How does bank ownership affect firm investment? Evidence from China

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How does bank ownership affect firm investment? Evidence from China Hongjian Wang a, Tianpei Luo b, Gary Gang Tian c,∗, Huanmin Yan a a

Department of Accounting, Nanchang University, Jiangxi, China Department of Finance and Banking, Curtin University, Australia c Department of Applied Finance, Macquarie University, Australia b

a r t i c l e

i n f o

Article history: Received 30 August 2018 Accepted 9 January 2020 Available online xxx JEL: G21 G31 G32 G34 Keywords: Bank ownership Investment efficiency Ownership structure Corporate cash holding Bank loan Chinese capital market

a b s t r a c t This study examines how holding voting shares in banks can impact the improvement of firms’ investment efficiency in the Chinese capital market. We found that bank ownership improved firms’ investment efficiency by mitigating both overinvestment and underinvestment and by improving investment sensitivity to investment opportunities. We further found that alleviation of overinvestment in firms was driven by the enhancement of corporate governance (disclosure channels). The better corporate governance in bank holding firms reduced corporate cash holdings and controlling shareholder expropriations. Moreover, we found that this bank-firm connection reduced underinvestment by mitigating financial constraints (financing channels), through the raising of more bank loans and the reduction of the cash flow sensitivity of cash holdings. This connection also served as a buffer when bank lending is tightened. Finally, we found that bank ownership had a more pronounced impact on improving investment efficiency in non-SOEs, in firms located in provinces with low marketization, and in firms without institutional investors.

1. Introduction This study investigates whether non-financial firms’ ownership of voting shares in banks (henceforth, bank ownership) alleviates investment inefficiency in China. Previous research has documented that investment inefficiency can be potentially relieved if banks control non-financial firms (see, e.g., Jiang et al., 2010b; Kang and Shivdasani, 1995), thus forming what we refer to as an “upward vertical” relationships. However, the cost of this upward vertical relationship, such as potential collusion between bank managers and firms, may eventually outweigh the abovementioned benefits and even adversely affect firms’ value especially in emerging markets (Lin et al., 2009; Luo et al., 2011; MahrtSmith, 2006). This paper contributes to the literature by looking at a lessdiscussed alternative bank-firm connection that is, the mechanisms through which non-financial firms directly acquire banks’ shares and become shareholders of banks. We refer to such bank-firm

∗

Corresponding author. E-mail addresses: [email protected] (H. Wang), [email protected] (T. Luo), [email protected] (G.G. Tian), [email protected] (H. Yan).

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relationships as “downward vertical” relationships and the focal firms as bank holding firms. This downward vertical bank-firm connection is not unique to China and can be found in other countries, especially in the developing ones.1 Many controlling shareholders of business groups own banks and financial institutions in Asia and even in Europe (Faccio et al., 2003; La Porta et al., 2003); some examples of such business groups include the SK Group in Korea, the Tata Group in India and Daimler Group in Germany . Nevertheless, little attention has been paid to this alterative bankfirm connection, including the impacts of bank ownership on cor-

1 For example, Mexican banks are typically controlled by shareholders of nonfinancial firms (La Porta et al., 2003). Banks that are owned or controlled by individuals or entities are also prevalent in many other developing countries, including Brazil, Chile, Russia, and Turkey. In developed markets such as Germany, Japan, and South Korea, among business groups, many shareholders that control nonfinancial corporations also own banks and other financial institutions (Faccio et al., 2003). However, in the US, a bank holding company (BHC) is defined as any company that has control over a bank through its ownership of more than 25% of the bank’s voting stock (https://www.fdic.gov/regulations/laws/rules/750 0-210 0. html#fdic7500sec.2). However, to the best of our knowledge, it seems that most BHCs are financial institutions. Therefore, the BHCs in the US are not the same as the bank holding firms in this paper, which are defined as nonfinancial firms who are shareholders in banks.

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porate investment decisions, especially in emerging markets.2 This study intends to fill this void by investigating whether and how bank ownership influences firms’ investment decisions in China. We believe that this downward vertical relationship may not only help bank holding firms maintain the benefits of accessing bank loans as the banks’ related parties but that it may also alleviate agency costs, which could consequently enhance investment efficiency. We propose that bank ownership could improve investment efficiency through the disclosure channel effect and the financing channel effect. With regard to bank ownership, the disclosure channel effect reduces potential conflicts of interest between insiders (controlling shareholders and managers) and minority shareholders, thus mitigating overinvestment, and the financing channel effect strengthens a firm’s financing capacity, consequently mitigating underinvestment. First, we hypothesize that bank ownership may alleviate firms’ overinvestment arising from agency problems. Previous studies argued that transparent financial reporting and intense supervision from regulatory agencies could enhance corporate governance (Biddle et al., 2009; La Porta et al., 20 0 0). In China, bank holding firms are supervised by two regulatory agencies: China Security Regulatory Commission (CSRC) and China Banking Regulatory Commission (CBRC); firms in general are supervised only by CSRC. Meanwhile, bank holding firms must comply with additional disclosure requirements; this situation improves information transparency of bank holding firms. Thus, stringent disclosure requirements and dual monitoring largely inhibit insiders from undertaking value-destroying activities (Chen et al., 2011). In addition, we hypothesize that bank ownership will strengthen a firm’s financing capacity and mitigate underinvestment. As a shareholder of the bank, a bank holding firm can assign representatives to the bank’s board of directors. These representatives are likely to influence bank managers’ lending decisions, which, in turn, benefits bank holding firms (see, e.g., Charumilind et al., 2006; La Porta et al., 2003). The bank-firm connection also facilitates the bank in obtaining the related firm’s information; this helps to reduce a bank’s concern regarding a firm’s risk of default. Furthermore, being regard as a related party to the banks, the bank holding firms will be more likely to obtain a line of credit from connected banks in China. These privileges reduce a firm’s cost of capital and enhance its flexibility in terms of obtaining bank loans. As financial constraint is one of the major frictions causing underinvestment, we propose that bank ownership may alleviate financial constraint and consequently reduce underinvestment. To test our above-mentioned propositions, we focused on the Chinese capital market, which provides the unique institutional settings for this study. Our reasons for choosing this setting were as follows. First, the Chinese setting provides an ideal laboratory for investigating firms’ investment decisions under conditions presenting both financial constraints and agency conflicts (Guariglia and Yang, 2016). The underdeveloped Chinese stock market, coupled with the absence of a mature bond market, induces serious financial constraints in most firms. At the same time, the weak legal institutions and poor corporate governance mechanisms cause rather severe agency problems. This institutional setting makes the effects of bank ownership more pronounced and the bank-firm connections more prevalent in China. Second, in contrast with other countries where banks are able to acquire ownership of listed firms (e.g., the Japanese banking group [financial keiretsu], the German universal banks, and the 2 With a few exceptions, Lu et al. (2012) found that bank ownership alleviated bank discrimination against private firms and improved their performance, while La Porta et al. (2003) documented that related lending through bank ownership was a manifestation of looting.

US banks that control firms through their trust businesses), under China’s Banking Law, which was implemented in 1995, commercial banks are forbidden from acquiring stocks in firms.3 However, the Law allows firms to acquire bank shares. This unique institutional environment provides a clean setting for examining whether and how bank ownership can influence firms’ investment decisions. Bank holding firms grew fast with government support from both state governments and the State-owned Asset Supervision and Administration Commission of the State Council (SASAC). Based on our sample, we found that there were 133 listed bank holding firms in China in 2004, which accounted for about 8% of the listed firms on the Shanghai and Shenzhen Stock Exchanges. By the end of 2016, about 16% of the listed firms (467 firms) had invested in banks. The popularity of bank holding firms in China makes our study into this phenomenon a worthwhile contribution to the research literature. We drew on a sample of listed non-financial A-share firms that were operating in China during the 2005–17 period, and our main findings are summarized below. First, we employed two measurements for investment efficiency: investment inefficiency by Richardson (2006) and investment sensitivity to investment opportunities by McLean et al. (2012). We found that bank ownership reduced investment inefficiency and improved investment sensitivity to investment opportunities. These results support our argument that bank ownership improves firms’ investment efficiency. Second, we investigated the channels through which bank ownership influenced investment efficiency. Consistent with our argument of disclosure channels, we found that bank ownership improved the financial reporting quality in bank holding firms. The enhancement of information disclosure and dual regulatory agencies’ supervision helped to improve the corporate governance; this consequently alleviated controlling shareholders’ tunneling through related-party transactions. In addition, bank ownership reduced the agency motive of corporate cash holdings and improved the value of cash, especially in firms with weaker corporate governance. In line with our argument regarding financing channels, we found that bank ownership empowers firms to access more bank loans and reduces their incentives to save cash out of cash flow. The influence of bank ownership with regard to alleviating financial constraints is particularly important when the macroeconomic situation is unfavorable, and bank lending has been tightened. Finally, we found that holding bank ownership had a more pronounced impact in privately owned enterprises (non-SOEs), in firms located in low-marketization provinces, and in firms without institutional investors. In addition, we found that bank ownership improved the firm’s value. We assessed the robustness of our main findings; with regard to corrections for potential sample selection bias and endogeneity concerns related to bank ownership, we used the Heckman two stage selection model with instrument variables and propensity score matching. The evidence of robustness was also immune to different measurements for bank ownership, potential measurement error related to the investment inefficiency proxy, and alternative explanations. Overall, our results supported that bank ownership improved investment efficiency in China. This study makes several contributions to the extant literature. First, our study enriches research regarding the bank-firm connection. Most existing studies on this subject focus on the upward vertical relationship, where banks dominate the bank-firm connec-

3 Although banks cannot acquire firm ownership through direct investment, it is worth noting that there are a few firms whose ownership is held by banks. These firms’ ownerships were acquired before the passage of the Commercial Bank Law in 1995 and were not liquidate for some reasons. Luo et al. (2011) reported that there were 51 firms owned by banks in 2006, which were about 3% of the listed firms on the Shanghai and Shenzhen Stock exchanges.

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tions: banks appropriate most of the benefits (Bae et al., 2002), play a less effective monitoring role (Luo et al., 2011), and distort firms’ investment decisions (Lin et al., 2009), especially in emerging markets. We investigated the issue of bank-firm connections utilizing a different angle that of firms acquiring bank ownership and becoming shareholders in banks. We found that this downward vertical bank-firm connection (i.e., one where the firm dominates the connection) can effectively improve investment efficiency in an emerging market like China. This finding indicated that the party that controls the bank-firm connection is critical to its value in terms of investment decisions. Second, our paper aims to add new insights to this emerging scholarship by extending understanding of the economic consequences of bank ownership. We identified that improving investment efficiency could be another channel through which bank ownership can affect firms’ performance. This finding could have profound implications for the regulatory design of banking institutions in emerging markets, and it may also contribute to solving the mixed results regarding the value of bank ownership in previous studies (La Porta et al., 2003; Lu et al., 2012). Finally, our study contributes to the literature on the determinants of firm-level investment efficiency and documents how bank ownership improves investment efficiency. The remainder of this paper is organized as follows. Section 2 provides the institutional background of China and develops our hypotheses. Section 3 describes the data, sample, variable measures, and methodology. Section 4 presents the empirical results and interpretations, and Section 5 summarizes and concludes this paper. 2. Institutional background and hypothesis development 2.1. The institutional background of bank ownership The Chinese economy has been growing substantially since the 1990s, and the demand for capital from the financial market has increased. The fast-growing Chinese firms are eager to seek help from banks in gaining capital by establishing bank-firm connections. However, the Commercial Bank Law in China (adopted in 1995 and revised in 2003) prohibits commercial banks from acquiring shares in firms.4 Instead, firms are allowed to invest in banks and become bank holding firms if firms meet certain qualification criteria. This regulation enables Chinese firms to build bankfirm connections in a way that is distinct from that of other countries where the upward vertical relationships dominates the connections. With growing awareness of the synergy within bank-firm connections, new regulations have been enacted in order to encourage firms to acquire banks ownership in China. In 2008, the CBRC announced the “Regulation of Controlling Shareholders in Banks,” which stipulates the requirements for firms that seek to become shareholders in banks and assists firms in making investments in banks.5 During the National People’s Congress meeting and Chinese Political Consultative Conference in 2012, the central government officially promoted firms to become shareholders in banks. In March 2013, the Ministry of Industry and Information Technology, People’s Bank of China, and CBRC proposed a specific scheme and 4 According to the Commercial Bank Law, commercial banks cannot become shareholders of listed companies through public offerings. In addition, the law prohibits commercial banks from becoming shareholders of listed companies through other channels for example, becoming legal shareholders of distressed companies that defaulted on their loans or through a debt-for-equity swap. 5 For example, in 2009, the China Baowu Steel Group, China Aerospace Science and Technology Corporation, Shenergy Group, and 5 other SOEs acquired 15.5% ownership in China Everbright Bank for RMB 11.5 billion. Detailed information regarding this can be found via http://finance.qq.com/a/20 090827/0 02341.htm.

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program calendar to further encourage firms to acquire bank ownership. These new regulations enable firms to acquire bank ownership in China. 2.2. Does bank ownership improve investment efficiency? Prior literature shows that bank-firm connections assist in providing oversights to listed firms and facilitate capital flows between firms and external financial markets (Jiang et al., 2010a; Kang et al., 20 0 0; Nini et al., 2012; Vashishtha, 2014). Lu et al. (2012) found that bank holding firms in China can enjoy benefits such as lower financial expenses and better lending terms. Therefore, bank ownership may overcome market frictions and alleviate investment inefficiency. We thus expected to find that bank ownership reduces market frictions and improves investment efficiency in bank holding firms and developed the following hypothesis: H1a. : Bank ownership improves investment efficiency. However, acquiring bank ownership may reduce the free cash flow of bank holding firms. The reduced free cash flow could check insiders’ overinvestment decisions, but it may deteriorate the underinvestment. If this argument holds, the overall effect of bank ownership on investment efficiency remains unclear. Therefore, we developed the following competing hypothesis: H1b. : Bank ownership has no effect on or worsens investment efficiency. 2.3. How does bank ownership affect investment efficiency? 2.3.1. Bank ownership, the agency problem, and overinvestment: disclosure channel Information transparency, an efficient corporate governance mechanism, is expected to reduce agency costs and, in turn, mitigate insiders’ ability to make overinvestment decisions (Biddle et al., 2009). In developed countries such as Japan and South Korea, bank holding firms are usually under closer scrutiny from regulatory agencies and are mandated to provide comprehensive disclosures. For example, in Japan, the Japanese bank’s principal shareholders are supervised by the Financial Service Agency of Japan (FSA), which is the primary regulator of the Japanese banking industry. Under the Banking Act, bank’s principal shareholders are required to provide financial reports and other necessary documents required by the FSA and take any actions the FSA considers necessary (Akagami et al., 2018). In South Korea, the Financial Services Commission (FSC) conducts frequent audits of bank’s shareholders and requires them to regularly report their financial conditions and other required details. These stricter supervisory powers and additional disclosure requirements serve as tools for supervising shareholders of major banks, especially if there are signs of unlawful related-party transactions.6 In China, in addition to meeting the standard disclosure requirements imposed by and monitored by the CSRC, bank holding firms, especially those with a bank ownership above 5%, are more stringently supervised by the CBRC and must comply with higher disclosure standards. For example, a firm seeking to acquire more than 1% ownership in a bank must report to the CBRC for approval. The CBRC screens the source of capital utilized for the acquisition and the bidder’s background to ensure that the bidder is practicing good corporate governance and to safeguard against any deals being initiated to facilitate insiders’ expropriations. Firms that have 6 Further detailed information can be found via https://www.lexology.com/ library/detail.aspx?g=cc90c51e- 9095- 4520- 9620- 1f27230a7694.

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opacity in terms of accounting information and ownership structure and frequently unusual related-party transactions are not allowed to acquire bank ownership. In addition, to prevent insiders from pursuing private benefits through bank ownership, the CBRC subjects bank holding firms to intense monitoring and requires them to disclose all necessary information, as mandated by the CBRC. These firms are also required to report any operational decisions that could affect firm performance to the CBRC in a timely and accurate manner. This regulation requires bank holding firms to report all related-party transactions to the CBRC, especially transactions related to banks, rather than only transactions that could significantly affect firm performance. Such strengthened disclosure requirements and monitoring enforced by the CBRC enhance information transparency and contribute to improving corporate governance in bank holding firms, which, in turn, largely mitigate insiders’ expropriations. Stricter disclosure requirements improve monitoring of bank holding firms and improve corporate governance; we thus expected that bank ownership would alleviate overinvestment caused by agency conflicts (the disclosure channel). Therefore, we developed the following hypothesis: H2. : Bank ownership mitigates overinvestment by alleviating agency conflicts. 2.3.2. Bank ownership, financial constraints, and underinvestment: financing channel Financial constraint is one well documented major reason for underinvestment. As the most important financial intermediary, banks specialize in raising funds for firms and providing information to investors. Bank-firm connections developed through bank ownership could strengthen firms’ ability to raise capital by influencing bank managers’ lending decisions and facilitate banks in accumulating propriety information about firms, which could consequently reduce their concerns regarding loan defaults (Ferreira and Matos, 2012; Lu et al., 2012). In China, holding 5% in a bank’s ownership enables the firm to assign representatives to the bank’s board of directors. These representatives are more likely to influence bank managers’ decisions, especially with regard to related-party lending. Even though the CBRC imposes restrictions on related-party lending, bank holding firms can obtain a line of credit, which can be equivalent to up to 10% of a bank’s equity. Bank ownership thus enables firms to access an additional source of capital from the connected banks and thus alleviates their financial constraints. Based on the above-mentioned arguments, we expected that bank ownership would mitigate financial constraints and alleviate underinvestment in bank holding firms (the financing channel). Therefore, we developed the following hypothesis: H3. : Bank ownership mitigates underinvestment by alleviating financial constraints. 2.4. The conditional effects of bank ownership on investment efficiency 2.4.1. Bank ownership, state ownership, and investment efficiency Ownership homogeneity among banks and SOEs and implicit government guarantees regarding repayments unsurprisingly prioritize SOEs in obtaining bank loans (Megginson et al., 2014). This preferential treatment mitigates SOEs’ incentive to acquire bank ownership for accessing the capital market. Moreover, local governments are incentivized to intervene in investment decisions taken by SOEs for social and political agendas, which may cause overinvestment, regardless of their status as bank holding firms. In contrast, non-SOEs suffer from banking discrimination and often face more severe financial constraints; they therefore display greater

willingness to initiate bank connections. The bank ownership is expected to be more valuable in non-SOEs. We thus expect the positive impact of bank ownership on investment efficiency to be more pronounced in non-SOEs; we developed the following hypothesis: H4a. : The impact of bank ownership on improving investment efficiency is more pronounced in non-SOEs. 2.4.2. Bank ownership, institutional development, and investment efficiency Prior studies show that institutional development has a significant impact on firm’s investment decisions. A well-developed financial market enables firms to raise capital from diversified sources (Lin et al., 2009), and strong legal protections check agency conflicts (Burkart and Panunzi, 2006). Therefore, a developed institutional environment could mitigate for bank ownership’s impact on investment efficiency. The variations in institutional environments across China allowed us to test this argument. We expected that bank ownership would have a more pronounced impact on investment efficiency in less developed regions with low marketization; thus, the following hypothesis was developed: H4b. : The impact of bank ownership on improving investment efficiency is more pronounced in regions with low marketization. 2.4.3. Bank ownership, institutional investors, and investment efficiency Previous research has shown that institutional investors’ presence is likely to intensify the demand for analyst services with regard to firm performance (Frankel et al., 2006). Thus, institutional ownership improves managerial disclosure and reduces information asymmetry (Boone and White, 2015); this, in turn, reduces the firm’s financial constraints (Bhojraj and Sengupta, 2003). Furthermore, institutional investors can effectively monitor corporate behavior with regard to mitigating agency problems and implement strong corporate governance (Bena et al., 2017). These substitution effects could diminish the positive relationship between bank ownership and investment efficiency. Therefore, we developed the following hypothesis: H4c. : The impact of bank ownership on improving investment efficiency is more pronounced in firms without institutional investors. 3. Sample selection and methodology Our sample included all listed A-share firms on the Shanghai and Shenzhen stock exchanges during the 2004–17 period. The data were collected from the WindDB database and the China Security Market and Accounting Research (CSMAR) database, which are the most widely used databases for Chinese capital market studies. We focused on bank ownership data with 2004 as the starting point, because from 2004 onward, the WindDB database started to report data for bank ownership held by listed firms.7 As most of these data were missing in 2004, we manually added these missing bank ownership data by examining firms’ annual reports and announcements. As financial firms have different reporting requirements, we excluded listed financial firms from our sample. We also excluded firm-year observations that lacked information with regard to variables. To minimize outlier impact, we winsorized our sample at 1% with regard to each variable in each tail. The final sample contains 22,258 firm-year observations from the 2005–17 period, including all non-financial industries according to the 2012 CSRC industry classification. 7 We used the lagged value of bank ownership in our regression because bank ownership is expected to influence firms’ investment decisions after the bank’s ownership has been acquired.

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3.1. Bank holding firms Following Lu et al. (2012), we defined a bank holding firm as a dummy variable, Bank, which equals 1 if the listed firm is a shareholder in at least one bank, and 0 otherwise. To provide robust evidence, we employed two other proxies for bank ownership to measure a bank holding firm. BankN indicated the number of banks a firm invested in. BankR indicated the highest percentage of bank ownership held by a firm in our sample.

3.2.2. Basic empirical regression models Following Chen et al. (2011) and Biddle et al. (2009), we estimated Eq. (2) to test our hypotheses. This regression model was as follows:

Investment Ine f f iciencyi,t =

3.2. Methodology and regression models 3.2.1. Measuring investment efficiency We measured investment efficiency in two different ways. First, following Richardson (2006), we measured investment inefficiency by using deviations in investment expenditure from the optional level of investment.8 Second, we measured investment efficiency by using the investment sensitivity to investment opportunities measured by Tobin’s Q, following Chen et al. (2017) and McLean et al. (2012), among others. The lower deviation from the optional level of investment and higher investment sensitivity to investment opportunities indicated more efficient investment decision-making. Richardson (2006) decomposes new investments-related expenditure into expected investment expenditure and inefficient investment expenditure (overinvestment or underinvestment). Expected investment is the function of growth opportunities and other factors that may affect investment decisions, while inefficient investment is the deviations from the optimal level of investment expenditure, which is caused by frictions, such as agency problems and/or financial constraints. Following Richardson (2006), we employed the following model to predict the optimal investment expenditures:

Investmenti,t =

α0 + α1 T bqi,t−1 + α2 Investmenti,t−1 + α3 Reti,t−1 + α4Cash Holdingi,t−1 + α5 Lnsizei,t−1 + α6 Lnagei,t−1 + α7 Levi,t−1 + Year Indicators + Industry Indicators + εt

We defined Investmenti,t as the total investment expenditures scaled by the total assets for firm i in year t. We contlled for the firm’s growth opportunity (lagged by one year) by using Tobin’s Q (Tbqi,t-1 ), which is the ratio of the market value of assets to the current replacement cost for these assets. We also controlled for other one-year lagged variables that were shown as determinants of investment decisions in prior research; these included investment expenditure (Investmenti,t-1 ), annual stock return (Reti,t-1 ), cash holdings (Cash Holdingi,t-1 ), firm size (Lnsizei,t-1 ), listed age (Lnagei,t-1 ), and leverage (Levi,t-1 ). We also included industry- and year-fixed-effects to control for unobservable industry- and yearspecific factors. Investment inefficiency is the difference between actual investment expenditure and expected investment; this is measured by the residual of Eq. (1). It can be either positive or negative, corresponding to overinvestment or underinvestment, respectively. The advantage of this method is that it decomposes investment inefficiency and enables us to distinguish the impact of disclosure channel and financing channel of bank ownership on reducing overinvestment and underinvestment, respectively. 8 This is a widely used method for investigating investment efficiency in accounting literature as well as in finance literature. For example, previous studies found that financial constraints, agency problems, and government intervention deteriorated investment efficiency among Chinese listed firms (Deng et al., 2017; Guariglia and Yang, 2016), while corporate philanthropy and the presence of multiple large shareholders effectively reduced value-destroying investment decisions (Chen et al., 2018; Jiang et al., 2018).

β0 + β1 Banki,t−1 + β2 Lnsizei,t−1 + β3 Tangi,t−1 + β4 ROAi,t−1 + β5 Lossi,t−1 + β6 Big4i,t−1 + β7 Lnboar di,t−1 + β8 Duali,t−1 + β9 L arg esti,t−1 + Year Indicators + F irm indicators + εi,t (2)

where Investment Inefficienti,t measures the investment inefficiency. This is the absolute value of residual of the Eq. (1). The positive residual and the negative residual’s absolute value were employed to measure overinvestment (Overinvestment) and underinvestment (Underinvestment), respectively. Banki,t -1 is a dummy variable that takes the value of 1 if a firm is a shareholder in at least one bank. We expected that Banki,t -1 would be negatively and significantly associated with investment inefficiency. Motivated by previous studies, we controlled the firm size (Lnsizei,t-1 ), tangibility (Tangi,t-1 ), return on assets (ROAi,t-1 ) and losses (Lossi,t-1 ) for the financial characteristics of firms. We also included firm’s auditor (Big4i,t-1 ), board size (Lnboardi,t-1 ), CEO duality (Duali,t-1 ), and the largest shareholder ownership (Largesti,t-1 ) to control for corporate governance. We also included the firm- and year-fixed-effect to control for the unobservable firm-, and year-specific factors. A detailed definition of the variables is presented in Appendix A. To provide robust results regarding bank ownership’s impact on improving investment efficiency, we also employed an alternative investment efficiency measurement following Chen et al. (2017) and McLean et al. (2012). We proxy for investment efficiency by using the investment sensitivity to investment opportunities measured by Tobin’s Q. This model was as follows:

Investment =

(1)

5

β0 + β1 Banki,t−1 + β2 T bqi,t−1 + β3 Banki,t−1 × T bqi,t−1 + β4 Lnsizei,t−1 + β5 Tangi,t−1 + β6 ROAi,t−1 + β7 Lnboar di,t−1 + β8 Big4i,t−1 + β9 Lossi,t−1 + β10 Duali,t−1 + β11 L arg esti,t−1 + β12 Investi,t−1 + β13 Reti,t−1 + β14Cash Holdingi,t−1 + β15 Levi,t−1 + β16CF Oi,t−1 + β17 Lnagei,t−1 + Year Indicators + F irm indicators + Industry Indicators + εi,t (3)

where dependent variable, Investmenti,t , is firm i’s investment expenditure scaled by the total assets in year t. The Tobin’s Q (Tbqi,t-1 ) measures the growth opportunities, which is the ratio of the market value of assets to the current replacement cost of these assets. Banki,t -1 × Tbqi,t -1 is the interaction term between bank ownership and Tobin’s Q. We expected that the coefficient of the interaction term would be positive and statistically significant, thus indicating that bank ownership improved investment efficiency. We also controlled other factors that could potentially affect the firm’s investment decisions and the unobserved firmsand year-specific factors. All these variables’ definitions are listed in Appendix A. 4. Empirical results 4.1. Sample description and univariate tests Table 1 presents the descriptive statistics of our sample and the univariate tests. Panel A of Table 1 shows that 38% (=8368/22,258)

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H. Wang, T. Luo and G.G. Tian et al. / Journal of Banking and Finance xxx (xxxx) xxx Table 1 Summary statistics and univariate tests. Panel A. Summary statistics. The Panel A of Table 1 presents summary statistics for our variables including the number of observations, mean, standard deviation (Std.), 25% percentile (P25), median (P50), and 75% percentile (P75). Variables are defined in Appendix A. Variable

No.

Mean

Std.

P25

P50

P75

Investment Efficiency Overinvestment Underinvestment Investment Bank Cashholding Loan RPT Discretionary Accruals Lnsize Tang ROA Lnboard Big4 Loss Dual Largest Excess Stock25 Lev CFO Mshare InDep Lnage Growth Tbq I D

22,258

0.0253

0.028

0.0081

0.017

0.031

8 368 13 890 22,258 22,258 22,258 22,258 21,839 21,832

0.0336 0.0202 0.0508 0.1579 0.1683 0.1775 0.3311 0.0631

0.0378 0.0182 0.0501 0.3663 0.1208 0.1507 0.4536 0.0652

0.0074 0.0085 0.014 0.0000 0.0832 0.0432 0.0538 0.0191

0.0202 00,159 0.0355 0.0000 0.1369 0.1564 0.1878 0.0425

0.0459 0.0262 0.071 0.0000 0.2207 0.2765 0.4258 0.0826

22,258 22,258 22,258 22,258 22,258 22,258 22,258 22,258 22,241 22,241 22,258 22,258 21,839 21,839 22,258 22,241 22,258 21,802 21,802

21.8387 0.2536 0.0333 2.1234 0.0591 0.1069 0.1934 0.3616 0.0601 0.4598 0.4714 0.0401 0.0558 0.3908 2.1375 0.2157 2.0939 0.0245 0.0092

1.2611 0.1786 0.0603 0.2611 0.2358 0.309 0.3949 0.1537 0.0833 0.3766 0.2167 0.0687 0.1357 0.0973 0.6812 0.572 1.9932 0.0167 0.0124

20.9503 0.1137 0.0114 1.9459 0.0000 0.0000 0.0000 0.2395 0.0000 0.1658 0.3068 0.0033 0.0000 0.3333 1.6094 −0.0248 0.8105 0.0131 0.0003

21.6917 0.2201 0.0325 2.1972 0.0000 0.0000 0.0000 0.3402 0.0000 0.3634 0.4751 0.0385 0.0000 0.3333 2.3026 0.1201 1.4771 0.0219 0.0078

22.554 0.3658 0.0611 2.1972 0.0000 0.0000 0.0000 0.4745 0.1181 0.6479 0.628 0.0788 0.0022 0.4286 2.7081 0.297 2.6115 0.03222 0.0168

Panel B Univariate test of the impact of bank ownership on reducing investment inefficiency. The panel B of Table 1 presents the univariate tests of investment inefficiency (Overinvestment and Underinvestment) for bank holding firms and non-bank holding firms. ‘Non-bank holding firms’ and ‘Bank holding firms’ refers to non-bank holding firms and bank holding firms, respectively. ‘Investment Inefficiency’ is the deviation from optimal level of investment which is the absolute value of the residual of Eq. (1). ‘Overinvestment’ measures the potential overinvestment which is the absolute value of positive residual of Eq. (1). ‘Underinvestment’ measures potential underinvestment which is the absolute value of negative residual of Eq. (1). ‘Difference Tests’ columns report p value for T-test and for Wilcoxon test of difference in mean and median, respectively. ∗ , ∗ and ∗∗∗ represent significant at 10%, 5% and 1% levels, respectively. Investment inefficiency

Non-bank holding firms Bank holding firms Difference tests (p value)

Overinvestment

Underinvestment

Mean Test

Median Test

Mean Test

Median Test

Mean Test

Median Test

0.0259

0.0172

0.0346

0.0208

0.0207

0.0162

0.0217 0.0042∗∗∗ (0.000)

0.0155 0.0017∗∗∗ (0.000)

0.0281 0.0065∗∗∗ (0.000)

0.0176 0.0031∗∗∗ (0.000)

0.0181 0.0026∗∗∗ (0.000)

0.0148 0.0014∗∗∗ (0.000)

of firms experienced overinvestment, while an overwhelming majority of sample firms suffered underinvestment. This result confirmed that Chinese firms were more likely to be subject to underinvestment due to the difficulties they experienced in accessing external financing. We also found that 16% of listed firms were bank holding firms. Panel B of Table 1 reports the univariate test results for investment inefficiency among bank holding firms and non-bank holding firms. The results indicated that the investment inefficiency problem was less server in bank holding firms. Moreover, bank ownership significantly reduced both underinvestment and overinvestment. This finding is consistent with our hypotheses H1a. 4.2. Does bank ownership improve investment efficiency? Table 2 presents the results of Eq. (2) for the full sample in Column 1 and the overinvestment and underinvestment subsamples in Column 2 and Column 3, respectively. We also reported the results in Column 4 by using Eq. (3) for the investment sen-

sitivity to investment opportunities measure of investment efficiency. Supporting our conjecture, the result in Column 1 indicates that the coefficient on Bank is negative and significant at the 1% level. It suggests that bank ownership reduces investment inefficiency; this finding supports our Hypothesis H1a. The results reported in Columns 2 and 3 reveal that bank ownership is significantly and negatively associated with both underinvestment and overinvestment. Column 4 shows that the coefficient of interaction term, Bank × Tbq, is positive and statistically significant, thus indicating that bank ownership improves investment sensitivity to investment opportunities and increases investment efficiency in bank holding firms. In terms of control variables, tangibility (Tang) has a significant negative coefficient, indicating that a higher volume of tangible assets leads to higher investment efficiency; this finding is consistent with the findings of Bae et al. (2017) and Chen et al. (2018). We found that firm size (Lnsize) improved investment efficiency. The coefficients of return on assets (ROA) and largest shareholder’s ownership (Largest) were positive and significant, thus suggest-

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Table 2 The impact of bank ownership on investment efficiency. This table presents the empirical results on the impact of bank ownership on investment efficiency. The dependent variable in Column 1 is investment inefficiency, ‘Investment Inefficiency’ which is the absolute value of deviation from the optimal investment estimated from Eq. (1). Columns 2 and 3 present the regression results for the impact of bank ownership on overinvestment and underinvestment, respectively. Overinvestment is measured by the positive residuals from Eq. (1) and Underinvestment is measured by the absolute value of negative residuals from Eq. (1). The Column 4 presents the regression result for the impact of bank ownership on investment sensitivity to investment opportunity from Eq. (3). The dependent variable, ‘Investment’ is measured the total investment expenditures scaled by the by the total assets. The independent variable, Bank, is a dummy variable which takes the value of 1 if a firm is a bank holding firm, and 0 otherwise. The independent variable (Tbq) is the ratio of the market value of assets to the current replacement cost of these assets. The independent variable (Bank × Tbq) is the interaction term of Bank and Tbq. Control variables are defined in Appendix A. All independent variables are one year lagged. All regressions include firm and year fixed effect. Robust standard errors are clustered at the firm level and reported in parentheses. ∗ , ∗∗ and ∗∗∗ indicate significance at the 10%, 5% and 1% levels, respectively. (1)

(2)

(3)

Dependent variables: Investment inefficiency

Bank

Dependent variables: Investment

Full sample

Overinvestment

Underinvestment

Full sample

−0.0024∗∗∗ (0.0009)

−0.0045∗∗ (0.0021)

−0.0013∗∗ (0.0006)

−0.0042∗∗∗ (0.0006) −0.0199∗∗∗ (0.0031) 0.0410∗∗∗ (0.0063) 0.0020 (0.0016) −0.0014 (0.0019) 0.0009 (0.0009) −0.0004 (0.0008) 0.0063∗ (0.0037)

−0.0107∗∗∗ (0.0012) −0.0412∗∗∗ (0.0068) 0.0628∗∗∗ (0.0149) 0.0019 (0.0039) −0.0009 (0.0045) 0.0025 (0.0024) 0.0001 (0.0020) 0.0013 (0.0078)

−0.0003 (0.0004) −0.0007 (0.0026) 0.0204∗∗∗ (0.0043) 0.0009 (0.0013) −0.0004 (0.0013) −0.0000 (0.0007) −0.0009 (0.0006) 0.0061∗∗ (0.0028)

0.1220∗∗∗ (0.0131)

0.2773∗∗∗ (0.0282)

0.0312∗∗∗ (0.0101)

0.0008∗∗∗ (0.0003) −0.0009 (0.0015) 0.0014∗∗ (0.0007) −0.0023∗∗∗ (0.0009) −0.0424∗∗∗ (0.0045) 0.0545∗∗∗ (0.0095) 0.0028 (0.0024) −0.0022 (0.0030) 0.0002 (0.0012) 0.0014 (0.0011) 0.0085∗ (0.0051) 0.3165∗∗∗ (0.0104) 0.0015∗∗∗ (0.0006) 0.0461∗∗∗ (0.0043) −0.0132∗∗∗ (0.0032) −0.0031 (0.0047) −0.0030 (0.0019) 0.0971∗∗∗ (0.0191)

Tbq Bank × Tbq Lnsze Tang ROA Lnboard Big4 Loss Dual Largest Invest Ret Cash Holding Lev CFO Lnage _cons

β 2 +β 3 = 0

9.16∗∗∗ (0.003)

(p-value) Firm and Year Effect A.dj. R2 F Value N

(4)

Control 0.057 29.5966 22,258

Control 0.066 11.2853 8368

ing that past firm performance and ownership concentration reduced investment efficiency. These findings were generally consistent with those of previous studies. 4.3. Channels that facilitate bank ownership’s improvement of investment efficiency 4.3.1. Does bank ownership mitigate overinvestment through the disclosure channel? In this section, we investigate whether disclosure channels drive the mitigation of overinvestment in bank holding firms. If this disclosure channel exits, we expect that bank ownership can curb agency conflicts. Moreover, we expect that the availability of additional information will directly contribute to improving reporting quality among bank holding firms.

Control 0.092 28.8170 13,890

Control 0.236 64.9800 22,258

In China, the dominant agency problem involves controlling shareholders’ expropriations. Excess control rights motivate controlling shareholders to conduct tunneling through related-party transactions,9 which benefit themselves but cost minority shareholders. The most common type of tunneling transaction is asset acquisition by controlling shareholders, which results in overinvestment and reduces firm value (Cheung et al., 2006; Jiang et al., 2010a; Wu and Wang, 2005). In other words, firms are more likely to overinvest when controlling shareholders have excess control rights and high associated related-party transactions; this is because the overinvestment costs are shared between controlling and

9 Those transactions include asset acquisitions, asset sales, equity sales, trading relationships, and cash payments to connected parties.

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Table 3 The impact of bank ownership on related party transactions and financial reporting quality. This table presents the empirical results on the impact of bank ownership on controlling shareholders expropriation and financial reporting quality. In Column 1 and Column 2, the dependent variable, ‘RPT’, is the ratio of related party transactions to total assets by following Cheung et al. (2006). The dependent variable in Column 3 and Column 4, ‘Discretionary Accruals’ is measured by the absolute residual of a performance-adjusted discretionary accruals model, following Kothari et al. (2005). The independent variable, ‘Bank’, is a dummy variable which takes the value of 1 if a firm is a bank holding firm, and 0 otherwise. The ‘Excess’ is the excess control rights which is the difference between controlling shareholders’ control rights and cash flow rights. The ‘Stock25’ is the total shares held by the second to fifth largest shareholders. The ‘Bank× Excess’ and ‘Bank×Stock25’ is the interaction between ‘Bank’ and ‘Excess’ and the interaction between ‘Bank’ and ‘Stock25’, respectively. Control variables are defined in Appendix A. All independent variables are one year lagged. All regressions include firm and year fixed effect. Robust standard errors are clustered at the firm level and reported in parentheses. ∗ , ∗∗ and ∗∗∗ indicate significance at the 10%, 5% and 1% levels, respectively. (1)

(2)

(3)

Dependent variable: RPT Bank (β 1 ) Excess(β 2 ) Stock25(β 2 ) Excess × Bank(β 3 ) Stock25 × Bank(β 3 )

∗∗∗

−0.0326 (0.0105) 0.0604∗∗∗ (0.0055)

(4)

Dependent variable: Discretionary accruals −0.0632 (0.0134)

∗∗∗

−0.0042∗∗∗ (0.0014) 0.0044∗∗∗ (0.0008)

−0.0226∗∗ (0.0106) −0.1734∗∗ (0.0888)

−0.0081∗∗∗ (0.0017)

0.0011 (0.0014) −0.0225∗ (0.0135)

−0.0505∗∗∗ (0.0120) 0.4992∗∗∗ (0.0435) 0.0197∗∗∗ (0.0059) −0.0212 (0.0610) −0.0919 (0.0998) 0.1338∗∗∗ (0.0449) 0.0247 (0.0359) 0.0046 (0.0128) −0.0733 (0.0749) −0.0777 (0.0516) −0.0258 (0.0364) 0.0247 (0.0201) 0.8236∗∗∗ (0.2839)

0.0483∗ (0.0278) −0.0153∗∗∗ (0.0040) 0.4958∗∗∗ (0.0245) 0.0316∗∗∗ (0.0065) −0.029 (0.0585) −0.3781∗∗∗ (0.0820) 0.012 (0.0292) −0.0303∗∗ (0.0133) −0.007 (0.0077) −0.0905∗ (0.0530) −0.1442∗∗∗ (0.0200) −0.0126 (0.0176) 0.0547∗∗∗ (0.0057) 0.2389∗∗∗ (0.0825)

−0.0204∗∗∗ (0.0016) 0.0307∗∗∗ (0.0058) 0.0027∗∗∗ (0.0010) −0.0401∗∗∗ (0.0100) 0.0138 (0.0144) 0.0131∗ (0.0070) 0.0078∗ (0.0042) 0.0007 (0.0020) 0.0113 (0.0107) −0.0067 (0.0105) 0.004 (0.0048) 0.0018 (0.0028) 0.4652∗∗∗ (0.0372)

0.0072∗∗ (0.0034) −0.0088∗∗∗ (0.0005) 0.0417∗∗∗ (0.0031) 0.0048∗∗∗ (0.0010) −0.0777∗∗∗ (0.0085) 0.0242∗∗ (0.0114) 0.0196∗∗∗ (0.0042) 0.0039∗∗ (0.0018) 0.0022∗∗ (0.0011) 0.0137∗ (0.0073) 0.0039 (0.0037) −0.0061∗∗ (0.0025) 0.0046∗∗∗ (0.0008) 0.2277∗∗∗ (0.0115)

(p value)

6.23∗∗ (0.013)

0.14 (0.438)

4.27∗∗ (0.039)

0.14 (0.711)

Firm and Year Effect Adj. R2 F Value N

Control 0.068 13.9698 21,839

Control 0.102 49.4111 21,839

Control 0.035 7.658 21,832

Control 0.08 28.5387 21,832

Lnsize Lev Growth CFO

t -1

ROA Cash Holding Big4 Dual Indep Mshare Lnboard Lnage _cons

β 1 +β 3 = 0

minority shareholders, while the potential benefits are enjoyed by controlling shareholders. The additional disclosure requirements imposed on bank holding firms and the more stringent supervision by dual authorities are expected to reduce controlling shareholders’ tendency to commit expropriations and consequently alleviate overinvestment. We thus expected that bank ownership would reduce tunneling through related-party transactions, especially in firms with more severe agency problems. Following Jiang et al. (2010a), we measured the controlling shareholders’ expropriation incentives by examining their excess control rights which are the differences between controlling shareholders’ control rights and cash flow rights (Excess). In addition, we employed the second to fifth largest shareholders’ ownerships to capture the monitoring intensity of the non-controlling large shareholders (Stock25). It was expected that these noncontrolling large shareholders would have both incentive and ability to monitor controlling shareholders’ expropriations and

thus improve corporate governance (Chen et al., 2012). Following Cheung et al. (2006), we measured the controlling shareholders’ expropriation activities by using related-party transaction (RPT). Column 1 of Table 3 shows that bank ownership significantly reduces related-party transactions, while excess control rights increase expropriations. More importantly, we find that the interaction term, Excess × Bank, is negative and significantly correlated with related-party transactions; this finding indicates that bank ownership alleviates expropriation, especially in firms with more serious agency problems. Similarly, in Column 2 of Table 3, we find that bank ownership has a more pronounced impact when noncontrolling large shareholders’ ownerships are low, and their monitoring intensity is weak. To provide direct evidence for our disclosure channel argument, we further investigated whether stricter disclosure requirements and more stringent monitoring improved financial reporting quality (Discretionary Accruals) among bank holding firms. Following

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Table 4 The impact of bank ownership on corporate cash holding. This table presents the impact of holding bank ownership on corporate cash holdings. The dependent variable in Column 1 and Column 2, ‘Cash Holding’ is the ratio of cash and cash equivalent assets to the total assets. The dependent variable in Column 3 and Column 4, ‘Excess cash holding’ is the difference between corporate cash holdings and industry median of corporate cash holdings. The independent variable, ‘Bank’, is a dummy variable which takes the value of 1 if a firm is a bank holding firm, and 0 otherwise. The ‘Excess’ is the excess control rights which is the difference between controlling shareholders’ control rights and cash flow rights. The ‘Stock25’ is the total shares held by the second to fifth largest shareholders. The ‘Bank × Excess’ and ‘Bank × Stock25’ is the interaction between ‘Bank’ and ‘Excess’ and the interaction between ‘Bank’ and ‘Stock25’, respectively. Control variables are defined in Appendix A. All independent variables are one year lagged. All regressions include firm and year fixed effect. Robust standard errors are clustered at the firm level and reported in parentheses. ∗ , ∗∗ and ∗∗∗ indicate significance at the 10%, 5% and 1% levels, respectively.

Bank Excess

(1)

(2)

(3)

(4)

Dependent variables: Cash holding

Dependent variables: Cash holding

Dependent variables: Excess cash holding

Dependent variables: Excess cash holding

−0.0036 (0.0032) −0.0054 (0.0182)

−0.0102∗∗∗ (0.0038)

−0.0033 (0.0032) −0.0044 (0.0181)

−0.0107∗∗∗ (0.0038)

0.0185∗∗∗ (0.0055)

Stock25 Excess × Bank

−0.0513∗∗ (0.0138)

0.0148∗∗∗ (0.0055) −0.0586∗∗ (0.0260)

−0.0216∗∗∗ (0.0026) −0.0688∗∗∗ (0.0089) 0.1306∗∗∗ (0.0118) 0.0033∗∗ (0.0013) −0.1329∗∗∗ (0.0105) 0.1196∗∗∗ (0.0239) 0.0078 (0.0071) 0.0127∗∗∗ (0.0028) 0.0620∗∗∗ (0.0140) 0.6103∗∗∗ (0.0573)

0.0114∗ (0.0060) −0.0230∗∗∗ (0.0026) −0.0666∗∗∗ (0.0090) 0.1313∗∗∗ (0.0118) 0.0031∗∗ (0.0013) −0.1315∗∗∗ (0.0105) 0.1160∗∗∗ (0.0238) 0.0055 (0.0071) 0.0126∗∗∗ (0.0028) 0.0747∗∗∗ (0.0146) 0.6342∗∗∗ (0.0579)

−0.0193∗∗∗ (0.0025) −0.0615∗∗∗ (0.0088) 0.1247∗∗∗ (0.0116) 0.0026∗∗ (0.0013) −0.1305∗∗∗ (0.0104) 0.1111∗∗∗ (0.0233) 0.0083 (0.0070) 0.0119∗∗∗ (0.0028) 0.0603∗∗∗ (0.0140) 0.4761∗∗∗ (0.0562)

0.0121∗∗ (0.0059) −0.0205∗∗∗ (0.0026) −0.0598∗∗∗ (0.0088) 0.1252∗∗∗ (0.0116) 0.0024∗ (0.0013) −0.1293∗∗∗ (0.0104) 0.1082∗∗∗ (0.0232) 0.0064 (0.0070) 0.0118∗∗∗ (0.0028) 0.0704∗∗∗ (0.0146) 0.4959∗∗∗ (0.0568)

(F value, p value)

4.81∗∗ (0.028)

0.07 (0.794)

6.32∗∗ (0.012)

0.01 (0.752)

Firm and Year Effect Adj. R2 F Value N

Control 0.094 19.646 22,241

Control 0.097 19.716 22,241

Control 0.072 16.4783 22,241

Stock25 × Bank Lnsize Lev CFO Growth Tang ROA Lnboard Loss Largest _cons

β 1 +β 3 = 0

Kothari et al. (2005), we measured the financial reporting quality by employing the absolute residual of a performance-adjusted discretionary accruals model. Lower values indicated better financial reporting quality. Columns 3 and 4 of Table 3 show that the coefficients of interaction terms, Excess × Bank (Stock25 × Bank), are statistically significant and negative (positive). These results indicate that bank ownership improves financial reporting quality, especially in firms with severe agency problems. Moreover, the joint tests of Bank and Excess × Bank are statistically significant, which suggests that bank ownership reduces tunneling transactions and improves reporting quality when controlling shareholders have a strong incentive to tunnel. The insignificant joint tests of Bank and Stock25 × Bank indicate that bank ownership’s impacts are weakened when non-controlling shareholders’ ownership is high. Overall, the empirical results in Table 3 support our disclosure channel argument and hypothesis H2 by indicating a disclosure channel, through which bank ownership alleviates overinvestment in bank holding firms. To provide further evidence with regard to the disclosure argument, we examined whether bank ownership reduced agency motives corporate cash holding and increased the value of cash. Pre-

Control 0.075 15.927 22,241

vious literatures proposed that managers have incentives to hoard excess cash for their interests (Chen et al., 2012; Dittmar and Mahrt-Smith, 2007). Since higher disclosure and dual monitoring standards checked managerial opportunistic behavior, we expected that bank ownership would reduce excess cash holdings and improve the value of cash, especially in firms with more serious agency conflicts. The empirical results in Tables 4 and 5 support this argument. Table 4 shows that the interaction between bank ownership and controlling shareholders’ excess control rights (non-controlling large shareholders’ ownerships) is negatively (positively) associated with both corporate cash holdings and excess corporate cash holdings. Table 5 shows that the coefficient of Bank × Cash Holding is only significant and positive in firms where controlling shareholders have excess control rights, and non-controlling large shareholders have low ownership, thus suggesting that bank ownership significantly improves the value of cash, especially in firms with severe agency problems. Overall, our results in Tables 3–5 are consistent with our disclosure channel argument: through bank ownership, better corporate governance alleviates overinvestment.

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Table 5 The impact of bank ownership on value of cash holding. This table present the regression results for the impact of bank ownership on the value of cash. Column 1 (Column 2) presents the regression results for the firms which controlling shareholders have not (have) excess control rights. Column 3 (Column 4) presents the regression results for the firms that shares held by the second to fifth largest shareholders are higher (lower) than industry median. The dependent variable, ‘Tbq’ is the Tobin’s q which is measured by the market value to the replacement value of total assets. The independent variable, ‘Bank’, is a dummy variable which takes the value of 1 if a firm is a bank holding firm, and 0 otherwise. The independent variable, ‘Cash Holding’, is the ratio of cash and cash equivalent assets to the total assets. The ‘Bank × Cash Holding’ is the interaction between Bank and Cash Holding. Xt is the level of variable X in year t divided by the level of asset in year t. dX is the change in level of X from year t to year t-1 divided by the total asset in year t ((Xt –Xt-1 )/At ). fdX is the change in level of X from year t + 1 to year t divided by the total asset in year t ((Xt+1 –Xt )/At ). Control variables are defined in Appendix A. All regressions include firm and year fixed effect. Robust standard errors are clustered at the firm level and reported in parentheses. ∗ , ∗∗ and ∗∗∗ indicate significance at the 10%, 5% and 1% levels, respectively. (1)

(2)

(3)

(4)

No Excess

Excess

High Stock25

Low Stock25

−0.3672 (0.3280) −0.0828 (0.0766) −0.1321 (0.4028) 2.9818∗∗∗ (0.5167) −0.6674∗∗∗ (0.2520) 1.1308∗∗∗ (0.1903) −0.4150∗∗∗ (0.1199) 0.3638∗∗∗ (0.0576) −17.0921∗∗∗ (5.6408) −1.4433 (3.7991) −14.8981∗∗∗ (2.4515) 1.2491 (2.5214) 1.6758 (1.3049) 5.3132∗∗∗ (1.3866) −0.2802 (0.5617) 0.6323∗ (0.3283) 0.6830∗∗∗ (0.2614) −0.4852∗∗∗ (0.0144) 1.5086∗∗∗ (0.3115)

−0.2128 (0.3166) −0.3662∗∗∗ (0.1302) 0.7214∗∗ (0.3037) 1.7596∗∗∗ (0.5290) −0.4716 (0.2904) 0.9000∗∗∗ (0.1961) −0.8781∗∗∗ (0.1447) 0.4650∗∗∗ (0.0739) −22.1271∗∗∗ (5.4117) −6.5652∗ (3.3587) −14.8242∗∗∗ (2.8446) 0.155 (2.7258) 2.6494 (1.6280) 3.6528∗∗∗ (1.2755) 1.4431 (0.9462) 0.4019 (0.6106) 0.9772∗∗∗ (0.3181) −0.4565∗∗∗ (0.0160) −0.6648 (1.4547)

0.3278 (0.3152) −0.1184 (0.0721) −0.0924 (0.3022) 1.6901∗∗∗ (0.4483) −0.4449∗∗ (0.2185) 0.9251∗∗∗ (0.1820) −0.7041∗∗∗ (0.1145) 0.2054∗∗∗ (0.0577) −19.2191∗∗∗ (4.1784) −7.9871∗∗∗ (3.0089) −15.0347∗∗∗ (2.4176) 3.1358 (2.4258) 2.5104∗∗ (1.2725) 5.0831∗∗∗ (1.1161) 2.1281∗∗∗ (0.6276) −0.2158 (0.3824) 1.0819∗∗∗ (0.2664) −0.4432∗∗∗ (0.0180) 0.1811 (0.7335)

−0.2649 (0.3318) −0.3270∗∗∗ (0.1152) 0.6332∗ (0.3778) 3.5842∗∗∗ (0.6261) −0.8393∗∗∗ (0.3121) 1.3813∗∗∗ (0.2113) −0.4809∗∗∗ (0.1488) 0.5467∗∗∗ (0.0660) −19.6605∗∗∗ (5.2334) 0.8922 (4.0317) −11.3860∗∗∗ (2.5840) 2.3775 (2.6723) 0.8921 (1.4306) 4.1840∗∗∗ (1.4744) −0.3188 (0.7533) 0.7809∗ (0.4549) 0.5973∗ (0.3061) −0.4971∗∗∗ (0.0117) 1.1194∗∗ (0.5129)

(p value)

1.32 (0.251)

2.69 (0.101)

0.69 (0.406)

0.95 (0.329)

Firm and Year Effect Adj. R2 F Value N

Control 0.503 197.9671 11,375

Control 0.483 171.4246 10,427

Control 0.469 165.8216 10,898

Control 0.524 200.6361 10,904

Dependent variables: Tbq

Cash Holding(β 1 ) Bank(β 2 ) Bank × Cash Holding(β 3 ) CFO dCFO fdCFO dNA fdNA I dI fdI Div dDiv fdDiv Capx dCapx fdCapx fdtbq _cons

β 1 +β 3 = 0

4.3.2. Does bank ownership mitigate underinvestment through the financing channel? In this section, we investigated the influence of bank ownership on financial constraints to support our financing channel argument. As discussed before, we expected that bank ownership would facilitate firms in obtaining bank loans. Table 6 presents the empirical results for this argument. Bank ownership enabled firms to raise bank loans, especially for short-term bank loans; this finding is indicated by the significantly positive coefficient of Bank in Columns 1 and 3 of Table 6. We conjectured that bank holding firms would be more likely to obtain bank loans through relatedparty loans when they needed capital. Therefore, they may not finance projects, especially short-term projects, with more costly

long-term loans. Moreover, we further divided our sample into two groups based on the likelihood of overinvestment and underinvestment, respectively, and found that bank ownership’s impacts on obtaining short-term loans were more pronounced in firms with underinvestment problems. These findings provide direct evidence for our financing channel argument and show that bank ownership helps firms access bank loans, especially in the case of financially constrained firms. We further investigated whether bank ownership would weaken the precautionary motivation for cash holding. Denis and Sibilkov (2010) argued that cash could alleviate underinvestment arising from financial constraints. Compared to firms that can easily raise capital in the financial market, financially constrained

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Table 6 The impact of bank ownership on bank loans. This table presents the regression results for the impact of bank ownership on bank loans. Column 1 presents the regression results on the impact of bank ownership on the total bank loans (Total Loan). The ‘Total Loan’ is the level of bank loans during the fiscal year divided by the total assets. Columns 2 and 3 present the regression results for the impact of bank ownership on Long-term bank loans (Long Term) and short-term bank loans (Short Term), respectively. ‘Long Term’ is equal to the long-term bank loans dividend by the total assets and ‘Short Term’ is measured by the ratio of short-term bank loans to the total assets. Columns 4 and 5 present the regression results for the impact of bank ownership on short-term bank loans in firms who are more likely to overinvest and to underinvest, respectively. The independent variable, ‘Bank’, is a dummy variable which takes the value of 1 if a firm is a bank holding firm, and 0 otherwise. Control variables are defined in Appendix A. All independent variables are one year lagged. All regressions include firm and year fixed effect. Robust standard errors are clustered at the firm level and reported in parentheses. ∗ , ∗∗ and ∗∗∗ indicate significance at the 10%, 5% and 1% levels, respectively. (1)

(2)

(3)

(4)

(5)

Total Loan Full Sample

Long Term Full Sample

Short Term Full Sample

Short Term Overinvestment

Short Term Underinvestment

0.0054∗∗ (0.0027) 0.0066 (0.0068) 0.0261∗∗∗ (0.0030) 0.2612∗∗∗ (0.0120) −0.1719∗∗∗ (0.0145) 0.0327∗∗ (0.0134) −0.0135∗∗∗ (0.0035) −0.0670∗∗∗ (0.0107) −0.1193∗∗∗ (0.0297) −0.0049 (0.0081) −0.0109 (0.0080) −0.0011 (0.0163) −0.3944∗∗∗ (0.0710)

−0.0033 (0.0024) −0.0016 (0.0038) 0.0171∗∗∗ (0.0017) 0.0813∗∗∗ (0.0072) −0.0714∗∗∗ (0.0086) 0.0002 (0.0094) −0.0092∗∗∗ (0.0022) −0.0159∗∗∗ (0.0060) 0.0141 (0.0154) −0.0054 (0.0051) −0.0117∗∗ (0.0060) 0.0215∗ (0.0112) −0.3367∗∗∗ (0.0389)

0.0087∗∗∗ (0.0032) 0.0082 (0.0062) 0.0091∗∗∗ (0.0027) 0.1799∗∗∗ (0.0110) −0.1005∗∗∗ (0.0137) 0.0325∗∗∗ (0.0124) −0.0044 (0.0033) −0.0511∗∗∗ (0.0100) −0.1334∗∗∗ (0.0276) 0.0005 (0.0074) 0.0008 (0.0073) −0.0226 (0.0153) −0.0577 (0.0640)

−0.0017 (0.0052) 0.0056 (0.0081) 0.0032 (0.0035) 0.1670∗∗∗ (0.0150) −0.1044∗∗∗ (0.0248) 0.0516∗∗∗ (0.0168) −0.0133∗∗ (0.0056) −0.0442∗∗∗ (0.0150) −0.1786∗∗∗ (0.0447) −0.0023 (0.0105) 0.0156 (0.0131) −0.0226 (0.0212) 0.0852 (0.0860)

0.0111∗∗∗ (0.0039) 0.0055 (0.0076) 0.0117∗∗∗ (0.0032) 0.1840∗∗∗ (0.0140) −0.0869∗∗∗ (0.0166) 0.0125 (0.0159) 0.0002 (0.0042) −0.0605∗∗∗ (0.0123) −0.1122∗∗∗ (0.0342) 0.0037 (0.0088) −0.0009 (0.0087) −0.0241 (0.0195) −0.1118 (0.0773)

Control 0.158 157.9401 22,258

Control 0.034 46.3175 22,258

Control 0.11 125.3332 22,258

Control 0.138 31.9754 8368

Control 0.055 78.3743 13,890

Dependent variables:

Bank Nonstate Lnsize Lev CFO Tang Loss Cash Holding ROA Lnboard Big4 Largest _cons Firm and Year Effect Adj. R2 F Value N

firms tend to accumulate cash out of cash flow (Almeida et al., 2004; Chen et al., 2012). If bank ownership reduces financial constraints, bank holding firms should have less incentive to save cash out of cash flows for future investment. Table 7 shows that the interaction term (Bank × CFO) is significantly and negatively correlated with the changes in cash holdings. Moreover, the reduction in the sensitivity of cash flow to cash was only observable in the underinvestment firms that were more likely to suffer financial constraints. This result further supports our financing channel argument with regard to bank ownership. Monetary policy significantly affects bank lending behavior, which consequently influences firm investment decisions (Mojon et al., 2002; Sun et al., 2010). When monetary supply is limited, banks tighten lending, and firms are more likely to experience financial constraints; this deteriorates underinvestment. However, if bank holding firms have the advantages of accessing bank loans, they are less concerned about the possibility of cash shortage. Thus, compared to their counterparts, tightened monetary policy’s impact on investment efficiency will be less pronounced in bank holding firms. We used broad money, M2 growth rate, to measure the national monetary policy. We defined a dummy variable, Monetary, which equaled 1, for the period of tightened monetary policy, when the growth rate of M2 was less than its median. The empirical results are presented in Table 8.

Consistent with our argument, the interaction (Bank × Monetary) is significantly and negatively correlated with investment inefficiency in Column 1 and with underinvestment in Column 3. The results in Column 4 suggest that bank ownership improves the investment sensitivity to investment opportunities during tight monetary policy periods. Overall, the results in Tables 6–8 support our financing channel argument. Bank ownership alleviates financial constraints and consequently improves investment efficiency among bank holding firms. 4.4. The conditional effects of bank ownership on investment efficiency As we discussed before, we expected that bank ownership would have a more pronounced impact if firms were non-SOEs, located in less-developed regions, and did not have institutional investors. Panel A of Table 9 measures the private control (Nonstate) by employing the dummy variable, which takes a value of 1 if the firm is a private firm. The interaction between bank ownership and non-SOEs (Bank × Nonstate) significantly reduces underinvestment. Moreover, the coefficient of Bank × Tbq is positive and significant only in non-SOEs. Overall, these results show that bank ownership has a more pronounced impact on improving investment efficiency by alleviating financial constraints in non-SOEs, thus supporting H4a.

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H. Wang, T. Luo and G.G. Tian et al. / Journal of Banking and Finance xxx (xxxx) xxx Table 7 The impact of bank ownership on the cash flow sensitivity of cash. This table presents the impact of bank ownership on the firm’s cash flow sensitivity of cash. Column 1 presents the regression result for the impact of bank ownership on the cash flow sensitivity of cash for full sample. The Columns 2 and 3 present the regression results for the overinvestment and underinvestment subsample, respectively. The dependent variable measures the changes in corporate cash holdings: (࢞Cash Holding) is the change in cash holdings from year t−1 to t for firm i, scaled by total assets. The independent variable, ‘Bank’, is a dummy variable which takes the value of 1 if a firm is a bank holding firm, and 0 otherwise. The ‘CFO’, is the cash flow from operations scaled by total assets. ‘Bank × CFO’ is the interaction between ‘Bank’ and ‘CFO’. Control variables are defined in Appendix A. All regressions include firm and year fixed effect. Robust standard errors are clustered at the firm level and reported in parentheses. ∗ , ∗∗ and ∗∗∗ indicate significance at the 10%, 5% and 1% levels, respectively. (1)

(2)

(3)

Dependent variables: ࢞Cash holding Full sample

Overinvestment

Underinvestment

0.1200∗∗∗ (0.0192) 0.0086∗∗ (0.0037) −0.0886∗∗ (0.0362) −0.0425∗∗∗ (0.0023) 0.0578∗∗∗ (0.0087) 0.0112∗∗∗ (0.0018) 0.0556∗∗∗ (0.0046) 0.0119∗∗∗ (0.0019) 0.0435∗∗ (0.0204) −0.0128 (0.0215) 0.0039 (0.0175) −0.0072∗∗ (0.0032) 0.7860∗∗∗ (0.0493)

0.1623∗∗∗ (0.0321) 0.0025 (0.0065) −0.0436 (0.0633) −0.0527∗∗∗ (0.0042) 0.1066∗∗∗ (0.0160) 0.0108∗∗∗ (0.0030) 0.0643∗∗∗ (0.0076) 0.0120∗∗∗ (0.0033) −0.04 (0.0351) 0.0489 (0.0388) 0.0085 (0.0301) −0.0001 (0.0057) 1.0098∗∗∗ (0.0941)

0.0977∗∗∗ (0.0260) 0.0112∗∗ (0.0050) −0.0942∗∗ (0.0488) −0.0392∗∗∗ (0.0030) 0.0266∗∗ (0.0112) 0.0111∗∗∗ (0.0023) 0.0431∗∗∗ (0.0065) 0.0119∗∗∗ (0.0024) 0.0214 (0.0280) −0.0203 (0.0290) −0.0009 (0.0227) −0.0126∗∗∗ (0.0041) 0.7454∗∗∗ (0.0640)

(F value, p value)

11.33∗∗∗ (0.000)

38.56∗∗∗ (0.000)

2.43 (0.336)

Firm and Year Effect Adj. R2 F Value N

Control 0.062 29.9124 22,109

Control 0.093 14.8563 8319

Control 0.05 14.3308 13,790

CFO(β 1 ) Bank (β 2 ) Bank × CFO(β 3 ) Lnsize Lev Growth Lnage Ret CapEx MShare InDep Dual _cons

β 1 +β 3 = 0

Panel B of Table 9 employs the provincial level of the Chinese marketization index produced by the National Economic Research Institute (Fan et al., 2016) to measure the extent of regional institutional development.10 The coefficient of the interaction term (Bank × Market) is positive and significant in Columns 1 to 3. Furthermore, Column 4 shows that bank ownership improves the investment sensitivity to investment opportunity only in less developed regions. These results support H4b and indicate that bank ownership has a more pronounced impact on improving investment efficiency in less developed regions. Panel C of Table 9 tabulates the impact of institutional investors’ presence on the relationship between bank ownership and 10 This marketization index has been used widely in the literature (see, e.g., Lu et al., 2012; Qian et al., 2017). It captures 23 dimensions of provincial market development, such as relationship between government and markets, development of legal environments and market intermediaries, development of banking and factor markets, development of the private sector, and development of product markets. A higher index score (Market) suggests greater institutional development.

investment efficiency. We measured the presence of institutional investors by employing a dummy variable (Ins), which takes a value of 1 if one of the 10 largest shareholders is an institutional investor in the firm, and 0 otherwise. As expected, the interaction term (Bank × Ins) was significantly and positively associated with investment inefficiency. Moreover, Columns 4 and 5 show that the interaction term (Bank × Tbq) is only significant in firms without institutional investors. These results reveal that bank ownership has more pronounced impacts on improving investment efficiency in firms without institutional investors, thus supporting H4c.

4.5. Endogeneity problems and robustness tests 4.5.1. Dealing with endogeneity concerns In this section, we try to address a potential endogeneity issue: the likelihood of being bank holding firms is endogenously determined among firms. Therefore, the acquiring bank’s equity ownership may affect the firm’s investment decision. In addition, bank ownership may induce managers in a previously underinvesting firm to make wasteful investments if financial constraints and agency problems concurrently exist in that firm. To control for this potential endogenous problem, we used the Heckman (1979) twostage model. In the first stage, we estimated the probit regression of the choice of being a bank holding firm by controlling a set of control variables including the instrument variable and the overinvestment dummy. In the second stage, we estimated Eqs. (2) and (3), including the inverse Mill’s ratio (MILLS), which was calculated based on the estimation results from the first stage. The choice of instrument variable is vital for implementing the selection model. Motivated by Karpoff et al. (2017) and Opie et al. (2019), our first instrument (Geographic IV) is a 5-year lagged percentage of bank holding firms that are in the same region as the focal firm but are not in the same industry (henceforth, geographically-proximate firms) .11 Previous studies have argued that geographic proximity has important implications for the financial and operational decisions of listed firms (Pirinsky and Wang, 2006). Geographic proximity can explain a firm’s tendency to acquire bank ownership if the firms share a common legal system, local government policies, consulting services within the region the firms are located in, and/or a spillover of management ideas at the local level. We therefore expected that the percentage of geographically-proximate firms would be positively associated with the likelihood of being bank holding firms. We argue that the geographical instrument variable is more likely to meet the exclusive restriction conduction. First, the instrument variable is defined as the percentage of geographicallyproximate firms, years before the year of analysis. Our sample shows that, after firms acquire a bank’s equity ownership, they are rarely likely to relinquish their position. Thus, the correlation in acquiring bank ownership observed among geographically-proximate firms, exists for reasons that occurred years before the year of analysis. These reasons should not directly affect the firms’ current investment decisions. Moreover, firms may make location decisions for diverse reasons in different years because economic and political conditions may change over time in different locations. Therefore, we considered it unlikely that the focal firm and the geographically-proximate firms would all choose the same headquarter location for the same reasons in different years that would then still explain both their tendency of acquiring bank ownership and their investment efficiency. We therefore argue that the exclu11 To illustrate the construction of these instruments, assume that, five years before the year of analysis, there were five firms located in the same province as the focal firm but in different industries. Three of them were bank holding firms. The instrument value for this focus firm would be 0.75.

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Table 8 The impact of monetary policy on the relationship between bank ownership and investment efficiency. This table presents the results of impact of monetary policy on the relationship between bank ownership and investment efficiency. The dependent variable is investment inefficiency, ‘Investment Inefficiency’, which is the absolute value of deviation from the optimal investment estimated from Eq. (1) in Column 1. The dependent variable in Column 2 and Column 3 is the ‘Overinvestment’ measured by the positive residuals from Eq. (1) and ‘Underinvestment’ measured by the absolute value of negative residuals from Eq. (1), respectively. The regression result in Column 4 (Column 5) presents the impact of bank ownership on investment sensitivity to investment opportunity in the period of tight (loose) monetary policy. In Columns 4 and 5, the dependent variable, ‘Investment’ is measured the total investment expenditures scaled by the by the total assets. The independent variable, ‘Bank’, is a dummy variable which takes the value of 1 if a firm is a bank holding firm, and 0 otherwise. The independent variable ‘Monetary’ is a dummy variable which takes the value of 1 if the growth rate of M2 is lower than the sample medium, and 0 otherwise. The independent variable (Tbq) is the ratio of the market value of assets to the current replacement cost of these assets. ‘Monetary × Bank’ is the interaction between ‘Bank’ and ‘Monetary’. ‘Bank × Tbq’ is the interaction term of Bank and Tbq. All independent variables are one year lagged. All regressions include firm and year fixed effect. Robust standard errors are clustered at the firm level and reported in parentheses. ∗ , ∗∗ and ∗∗∗ indicate significance at the 10%, 5% and 1% levels, respectively. (1)

(2)

(3)

Dependent variables: Investment inefficiency Full sample Bank(β 1 ) Monetary(β 2 ) Monetary × Bank(β 3 ) Tbq(β 2 )

−0.0012 (0.0010) −0.0002 (0.0011) −0.0021∗∗ (0.0009)

Overinvestment −0.0029 (0.0023) 0.0004 (0.0032) −0.0027 (0.0021)

−0.0002 (0.0008) −0.0005 (0.0010) −0.0018∗∗ (0.0008)

−0.0041∗∗∗ (0.0006) −0.0199∗∗∗ (0.0031) 0.0410∗∗∗ (0.0063) 0.002 (0.0016) −0.0014 (0.0019) 0.0009 (0.0009) −0.0004 (0.0008) 0.0062∗ (0.0037)

−0.0107∗∗∗ (0.0012) −0.0412∗∗∗ (0.0068) 0.0628∗∗∗ (0.0149) 0.0019 (0.0039) −0.001 (0.0045) 0.0026 (0.0024) 0.0001 (0.0020) 0.0012 (0.0078)

−0.0003 (0.0004) −0.0007 (0.0026) 0.0205∗∗∗ (0.0043) 0.0009 (0.0013) −0.0003 (0.0013) 0.0000 (0.0007) −0.0009 (0.0006) 0.0061∗∗ (0.0028)

_cons

0.1218∗∗∗ (0.0131)

0.2766∗∗∗ (0.0282)

0.0310∗∗∗ (0.0101)

β 1 +β 3 = 0

10.99∗∗∗ (0.001)

5.46∗∗ (0.020)

8.28∗∗∗ (0.004)

Tang ROA Lnboard Big4 Loss Dual Largest Invest Ret Cash Holding Lev CFO Lnage

(p value) β 2 +β 3 = 0 (p value) Firm and Year Effect Adj. R2 F Value N

Control 0.057 29.2303 22,258

Control 0.066 11.1577 8368

sion restriction condition is satisfied because the past bank ownership acquisition decisions of geographically-proximate firms are not directly related to the current investment efficiency of the focal firm. Therefore, our instrument variable, Geographic IV, should not affect investment efficiency in any way other than the bank ownership. To provide sensitivity analyses for the robustness of the instrument variable, we employed the second instrument variable, the

(5)

Dependent variables: Investment Underinvestment

Bank × Tbq(β 3 ) Lnsize

(4)

Control 0.093 28.2625 13,890

Tight −0.0072 (0.0025)

Loose ∗∗∗

0.0000 (0.0018)

0.0004 (0.0005) 0.0021∗ (0.0011) −0.0051∗∗∗ (0.0013) −0.0430∗∗∗ (0.0066) 0.0438∗∗∗ (0.0136) 0.0045 (0.0040) −0.003 (0.0044) 0.0000 (0.0019) 0.0006 (0.0019) 0.0113 (0.0074) 0.2784∗∗∗ (0.0142) 0.0021∗∗ (0.0008) 0.0627∗∗∗ (0.0079) −0.0252∗∗∗ (0.0051) −0.009 (0.0068) 0.0009 (0.0034) 0.1569∗∗∗ (0.0290)

0.0006 (0.0005) 0.0012 (0.0007) −0.0037∗∗ (0.0015) −0.0835∗∗∗ (0.0079) 0.0461∗∗∗ (0.0132) 0.0040 (0.0031) −0.0056 (0.0036) 0.0017 (0.0017) 0.0007 (0.0015) 0.0117 (0.0084) 0.2278∗∗∗ (0.0154) 0.0015 (0.0009) 0.0310∗∗∗ (0.0058) −0.0021 (0.0051) 0.0015 (0.0067) −0.0096∗∗∗ (0.0028) 0.1470∗∗∗ (0.0389)

6.74∗∗∗ (0.009)

6.04∗∗ (0.014)

Control 0.175 44.0367 11,350

Control 0.235 62.6252 10,908

regional population in 20 0 0 (5 years prior to the start of the sample period). Lu et al. (2012) showed that the high populated regions have greater demand for banking services, and banks are therefore more likely to allocate in these regions in order to attract savings. This situation provides greater opportunities for firms to acquire bank ownership. The regional population 5 years before the start of the sample period may also reduce the chance of violating the exclusion restriction condition.

Please cite this article as: H. Wang, T. Luo and G.G. Tian et al., How does bank ownership affect firm investment? Evidence from China, Journal of Banking and Finance, https://doi.org/10.1016/j.jbankfin.2020.105741

(2)

(3)

(4)

Dependent variables: Investment inefficiency

Bank(β 1 )

Bank × Nonstate(β 3 )

Dependent variables: Investment

Full Sample

Overinvestment

Underinvestment

Non-SOEs

SOEs

−0.0023∗∗ (0.0010) 0.0027∗∗ (0.0011) −0.0003 (0.0014)

−0.0054∗∗ (0.0025) 0.0007 (0.0028) 0.0022 (0.0035)

−0.0004 (0.0008) 0.0023∗∗ (0.0009) −0.0024∗∗ (0.0012)

−0.0014 (0.0028)

0.0002 (0.0017)

0.0010∗∗ (0.0004) 0.0016∗∗ (0.0008)

0.0005 (0.0006) 0.0008 (0.0008)

9.14∗∗∗ (0.003)

2.24 (0.1345)

Bank × Tbq(β 3 )

β 1 +β 3 = 0 (p value) β 2 +β 3 = 0 (p value) Control variables Firm and Year Effect Adj. R2 F Value N

4.83∗∗ (0.028)

7.76∗∗∗ (0.005)

1.26 (0.261)

Control Control 0.075 28.5994 22,258

Control Control 0.3 10.8734 8368

Control Control 0.116 27.7067 13,890

Control Control 0.193 45.1227 10,982

Control Control 0.271 78.7216 11,278

(1)

(2)

(3)

(4)

(5)

Panel B The Panel B of Table 9 presents the regression results for the impact of regional marketization on the relationship between bank ownership and investment efficiency. The independent variable ‘Market’ is the provincial-level Chinese marketization index produced by the National Economic Research Institution (Fan et al., 2016). ‘Bank × Market’ is the interaction between ‘Bank’ and ‘Market’. ‘Bank × Tbq’ is the interaction term of ‘Bank’ and ‘Tbq’. The regression result in Column 4 (Column 5) presents the impact of bank ownership on the investment sensitivity to investment opportunity in regions with marketization index lower (higher) than sample median. Other variables are defined in Table 2. Control variables are same as reported in Table 2 and defined in Appendix A. All independent variables are one year lagged. All regressions include intercept, and firm and year fixed effect. Robust standard errors are clustered at the firm level and reported in parentheses. ∗ , ∗∗ and ∗∗∗ indicate significance at the 10%, 5% and 1% levels, respectively. Dependent variables: investment Inefficiency Full Sample Bank(β 1 )

Bank × Market(β 3 ) Tbq(β 2 ) Bank × Tbq(β 2 )

−0.0104 (0.0040) −0.0019 (0.0072) 0.0102∗∗∗ (0.0034)

Dependent variables: Investment

Overinvestment ∗∗∗

−0.0231 (0.0085) −0.0054 (0.0161) 0.0244∗∗∗ (0.0082)

Underinvestment −0.0072 (0.0024) −0.0011 (0.0056) 0.0074∗∗ (0.0029)

∗∗∗

Low Marketization

High Marketization

−0.0015 (0.0023)

0.0006 (0.0020)

0.0007 (0.0005) 0.0025∗∗ (0.0011)

0.0011∗∗ (0.0005) 0.0001 (0.0009) (continued on next page)

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Market(β 2 )

∗∗∗

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Tbq(β 2 )

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Nonstate(β 2 )

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Table 9 The conditional effects of bank ownership on investment efficiency. The Panel A of Table 9 presents the regression results for the impact of ownership structure on the relationship between bank ownership and investment efficiency. The independent variable ‘Nonstate’ is a dummy variable which takes the value of 1 if the firm is a private firm, and 0 otherwise. ‘Bank × Nonstate’ is the interaction between ‘Bank’ and ‘Non-SOEs’. ‘Bank × Tbq’ is the interaction term of ‘Bank’ and ‘Tbq’. The regression result in Column 4 (column 5) presents the impact of bank ownership on the sensitivity of investment to investment opportunity in Non-SOEs (SOEs). Other variables are defined in Table 2. Control variables are same as reported in Table 2 and defined in Appendix A. All independent variables are one year lagged. All regressions include intercept, and firm and year fixed effect. Robust standard errors are clustered at the firm level and reported in parentheses. ∗ , ∗∗ and ∗∗∗ indicate significance at the 10%, 5% and 1% levels, respectively.

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β 1 +β 3 = 0 (p value) β 2 +β 3 = 0 (p value) Control variables Firm and Year Effect Adj. R2 F Value N

0.02 (0.886)

0.15 (0.699)

0.04 (0.840) 13.31∗∗∗ (0.000)

Control Control 0.058 28.6649 22,258 (1)

Control Control 0.068 11.0881 8368 (2)

Control Control 0.093 27.6627 13,890 (3)

Control Control 0.266 72.3545 11,057 (4)

2.05 (0.152) Control Control 0.186 45.1054 11,201 (5)

The Panel C of Table 9 presents the regression results for the impact of institutional ownership on the relationship between bank ownership and investment efficiency. The independent variable, ‘Ins’ is a dummy variable which takes value of 1 if one of 10 largest shareholders is an institutional investor in the firm, and 0 otherwise. ‘Bank × Ins’ is the interaction between ‘Bank’ and ‘Ins’. The regression result in Column 4 (Column 5) presents the impact of bank ownership on the investment sensitivity to investment opportunity in firms with institutional investors’ ownership lower (higher) than sample median. Other variables are defined in Table 2. Control variables are same as reported in Table 2 and defined in Appendix A. All independent variables are one year lagged. All regressions include intercept, and firm and year fixed effect. Robust standard errors are clustered at the firm level and reported in parentheses. ∗ , ∗∗ and ∗∗∗ indicate significance at the 10%, 5% and 1% levels, respectively. Dependent Variables: Investment Inefficiency

Bank(β 1 ) Ins(β 2 ) Bank × Ins(β 3 ) Tbq(β 2 )

Dependent Variables: Investment

Full Sample

Overinvestment

Underinvestment

Without Institutional Ownership

With Institutional Ownership

−0.0043∗∗∗ (0.0014) 0.0046∗∗∗ (0.0015) 0.0050∗ (0.0027)

−0.0097∗∗∗ (0.0034) 0.0100∗∗∗ (0.0035) 0.0134∗∗ (0.0064)

−0.0021 (0.0013) 0.0015 (0.0013) 0.0020 (0.0028)

−0.0030 (0.0029)

0.0005 (0.0021)

0.0007 (0.0005) 0.0019∗ (0.0010)

0.0005 (0.0005) 0.0012 (0.0009)

3.48∗ (0.062)

3.64∗ (0.057)

Bank × Tbq(β 2 )

β 1 +β 3 = 0 (p value) β 2 +β 3 = 0 (p value)

Control Control 0.058 18.0809 22,258

0.73 (0.393)

Control Control 0.069 11.4027 8368

0.00 (0.947)

Control Control 0.093 26.0784 13,890

Control Control 0.156 36.2642 11,129

Control Control 0.252 66.7642 11,129

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Control variables Firm and Year Effect Adj. R2 F Value N

0.14 (0.711)

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Table 9 (continued)

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(9)

(10)

(11)

(12)

Second Stage

First Stage

Second Stage

First Stage

Second Stage

First Stage

Second Stage

Dependent variable: Bank

Dependent variables: Investment Inefficiency

Dependent variable: Bank

Dependent variables: Investment

Dependent variable: Bank

Dependent variables: Investment Inefficiency

Dependent variable: Bank

Dependent variables: Investment

Full

Full

Full

Full

Full

Full

Overinvestment

Underinvestment

−0.0033∗∗∗ (0.0010)

−0.0050∗∗ (0.0025)

−0.0023∗∗∗ (0.0007)

−0.0043∗∗ (0.0018) 0.0004 (0.0004) 0.0020∗∗∗ (0.0008)

Tbq Bank × Tbq 0.7578∗∗∗

1.6375∗∗∗

(0.1478)

(0.1919) −0.5531∗∗∗

Geographic IV × Tbq

Full

Overinvestment

Underinvestment

−0.0044∗∗∗ (0.0010)

−0.0054∗∗ (0.0026)

−0.0024∗∗∗ (0.0007)

0.0004 (0.0004) −0.0040∗∗ (0.0018) 0.0020∗∗∗ (0.0008)

(0.0617) 0.1982∗∗∗ (0.0422)

Population

0.7567∗∗∗ (0.1517) −0.1666∗∗∗

Population × Tbq (0.0175) −0.0297

−0.0246

Overinvestment Lnsize Tang ROA Lnboard Big4

Dual Largest

0.0003 (0.0010) −0.0358∗∗∗ (0.0041) 0.0109 (0.0080) 0.0265∗∗∗ (0.0041) 0.0012 (0.0018) −0.0034∗∗∗ (0.0011) −0.0021∗∗ (0.0009) 0.0001 (0.0045)

−0.0061∗∗∗ (0.0018) −0.0569∗∗∗ (0.0089) 0.0264 (0.0187) 0.0188∗∗∗ (0.0065) 0.0005 (0.0047) −0.0009 (0.0027) −0.0018 (0.0023) 0.0002 (0.0099)

−0.0001 (0.0007) −0.0041 (0.0037) 0.0093∗ (0.0055) 0.0041 (0.0026) 0.0027 (0.0017) −0.0009 (0.0009) −0.0009 (0.0007) 0.0063∗ (0.0037)

0.1138∗∗∗ (0.0127) −0.6021∗∗∗ (0.0935) 0.5745∗ (0.3286) 0.9331∗∗∗ (0.0525) 0.0311 (0.0504) −0.0890∗ (0.0531) 0.0276 (0.0316) −0.1279 (0.0831)

−0.0003 (0.0018) −0.0743∗∗∗ (0.0082) 0.0516∗∗∗ (0.0110) 0.0176∗ (0.0099) −0.0003 (0.0030) −0.0015 (0.0022) 0.0014 (0.0013) 0.0126∗ (0.0066)

(0.0244) 0.2004∗∗∗ (0.0108) −0.3963∗∗∗ (0.0838) −0.7335∗∗∗ (0.2827) 0.9096∗∗∗ (0.0501) −0.0404 (0.0501) −0.1591∗∗∗ (0.0524) −0.0412 (0.0306) −0.3581∗∗∗ (0.0812)

0.0319∗∗∗ (0.0027) −0.0966∗∗∗ (0.0063) −0.1043∗∗∗ (0.0121) 0.1677∗∗∗ (0.0123) −0.0058∗∗∗ (0.0019) −0.0284∗∗∗ (0.0023) −0.0085∗∗∗ (0.0011) −0.0560∗∗∗ (0.0064)

0.0042 (0.0084) −0.0784∗∗∗ (0.0190) −0.0100 (0.0357) 0.0649∗ (0.0386) −0.0013 (0.0049) −0.0092 (0.0071) −0.0037 (0.0029) −0.0185 (0.0173)

0.0021 (0.0025) −0.0086 (0.0061) 0.0013 (0.0103) 0.0141 (0.0111) 0.0021 (0.0018) −0.0026 (0.0021) −0.0013 (0.0009) 0.0023 (0.0055)

0.1186∗∗∗ (0.0125) −0.6149∗∗∗ (0.0935) 0.6767∗∗ (0.3319) 0.9022∗∗∗ (0.0521) 0.0389 (0.0504) −0.0871 (0.0531) 0.0347 (0.0316) −0.1299 (0.0833)

−0.0003 (0.0018) −0.0743∗∗∗ (0.0082) 0.0516∗∗∗ (0.0110) 0.0176∗ (0.0099) −0.0003 (0.0030) −0.0015 (0.0022) 0.0014 (0.0013) 0.0126∗ (0.0066)

(continued on next page)

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Loss

(0.0244) 0.1949∗∗∗ (0.0108) −0.3788∗∗∗ (0.0839) −0.7614∗∗∗ (0.2830) 0.9540∗∗∗ (0.0509) −0.0314 (0.0501) −0.1557∗∗∗ (0.0524) −0.0492 (0.0306) −0.3175∗∗∗ (0.0811)

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First Stage

Bank

Geographic IV

(8)

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Table 10 Heckman selection two-stage selection model. This table presents the Heckman selection two-stage selection model for the impact of holding bank ownership on investment efficiency. First-stage probit analyses are presented in Columns 1, 5, 7 and 11, and the second-stage regression results are presented in Columns 2, 3, 4, 6, 8, 9, 10 and 12. In the first stage, the dependent variable, ‘Bank’, is a dummy variable which takes the value of 1 if a firm is a bank holding firm, and 0 otherwise. The instrument variable in Columns 1 and 5, ‘Geographic IV’, is the 5-year lagged percentage of bank holding firms that are in the same region as the focus firm but are not in the same industry. The instrument variable in Columns 7 and 11, ‘Population’, is the provincial population in 20 0 0 in million. The inverse Mills ratio is estimated in the first stage model and included as additional independent variable in second stage. In the second stage, variables are same as Table 2 and defined in Appendix A. All independent variables are one year lagged. Robust standard errors are clustered at the firm level and reported in parentheses. ∗ , ∗∗ and ∗∗∗ indicate significance at the 10%, 5% and 1% levels, respectively.

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Invest Ret

Lev CFO Lnage MILLS _cons

−6.8342∗∗∗ (0.2595)

0.0332∗∗∗ (0.0048) −0.0686∗∗ (0.0331)

0.0277∗∗∗ (0.0062) 0.1329∗∗ (0.0529)

0.0048∗ (0.0027) 0.0052 (0.0211)

0.2637∗∗∗ (0.012) 0.0018∗∗∗ (0.0007) 0.0297∗∗∗

−0.1373 (0.2654) 0.0761∗∗∗ (0.0187) −0.4903∗∗∗

(0.1176) 0.0099 (0.0774) −0.0560 (0.2032) 0.2559∗∗∗ (0.0216)

(0.0070) −0.0091∗∗ (0.0042) 0.0001 (0.0054) −0.0021 (0.0034) 0.0187∗∗ (0.0086) 0.0057 (0.0764)

(0.1179) −0.0293 (0.0775) −0.0624 (0.2034) 0.2625∗∗∗ (0.0216)

−5.5415∗∗∗ (0.2930)

β 1 +β 3 = 0

0.0911∗ (0.0530) −0.2586 (0.3249)

0.0187∗∗ (0.0072) −0.0801 (0.0937)

−5.4354∗∗∗ (0.2925)

12.82∗∗∗ (0.0000)

(F value, p value) Firm Effect Year Effect Pseudo R2 Adj. R2 F Value N

−6.6584∗∗∗ (0.2606)

0.2286∗∗∗ (0.0169) −1.2712∗∗∗ (0.1028)

NO Control 0.092

17,476

Control Control

Control Control

Control Control

0.057 15.4251 17,476

0.054 6.1082 6636

0.093 21.5805 10,840

NO Control 0.105

17,476

Control Control 0.225 53.066 17,476

0.2637∗∗∗ (0.0120) 0.0018∗∗∗ (0.0007) 0.0297∗∗∗ (0.0070) −0.0091∗∗ (0.0042) 0.0001 (0.0054) −0.0021 (0.0034) 0.0187∗∗ (0.0086) 0.0057 (0.0764) 8.49∗∗∗ (0.0030)

NO Control 0.092

17,476

Control Control

Control Control

Control Control

0.067 19.7815 17,476

0.051 5.4994 6636

0.093 21.4133 10,840

NO Control 0.112

17,476

Control Control 0.225 53.066 17,476

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−0.1419 (0.2653) 0.0632∗∗∗ (0.0183) −0.4881∗∗∗

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Table 10 (continued)

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Table 10 reports the results for the Heckman two-stage selection model. In the first stage, the coefficient of Geographic IV is positive and statistically significant, as shown in Columns 1 and 5 of Table 10. This result indicates that firms are more likely to acquire bank ownership if the percentage of geographicallyproximate firms is high. In the second stage, we included the inverse Mill’s ration (MILLS) as an additional control variable in our investment efficiency regressions. The results are quantitatively similar, as shown in Columns 2 to 4 and Column 6 in Table 10. Bank ownership improves investment efficiency among bank holding firms. In Columns 7 and 11 of Table 10, the regional population 5 years before the start of the sample period is the second instrument variable, and these results are consistent with our previous findings.

cess stock returns (adjusted for firm size and market) to book ratio as the measure of the firm’s stock performance. Following Aktas et al. (2015) and Barber and Lyon (1997), we defined excess stock return (Excess return) as the difference between firm and benchmark portfolio buy-and-hold annual returns. The benchmark portfolios were the 25 Fama-French portfolios formed based on size and book to market ratio. The benchmark portfolio return is a value-weighted return based on market capitalization within each of the 25 portfolios. In Table 11, bank ownership significantly improved firm value, as shown in Columns 1 to 3, and stock performance, as shown in Columns 4 to 6, for full sample, overinvestment, and underinvestment subsamples. This result ruled out the above mentioned concern and provided robust evidence for our argument that bank ownership improves investment efficiency and increases firm value.

4.5.2. Bank ownership and firm value Another potential concern was that the reduction of overinvestment and underinvestment would not necessarily suggest an improvement in investment efficiency. For example, alleviated financial constraints may induce insiders to misuse the additional capital obtained through bank ownership. To provide robust evidence, we examined the impact of bank ownership on firm value and reported the results in Table 11. Following Correa and Lel (2016) and Ravid and Sekerci (2018), we measured the firm value by using the natural logarithm of Tobin’s Q. In addition, we used ex-

4.5.3. Additional robustness tests In this section, we discuss additional tests that we utilized to ensure the robustness of our results. First, to further mitigate concerns regarding potential selection bias, we performed the Propensity Score Matching (PSM) estimation to test the influence of bank ownership on investment efficiency and our channel arguments. We matched each bank holding firm with a non-bank holding firm that had the closest propensity score in the same year and industry. The propensity score was estimated by using firm size, ROA, growth rate, Tobin’s Q, tangibility, number of board of directors,

Table 11 The impact of bank ownership on firm value. This table presents the regression results for the impact of bank ownership on firm value. The Columns 1 and 4 present the regression result for the full sample. The Columns 2 and 3, and 5 and 6 present the regression results for overinvestment firms subsample and underinvestment firms subsample, respectively. The dependent variable, ‘ln(tbq)’ is the logarithm of Tobin’s Q in Columns 1 to 3. The dependent variable, ‘Excess return’ is excess stock return which is the difference between annual stock return and annual value-weighted benchmark portfolio return. The independent variable, Bank, is a dummy variable which takes the value of 1 if a firm is a bank holding firm, and 0 otherwise. Control variables are defined in Appendix A. All independent variables are one year lagged. All regressions include firm and year fixed effect. Robust standard errors are clustered at the firm level and reported in parentheses. ∗ , ∗∗ and ∗∗∗ indicate significance at the 10%, 5% and 1% levels, respectively. (1)

(2)

(3)

Dependent variables: ln(tbq)

Bank Lnsze Tang ROA Lnboard Loss Dual Largest Invest Lev CFO Lnage _cons Firm and Year Effect Adj. R2 F N

(4)

(5)

(6)

Dependent variables: Excess return

Full Sample

Overinvestment

Underinvestment

Full Sample

Overinvestment

Underinvestment

0.0588∗∗∗ (0.0170) −0.4819∗∗∗ (0.0127) −0.05 (0.0569) 1.5265∗∗∗ (0.1341) 0.1903∗∗∗ (0.0228) 0.1681∗∗∗ (0.0185) 0.0693∗∗∗ (0.0165) −0.2366∗∗∗ (0.0795) −0.1571 (0.1098) −0.2989∗∗∗ (0.0481) 0.6911∗∗∗ (0.0722) 0.6231∗∗∗ (0.0201) 9.0776∗∗∗ (0.2824)

0.0726∗∗ (0.0312) −0.3863∗∗∗ (0.0198) 0.0506 (0.0823) 1.4494∗∗∗ (0.2365) 0.1037∗∗∗ (0.0397) 0.1724∗∗∗ (0.0336) 0.0437 (0.0279) −0.3660∗∗∗ (0.1227) −0.4218∗∗ (0.1786) −0.1663∗∗ (0.0739) 0.8707∗∗∗ (0.1380) 0.4562∗∗∗ (0.0320) 7.8441∗∗∗ (0.4312)

0.0486∗∗ (0.0207) −0.5181∗∗∗ (0.0152) −0.0555 (0.0731) 1.4144∗∗∗ (0.1649) 0.2239∗∗∗ (0.0288) 0.1653∗∗∗ (0.0224) 0.0737∗∗∗ (0.0203) −0.2431∗∗ (0.0962) 0.0319 (0.1387) −0.3225∗∗∗ (0.0607) 0.6387∗∗∗ (0.0855) 0.6907∗∗∗ (0.0244) 9.5685∗∗∗ (0.3398)

0.0586∗∗ (0.0232) −0.2411∗∗∗ (0.0117) 0.5665∗∗∗ (0.0610) −1.1453∗∗∗ (0.1680) 0.2839∗∗∗ (0.0250) −0.0566∗∗ (0.0270) 0.0231 (0.0186) 0.3171∗∗∗ (0.0755) −0.2275∗ (0.1316) 0.2346∗∗∗ (0.0483) 0.3238∗∗∗ (0.1033) −0.0536∗∗∗ (0.0184) 4.8827∗∗∗ (0.2723)

0.0682∗ (0.0365) −0.2637∗∗∗ (0.0248) 0.4536∗∗∗ (0.1237) −1.5490∗∗∗ (0.3534) 0.2414∗∗∗ (0.0512) −0.0621 (0.0503) 0.0377 (0.0411) 0.4462∗∗∗ (0.1673) −0.3714 (0.2593) 0.2833∗∗∗ (0.1038) 0.2958 (0.2024) −0.0457 (0.0397) 5.5545∗∗∗ (0.5733)

0.0649∗∗ (0.0312) −0.2257∗∗∗ (0.0161) 0.6129∗∗∗ (0.0875) −1.1249∗∗∗ (0.2189) 0.3043∗∗∗ (0.0346) −0.0519 (0.0349) 0.0099 (0.0253) 0.2590∗∗ (0.1010) −0.2099 (0.1833) 0.1631∗∗ (0.0673) 0.3572∗∗∗ (0.1302) −0.0813∗∗∗ (0.0264) 4.5264∗∗∗ (0.3666)

Control 0.235 87.3935 22,258

Control 0.166 39.2696 8368

Control 0.259 67.938 13,890

Control 0.075 75.1362 22,256

Control 0.077 16.9246 8368

Control 0.074 39.8967 13,888

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Table 12 Propensity score matching analysis. This table presents the regression results for impact of holding bank ownership in reducing investment inefficiency by employing the propensity score matching model. Variables are same as Table 2 and are defined in Appendix A. All independent variables are one year lagged. All regressions include intercept, and firm and year fixed effect. Robust standard errors are clustered at the firm level and reported in parentheses. ∗ , ∗∗ and ∗∗∗ indicate significance at the 10%, 5% and 1% levels, respectively. (1)

(2)

(3)

(4)

Dependent variables: Investment inefficiency Full Sample Bank

−0.0022 (0.0007)

∗∗∗

Overinvestment −0.0039 (0.0014)

∗∗∗

Dependent variables: Investment Underinvestment −0.0011 (0.0006)

∗

Tbq Bank × Tbq Firm and Year Effect Adj. R2 F Value N

Control 0.076 12.7248 7106

Control 0.065 5.4065 2645

Control 0.111 16.6473 4461

Full Sample −0.0002 (0.0013) 0.0000 (0.0004) 0.0012∗∗ (0.0005) Control 0.478 34.1482 7122

Table 13 The impact of bank ownership on investment efficiency: Top and bottom quartile of abnormal investment evidence. This table presents the empirical results on the impact of bank ownership on investment inefficiency in sample of top and bottom quartile of unexpected investment based on Eq. (1). Variables are same as reporting in Table 2 and are defined in Appendix A. All independent variables are one year lagged. All regressions include intercept, and firm and year fixed effect. Robust standard errors are clustered at the firm level and reported in parentheses. ∗ , ∗∗ and ∗∗∗ indicate significance at the 10%, 5% and 1% levels, respectively. (1)

Bank

(2)

(3)

(4)

Dependent variables: Investment inefficiency Full Sample Overinvestment

Underinvestment

Dependent variables: Investment Full Sample

−0.0035∗∗ (0.0015)

−0.0028∗∗ (0.0014)

−0.0063∗∗ (0.0029)

−0.0006 (0.0032) 0.0004 (0.0006) 0.0025∗ (0.0013)

Control 0.049 11.8537 11,130

Control 0.055 5.6502 5565

Control 0.065 6.9450 5565

Control 0.130 27.6636 11,130

Tbq Bank × Tbq Firm and Year Effect Adj. R2 F Value N

firm’s auditor, duality, whether the firm had negative profits.12 The results reported in Table 12 are consistent with our previous findings.13 Bank ownership significantly reduced investment inefficiency by mitigating overinvestment and underinvestment through the disclosure channel and financing channel, respectively. Second, we acknowledged the possibility that our results could be biased by the coexistence of financial constraints and agency problems. If firms are subject to both financial constraints and agency problems, bank ownership may induce a previously overinvesting (underinvesting) firm to move to underinvesting (overinvesting). Thus, reduction in investment inefficiency may not be driven by improvement of investment efficiency but, rather, by shifting dominating frictions. To address this potential concern, we split the sample into quartiles based on the residual from Eq. (1) and focused on the top and bottom quartiles of the firm-year observations only. Those firms were less likely to shift from overinvestment (underinvestment) to underinvestment (overinvestment). Thus, the results reported in Table 13 were found to be robust. Besides the results reported above, we also conducted a series of robustness tests. First, we excluded firms that were shareholders of listed banks; this was done in order to rule out the following al-

12 Our results were robust when we used different matching methods, and we employed different set of variables to estimate the propensity score. 13 For the sake of brevity, the PSM results are not reported for our channel tests. These results are consistent with our previous findings.

ternative explanation: the improved investment efficiency is driven by the return from investment in banks. Since unlisted banks’ equity is much more illiquid, firms have less incentive to hold ownership in unlisted banks if they are seeking high investment returns. Second, we employed alternative measurements for bank ownership: the highest bank ownership held by a non-financial firms (BankR) and the number of banks where a non-financial firm has equity ownership (BankN). Third, following Lu et al. (2012), we set the bank ownership threshold as 5% equity in banks; furthermore, we examined whether the impact of holding bank ownership was affected by this ownership threshold. We found that our results were robust. We have not included the tables recording these estimations for brevity reasons. 5. Conclusion and discussion This study examined bank ownership and investment decisions in the Chinese capital market. We found significant evidence that bank ownership improves investment efficiency by reducing both underinvestment and overinvestment and by improving investment sensitivity to investment opportunities. Further evidence supported our conjecture that bank ownership’s positive impact on investment efficiency is facilitated through intensified disclosure requirements and supervisions (disclosure channel) and reduced financial constraints (financing channel). Consistent with our disclosure channel argument, bank ownership was found to reduce both tunneling through related-party

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transactions and excess corporate cash holdings; furthermore, it improved the quality of firms’ financial reporting and the market value of cash, especially in firms with more serious agency problems. In addition, we found that bank holding firms had access to more bank loans, had lower cash flow sensitivity of cash, and were less sensitive to tight monetary policy. These results supported the argument that bank ownership alleviates financial constraints, which, in turn, reduces underinvestment. In addition, we found that bank ownership had a more pronounced impact on investment efficiency in non-SOEs, in firms located in provinces with less developed institutions, and in firms with less institutional investors. Our results are robust regarding corrections based on bank ownership endogeneity and alternative explanations. Bank holding firms are not unique to China, and they can be found in several other countries. La Porta et al. (2003) showed that the value of non-financial entities controlling a bank depended on the quality of disclosure requirements and supervision. In many developing countries, weak institutional environments enable bank holding firms to allocate banks’ capital to areas where they can expropriate for a higher return; thus, weakly designed disclosure regulations and supervision systems can largely reduce the value of this downward vertical bank-firm connection. Our study suggests that implementation of strong governance mechanisms in bank holding firms can maximize the benefits of this unique ownership structure. The regulatory designs of bank holding firms in China may offer some experience for other countries with similar institutional settings. To minimize insiders’ expropriation, we suggest that governments should impose strict disclosure requirements on bank holding firms and closely monitor related-party transactions within such business groups. Supplementary materials

Variable Excess cash holding Geographic IV

Growth

I InDep Ins

Largest

Lev Lnage Lnboard Lnsize Long Term Loss Market

MB MShare Monetary

NA Nonstate

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.jbankfin.2020.105741.

CFO Population Ret ROA RPT

Appendix A. Variable definition

Separation Short Term Stock25

Variable Investment Investment inefficiency Overinvestment Underinvestment Bank

BankN BankR Big4 CapEx Cash Holding Discretionary Accruals

Div Dual Excess Excess return

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Definition The total investment expenditures scaled by the by the total assets. The deviation from the optimal level of investment which is the residual of the Eq. (1). The absolute value of positive residual of Eq. (1). The absolute value of negative residual of Eq. (1). A dummy variable which takes the value of 1 if a firm who is the shareholder in at least one bank, and 0 otherwise. The number of banks a firm holds their ownership. The highest banks’ equity stakes a firm holds. A dummy variable that equals 1 if the firm’s auditor is one of the big-four audit firms, and 0 otherwise. Ratio of capital expenditures to total assets. Cash and cash equivalents assets divided by total assets. The absolute residual of a performance-adjusted discretionary accruals model, following Kothari et al. (2005). Ratio of total cash dividend payment to total assets. A dummy variable that equals 1 if firm’s CEO and chairperson is the same person, and 0 otherwise. The difference between controlling shareholders’ control rights and cash flow rights. The difference between firm and benchmark portfolio buy and hold annual returns.

Tang Tbq

Total Loan

Definition The difference between corporate cash holdings and industry median of corporate cash holdings. The 5-year lagged percentage of bank holding firms that are in the same region as the focus firm but are not in the same industry. The difference between this year’s sale and the previous year’s sale divided by the previous year’s sale. Ratio of total financial expenses to total assets. Ratio of number of intendent directors to total number of directors on the board. A dummy variable equals 1 if one of the firm’s 10 largest shareholders is an institutional investor, and 0 otherwise. A dummy variable that equals 1 if firm’s largest shareholder holds more than 50% of firm ownership, and 0 otherwise. Ratio of total liabilities to total assets. Logarithm of one plus number of years since the firm was listed on the stock exchange. Logarithm of total number of directors on the board. Logarithm of total assets. Ratio of long term bank loans to total assets. A dummy variable that equals 1 if a firm has negative net profit, and 0 otherwise. The provincial level Chinese marketization index produced by the National Economic Research Institute (Fan et al., 2016). Ratio of market value to book value of equity. Ratio of shares owned by managers to total share outstanding. A dummy variable that equals 1 for the period of tight monetary policy when the growth rate of M2 is less than its median. Ratio of net asset which defined as the total asset minus cash to total assets. A dummy variable if firm is not controlled by government agency, and 0 otherwise. Cash from operation scaled by total assets. The provincial population in 100 million in 2000. Annual stock return. Ration of after-tax operating income to total assets. The ratio of related party transactions to total asset by following Cheung et al. (2006). The differences between control rights and cash flow rights. Ratio of Short term bank loans to total assets. The total shares held by the second to fifth largest shareholders. Ratio of tangible assets to the total assets. Ratio of market value to book value of assets; market value of assets is proxies by market value of equity plus book value of total liabilities. Ratio of total bank loans to total assets.

CRediT authorship contribution statement Hongjian Wang: Conceptualization, Methodology, Software. Tianpei Luo: Writing - original draft. Gary Gang Tian: Validation, Methodology, Supervision, Writing - review & editing. Huanmin Yan: Data curation, Visualization, Investigation. Reference Akagami, H., Ishii, W., Sohkawa, H., 2018. Japan. In: Putnis, J. (Ed.), The Banking Regulation Review, ninth ed. The LawReviews, United Kindom. Aktas, N., Croci, E., Petmezas, D., 2015. Is working capital management valueenhancing? Evidence from firm performance and investments. J. Corp. Finance 30, 98–113. doi:10.1016/j.jcorpfin.2014.12.008. Almeida, H., Campello, M., Weisbach, M.S., 2004. The cash flow sensitivity of cash. J. Finance 59, 1777–1804. doi:10.1111/j.1540-6261.20 04.0 0679.x. Bae, G.S., Choi, S.U., Dhaliwal, D.S., Lamoreaux, P.T., 2017. Auditors and client investment efficiency. Account. Rev. 92, 19–40. doi:10.2308/accr-51530. Bae, K.-H., Kang, J.-K., Kim, J.-M., 2002. Tunneling or value added? Evidence from mergers by Korean business groups. J Finance 57, 2695–2740. doi:10.1111/ 1540-6261.00510.

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Please cite this article as: H. Wang, T. Luo and G.G. Tian et al., How does bank ownership affect firm investment? Evidence from China, Journal of Banking and Finance, https://doi.org/10.1016/j.jbankfin.2020.105741