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The Impacts of Market Structure on Profitability: An Application to China’s Banking

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The Impacts of Market Structure on Profitability: An Application

to China’s Banking

Yanjun Huang

China Foreign Affairs University

[email protected]

Jiawen Yang

the George Washington University

[email protected]


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The Impacts of Market Structure on Profitability: An Application

to China’s Banking

Abstract

In this paper, we study the structure-performance relationship by employing a unique panel data of 95

banks in China covering 2003-2013 period. Contrary to the previous work in developed countries, our

results show that market concentration leads to lower profitability and no significant relationship is

observed between market power and profitability, indicating little evidence to support SCP and RMP

hypotheses in China’s banking. By investigating the structure-performance relations across banks with

different size, we find that concentration accounts for profitability in the largest banks, and the

undermining effects of market share on profitability is significant; inversely, concentration seems to

decrease profitability in the rest of banking sector, rather than market share. In addition, we find that

unexpectedly both of concentration and market power increase bank profitability during financial crisis.

By exploring the effects of foreign minority ownership, we confirm that foreign entry tends to improve

banking profitability under the tremendous banking system reform in China. And we also find that listed

banks are prone to gaining less profits.

Key words: market structure, banking profitability, foreign acquisition


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1. INTRODUCTION

Many studies have been are devoted to the relationship between market structure and profitability in

regulated and concentrated industries such as banking from the perspective of industrial organization

theory. Berger (1995) organizes two hypothesis for such a relationship in banking. One interpretation, the

traditional structure-conduct-performance hypothesis (SCP), constructs a model of oligopolistic behavior

of firms, stating that high market concentration decreases the cost of collusion and firms are able to extract

monopolistic rents. Market concentration will also price the products inefficiently, which means in

imperfectly competitive markets higher concentration enables firms to set prices less favorable to

consumers. The other interpretation is the relative-market-power hypothesis (RMP), which indicates that

only firms with larger market shares and well-differentiated products are able to be price-makers who can

profitably raise the market price of a product or service over marginal cost and control a large portion of

market to gain high profits by owning market power.

Many works test these two hypothesis on the structure-performance relationship in banking but

empirical evidence about the effects of market structure on profitability reaches no completely consensus.

Some studies find a positive relationship between market structure and profitability (Jeon & Miller,

2005;Claeys& Vander-Vennet, 2009), which implies both SCP paradigm and RMP hypothesis are

supported, while others take the opposite view(Berger, 1995; Goldberg & Rai, 1996). These previous

studies indicate that although the substantial differences are involved in operational structure and

regulatory pattern between banks across the fast-changing world, there is still a possibility to conduct a

meaningful analysis of the impact of market structure on profitability in banking.


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China’s economy has witnessed an annual growth around 10% and become one of the world’s largest

economy over the last decade. Under globalization environment and unprecedented reform, new policies

are imposed on banking sector to open up the market for foreign investors. Research on developing

nations and the financial growth indicates that high growth rates are associated with the reform of banking

system and financial infrastructure. With respect to the structure-performance relationship, this paper

investigates whether these two hypothesis are applied to banking in China or whether banking sector is

benefitting from concentration during the reform of China’s banking as the same as banking in advanced

economies.

Unlike the structure-performance relationship in developed countries, our results show SCP and RMP

hypotheses are lack of support in China’s banking. We are also interested in the structure-performance

relations in banks with different size and we find that the relationship between market structure and

profitability is heterogenous among banks with different size. Another interesting result is that

concentration accounts for bank profitability during financial crisis. We also explore other determinants of

the relations(i.e. foreign capital), and confirm that foreign investment is very crucial to banking

profitability, moreover unlisted banks are unexpected to outperform listed banks, especially for sample

excluding these largest banks.

Our paper contributes to the existing literature in a number of dimensions.

First, studies measuring the structure-profitability relations in developing economies are limited. This

paper fills the gap by testing these two hypotheses for China, as a representative case of emerging

countries. Second, reflecting the tremendous changes of banking reform and innovation environment in

the last decade, we develop a model of the relationship between market structure and profitability for

China with the widening scope of explanatory variables and the latest data. An understanding of the

structure-performance relationship could give implication to policy-making related to the current reform


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and the subsequent stage. Third, we investigate the structure-performance relationship by dividing banks

by size and examine financial crisis and non-crisis separately.

In this paper, Section 2 describes the background of China’s banking system. Section 3 organizes the

literature review and develops the hypotheses. Section 4 defines the variables and data. Section 5 conducts

the methodology. Empirical results and robustness check are showed in Section 6 and Section 7 separately.

Section 8 concludes.

2. CHINA’S BANKING SYSTEM

Prior to 1978, mono-bank model is operated in China’s banking system where People’s Bank of China

(PBC) was established not only to issue currency as a central bank but also have commercial service as a

financial hub. Since the first economic reform, a two-tiered banking system was substituted for mono-

banking model to improve economic efficiency and resource allocation. Big Four state-owned banks,

including Bank of China (BOC), China Construction Bank (CCB), Agricultural Bank of China (ABC) and

Industrial and Commercial Bank of China (ICBC), were established, whereas they were initially restricted

to serving assigned sectors separately.

Until 1985, Big Four was permitted to widen the scope of raising funds and allocating capital so that

they were able to compete with each other in all the sectors. They expanded to universal banks with kinds

of financial affiliates in 1986. Nonetheless, they were lack of incentives to compete due to national policy.

Then bank reform was incrementally focused on ownership. New “small and medium sized” joint-

stock commercial banks which were allowed to offer services to households and firms were established by

government, such as Bank of Communications, CITIC Industrial bank and China Merchants Bank. In

1981 Nanyang Commercial Bank set up branches in Shenzhen, as the first foreign bank entry since the

reform and opening up.


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From 1993, a second stage of banking reform was launched for alleviating the deteriorating asset

quality of state-owned banks. Numerous measures were implemented as follows:

Big Four was recapitalized through the special bonds issued by the Ministry of Finance in 1998 and

NPL was transferred to newly established asset management companies which are also SOEs.

Under the Central Bank Law, PBC, to reduce the influence of government on credit allocation

decisions, was confirmed to be responsible for the implementation of monetary policy. Urban and rural

credit unions started to merge then formed city commercial banks, though they are still controlled by the

state and SOEs. This means one of the reform subjects was to create a competitive commercial banking

environment.

Government turned to encourage foreign bank entry by offering the tax-exempt incentives available to

all the foreign companies. Since Asian Development Bank acquired a 1.9% equity in China Everbright

Bank in 1996, foreign investor were further allowed to purchase stakes in domestic banks but limited

proportion with restricted regulations.

After WTO entry in 2001, China makes further efforts to open up the banking system with a new set

of rules. Interest rates are more liberalized, and ownership takeovers and M&A are less restricted. Foreign

banks were allowed incrementally to conduct RMB business with enterprises in certain regions from 2002.

China Banking Regulatory Commission (CBRC) was created in 2003 to monitor the banking industry.

CBRC launched a set of new rules to encourage foreign acquisitions with a limited share up to 25%.

China’s financial market is attractive to strategic foreign investors. Many commercial banks transferred a

proportion of equity to foreign investors. In addition, foreign investors participated in establishing of

Chinese bank by offering foreign minority stake. Partial privatization has been overwhelming across the

country though commercial banks are still state-owned. Management improvement in banking has been

put on the agenda of reform.


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In 2005, China established a managed floating exchange rate regime based on market demand and

supply with reference to a basket of currencies. Then commercial banks confronted with a more volatile

environment full of more new requirements, new markets and new financial tools, are accelerating the

transformation of management theories.

To deepen the reform of shareholding systems and simultaneously increase state-owned banks’

operational efficiency, three of the Big Four (ICBC, CCB and BOC) were listed on stock exchanges in

Hong Kong and Shanghai from 2005 to 2006. After preparation and trimming down the NPLs, the ABC,

was finally listed in Hong Kong and Shanghai in mid-2010 to allow more market discipline to monitor its

performance, which is a landmark achievement for financial system reform in China.

In 2012, Wenzhou Financial Comprehensive Reform Area was approved to establish for encouraging

private financing. In 2013, policymakers gradually lowered the lower limit of lending rates and finally

ended all restrictions on lending rates. Interest rate liberalization will facilitate the private sector an access

to credit, which will benefit China’s economy in a long term run. However, the government also realizes,

as a key component of economic reform policy, a market-based interest rate environment will likely put

enormous pressure on reduction of financial market volatility. Despite of the need to maintain the financial

stability, interest rate liberalization is expected to improve the allocation of capital resources and make a

historical progress for China’s economy development.

3.THEORY AND HYPOTHESES

The bulk of previous literature related to banking concentrates on exploring the statistical relationship

between profitability and market structure. Researches fall into two distinct industrial organization

theories: SCP paradigm and RMP hypothesis. For the former hypothesis, the market structure imposes an

influence on the conduct of firms (i.e. price-setting, trade policy) and finally causes the changes of

individual performance (i.e. profitability, efficiency). According to SCP hypothesis, high level of


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concentration lowers the cost of collusion, which fosters collusions among firms and gives rise to

monopoly rents. Then it affects the way firms behave, enabling them to gain supernormal profits. So

concentrated market structure causes higher profitability for firms. As for the highly concentrated banking

industry, a bank can set higher interest spreads by offering lower deposit rates and charging higher loan

rates due to competitive imperfections, therefore get high profits.

With respect to SCP paradigm which focuses on the top largest firms in the industry, RMP hypothesis

pays more attention to market share of individual banks. Based on the latter approach, market share is able

to capture market power arising from product differentiation, which means only firms with a large market

share have higher quality products and thus set higher prices and increase profitability.

Shepherd (1982) asserts that banks with a higher market share exert more market power and earn

higher profits, independent of the level of market concentration.

The empirical evidence in the existing literature on the structure-profitability relationship is mixed.

Although SCP studies utilizing manufacturing data find a positive relationship between concentration and

profitability, Smirlock (1985) doubts that there exists similar correlation in banking industry. Using a

panel data from 2,700 unit state banks over a period 1973-1978, Smirlock finds that there is no evidence

to support SCP hypothesis once market share is controlled. In his paper, market share, rather than

concentration, has a significant and positive impact on bank profitability. As reviewed previous studies

using bank call report data, Gilbert (1984) finds only one of the five price measures produces a coefficient

on concentration which is statistically significant. After examining the determinants of international bank

profitability and reviewing the relevance of expense preference behavior theories, Bourke (1989) finds

that concentration is positively related to profitability in banking of Europe, North America and Australia.

In 1990s, some researches focus on the relationship between market structure and profitability

incorporating efficiency-structure hypothesis including X-efficiency and scale-efficiency. Berger (1995)

creates and implements tests that containing direct measures of both market structure and efficiency in the


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same model to distinguish the effects on profitability in banking of RMP and Efficient Structure (ES)

hypotheses. He finds limited support for all the four hypotheses by employing 1980s data of US banks.

Berger and Hannan (1997) use US bank data and find more support for SCP hypothesis than the rest of all

the hypotheses. And they also prove that the “quiet life” hypothesis where firms with larger market power

are less efficient as a result of slack management, is supported. After US banking has been studied

extensively, Goldberg and Rai (1996) find there is no significantly positive relationship between

concentration and profitability for large banks across 11 European countries from 1988 to 1991. Their

finding suggests that RMP hypothesis plays more significant role than SCP hypothesis, and only in banks

located in low concentration countries, ES hypothesis is supported.

This is opposite to the findings of the study by Goddard et al. (2004), who assert that evidence in their

paper favoring the SCP hypothesis of a positive association between concentration and profitability, but

little apparent relationship between X-inefficiency and profitability in bank level.

The research papers that follow in this special issue push significantly further in expanding research

on the structure-performance relationship in developing countries.

Claeys and Vander Vennet (2009) review banking in Central and Eastern European nations and

suggest that SCP hypothesis is applicable in these countries by utilizing SFA technique. In Jeon and Miller

(2005), the findings indicate that there is strong evidence supporting for a positive relationship between

concentration and profitability through a state-by-state basis. Furthermore, by temporal causality tests,

they conclude that SCP paradigm is an explanation for bank profitability, therefore market power

hypothesis is supported. This is the same as the findings of the research by Tregenna (2009). In this study,

Tregenna finds that the concentration-profitability relationship in banking sectors is positive and robust,

but the efficiency-profitability relationship is weaker.


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Nowadays, new papers generally have an international orientation that includes different groups, such

as developed and developing nations, a significant departure from the vast majority of the studies in the

extant literature. But papers related to emerging groups are still limited.

Mirzaei et al. (2013) examine the effects of market structure on profitability in banking from

emerging economies and advanced economies separately. They find evidence that RMP hypothesis is

supported in advanced economies. However, there is little evidence to prove that SCP hypothesis is

applicable to both of groups. In addition, the impact of concentration on profitability is unexpectedly

negative in emerging economies.

For Chinese case, Fu and Heffernan (2009) investigate the relationship between market structure and

profitability in China’s banking sectors by using two subsample panel data to observe the impacts in

banking before and after the reform in China banking. Through the test, they find that prior to the reform,

RMP hypothesis is applicable to China’s banking. In contrast with RMP hypothesis, concentration affects

profitability negatively after financial liberalization started in 1992, which indicates that SCP is not

supported with China’s banking system. Garcia-Herrero et al. (2009) analyze the determinants of low

profitability of China’s banking sectors for the period from 1997to 2004 and find that profitability is

affected negatively by market share and there is no significant relationship between concentration and

profitability.

We investigates empirically profitability of China’s banking in SCP framework. Our first series of

hypotheses are:

Hypothesis 1A. Bank concentration improves bank profitability in China.

Hypothesis 1B. There is no positive relationship between bank concentration and profitability in

China.


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Based on the SCP hypothesis, concentration results in a lower collusion cost so firms are able to

extract monopolistic rents, which means bank concentration is expected to lead to higher profitability in

China.

Alternatively, focusing on RMP hypothesis, second series of hypotheses are:

Hypothesis 2A. Banks with larger share tend to be more profitable in China.

Hypothesis 2B. There is no positive relationship between market share and profitability in China’s

banking.

In RMP hypothesis, firms with large market shares and well-differentiated products can exert their

market power in pricing products, therefore they are able to control the market and earn high profits. In

line with RMP hypothesis, market share is expected to have a positive impact on profitability in China’s

banking.

4. METHODOLOGY

Following Smirlock(1985), the traditional hypothesis can be tested by the profit equation shown

below:

Πit=f (Market Structureit) (1)

Where Πit is the dependent variable measuring the profitability of ith bank at time t; Market

Structureit refers to either market share (MS) of ith bank at the firm level or the concentration ratio (CR) at

the industry level.

The expanded version is as follows:

Πit=β0+β1MSit +β2CR t +µit (2)


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Where MS measures market share of bank ith; CR is the index which measures the top largest firm

concentration ratio. This formula is assumed to reflect the two hypothesis of SCP and RMP.

We are following the reasonable expansion of model constructed by Mirzaei et al. (2013), employing

different variables which is much more applicable to China’s case.

Πit=β0+ β1MSit +β2CR t +∑Bit +∑Mt +µi+ut+vit(3)

Bit is the first vector of control variables which account for bank-specific characteristics; Mt is the

second vector of control variables which denote financial structure and macroeconomics characteristics.

An error term for each bank i at the time t includes three components: µi is standing for the unobserved

individual specific effects; ut is the unobserved time effects; vit is the normal stochastic disturbance.

5. DATA AND VARIABLES

5.1 Data

We employ an unbalanced panel data obtained from Bankscope and annual reports from banks. The

macroeconomic level data are retrieved from the World Bank. The full sample runs from 2003 to 2013with

95 observations in China.

5.2Variables

All the variables are presented by Table 1.

5.2.1 Dependent variables

In the empirical analysis performance measures of banking are focused on as dependent variables. In

the previous banking literature the profitability variables of banking are represented by two alternative

measures: the ratio of profits to assets, i.e. the return on average assets (ROAA) and the profits to equity


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ratio, i.e. the return on average equity (ROAE), which refers to the ability of banks’ asset and equity

generating revenues (Lloyd-Williams et al., 1994; Fu & Heffernan, 2009).

5.2.2 The focal variables

The focal variables focus on market structure of banking sectors in China. To be taken to investigate

RMP hypothesis, market share, which represents market power at a firm level, is calculated as the ratio of

the individual bank asset to the total asset of the whole industry in China. SCP hypothesis employs the

concentration ratio which estimates the extent to that the top largest banks take control of the entire

industry. According to Demirguc-Kunt et al. (2003), we measure bank concentration as the fraction of

bank assets held by the five largest banks in China. We use the 5-firm concentration ratio due to Chinese

situation in which assets held by top five largest banks are much higher than assets held by the rest of the

banking sector.

5.2.3 Control variables

Control variables are composed of bank-specific variables, financial structure and macroeconomics

variables, which are instrumental in explaining bank profitability are introduced into the regressions.

First, ratio of equity to total assets is considered as a measure of bank capital strength. In perfect

competitive market assumption with symmetric information, capital refers to the amount of own funds

available making contribution to earnings and supporting banks’ business (Athanasoglou et al., 2008). In

imperfect competitive market assumption, banks are expected to have better performance to transmit

asymmetric information through the higher capital ratio. In addition, a bank can have more possibility to

earn profits from holding capital in excess of the regulatory minimum and reducing potential risk by

holding an adequate capital (Mirzaei et al., 2013). This regressor is expected to be positively correlated

with profitability (Pasiouras & Kosmidou, 2007).


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Second, the ratio of overheads to total assets is used to proxy bank cost which measures X-

efficiency(Tregnna, 2009). Overheads to total assets ratio providing information on the fluctuation of bank

cost compares a bank’s cost efficiency with other banks indirectly. Another popular indicator that has the

same function is cost to income ratio, but in China the lending and deposit rates have not been fully

liberalized over 2004-2012 yet. We use the former indicator to represent bank cost, which is expected to

be negatively correlated with bank profitability (Garcia-Herrero et al., 2009).

Third, considered to be relative to bank profitability, bank size is measured by the log of total assets.

Garcia-Herrero and Vazquez (2007) shows that banks with large size are able to maintain lower cost

owing to scale efficiency. However, Stiroh and Rumble (2006) hold that big banks are too large to manage,

which leads to less profits. Therefore, the effects of bank size are mixed.

Fourth, diversification of bank income is constructed as an indispensable variable in this model.

Following the literature (Stiroh, 2004; Casu & Girardone, 2005), non-interest income produced by non-

traditional activities is a share of banking profitability and also increase the volatility of bank revenue

(DeYoung & Roland, 2001).

Fifth, based on the paper (Smirlock, 1985), market growth is likely to influence bank profits. The rate

of growth in lending loan growth is employed as an indicator to represent market growth.

Sixth, the effects of foreign minority ownership on profits are examined with dynamics dummies.

Unlike other countries, except foreign-owned banks, China’s banks are owned by either local government

or state-owned enterprises. Foreign acquisitions were restricted with government policy in China,

including offering a limited foreign minority stake. According to previous literature, banks with foreign

investors tend to higher profits than domestic banks in developing countries(Berger et al., 2009). The

dummy variable is equal to 1 if foreign investors acquire a share of the particular bank in the given year.


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Moreover, we include the dynamic dummy variable listed that takes the value of 1 when a bank is

listed in the stock exchange in the given year, which assesses the role of increasing privatization in

China’s banking sector.

As with macroeconomic environment in which banks operate may influence bank profits, the

previous studies show that economic growth (Demirguc-Kunt& Huizinga, 1999; Bourke, 1989) and

inflation (Boyd et al. 2001; Demirguc-Kunt et al., 2003) increase banking profitability. Therefore we

specify GDP growth and inflation rate as macroeconomics indicators in the model.

6. EMPIRICAL RESULTS

As discussed above, we examines empirically the impact of market structure on bank profitability

with annual panel data for a maximum of 168 banks over the period 2004-2012.

6.1 Testing the structure-performance relationship in China’s banking

Table 2 reports the empirical results for the baseline specification. Both market share of individual

banks and industry concentration have been correlated negatively with ROAA. With respect to ROAA, the

result shows that the coefficient of 5-firm concentration is negative and statistically significant at the 5%

level, suggesting that an increase in market concentration leads to a decline of returns on assets of a bank,

but market share is not significantly correlated, although the sign of market share is negative. With regard

to ROAE, the result indicates that both measures of market structure have positive coefficients which has

the opposite trend from the measure of ROAA, but not significantly. These results run strongly contrary to

the existing literature supporting SCP and RMP paradigm in developed countries and consistent with some

of the views related to developing countries (Mirzaei et al. 2013).

Among the control variables, capital strength is not significant and unexpected to be negative with

both ROAA and ROAE.


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The sign of bank size varies with different measures of profitability. But each is not significant, which

may be explained by the reason that in China’s banks with larger size are involved with massive and

complicated government intervention.

The coefficients on bank cost and income diversification are not significantly negative, which means

operational efficiency and income diversification in business seems a key factor enabling banks to gain

high profits.

No significant relationship between market growth and profitability has been observed. The weak

results for the effects of loan growth on profitability might be interpreted as that banking loan growth is

unable to create a market environment in China’s banking to promote the high returns.

Foreign capital is highly correlated with ROAA, indicating that corporate governance with foreign

acquisition fosters profitability in China’s banking from the year that foreign capital enters the particular

bank. This may be based on three reasons: first, foreign minority ownership has spillover effects,

including introduction of new banking technology and management which leads to higher profitability;

secondly, it is relatively easy to make financial innovations to gain higher revenue under foreign minority

ownership with new products and services in the local market; thirdly, foreign acquisition profit-seeking

conduct will improve the competitive environment (Bonin et al., 1998).

There is negative relationship between listed and profitability, especially significantly with ROAA,

which suggests listed banks are less profitable than unlisted banks in China. Listed banks tend to have a

lower NPL ratio, therefore they are prone to less risky behavior. As capital strength has a negative impact

on profitability, unlisted banks perform better than listed banks.

For macroeconomic environment variables, inflation is positively associated with bank profits,

whereas GDP growth is not significantly correlated. Inflation may influence banks through net interest

margin but not economically huge (Demirgüç-Kunt et al., 2003).


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6.2 Testing the structure-performance relationship on different types of banks

One objective of the estimates is investigating that the difference of the concentration-performance

relationship between the top largest banks and the rest with smaller size of the banking sector in China

(Table 3). And we add an interactive term for market share ratio with foreign capital dynamic dummy to

investigate whether the effect is heterogeneous across banks with different size.

The sign of concentration coefficient for Big Five varies when the dependent variables alternate. For

ROAA, as one of profitability measures, the coefficient of market share is negative in the Big Five,

independent of bank concentration, indicating that for Big Five, the larger proportion in market, the lower

profitability. It may reflect the fact that the top largest banks which are state-owned earned lower returns

due to government intervention, slack management and moral hazard. And market concentration has a

significantly positive coefficient of ROAE. Despite of government policy, Big Five acts as price-makers

for the rest of banking sector, therefore the collusive behavior facilitates an opportunity with higher

interest rate spreads and hence higher profits. The sign of diversification is expected to become positive,

in the meanwhile loan growth is found to be significantly negative with bank profits. It is likely that non-

interest income is gradually replacing traditional interest income in Big Five.

Turning to the rest of banks, compared with Big Five, the coefficient of market share is not significant,

whereas concentration is statistically significantly negative with ROAA. The results show concentration

affects ROAA in banks with smaller size more significantly. On one hand, larger banks extract higher

profits through bank concentration, on the contrary, other banks cannot benefit from this. On the other

hand, government interference in lending policies has an impact on bank profitability so large banks or

local banks may facilitate firms’ access to credit and the stability of the banking system. Barriers to entry

in the banking sector are high, which may result in that banks having little access to government support

earn less profits (Ruthenberg, 1994). There is also a difference lying in foreign entry that for the rest of

banks, foreign investment will facilitate smaller banks an increase in profitability. Instead, for Big Five,


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the structure-performance relationship in a bank with foreign capital entry shows an inverse trend. This

result may be based on the following reasons: Firstly, the effects on banks’ earning ability by foreign

minority ownership should be recognized; Secondly, foreign investors are not only seeking profits in

China’s banking but also attempting to step into the financial market in China through shares of bank

equity by different entry modes, so foreign investors are targeting at banks with larger size to get more

support from the government; Thirdly, although foreign acquisition seems to undermine profitability in

Big Five, bigger size in the five banks with foreign entry has more profits; At last, the obvious difference

between two types of banks may be a result of that Big Five is more involved with government

intervention and restricted with financial policies, so that foreign minority ownership is unable to play an

important role in boosting profits.

6.3 Testing the structure-performance relationship during the financial crisis

Since the financial crisis during the period over 2008-2009, world economy experienced a recession.

The global crisis was brought on by the disruptions of systemically important financial institutions.

Banking and financial sector across various countries collapsed and many banks failed during the crisis.

Turning to the financial crisis period, Table 4 shows that a positive sign on the concentration coefficient,

when both of ROAA and ROAE are employed as the dependent variable, suggesting that banks with

smaller size can also benefit from the high bank concentration during the crisis through redistribution of

profits or trickle-down effects within the whole banking sector.

Market share is also significantly positive with bank profitability, indicating that market power is able

to facilitate banks an access to gain high profits. Another important finding is that the coefficients on listed

and foreign capital are inverse of previous regressions. The significant relationship between listed and

ROAA indicates that listed banks outperform unlisted banks. As seen from Table 4, foreign investors are

capable of making profits while banking is confronted with non-financial crisis. But unexpectedly banks

with foreign minority ownership earn much less profits than banks without foreign minority ownership.


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This may arise from the fact that these foreign companies were taking a heavy toll abroad during crisis

period.

7. ROBUSTNESS CHECK

The empirical results are verified by applying an alternative measure of dependent variables and focal

variables. Herfindahl-Hirschman index, the summation of each bank’s square of market share, is

substituted for 5-firm concentration ratio, and share of a bank’s loans to total market loans is employed

instead of assets share. The estimates of this model specification are consistent with previous construction.

By using net interest margin and non-interest returns (NIR)(Goldberg& Rai, 1996), instead of ROAA and

ROAE, the alternative approach cannot have distinct results.

8. CONCLUSION

The objective of this study is to examine the impact of market structure on profitability in banking

sector incorporating two industrial organization theories.

We find bank concentration is negatively associated with ROAA in bank and no significant

relationship between market power and banking profitability, which provides little evidence to support

SCP and RMP hypotheses in banking of China. Different form the result based on developed countries, the

structure-performance relationship is negative in China, which is consistent with the viewpoint of

developing countries (Mirzaei et al., 2013). But for banks with different size, we find that market power

has more significantly negative impacts on profitability in top largest banks, independent of concentration,

whereas there is a more significantly positive relationship between concentration and profitability. For the


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rest of banking, both concentration and market power have no significant relationship with banking profits.

The signs of other crucial determinants(i.e. foreign capital, listed), also varies between these two types of

banks. However, concentration and market power do account for bank profitability when the banking

system is confronted with financial crisis. The coefficients on market share remains negative almost all the

time.

The results have important implication: firstly, SCP hypothesis does not dominate in the banking

system in China, therefore deconcentration is conducive to improving bank profitability. Policy makers

should focus on antitrust regulation and facilitate banks with a competitive environment; secondly, since a

decrease in profitability when market share increases, profits are not derived from market power in China;

thirdly, for banking excluding largest banks, deconcentration is crucial for profits, but for five largest

banks, eliminating the diseconomy of scale is necessary; fourthly, during the crisis, an increase in bank

concentration ratio may contribute to soundness of banking in China; Fifthly, since foreign investment

entering into China’s banking improves profitability to some extent, implementing measures to open up

the financial market, boost competition and establish various types of ownership should be encouraged, i.e.

desterilization of foreign minority ownership, income diversification promotion, entry barrier removal.


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Table 1 Variable definition

Variables Definition Unit Source

Profitability measures

ROAA Net profits before tax divided by average total

assets

Ratio Bankscope

ROAE Net profits before tax divided by average

equity

Ratio Bankscope

Market structure variables

Market share Share of a bank’s assets to total assets in the

market

Ratio Bankscope

5-firm concentration ratio Share of five largest bank assets to total assets

in the market

Ratio Bankscope

Bank-specific variables

Capital strength Equity divided by total assets Ratio Bankscope

Bank cost Overhead costs divided by total assets Ratio Bankscope

Income diversification 1- [(Net interest income - Other operating

income) /Total operating income]

Ratio Bankscope

Market growth Log loanst-log loanst-1 Ratio Bankscope

Foreign capital Defined as 1 if foreign minority ownership

exists in bank ith in year t

Dummy Bankscope

Listed Defined as 1 if bank ith is listed in year t Dummy Bankscope

Macroeconomics indicators

Inflation Based on consumer prices Ratio Worldbank

GDP growth Inflation-adjusted growth rate of GDP Ratio Worldbank


26

Table 2 Results for baseline specification

Dependent variables Independent variables ROAA ROAE 5-firm concentration -1.963** 6.478 (0.926) (40.420) Market share -5.679 270.171 (6.544) (551.780) Capital strength -0.002 0.826 (0.026) (1.076) Bank cost -0.408 -1,003.287 (29.151) (1,001.039) Bank size 0.058 2.010 (0.067) (1.984) Income diversification -0.193 -5.970 (0.323) (7.094) Market growth 0.013 -0.633 (0.013) (0.725) Foreign Capital 0.337** 3.378 (0.133) (5.529) Listed -0.301** -7.577 (0.122) (11.278) Inflation 0.049*** 1.274** (0.016) (0.564) GDP growth -0.039* -0.877 (0.021) (0.890) Constant 1.263 -12.220 (1.406) (44.033) Fixed Effect √ √ No. of observations 341 341 R-squared 0.288 0.128 No. of banks 95 95

Bank individual fixed effects are included in the regression. Standard errors are clustered at bank level. Robust standard errors in parentheses.

***, **, * indicate statistical significance at the 1%, 5%, and 10% (two-tail) test levels, respectively.


27

Table 3 Results for the effects of market structure on Big Five and the banks excluding Big Five

Big Five Non-Big Five

Dependent variables

Independent variables ROAA ROAE ROAA ROAE ROAA ROAE ROAA ROAE 5-firm concentration -1.672 634.706*** -1.431 676.515*** -1.888* -5.904 -1.662 -0.886 (1.762) (107.807) (1.389) (135.657) (1.077) (39.644) (1.061) (40.520) Market share -8.982** 147.513 -11.019* -252.266 -10.243 -279.318 -24.110 -587.095 (3.065) (242.813) (4.756) (266.644) (24.545) (604.786) (23.852) (651.821) Capital strength 0.063 14.420 0.014 5.377 -0.001 0.818 -0.002 0.809 (0.053) (8.790) (0.035) (4.479) (0.026) (1.087) (0.025) (1.085) Bank cost -29.434 -3,859.074 28.287 6,921.355 0.028 -941.638 2.634 -883.789 (38.076) (7,314.036) (41.789) (8,506.885) (29.810) (999.906) (30.230) (985.838) Bank size -0.153 7.827 0.049 46.432 0.062 2.214 0.063 2.237 (0.346) (40.805) (0.237) (38.486) (0.081) (2.061) (0.081) (1.994) Income diversification 0.431 59.447 0.304 32.640 -0.191 -5.864 -0.208 -6.227 (0.774) (80.794) (0.763) (69.238) (0.322) (7.064) (0.327) (7.209) Market growth -0.022 -4.021** -0.020 -3.756*** 0.016 -0.599 0.015 -0.615 (0.017) (1.347) (0.023) (0.625) (0.014) (0.726) (0.014) (0.729) Foreign Capital -0.088 -0.671 -111.927** 0.327** 1.859 0.068 -3.881 (0.135) (0.393) (29.157) (0.135) (5.323) (0.155) (5.613) Market share* Foreign Capital 4.664 905.223*** 54.191** 1,202.821** (2.217) (160.806) (25.170) (595.194) Listed 3.369 -0.126 -6.035 -1.044** -26.410*** (7.511) (0.210) (6.351) (0.427) (8.055) Inflation 0.026 1.078 0.021 0.145 0.052*** 1.312** 0.054*** 1.346** (0.017) (0.699) (0.018) (0.704) (0.018) (0.626) (0.018) (0.636) GDP growth -0.019 -5.473* -0.014 -4.519* -0.042* -0.669 -0.044* -0.730 (0.025) (2.151) (0.023) (1.727) (0.023) (0.915) (0.023) (0.932) Constant 6.136 -503.427 1.837 -1,317.077 1.145 -7.057 1.113 -7.771 (7.716) (846.789) (5.052) (904.242) (1.692) (44.470) (1.697) (43.331) Fixed Effect √ √ √ √ √ √ √ √ No. of observations 25 26 25 25 316 316 316 316 R-squared 0.886 0.669 0.903 0.802 0.281 0.138 0.291 0.143 No. of banks 5 5 5 5 90 90 90 90 Bank individual fixed effects are included in the regression. Standard errors are clustered at bank level. Robust standard errors in parentheses. ***, **, *

indicate statistical significance at the 1%, 5%, and 10% (two-tail) test levels, respectively.


28

Table 4 Results for different periods

Financial crisis period Non-crisis period

Dependent Variables Independent variables ROAA ROAE ROAA ROAE 5-firm concentration 18.390** 751.170 -3.100*** -39.559 (8.703) (538.798) (1.092) (25.461) Market share 8.242*** 362.598 -6.523 377.238 (1.963) (270.904) (8.005) (534.492) Capital strength -0.046*** -3.641** -0.006 -0.331 (0.013) (1.785) (0.030) (0.220) Bank cost -6.284 -1,042.068 11.756 -179.259 (19.083) (1,103.355) (36.481) (275.815) Bank size -0.278*** -14.125 0.099 1.550 (0.049) (10.303) (0.093) (1.747) Income diversification 0.279 -2.591 -0.277 -0.652 (0.202) (7.435) (0.328) (2.007) Market growth 0.012 -4.101 0.020 0.116 (0.048) (4.024) (0.014) (0.281) Foreign Capital -0.172 -10.753 0.324** 6.607* (0.139) (7.446) (0.127) (3.867) Listed 0.595** 29.356 -0.287 -7.968 (0.223) (22.636) (0.213) (14.594) Constant -3.531 -93.017 0.820 8.667

(1.987) (41.330) (138.326) √ √ √ 72 269 269

Fixed effects No. of observations R-squared

(4.582) √ 72

0.339 0.215 0.345 0.227 No. of banks 89 89 89 89

Bank individual fixed effects are included in the regression. Standard errors are clustered at bank level. Robust standard errors in parentheses. ***, **, * indicate statistical significance at the 1%, 5%, and 10% (two-tail) test

levels, respectively.


29

Table 5 Results for robustness checks

Dependent Variables Independent variables NIR NIR Net interest margin Net interest margin HHI -5.521* -7.310*** -15.079*** -18.105*** (2.921) (2.751) (4.772) (5.140) Market share (asset) -6.447 -2.273 (6.233) (10.162) Market share (loan) -18.839* -23.257** (9.524) (10.017) Capital strength -0.000 -0.019 0.047** 0.008 (0.026) (0.019) (0.023) (0.021) Bank cost 3.315 11.455 21.387 25.888 (28.452) (27.633) (24.753) (24.406) Bank size 0.101 0.083 -0.010 -0.059 (0.062) (0.065) (0.078) (0.086) Income diversification -0.172 -0.172 -0.817*** -0.851*** (0.337) (0.317) (0.242) (0.252) Market growth 0.012 0.005 -0.004 -0.008 (0.013) (0.013) (0.020) (0.018) Foreign Capital 0.348** 0.401*** -0.037 0.080 (0.133) (0.112) (0.223) (0.218) Listed -0.309** -0.335*** -0.262 -0.402* (0.123) (0.096) (0.242) (0.237) Inflation 0.050*** 0.052*** 0.086*** 0.087*** (0.016) (0.016) (0.013) (0.013) GDP growth -0.039* -0.036* -0.040 -0.040 (0.021) (0.019) (0.025) (0.024) Constant 0.935 1.554 4.016** 5.529*** (1.252) (1.217) (1.655) (1.780) Fixed effects √ √ √ √ No. of observations 340 348 340 348 R-squared 0.279 0.289 0.464 0.425 No. of banks 95 97 95 97

Note: Market share (loan) is total loans in each bank as a percentage of the market. The formulation of HHI is

HHI=∑(Market Share)2 . The formulation of NIR is NIR= (1 + ROAA)/(1 + net interest margin/total assets).Bank

individual fixed effects are included in the regression. Standard errors are clustered at bank level. Robust standard errors

in parentheses. ***, **, * indicate statistical significance at the 1%, 5%, and 10% (two-tail) test levels, respectively.

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