteristics, bank competition (Boone Index), macroeconomic environment, and the difference in national governance between host and home country. Panel A of Table 3 indicates that foreign banks show a significantly positive correlation to higher ROA than domestic banks, which means that foreign banks demonstrate outstanding ROA in all 47 Asian countries in comparison to domestic banks. This finding is consistent with the international evidence of Chen and Liao (2011). It is worth noting that uncompetitive bank market structure across different countries impose a significant role on bank ROA, based on the perspective of the Boone Index, in particular there exists significant and positive relationship between bank ROA and the degree of competition in the banking industry. This finding implies that bank profitability tends to be likely to increase as the trend of the banking industry in a country shifts to a uncompetitive condition (monopoly or oligopoly), due to the barriers to market entry. Specifically, foreign banks with larger differences in national governance significantly decrease their ROA and this result also remains the robustness by controlling for the individual indicator of country governance with respect to voice and accountability, political stability and absence of violence/terrorism, government effectiveness, regulatory quality, rule of law, and control of corruption.

Table 3 The effects of national governance on bank financial performance
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Regarding the bank’s financial characteristics, we confirm that banks with better liquidity and other operating incomes significantly foster bank’s ROA, while lower ROA of bank is related to the higher level of total assets, opportunity cost, credit risk, operating cost and interest payments. Finally, banks located in a country with higher level of GDP per capita, inflation rate, and real interest rate significantly perform better ROA. According to Panel B and Panel C in Table 3, we find the similar results of ROE and NIM in comparison to ROA, and confirm that foreign bank consistently and strongly boost higher profits than domestic bank, especially in uncompetitive host country.

3.3 Does Bank Competition Amplify or Mitigate the Impact of Differences in National Governance between Host and Home Country on Foreign Bank Profitability?

We then investigate the joint effects of the bank competition and differences in national governance on foreign bank profits and the results are shown in Table 4. In Panel A of Table 4, we find that the bank competition has positive effect on bank ROA while differences in national governance shows negative effect foreign bank ROA. We next explore the interaction of Boone Index and differences in national governance between host and home country (Boone IndexDifference in National Governance) on foreign bank profits. We find that the coefficient of Boone IndexDifference in national governance shows positive and statistically significant, implicating that foreign banks with uncompetitive banking structure in host country could significantly mitigate the negative effect of national governance between host and home country on the ROA of foreign bank by generating the market power in host country for foreign banks. Based on the Panel B in Table 4, we further verify that the results of ROE and NIM are robust to the ROA. This evidence suggest that foreign banks could generate their market power in uncompetitive banking structure to reduce the adverse influence of national governance between host and home country on their profitability.

Table 4 The joint effects of bank competition and national governance on bank financial performance
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4 Conclusions

There is limited published literature on the substantial influence of banking market structure, and the national governance quality between countries on bank profitability, particular in focusing on domestic banks versus foreign banks. Hence, in this paper, we used both bank- and country-level data from the banking sectors of 47 Asian countries during 2004–2019. We find that national governance mechanisms have an overall impact on bank performance. Assessing the effects of country-level governance quality and bank competition for bank-specific variations in bank profitability has direct implications in the context of international study. Furthermore, we specifically investigated the joint influences of bank competition and differences in national governance between the host and home country on foreign bank’s profitability.

Moreover, our empirical results reveal that foreign banks exhibit better profitability than domestic banks in Asia, while differences in the banking market structure in different countries plays a significant role in bank profitability. Banks in more uncompetitive markets promote higher profitability, while cross-country differences in macroeconomic condition also significant enhance bank profits. Specifically, our findings indicate that foreign bank with larger differences in national governance between host and home country significantly decrease their profits and this also remains the robustness in terms of individual indicator with respect to voice and accountability, political stability and absence of violence/terrorism, government effectiveness, regulatory quality, rule of law, and control of corruption. Finally, foreign banks could seize their market power in uncompetitive banking structure in host country to moderate the disadvantageous influence of national governance between host and home country on their financial performance.