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IPO excessive financing, managerial power, and private benefits: evidence from the IPO market in China IPO excessive financing, managerial power, and private benefits: evidence from the IPO market in...
Zhao, Gang; Liang, Shangkun; Wang, Weixing
2017-01-02 00:00:00
China Journal of aCC ounting StudieS , 2017 Vol . 5, no . 1, 73–99 http://dx.doi.org/10.1080/21697213.2017.1292727 IPO excessive financing, managerial power, and private benefits: evidence from the IPO market in China* a,b c b Gang Zhao , Shangkun Liang and Weixing Wang a b School of accountancy, Zhejiang university of f inance and economics, hangzhou, China; School of Business, Changzhou university, Changzhou, China; School of a ccountancy, Central university of f inance and economics, Beijing, China ABSTRACT KEYWORDS Excessive financing by means of an initial public offering (IPO) iPo excessive financing; is an important issue in the resource allocation efficiency of the managerial power; monetary capital market that has deeply concerned the public and regulatory private benefits; non- authorities. Within the Chinese context and applying the theory of monetary private benefits managerial power, we discuss the influence of IPO excessive financing on the private benefits of top managers. Using data on companies listed in 2006–2011, we find that: (1) the top managers of listed companies with excessive financing obtain greater monetary and non-monetary private benefits; (2) this phenomenon is significant for both state-owned and non–state-owned firms; (3) in non–state- owned enterprises, the greater the managerial power, the greater the monetary and non-monetary private benefits top managers receive, whereas this relation does not exist in state-owned enterprises; and (4) the market responds negatively to companies with excessive financing that provide greater monetary private benefits to top managers, but there is no significant response to companies that provide greater non-monetary private benefits to top managers. This paper expands the research on the economic consequences of excessive financing via an IPO and managerial power and provides regulatory implications of such excessive financing. 1. Introduction Since the opening of the Growth Enterprise Market (GEM) in China in 2009, three phenomena, namely high excessive financing, high offering prices, and high price-to-earnings ratios, have become increasingly common. High excessive financing refers to the scenario in which the amount a listed company actually raises in an initial public oe ff ring (IPO) exceeds the amount planned. According to a 2012 report in the Shanghai Business Daily, of 138 new firms that were first listed in 2012, 125 experienced excessive financing, comprising 90.58% of IPO cases; the excessive funds raised by the 138 IPO firms totalled 32.844 billion Yuan; otherwise stated, the average excessive funds raised per IPO case were 238 million Yuan and the CONTACT Weixing Wang wwx@cczu.edu.cn *Paper accepted by Cong Wang. Shanghai Business Daily, http://ipo.china.com.cn/ps/20120919/12763.shtml. © 2017 a ccounting Society of China 74 G. ZHAO ET AL. proportion of excessive financing was 88.16%. This phenomenon reflects investors’ expec - tations that IPO firms can create value in the future. However, do these listed companies use the excessive financing efficiently? According to the Shanghai Business Daily aforementioned reports, many companies with excessive financing have no proper projects to invest in for a long period and these funds can only be used to repay loans or supplement liquidity. . The inefficient use of the funds has aroused widespread concerns and queries from the public and regulatory authorities (Fang & Fang, 2011). The capital market’s main function is to optimise the allocation of resources, but the excessive allocation of funds is a mismatch of resources, which will lead to low efficiency in the use of funds, waste, and asset misappropriation (Jiang & Li, 2010). Excessive financing allows listed companies to obtain more cash flow than expected. Lacking effective planning, such cash flows are equivalent to an increase in the company’s free cash flow, which is likely to lead to opportunistic executive behaviour (Jensen, 1986). Will opportunistic behaviour, such as above-normal monetary rewards, arise after IPO excessive financing in listed com- panies? At the same time, because of monetary compensation regulations, more invisible perks become alternative choices for executive compensation. Accordingly, one question is whether the executives of companies with excessive financing will increase their private benefits by means of perks. In addition, many listed companies experience situations such as absence of ownership, chief executive officer (CEO) duality, and share decentralisation, all of which convey more power to top managers. The board of directors, then, cannot fully control the design of management compensation. Therefore, another question is whether managerial power increases the private benefits of executives of companies with excessive financing, damaging shareholder interests. To address the above questions, this paper discusses the impact of IPO excessive financing on the private benefits of executives, based on Chinese IPO financing data and the theory of managerial power. Using companies listed in 2006–2011 as our sample, we find that (1) the top managers of listed companies with excessive financing obtain greater monetary and non-monetary private benefits; (2) this phenomenon is significant in both state-owned and non–state-owned enterprises; (3) the increase in managerial power is helpful in the acqui- sition of monetary and non-monetary private benefits but occurs mainly in non–state-owned enterprises and not in state-owned enterprises; and (4) the market responds negatively when a company with excessive financing pays its executives the excess money but has no significant response to top managers’ excessive non-monetary private benefits. In various robustness tests, the above results remain stable. The contributions of this paper are as follows. First, this paper extends the research on the economic consequences of excessive financing. Previous studies on the economic con- sequences of excessive financing focus mainly on investment efficiency (Chen, 2012; Huang & Zhang, 2013), whereas research on managers’ motivation to obtain private benefits has been neglected. This paper provides more detailed empirical evidence of the impact of excessive financing on executives’ private benefits. In addition, executives are important participants in a company’s IPO decisions (e.g. listing location and timing), but previous studies have paid little attention to whether the executives receive any benefits in the pro - cess. Hung, Wong and Zhang (2012) found that overseas listings can increase the probability f or example, Qifeng Material Co., l td (002521), announced that the shareholder meeting had passed a proposal about the use of extra funds to supplement working capital. http://news.ioozoo.com/20120828/2316260.html. CHINA JOURNAL OF ACCOUNTING STUDIES 75 of executive promotion and our paper provides supplemental evidence from the perspective of private benefits. Second, this paper extends our knowledge on the consequences of managerial power. Managerial power can play an important role in both state-owned and non–state-owned enterprises. However, the results of previous research on whether managerial power differs and how it does with different property rights are unclear. With the unique and significant excessive financing that arises in China’s IPO market, this paper shows how managerial power plays a critical role in corporate governance. Third, this paper sheds light on the regulatory implications of excessive financing. With the restart of IPOs in 2014, although excessive financing has been restrained to a certain degree, how to effectively allocate scarce resources is an issue worthy of attention. In addition to the reform of the mechanism for issuing securities to provide investors with more invest- ment opportunities, effective supervision of the use of excessive funds is very important. The regulatory implications are, then, that information about the use of excessive funds should be released in a timely manner, state-owned enterprises that abuse excessive funds and non-state-owned enterprises whose management has great power should be closely monitored, and the abnormal growth of executive pay and management expenses should be audited. The remainder of the paper is organised as follows. Section 2 presents the institutional background, literature review, and hypothesis development. Section 3 describes the sample selection, variable definitions, and the empirical results. Section 4 presents robustness tests. Section 5 draws our conclusions and describes limitations. 2. Institutional background, literature review and hypothesis development 2.1. Institutional background After the opening of the GEM in 2009, the GEM and small and medium enterprises appeared to gain large amounts of excessive financing. Before an IPO, listed companies must assess the project listing and financing and must provide a detailed description of the funds required for the project in their prospectus, that is, the total amount of funds they plan to raise. After a listed company applies and obtains the approval for the IPO from the Chinese Securities Regulatory Commission (CSRC), it then prepares for the listing. The most important element is to price the value of its stock. Since 2004, IPO pricing has used the inquiry system. First, underwriters recommend that a listing company put on a road show and set the initial price range for institutional investors to make an inquiry. The underwriters will then consider the prices of offline investment institutions and the issuer’s willingness to determine the final issue price within the range of inquiry. Finally, an online placement will be made in accordance with the issue price. The company’s total amount of funds, online and offline, is the total amount raised by the IPO. Excessive funds are the difference between actual funds raised by the company and planned funds (Chen, Guan, Zhang, & Zhao, 2016). To regulate the use of excessive financing funds, the Shenzhen Stock Exchange issued ‘No. 1 GEM information disclosure business memorandum: The use of excessive financing funds’ (No. 1 GEM), addressing listed companies whose actual net funds raised exceed the excessive financing funds are used not only to pay excessive compensation, but also for investments (huang & Zhang, 2013), research and development (r&d; Zhen, 2013), and to supplement working capital (Zhang, l uo, & Yue, 2015). 76 G. ZHAO ET AL. planned amount by 50 million Yuan or exceed 20% of the funds that the companies plan to raise. The memorandum requires that (1) companies’ excessive funds be deposited in a spe- cial account to be managed; (2) excessive financing funds be used for the company’s main business, not for securities investments, entrusted investments, derivative investments, venture capital and other high-risk investments or to provide financial aid to others; (3) the amount of excessive financing funds that is used to supplement working capital and repay bank loans every 12 months should not exceed 20% of the total amount of excessive financ - ing funds but, at the same time, more than two-thirds of independent directors and the sponsor must agree in the deliberation process; and (4) excessive financing funds may be used to temporarily add liquidity equal to using idle funds to add working capital. No. 1 GEM also requires listed companies to draw up a plan for the use of excessive funds raised, to be disclosed after approval by the board of directors within no more than six months after the arrival of the funds raised, considering the company’s development plans and actual production and operation needs. The plan to use excessive financing funds should include (1) an accounting of the basic and excessive financing funds; (2) a description of the project(s) in which to invest the excessive financing funds; (3) the need to repay bank loans or to supplement working capital; (4) how the board of directors considered the use of the excessive funds raised; and (5) independent directors’ and recommendation agency’s sep- arate opinions about the rationality, compliance and necessity of the use of the excessive financing funds. Although the regulation places strict management requirements on excessive financing funds, their misuse still occurs. First, the regulation requires that companies propose, within six months, how they will use the excessive financing funds; however, because it is difficult to find more suitable investment projects in this short time, the likelihood of excessive financ - ing funds remaining idle and being abused will be significant. According to Zhao and Zhou (2014), of the excessive financing funds of 355 companies in the GEM, only 24.01% were invested in new projects, while the proportion of funds with no disclosure was 31.62%. Second, because regulations are not clear about the order of financing funds in IPOs and in plans, a listed company could use funds from the special excessive fund account first, to ultimately embezzle the cash. By contrast with the GEM, the management of excessive financ - ing funds by main boards and small boards has no corresponding regulation, thus increasing the risk of their invalid use of excessive financing funds. 2.2. Literature review 2.2.1. IPO excessive financing There are relatively few cases of IPO excessive financing in foreign countries, so the foreign literature on IPO excessive financing is relatively scant. Booth and Chua (1996) believed that IPO excessive financing would increase market liquidity in the secondary market. Chowdhry and Sherman (1996) found that, when an IPO issue price was set beforehand, the preset price information would be leaked as public information while all the investors were aware that the issue price was too low beforehand, leading to massive IPO excessive financing. Cornelli and Goldreich (2003) showed that IPO excessive financing has a significant impact on the IPO itself, with excessive financing and demand elasticity proportional to the return on the first day of the market. Kenourgios, Papathanasiou, and Melas (2007) studied the influence of excessive financing on IPO underpricing in the emerging Greek stock market CHINA JOURNAL OF ACCOUNTING STUDIES 77 and showed that underwriter reputation and an excessive financing ratio affect the IPO underpricing level. Research on IPO excessive financing has developed in recent years, especially since the GEM opened, mainly in two aspects: the influencing factors of IPO excessive financing and the economic consequences of IPO excessive financing. The literature has determined the following influencing factors in IPO excessive financing. (1) Stock-issuing system changes and supply and demand imbalance in the market Liu and Li (2011) believed that the main factors causing excessive financing in 2009 were stock-issuing system changes and an imbalance in the market’s supply and demand that disrupted the IPO pricing equilibrium and encouraged controlling shareholders and main underwriters, driven by profit, to conspire to boost issue prices. Frequent occurrences of IPO excessive financing could contribute to failure of the pricing mechanism and low fund uti- lisation, harming the interests of small shareholders and creating other problems. Therefore, the regulators ought to strengthen the supervision of IPO excessive financing and improve the distribution and sponsoring systems. (2) Sponsor reputation Wang, Xu, and Wang (2011) used GEM companies that raised capital before 1 July 2010, as their sample, studying the relation between underwriter reputation, income, and the IPO excessive financing during the listing process. The authors found that the better the under - writer’s reputation, the more excessive the IPO financing and, correspondingly, the higher the income of the underwriters in the distribution. Chen (2012) and Zhang and Hong (2012) also studied the effect of the reputation of securities firms on IPO excessive financing and found that underwriter reputation and IPO excessive financing have a significant positive relation, with underwriters with a strong reputation being associated with greater IPO financ - ing ability and more excessive IPO financing. (3) Auditor reputation Wang (2014) analysed a sample of 281 new shares listed on the GEM from 2009 to the end of 2011 and found that auditor reputation and IPO excessive financing have a significantly negative correlation, indicating that the high reputation of auditors significantly reduces the degree of the company’s excessive financing. (4) Investor enthusiasm Yi (2012) hypothesised IPO excessive financing to be inevitable due to incomplete IPO financ - ing contracts. Using GEM companies listed before 2010 as the sample, the author found that the enthusiasm of institutional investors in the primary market, public investor sentiment in the secondary market, and securities traders’ pushing hands are the main reasons for the serious IPO excessive financing of GEM listed companies. Analysis of the economic consequences of IPO excessive financing has mainly reflected the following aspects. (1) Excessive investments and low investment efficiency Chen (2012) found that underwriter reputation and the efficiency of the use of raised funds are negatively correlated, suggesting that it is difficult for the constraint function of the underwriter reputation mechanism to be effective in the context of China’s immature capital market. Huang and Zhang (2013) analysed IPO excessive financing behaviour and found 78 G. ZHAO ET AL. that excessive financing is significantly positively correlated with the probability of enterprise overinvestment behaviour but has a negative correlation with the company’s future value. (2) A decline in performance Huang and Zhang (2013) believed that IPO excessive financing leads to many redundant financial assets, where the greater the proportion of an enterprise’s financial assets, the larger the decline in performance after the IPO. (3) Executive overpayment Fang and Fang (2011) researched the impact of IPO excessive financing on executive com- pensation and found that excessive financing indeed readily contributes to excessive exec - utive compensation in listed companies. (4) Impact on R&D investment Zhen (2013) examined the mechanism of IPO excessive financing and venture R&D invest - ment and found that the amount of funds expected to be raised by managers affects the intensity of the enterprise’s R&D input. When the funds raised exceed the amount expected, the intensity of redundant R&D investment increases; when the scale of fund raising is lower than expected, the enterprise’s intensity of problem R&D investments decreases, resulting in a U-shaped relation between IPO excessive financing and R&D input. The above-mentioned research shows that IPO excessive financing has received the atten - tion of scholars, with a relatively wide range of research topics. However, specific aspects warrant further attention, such as the impact of IPO excessive financing on executive benefits. First, the related research is still relatively scant, with only a few papers, such as that of Fang and Fang (2011). Second, the details require further study. For example, Fang studied the effect of IPO excessive financing on executive compensation but mainly provided descriptive statistics and universal tests. In addition, the author did not examine the die ff rences between enterprises in great depth. 2.2.2. Executive compensation In a modern company, with separation of ownership and management rights, the main theory of compensation incentives includes optimal contract theory and managerial power theory. According to optimal contract theory, to avoid managerial decisions that deviate from maximising shareholder value, executive compensation should be closely linked to shareholder wealth through effective contractual arrangements that motivate management based on maximising shareholder interests (Jensen & Meckling, 1976). Regarding the con- tracts, managerial power theory assumes that the board of directors cannot completely control the design of managers’ compensation contracts. In the absence of effective super - vision, managers can influence their own pay and have rent-seeking power; the greater the managers’ power, the stronger their ability to control their own compensation (Bebchuk, Fried, & Walker, 2002; Bebchuk & Fried, 2005). Can the design of compensation motivate executives to perform better? A large number of studies of countries beyond China have confirmed that general managers’ compensation in listed companies is significantly positively correlated with corporate performance (Core, Holthausen, & Larcker, 1999; Jackson, Lopez, & Reitenga, 2008; Leone, Wu, & Zimmerman, 2006; Murphy, 1985), demonstrating the rationality of the managerial compensation system to a certain extent. However, Jensen and Murphy (1990) showed that, although US company CHINA JOURNAL OF ACCOUNTING STUDIES 79 executive compensation and performance are statistically significantly correlated, the eco - nomic impact is very weak, with a downward trend. In China, because the compensation of the managers of state-owned enterprises is reg- ulated, perks are popular as another type of compensation, in addition to salary and bonuses, and have a significant negative impact on company performance (Chen, Chen, & Wan, 2005). With the deepening reform of the salary system, the executive compensation of listed com- panies in China has presented significant performance sensitivity, but asymmetrically, with significantly higher amplitudes for increases in salary with increases in performance than the amplitudes of decreases in salary with declines in performance. At the same time, private enterprises and central government-controlled enterprises exhibit less executive compen- sation stickiness (Fang, 2009). On the whole, research on IPO excessive financing in executive compensation is still relatively scarce. Do the executives of companies that raised excessive funds gain higher private returns? Are these found in terms of monetary compensation or perks? What is the effect of managerial power on the private benefits of the executives of companies with IPO excessive financing? These issues are discussed further in this paper. 2.3. Hypothesis development The separation of ownership and management rights is an important feature of modern companies, producing agency problems between management and shareholders. The tar- gets of managers and shareholders are inconsistent, so managers will maximise their own interests to the detriment of shareholders. Effective compensation contract arrangements can closely link management compensation to shareholder value, to motivate managers to act based on the maximisation of shareholder interests (Jensen & Meckling, 1976). Implementation of such an arrangement requires more stringent conditions. For example, shareholders must have full access to information on management behaviour, be able to exercise their rights, and establish an effective external manager market to constrain man- agerial behaviour. However, because of information asymmetry in the Chinese context, shareholders cannot fully supervise managers’ behaviour and it is also difficult for share - holders to effectively exercise their rights. What is more, an effective manager market has not been established in China (Huang & Xi, 2009). Therefore, it is difficult for shareholders to put an end to the opportunistic behaviour of management. In the IPO process, many listed companies raise large amounts of funds. Although the Shenzhen Stock Exchange has made provisions for management of firms whose IPO raises excessive financing in the GEM to develop the use of excessive raised funds within six months, owing to the short time it has been difficult to carry out effective arrangements for all excess raised funds. In addition, no regulations were available on IPO excessive financing for the main boards and small boards of listed companies. Due to the absence of a specific plan to use the funds raised in advance, part of the funds increase the company’s free cash flow. According to Jensen (1986), the increase in the free cash flow of enterprises leads to the more opportunistic behaviour of executives. On the one hand, when cash flow is sufficient, executives directly enhance their levels of monetary compensation; on the other hand, because executive pay is related to firm size and growth, in the case of large free cash flows, executives build business empires, expanding enterprise control to obtain excess monetary compensation. At the same time, because perks and other non-monetary compensation do 80 G. ZHAO ET AL. not have to be disclosed, are more concealed and are not affected by government regulation, executives can also increase their private benefits through more perks (Quan, Wu & Wen, 2010). We therefore propose the following hypothesis. H1: Ceteris paribus, the higher the ratio of excess raised funds, the greater the private benefits of executives. IPO excessive financing provides managers with opportunities to increase private benefits, but these private benefits ultimately depend on their ability to obtain private benefits. For Chinese listed companies, ‘one dominating share’ is an important feature of ownership (Zhao, & Yu, 2005). Even after the split share structure reform, the proportion of first shareholders in many companies is very high (Li, Wang, Cheung, & Jiang, 2011; Liao, Shen, & Li, 2008). A large number of studies have indicated serious insider control in state-owned enterprises. For private enterprises, the power of management is mainly the power of large shareholders (Lu, Wei & Li, 2008). Because of management rights, boards of directors are often captured or affected by managers. Boards of directors cannot completely control the design of man- agement compensation contracts. In the absence of effective supervision, managers have the ability to influence their own compensation and use their power to seek rents; the greater the power, the stronger their ability to manipulate their own compensation (Quan, Wu, &Wen, 2010). According to the homo economicus hypothesis, executives maximise their own interests. The greater the power of executives, the stronger their ability to obtain private benefits. Therefore, we propose the following hypothesis. H2: Ceteris paribus, the greater of the managerial power of executives, the higher the private profits they obtain in a company with IPO excessive financing. 3. Sample selection, variable definitions, and empirical test 3.1. Sample selection Companies’ basic information, financial data, and compensation data are obtained from China Stock Market & Accounting Research. The listed companies’ financing plans and actual financing data are from the WIND database. We choose companies listed from 2006 to 2011 as the initial sample. The data start in 2006 because the CSRC carried out a large stock market adjustment in 2005, halting IPO issues for one year. After 2006, China’s stock market returned to normal. The sample period stops in 2011 to avoid the impact of anti-corruption regulations and the ‘eight rules’, which have restricted executive compensation and perks since 2012 (Mei & Ge, 2016). Since excess funds cannot have a long-term impact on an enterprise, the main impact should be reflected in the company’s first few years after the listing. We therefore select the first three years of listed companies as the observation period. We then screen the sample as follows: (1) we exclude financial and insurance industry companies, since their accounting standards are different from those of other industries; (2) we exclude cross-listed companies that list both B and H shares, since their regulatory environment and accounting systems differ from those of general A-share companies; and (3) we delete companies missing related data. Our final sample comprises 2059 observations. Panel A of Table 1 shows the annual distribution of the sample: 81, 195, 249, 404, 629 and 509. The 2010 figure is the largest, at 30.16%, and the 2006 figure is the smallest, at only 3.93%. Panel B shows the industry distribution, the largest number of samples belonging to the manufacturing industry, which accounts for 68.04% of the total sample. CHINA JOURNAL OF ACCOUNTING STUDIES 81 Table 1. Sample distribution. Panel a: Yearly distribution Year N Percent 2006 81 3.93 2007 195 9.47 2008 249 12.09 2009 404 19.62 2010 621 30.16 2011 509 24.72 t otal 2059 100.00 Panel B: industrial distribution industry N Percent a griculture, forestry, livestock farming, fishery 38 1.85 Mining 69 3.35 Manufacturing 1401 68.04 electric power, steam and hot water production and supply 16 0.78 Construction 56 2.72 t ransportation and storage 52 2.53 information technology industry 241 11.7 Wholesale and retail trade 53 2.57 real estate 31 1.51 Social services 66 3.21 Communication and cultural industry 29 1.41 Comprehensive 7 0.34 t otal 2059 100.00 3.2. Variable definitions (1) Excessive financing This paper uses two indicators to measure excessive financing. The variable OVR represents an excessive financing rate equal to funds actually raised minus funds planned to be raised, divided by funds planned to be raised. The variable HOV represent high excessive financing: If the proportion of excessive financing is greater than or equal to the median, its value is one and zero otherwise. (2) Executive monetary private benefits We use non-normal executive compensation to measure executive monetary private benefits and it is equal to management’s actual salary minus the expected normal pay of executives determined by economic factors (Core, Guay, & Larcker, 2008; Firth, Fung, & Rui, 2006; Quan et al., 2010). The expected normal pay of executives determined by economic factors can be estimated by the following model: LnPayment = + Size + ROE + ROE + Areawage + Central + West it 0 1 it 2 it 3 it−1 4 it 5 it 6 it + YearandIndustryDummies + it (1) where LnPayment represents the income of the top executives, the natural logarithm of the it pay of the top three executives; Size represents company size, the natural logarithm of total it assets; ROA represents the rate of return on total assets this year; ROA represents the rate it it–1 of return on total assets last year; Areawage represents the average wage of the employees it of the listed companies in prefecture-level cities; Central is a dummy variable that equals it one if the listed company is in the central region and zero otherwise 0; and West is a dummy it variable that equals one if the listed company is in the western region and zero otherwise. 82 G. ZHAO ET AL. We run a regression analysis using model (1) to predict the value in the model. The difference between the actual salary and the normal salary is the non-normal salary. (3) Executive non-monetary private benefits We use the gap between management consumption and normal perks determined by eco- nomic factors (Luo, Zhang, & Zhu, 2009; Quan et al., 2010). We use the following model to estimate normal executive consumption: Perks ΔSale PPE Inverntory it it it it = + + + + + LnEmployee + 0 1 2 3 4 5 it it Asset Asset Asset Asset Asset it−1 it−1 it−1 it−1 it−1 (2) where Perks represents executive in-service consumption, with data obtained from man- it agement fees deducted from directors’, executives’ and supervisors’ salaries, bad debts, declines in inventory, the amortisation of intangible assets, and other categories not part of in-service consumption; Asset represents total assets last year; ΔSale represents changes it–1 it in the main business income of the current period; PPE represents the net value of fixed it assets, such as plant, property and equipment; Inventory represents the total inventory of it the current period; and LnEmployee is the natural logarithm of the total number of employ- it ees employed by the enterprise. We use model (2) to conduct a regression analysis by year and industry. The values predicted through regression models represent normal perks. (4) Managerial power We measure managerial power indirectly by following the literature (Grinstein & Hribar, 2004; Lu, Wei & Li, 2008; Quan et al., 2010). We choose CEO duality, dispersed sharehold- ings, and a long tenure to define managerial power. CEO duality and dispersed sharehold- ings is reflected in the spatial dimension and a long tenure is reflected in the temporal dimension. The value of CEO duality (POWER1) is one when a person is both the chairper- son and CEO and zero otherwise. The value of dispersed shareholdings (POWER2) is one when the proportion of the first largest shareholder divided by the proportion of the second to tenth largest shareholders is less than one and zero otherwise. The value of long tenure (POWER3) is one if the chairperson or CEO is still in office before the IPO and four years after and zero otherwise. We then synthesise a composite variable from these three single-dimensional variables to represent managerial power: POWER_N = POWER1 + POWER2 + POWER3. The bigger POWER_N is, the greater the managerial power. The variable POWER_D is a dummy variable that equals one when POWER_N ≥ 2 and zero otherwise. (5) Limitations in index calculation There are limitations to the above method of calculating the power of management and private benefits. For example, in the calculation of the indicators of managerial power, we highlight the relation between the CEO and the chairperson. However, in the model, we choose the compensation of the top three highest paid executives instead of executive compensation and choose the total consumption of all senior executives instead of non-pe- cuniary compensation. There is therefore a logical inconsistency. These limitations are com- mon problems faced by such studies. CHINA JOURNAL OF ACCOUNTING STUDIES 83 3.3. Model setup To test H1, we add excessive financing (OVR/HOV) and related control variables based on the research of Jackson et al. (2008) and Quan et al. (2010). The model is as follows: Overpay∕Overperk = + OVR(HOV)+ Controls + (3) 0 1 where Overpay represents private benefits, that is, the difference between the natural log- arithm of executives’ salaries and the natural logarithm of the expected normal salary and Overperk represents the private non-monetary benefits of executives, which equals the dif- ference between executives’ actual perks and expected normal perks. Excessive financing is the main explanatory variable, using OVR and HOV measured from two aspects, where OVR represents the ratio of excessive financing, calculated as the actual amount of financing minus the amount of planned financing, divided by the amount of planned financing. The variable HOV is a dummy variable that equals one if the proportion is greater than or equal to the median and zero otherwise. The variable Size is the logarithm of a company’s total assets at the end of the year, measuring the size of the enterprise. The company’s size is in direct proportion to salary: the greater the scale, the higher the salary. The variable Leverage is the company’s long-term asset liability ratio, where a company that has a high rate of assets and liabilities may face greater risk, such that the asset liability ratio is negatively correlated with executive compensation. The variable ROE is the company’s return on net assets, where a high ROE can bring in more revenue to the company and reduce its risk. The better the company’s performance, the higher the pay of executives. The variable RET rep- resents stock returns and MB is the ratio of the market value to the book value, which indi- cates the enterprise’s growth. Enterprises with good prospects may face more risks but may also bring in more revenue to the company, so the impact of executive pay is uncertain. In addition, we control for broker reputation, the proportion of independent directors, whether manager’s compensation is received, whether there is an equity incentive, the number of shares, and the nature of the enterprise. The variable Top 10 stands for the repu- tation of the brokers the company hired and equals one if the rank of brokers underwrite is in the top 10 and zero otherwise. The broker’s reputation can help IPO companies raise more funds. The variable Indep_R is the proportion of independent directors. The higher this pro- portion, the stronger the supervision that can restrict management’s self-interest. Since some company executives do not get paid, to control for that impact, we construct the ZeoSalary variable, which equals one if the executives do not receive remuneration and zero otherwise. The variable Option is a dummy variable that equals one if the company has an equity incentive and zero otherwise. We also control for the number of shares held by man- agement, Managerial ownership (Manage share), which also affects executive pay. The unit of this measure is millions of shares. Depending on the nature of the ultimate controller, enterprises are divided into state-owned and private enterprises. If the ultimate controller is a state-owned holding, the value of SOE is one, and if the final control is a non-state-owned holding, such as a private, foreign, collective, corporate or employee stock holding company, the value of SOE is zero. The OVR (HOV) variable in the model is the value of the current period of the IPO and the other variables are the corresponding values of the IPO and those after three years. To analyse the impact of management’s power and test H2, we add the cross term of the excessive financing and managerial power variables to obtain the following model: 84 G. ZHAO ET AL. Overpay∕Overperk = + OVR(HOV)∗ Power + OVR(HOV)+ Power + Controls + 0 1 2 3 (4) We use two methods to measure management authority. One is based on the managerial power integration variables, calculating the sum of Power1, Power2 and Power3. The other is to set the dummy variable Power_D equal to one if Power1 + Power2 + Power3 ≥ 2 and zero otherwise (Grinstein & Hribar, 2004; Lu, Wei & Li, 2008; Quan et al., 2010). The other variables are defined as above. 3.4. Descriptive statistics and correlation statistics Table 2 presents the descriptive statistics of the main variables grouped according to the severity of excessive financing. For the low excessive financing group, HOV = 0 and HOV = 1 for the high excessive group. The latter group has a markedly significant level of contrast between the average and the median. The table shows that Overpay, for the top three exec- utives in terms of private income, is 0.931, with a median of 1.052 and a uniform distribution. In the low excessive financing group, the average private income is 0.792, while that for the high excessive financing group is 1.069. There are significant differences between the two subsamples, as well as significant differences in their medians, which indicates that execu- tives in companies with excessive financing receive more private benefits. The mean of Overperk, for the top three executives in terms of non-monetary private income, is 0.017, with a median of 0.012. Average non-monetary private income in the low excessive n fi ancing group is 0.013 and that in the high excessive financing group is much higher, at 0.021. There are also significant differences in the medians of the two groups, which suggests that exec - utives in companies with more excessive financing obtain greater non-monetary private benefits. The values of the two variables of managerial power (Power_N, Power_D) in the high excessive financing group are larger than in the low group. The mean of the enterprise scale is 21.186, with a median is 20.951. The mean financial leverage (Leverage) of the total sample is 0.32 and the mean in the high excessive financing group is 0.409, significantly higher than in the low group. The mean of return on net assets (ROE) of the total sample is 0.099 and that of the low group is 0.102 higher than that of the high group, which has a mean of 0.097. The average annual rate of return (RET) of the total sample is 0.058, with a median of –0.253, indicating that the majority of the stock returns of listed companies are negative. In the subsamples, the average annual rate of return in the low group is 0.35 and that in the high group is –0.232, significantly different. The mean of the enterprise growth rate (MB) of the total sample is 4.784 and the enterprise growth rate in the low excessive financing group is significantly higher than in the high group. The value of reputation (Top 10) in the high excessive financing group is significantly higher than in the low group, which shows that the greater the reputation of the brokerage firm, the greater the ability to raise more funds. The average value of the ratio of independent directors (Indep_R) is 0.369 and there is not much difference between the two groups. The probability of executives not receiving compensation in a company in the low excessive financing group is much greater than for a company in the high group. Equity incentives (options) and the mean of manage- ment shareholding in the high excessive financing group are larger than for the low group, which indicates that equity incentives and management shareholding can positively affect the amount of funds raised by enterprises. State-owned enterprises (SOE) account for 29.2% CHINA JOURNAL OF ACCOUNTING STUDIES 85 Table 2. d escriptive statistics. All Sample HOV = 0 Sample HOV = 1 Sample Variable N Mean SD Min Median Max N Mean Median N Mean Median Overpay 2059 0.931 1.069 –2.545 1.052 3.202 1027 0.792 0.973 1032 1.069*** 1.134*** Overperk 2059 0.017 0.034 –0.054 0.012 0.148 1027 0.013 0.008 1032 0.021*** 0.014*** OVR 2059 0.890 1.082 –0.409 0.401 4.557 1027 0.067 0.081 1032 1.710*** 1.520*** Power_N 2059 1.138 0.759 0.000 1.000 3.000 1027 1.311 1.000 1032 0.966*** 1.000*** Power_D 2059 0.313 0.464 0.000 0.000 1.000 1027 0.389 0.000 1032 0.237*** 0.000*** Size 2059 21.186 1.160 19.310 20.951 25.798 1027 21.204 20.895 1032 21.167 20.986* Leverage 2059 0.320 0.194 0.022 0.299 0.806 1027 0.409 0.415 1032 0.232*** 0.192*** ROE 2059 0.099 0.064 –0.078 0.087 0.361 1027 0.102 0.100 1032 0.097* 0.080*** RET 2059 0.058 0.724 –0.665 –0.253 1.845 1027 0.350 0.207 1032 –0.232*** –0.359*** MB 2059 4.784 2.346 1.489 4.308 13.404 1027 5.234 4.777 1032 4.336*** 4.038*** Top10 2059 0.380 0.486 0.000 0.000 1.000 1027 0.35 0.00 1032 0.411*** 0.000*** Indep_R 2059 0.369 0.052 0.333 0.333 0.571 1027 0.368 0.333 1032 0.369 0.333 Zerosalary 2059 0.090 0.287 0.000 0.000 1.000 1027 0.103 0.00 1032 0.078** 0.000** Option 2059 0.027 0.163 0.000 0.000 1.000 1027 0.018 0.00 1032 0.037*** 0.000*** Manage share 2059 21.720 35.433 0.000 6.817 337.300 1027 15.904 1.24 1032 27.508*** 14.413*** SOE 2059 0.292 0.455 0.000 0.000 1.000 1027 0.389 0.00 1032 0.195*** 0.000*** notes: f or definitions of the variables, please refer to appendix. ***, **, * indicates significance levels of 1%, 5% and 10% respectively. 86 G. ZHAO ET AL. of the total sample and the ratio of state-owned enterprises is higher in the low excessive financing group. Table 3 presents the correlation statistics of the main variables. The table shows that the measures for the first three senior executives in terms of private income (Overpay) and non-monetary private income (Overperk) are significantly positively correlated with the rate of excessive financing (OVR) and HOV, which is consistent with H1. The measures for the first three senior executives in terms of private income (Overpay) and non-monetary private income (Overperk) are significantly positively correlated with managerial power (Power_N), showing that the greater the managerial power, the higher the private income of the com- pany executives, consistent with H2. In addition, Overpay and Overperk are significantly negatively correlated with firm size (Size), the company’s asset liability ratio (Leverage), bro - kerage reputation (TOP 10), the proportion of independent directors (Indep_R), and the nature of the enterprise (SOE) and significantly positively correlated with equity incentive (Option) and management shareholdings (manage share). 3.5. Regression test results 3.5.1. Private benefits of top executives and excessive financing Columns (1) to (3) of Table 4 report the results of the multiple regression of executives’ monetary private benefits and the rate of excessive financing. The first column is for the regression of the total sample and shows that the rate of excessive financing (OVR) is 0.059, with a notable plus under 5%, which suggests that the ratio of excessive financing increases one percentage point, and the monetary private benefits of executives rise 0.059%. Further regression finds that excessive financing has a significant positive impact on the monetary private benefits of the top managers who work in state-owned and non-state-owned firms, but the degree of impact is high in the former. The second column shows the results of the regression of the subsample of state-owned firms, where the rate of excessive financing is 0.135, with a notable plus under 5%; however, in the third column of the regression of the subsample of private firms, the rate of excessive financing is 0.038, much smaller than the rate in the regression of state-owned firms. The positive correlation is only significant at the 10% level. Perhaps this is because some executives of private firms are family members, who obtain high monetary compensation and increase the cost of the family business because of their higher personal income tax (Li & Wu, 2015); therefore, this reduces the impact of excessive financing on private benefits. These findings support H1, that is, the higher the excessive financing, the greater the private benefits of executives. Among the control variables, company size (Size) has a notably positive correlation with top executives’ monetary private benefits, indicating that the larger the company, the fewer the monetary private benefits of executives. The coefficient of the asset liability ratio (lever - age) is significantly negative, indicating that the greater the liabilities of executives, the fewer their monetary private benefits, mainly because executives cannot obtain high monetary private benefits under the constraint of free cash. The stock’s annual return is significantly negative and the ratio of the market value of the firm to its book value (MB) in state-owned firms is significantly positive. Brokerage reputation (Top 10) is significantly positive, which shows that brokers with a high reputation can help companies obtain more financing. The presence of a negative correlation between executives who do not receive remuneration in the company (ZeoSalary) and monetary private benefits plays a significant role in the CHINA JOURNAL OF ACCOUNTING STUDIES 87 Table 3. Correlation of variables. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 1. Overpay 1.000 2. Overperk 0.430*** 1.000 3. OVR 0.170*** 0.120*** 1.000 4. Power_N 0.190*** 0.080*** –0.140*** 1.000 5. Size –0.660*** –0.340*** –0.050** –0.250*** 1.000 6. Leverage –0.380*** –0.210*** –0.490*** –0.010 0.400*** 1.000 7. ROE –0.200*** 0.180*** –0.080*** 0.050** 0.090*** 0.180*** 1.000 8. RET –0.100*** 0.001 –0.370*** 0.150*** –0.020 0.210*** 0.160*** 1.000 9. MB 0.020 0.180*** –0.190*** 0.120*** –0.090*** 0.200*** 0.300*** 0.290*** 1.000 10. Top10 –0.070*** –0.030 0.100*** –0.080*** 0.200*** 0.003 0.070*** 0.009 –0.070*** 1.000 11. Indep_R –0.110*** –0.020 –0.004 –0.060*** 0.190*** 0.100*** 0.000 0.027 0.009 0.050** 1.000 12. Zerosalary –0.020 –0.004 –0.050** –0.013 0.001 0.021 –0.050** 0.024 –0.022 –0.024 –0.010 1.000 13. Option 0.060*** 0.090*** 0.070*** 0.009 0.021 –0.008 0.050** –0.050** –0.007 0.004 0.026 –0.032 1.000 14. Manage 0.080*** 0.100*** 0.180*** 0.240*** –0.010 –0.130*** 0.050** –0.060** 0.019 0.050** 0.050** –0.050** 0.070*** 1.000 share 15. SOE –0.260*** –0.140*** –0.230*** –0.220*** 0.370*** 0.250*** 0.110*** 0.070*** –0.021 0.050** 0.011 0.040** –0.070*** –0.290*** 1.000 notes: f or definitions of the variables, please refer to appendix. ***, **, * indicates significance levels of 1%, 5% and 10% respectively. 88 G. ZHAO ET AL. Table 4. t he results of the multiple regression of executives’ monetary private benefits and the rate of excessive financing. Monetary private benefits Non-monetary private benefits (1) (2) (3) (4) (5) (6) Variables All sample SOE Non-SOE All sample SOE Non-SOE OVR 0.059** 0.135** 0.038* 0.003*** 0.007*** 0.002*** (2.00) (2.05) (1.96) (2.91) (3.90) (3.25) Size –0.600*** –0.603*** –0.558*** –0.009*** –0.009*** –0.013*** (–14.73) (–11.81) (–13.73) (–4.26) (–4.06) (–4.72) Leverage –0.368* –0.366 –0.287*** –0.019*** –0.008 –0.021*** (–1.71) (–0.65) (–3.61) (–3.12) (–1.04) (–13.30) ROE –2.300*** –2.289*** –2.518*** 0.101*** 0.085*** 0.117*** (–7.02) (–4.07) (–5.08) (6.57) (6.89) (6.66) RET –0.111** –0.145*** –0.071** 0.000 –0.002 0.002 (–2.42) (–2.89) (–2.31) (–0.19) (–0.91) (1.08) MB 0.011 0.045*** –0.004 0.002*** 0.002*** 0.002*** (1.34) (2.89) (–0.71) (5.07) (4.31) (3.39) Top10 0.102*** 0.142* 0.102*** 0.001 0.004 0.000 (2.80) (1.96) (4.59) (0.53) (1.14) (–0.05) Indep_R 0.267 –0.652 1.054*** 0.028* 0.089*** –0.026** (1.04) (–1.55) (4.38) (1.96) (4.36) (–2.03) ZeoSalary –0.077 –0.162** –0.031 0.002 0.005 0.000 (–1.33) (–2.28) (–1.67) (0.62) (0.69) (0.51) Option 0.441*** 0.604*** 0.402*** 0.015*** 0.002 0.016*** (6.53) (3.40) (7.00) (4.79) (0.23) (4.53) Manage share 0.002** 0.006** 0.001* 0.000*** 0.000 0.000*** (2.62) (2.56) (1.78) (3.46) (0.90) (5.25) SOE 0.152*** 0.001 (3.28) (0.44) Constant 13.584*** 13.970*** 12.529*** 0.183*** 0.156*** 0.290*** (15.99) (16.16) (13.39) (4.04) (3.46) (4.51) Year Dummy Yes Yes Yes Yes Yes Yes Industry Dummy Yes Yes Yes Yes Yes Yes Obs# 2059 601 1458 2,059 601 1458 a dj-R 0.504 0.656 0.285 0.207 0.264 0.185 notes: f or definitions of the variables, please refer to appendix. ***, **, * indicates significance levels of 1%, 5% and 10% respectively subsample of the state-owned firms. The presence of equity incentives (option) and mana- gerial ownership (manage share) and the monetary private benefits of executives have a significantly positive correlation, showing that equity incentives and managerial ownership can lead to executives obtaining higher private benefits. Columns (4) to (6) in Table 4 report the results of the multiple regression of the non-mon- etary private benefits of executives and the ratio of excessive financing. The fourth column shows the regression results for the total sample, where the rate of excessive financing (OVR) is 0.003, significant at the 1% level, which indicates that the higher the ratio of excessive financing, the higher the non-monetary private benefits of executives. Further regression in the subsamples of state-owned firms (fifth column) and non-state-owned firms (sixth column) finds that the rates of excessive financing (OVR) are significantly positive, which indicates that, whether in state-owned or private firms, the higher the ratio of excessive financing, the greater the non-monetary private benefits of the top executives. The coeffi- cient of the ratio of excessive financing in the subsample of state-owned firms is 0.007 and that for private firms is 0.002, with an obvious difference, where the impact of excessive financing on the non-monetary private benefits of executives is more prominent in CHINA JOURNAL OF ACCOUNTING STUDIES 89 state-owned firms. These findings further support H1, that is, the more excessive the financ - ing, the greater the non-monetary private benefits of the top executives. 3.5.2. Role of managerial power in the excessive financing and private benefits of top executives For further analysis of the impact of managerial power on excessive financing and the private benefits of top executives, the managerial power index (Power_N), and the product of man- agerial power and the excessive financing ratio (OVR) are added to the basic model (3) to form model (4). We then rerun the regression, obtaining the results in Table 5. Columns (1) to (3) report the regression results of executives’ monetary private benefits. The first column shows the regression results for the total sample and the second and third columns show the regression results for the subsamples of state-owned and private firms. The result shows that the coefficients of OVR*Power_N for the regression of state-owned and non-state-owned firms are 0.005 and 0.015, respectively, which is positively correlated with monetary private benefits, but not significantly. The coefficient of OVR*Power_N for the subsamples of private Table 5. role of managerial power in the excessive financing and private benefits of top executives. Monetary private benefits Non-monetary private benefits (1) (2) (3) (4) (5) (6) Variables All sample SOE Non-SOE All sample SOE Non-SOE OVR*Power_N 0.005 0.015 0.057*** 0.003*** –0.001 0.004*** (0.35) (0.19) (5.78) (2.85) (–0.17) (3.42) OVR 0.060 0.050 –0.026 –0.001 0.007*** –0.002 (1.23) (0.44) (–0.82) (–0.39) (2.71) (–1.26) Power_N 0.081* 0.109 0.020 –0.003** –0.002* –0.005* (1.97) (1.45) (0.71) (–2.12) (–1.86) (–1.89) Size –0.590*** –0.544*** –0.542*** –0.010*** –0.010*** –0.013*** (–15.37) (–6.11) (–14.78) (–4.76) (–4.08) (–5.79) Leverage –0.373* –0.578 –0.295*** –0.019*** –0.008 –0.021*** (–1.75) (–1.15) (–3.36) (–2.94) (–1.07) (–8.04) ROE –2.312*** –0.596 –2.532*** 0.100*** 0.086*** 0.115*** (–7.02) (–0.74) (–5.27) (6.94) (7.36) (7.01) RET –0.121** –0.129** –0.074** 0.000 –0.002 0.003 (–2.51) (–2.46) (–2.30) (0.08) (–0.88) (1.44) MB 0.009 0.029* –0.005 0.002*** 0.002*** 0.002*** (1.04) (1.69) (–0.76) (5.53) (6.02) (3.45) Top10 0.105*** 0.128 0.103*** 0.001 0.004 0.000 (2.91) (1.34) (4.87) (0.45) (1.12) (–0.13) Indep_R 0.316 –0.920* 1.108*** 0.027* 0.087*** –0.027* (1.19) (–1.68) (5.20) (1.87) (4.18) (–1.98) ZeoSalary –0.075 –0.068 –0.036 0.001 0.005 0.000 (–1.38) (–0.62) (–0.77) (0.42) (0.65) (–0.39) Option 0.441*** 0.903*** 0.399*** 0.015*** 0.002 0.016*** (6.20) (6.35) (6.54) (4.83) (0.21) (4.49) Manage share 0.002* 0.006* 0.001 0.000*** 0.000 0.000*** (1.87) (1.80) (1.04) (4.52) (1.18) (8.98) SOE 0.171*** 0.001 (4.75) (0.21) Constant 13.275*** 12.029*** 12.183*** 0.193*** 0.163*** 0.298*** (17.71) (6.36) (14.879) (4.86) (3.48) (5.91) Year Dummy Yes Yes Yes Yes Yes Yes Industry Dummy Yes Yes Yes Yes Yes Yes Obs# 2059 601 1458 2059 601 1458 adj -R 0.507 0.619 0.291 0.211 0.263 0.194 notes: f or definitions of the variables, please refer to appendix. ***, **, * indicates significance levels of 1%, 5% and 10% respectively. 90 G. ZHAO ET AL. firms is 0.057, significantly positively correlated with monetary private benefits at the 1% level, which indicates that the higher the ratio of excessive financing in private firms, the greater the managerial power and the greater the monetary private benefits of the top executives. The above results partly support H2, that is, the greater the managerial power, the greater the monetary private benefits of the top executives in firms engaged in excessive financing, a phenomenon mainly reflected in private firms. Columns (4) to (6) in Table 5 report the results of the regression of executives’ monetary private benefits. The fourth column shows the results of the regression of the total sample and the fifth and sixth columns show the regression results of the subsamples of state-owned and private firms, respectively. The results show that the coefficients of OVR*Power_N for the regression of the total sample and the private firm subsamples are, respectively, 0.003 and 0.004, with a significantly positive correlation with non-monetary private benefits at the 1% level. This result shows that the larger the ratio of excessive financing in private firms, the greater the managerial power and the greater the monetary private benefits of the top executives. However, OVR*Power_N in the subsamples of state-owned firms is not signifi- cantly related to non-monetary private benefits. Why did the private benefits of the top executives in state-owned firms not increase with the increase in managerial power? The reasons could be as follows. (1) Compared with non-state-owned firms, the development history of China’s state- owned firms is long and state-owned shareholders possess higher and more stable stakes, which makes the management model of these firms relatively stable, with an established behavioural model for management, where actual power makes little difference. However, private firms have different management models between different firms and some private firms are directly controlled by controllers with great actual power while management’s actual power in some firms is very weak due to equity restrictions. Therefore, managerial power and behaviour in private firms differ greatly. (2) The motivations of the top executives of state-owned firms are more diversified than those of the top executives of private firms. In addition to economic interests, political pro - motion is an important goal. Executives with higher authority in state-owned firms could be more likely to pursue political promotions. However, if so, these executives need to be more honest. The pursuit of political promotion therefore restrains executives’ pursuit of economic interests, that is, political and economic pursuits replace each other, which reduces the importance of obtaining economic benefits from managerial power. Due to the above two factors, the managerial power of private firms and the private benet fi s of top executives in the case of excessive financing is greater than in state-owned firms. Overall, the results support H2, that is, the greater the managerial power, the greater the non-monetary private benefits of the top executives in firms experiencing excessive financing, a phenomenon mainly reflected in private firms. 3.5.3. Further research Excessive financing is a good thing for a company’s IPO, because the company raises more money, which indicates that its financing ability is stronger, investors have higher expecta- tions for the company’s future development, and the market has a positive response to the company’s value. However, if a company’s management does not effectively use the funds raised and, instead, increases management pay and consumption, increasing agency costs, can the market identify management’s intention and have a negative response? With the CHINA JOURNAL OF ACCOUNTING STUDIES 91 help of IPOs, we test whether the market will have a negative reaction to companies expe- riencing excessive financing when they pay high private benefits to their top executives. We construct the following model: BHAR = + OVR ∗ Overpay_#year + OVR + Overpay_#year + Controls + (5) 0 1 2 3 where BHAR is excess returns obtained by the company in the first and second years after the IPO (buy-and-hold abnormal returns in the first/two years after the IPO); Overpay_#year is the top executives’ monetary private benefits in a company in #years; Overperk_#year is executives’ non-monetary private benefits in a company in #years; OVR*Overpay_#year is the product of executives’ monetary private benefits and the rate of excessive financing (OVR) in a company in #years; we control for the financial status of the listed company that year, and Size_IPO is the assets scale for listed companies that year; Leverage_IPO is the asset-to-liability ratio for listed companies that year; ROE_IPO is the return on equity for listed companies that year; and MB_IPO is the book-to-market ratio for listed companies that year. In addition, we also control for the company’s broker’s reputation (TOP 10), independent director ratio (Indep_R), whether there are executives who do not receive remuneration in the company (ZeoSalary), equity incentives (Option), management shareholdings (Manageshare), and enterprise ownership (SOE) that year. According to model (III), if companies experiencing excessive financing provide high private returns to executives, we expect the market to have a negative reaction, with the coefficient of OVR*Overpay_#year or OVR*Overperk_#year, that is, β , being significantly negative. Table 6 shows the reaction of the market to executives’ private benefits and excessive financing. The first and second columns are the regression results of market returns, execu- tives’ monetary private benefits, and excessive financing and the third and fourth columns are the regression results of market returns, executives’ non-monetary private benefits, and excessive financing. We find that the coefficient of OVR*Overpay_#year is significantly neg- ative, which indicates that the market identifies the behaviour of companies experiencing excessive financing giving their top executives excess monetary payments, and it has a negative reaction, reducing the value of these companies. However, the coefficient of OVR*Overperk_#year is negative but not significant, which indicates that the market does not see through the behaviour of companies with excessive financing giving their top exec - utives excess non-monetary payments. The coefficient of OVR is partly significantly positive, which indicates that the market has a positive response to listed companies experiencing excessive financing. 4. Robustness tests To further enrich the results of our study and enhance the robustness of the conclusions, we added the following tests. 4.1. Endogeneity The results of this paper could be influenced by endogenous factors. For example, the increase in the private benefits of management resulting from excessive financing could be due to other common factors, such as a good company being more sought after by the 92 G. ZHAO ET AL. Table 6. t he reaction of the market to executives’ private benefits and excessive financing. (1) (2) (1) (2) BHAR in the first BHAR in the two BHAR in the first BHAR in the two Variables year after IPO years after IPO Variables year after IPO years after IPO OVR*Overpay_#year –0.027* –0.021** OVR*Overperk_#year –0.212 –0.137 (–1.90) (–2.047) (–1.01) (–0.35) OVR 0.052** 0.080*** OVR 0.018 0.043*** (2.17) (7.67) (0.95) (3.05) Overpay_1year –0.025 Overperk_1year 0.351 (–1.49) (0.48) Overpay_2year –0.065*** Overperk_2year 1.371 (–3.72) (1.47) Size_IPO –0.050*** –0.159*** Size_IPO –0.017* –0.095*** (–4.50) (–7.31) (–2.00) (–4.48) Leverage_IPO 0.030 0.095 Leverage_IPO 0.011 0.131 (0.28) (1.24) (0.08) (1.43) ROE_IPO 1.962*** 2.203*** ROE_IPO 2.073*** 2.053*** (4.93) (8.34) (5.23) (4.15) MB_IPO 0.024 0.021 MB_IPO 0.023 0.019 (1.59) (1.37) (1.37) (1.00) TOP10 0.006 0.064** TOP10 0.000 0.049** (0.51) (2.52) (0.00) (2.02) Indep_R 0.151 0.680** Indep_R 0.107 0.620*** (0.78) (2.23) (0.57) (2.79) ZeoSalary –0.040*** –0.032 ZeoSalary –0.040 –0.039 (–2.88) (–1.19) (–1.53) (–1.16) Option 0.132* 0.194*** Option 0.115 0.175*** (1.69) (6.86) (1.63) (4.79) Manage share 0.000 0.000 Manage share 0.000 0.000 (0.60) (–0.18) (0.45) (–0.18) SOE 0.002 0.027 SOE –0.015 0.003 (0.06) (0.81) (–0.62) (0.12) Constant 0.682*** 2.763*** Constant 0.058 1.433*** (3.06) (5.81) (0.62) (3.36) Year Dummy Yes Yes Year Dummy Yes Yes Industry Dummy Yes Yes Industry Dummy Yes Yes Obs# 682 345 Observations 682 345 2 2 a dj-R 0.112 0.144 Adjusted R 0.092 0.117 notes: f or definitions of the variables, please refer to appendix. ***, **, * indicates significance levels of 1%, 5% and 10% respectively. market, so that its issue price is higher, it raises more funds, and its executives gain more private benefits. To alleviate the influence of endogenous factors on our results, we need to find instrumental variables related to excessive financing but unrelated to the private benefits of executives, and conduct a two-stage regression test. We use the cumulative rate of return on the market for the three months prior to the listing of the company (MRET_3month) as an instrumental variable and the variable is exogenous, reflecting market sentiment before listing. If the cumulative rate of return on the market for the three months prior to the company’s listing is high, market sentiment is said to be relatively high and the company could raise more funds; on the contrary, it could raise less money, with the vari- ables having nothing to do with the private income of the executives. We build the following model using the excessive financing rate (OVR) and the cumulative rate of return on the market for the three months prior to the company’s listing (MRET_3month) to conduct a regression: CHINA JOURNAL OF ACCOUNTING STUDIES 93 Table 7. endogeneity test. (1) (2) (3) Variables OVR Variables Overpay Overperk MRET_3month 0.839*** IV_OVR 0.253*** 0.009*** (4.68) (24.23) (11.08) Size_BIPO –0.004 Size –0.649*** –0.011*** (–0.17) (–17.34) (–6.27) Leverage_BIPO –0.871*** Leverage 0.139 –0.002 (–3.84) (0.69) (–0.55) ROE_BIPO 1.465*** ROE –2.179*** 0.102*** (7.37) (–5.72) (8.93) CR_BIPO 0.166*** RET –0.088** –0.001 (7.52) (–2.23) (–1.39) Growth_BIPO 0.213*** MB 0.006 0.001*** (3.19) (0.54) (4.63) Top10 0.163* Top10 0.072** 0.000 (1.87) (2.20) (–0.29) Indep_R 0.254 Indep_R 0.083 0.016 (0.59) (0.27) (1.48) ZeoSalary –0.068 ZeoSalary –0.033 0.004* (–1.37) (–0.95) (1.85) Option 0.164 Option 0.319*** 0.009** (0.71) (5.11) (2.18) Manage share 0.001 Manage share 0.001** 0.000** (1.38) (2.01) (2.47) SOE –0.338*** SOE 0.275*** 0.007** (–5.77) (4.46) (2.29) Constant 0.790 Constant 14.681*** 0.237*** (1.23) (19.46) (5.77) Year Dummy Yes Year Dummy Yes Yes Industry Dummy Yes Industry Dummy Yes Yes Obs# 2059 Obs# 2059 2059 2 2 a dj-R 0.300 a dj–R 0.532 0.286 notes: f or definitions of the variables, please refer to appendix. ***, **, * indicates significance levels of 1%, 5% and 10% respectively. OVR = + MRET_3month + Controls + (6) 0 1 We use the results of the first stage of the regression to predict the value of the model, which we then insert into model (6) and the second-stage regression test is carried out. Since the influencing factors of excessive financing are mainly pre-IPO company charac - teristics, we control for financial and related variables before the company’s listing: for the three years prior to the company’s listing, Size_BIPO is the average asset size, Leverage_BIPO is the average asset liability ratio, ROE_BIPO is the average return on net assets, CR_BIPO is the average current ratio, and Growth_BIPO is the average sales revenue growth rate. The other variables are defined as above. Column (1) of Table 7 shows the results of the first-stage regression, and MRET_3month , with a coefficient of 0.839, is significantly positively correlated with the excessive financ - ing rate. We use the model predicted values as alternative variables for the excessive financing rate (IV_OVR) in model (I) and the results show that the variable is significantly positively correlated with the monetary and non-monetary private benefits of executives, which indicates that excessive financing indeed increases the private benefits of executives. 94 G. ZHAO ET AL. 4.2. Using the variable of whether the enterprise is highly excessive financing to replace the excessive financing rate We adopt the variable of ‘high excessive financing’ to replace the excessive financing rate and rerun the tests. Columns (1) and (3) of Table 8 report the regression results of the mon- etary private benefits of the executives and high excessive financing. The first column shows the results of the regression of the total sample and the coefficient of high excessive financing (HOV) is 0.144, which is significant at the 1% level. In a further subsample regression, we find that the impact of excessive financing on the monetary private benefits of executives exists mainly in state-owned enterprises. The second column shows the results of the regression of the subsamples of state-owned enterprises, and the coefficient of high excessive financing (HOV) is 0.207, which is significant at the 1% level. The third column is for the regression of the subsamples of privately operated enterprises and the coefficient of high excessive financ - ing (HOV) is 0.077, which is much smaller than among state-owned enterprises and not statistically significant. Columns (4) to (6) in Table 8 report the regression results of the non-monetary private benefits of executives and high excessive financing. The fourth column shows the results of the regression for the total sample and the coefficient of high excessive financing (HOV) is 0.007, which is significant at the 1% level. The results show that the more excessive the financing, the higher the non-monetary private income of the executives. In further sub - sample regressions, we find that in the state-owned enterprises subsample, in column (5), and the non-state-owned enterprises sample, in column (6), the coefficients of high excessive financing (HOV) are significantly positive. This finding shows that, whether state-owned or private enterprises, the more excessive the financing, the higher the non-monetary private income of the executives. The coefficients of high excessive financing (HOV) in the state- owned enterprises sample is 0.018 but the coefficient for private enterprises is 0.004, signif- icantly different, indicating that this situation is more prominent among state-owned enterprises. The results of Table 8 are consistent with the previous findings. Columns (1) to (3) in Table 9 show the product of managerial power index (Power_N) and high excessive financing (HOV) and the results of analysing the impact of excessive financing on the monetary private benefits of executives. We can see that the coefficient of the regression product HOV*Power_N of privately operated enterprises is 0.145 and is Table 8. t he regression results of the non-monetary private benefits of executives and high excessive financing. Monetary private benefits Non-monetary private benefits (1) (2) (3) (4) (5) (6) Variables All sample SOE Non-SOE All sample SOE Non-SOE HOV 0.144*** 0.207*** 0.077 0.006*** 0.018*** 0.004* (3.36) (2.75) (1.53) (3.48) (5.70) (1.72) Control Variables Yes Yes Yes Yes Yes Yes Constant 13.612*** 13.842*** 12.531*** 0.189*** 0.167*** 0.292*** (41.13) (32.89) (18.71) (12.59) (9.39) (9.96) Year Dummy Yes Yes Yes Yes Yes Yes Industry Dummy Yes Yes Yes Yes Yes Yes Obs# 2059 601 1458 2059 601 1458 a dj-R 0.505 0.668 0.285 0.208 0.289 0.183 notes: f or definitions of the variables, please refer to appendix. ***, **, * indicates significance levels of 1%, 5% and 10% respectively. CHINA JOURNAL OF ACCOUNTING STUDIES 95 Table 9. analysis of private benefits, excessive financing and managerial power. Monetary private benefits Non-monetary private benefits (1) (2) (3) (4) (5) (6) Variables All sample SOE Non-SOE All sample SOE Non-SOE HOV*Power_N 0.020 –0.159 0.145*** 0.003* 0.005 0.006*** (0.46) (–1.36) (2.86) (1.65) (0.94) (2.79) Control Variables Yes Yes Yes Yes Yes Yes Constant 13.280*** 13.373*** 12.787*** 0.190*** 0.170*** 0.300*** (37.8) (28.47) (18.26) (12.35) (9.15) (10.24) Year Dummy Yes Yes Yes Yes Yes Yes Industry Dummy Yes Yes Yes Yes Yes Yes Obs# 2059 601 1458 2059 601 1458 a dj-R 0.508 0.674 0.293 0.211 0.289 0.187 notes: f or definitions of the variables, please refer to appendix. ***, **, * indicates significance levels of 1%, 5% and 10% respectively. significantly positively correlated with non-monetary private benefits at the 1% level. This finding shows that the more excessive the financing of privately operated enterprises, the greater the managerial power and the higher the monetary private income of the executives. Columns (4) to (6) of Table 9 show the managerial power index number (Power_N), high excessive financing (HOV), and their product, respectively, and the results of analysing the impact of excessive financing on the monetary private benefits of executives. The coefficients of the product HOV*Power_N for the total sample and the subsample of privately operated enterprises are 0.003 and 0.006, respectively, significantly positively correlated with non-mon - etary private benefits at the 1% level. This result shows that the more excessive the financing of privately operated enterprises, the greater the managerial power and the higher the non-monetary private income of the executives. The results of Table 9 are consistent with the previous findings. 4.3. Whether the founder of a privately operated enterprise is also an executive The executives of listed companies are either the founder or a founder team member and there is a difference in salary expectations between those who are not founders but just executives; however, this case is limited to privately operated enterprises. To distinguish the impact of this factor on the private benefits of executives, we distinguish between whether the founder serves as an executive, and the results are shown in Table 10. We can see that when the founder serves as an executive, excessive financing has a significant positive impact on non-monetary private benefits but no significant effect on monetary private benefits, indicating that founding executives are more likely to increase their own private wealth in the form of non-monetary benefits. However, in the subsample in which founders do not serve as executives, excessive financing has a significant positive impact on their monetary and non-monetary private benefits. 4.4. Other robustness tests In addition to using different excessive financing indexes to conduct robustness tests, we adopt a die ff rent managerial power index, such as the dummy variables of managerial power (Power_D), two concurrent duties (Power1), dispersed ownership (Power2), executives with 96 G. ZHAO ET AL. Table 10. Whether the founder of a privately operated enterprise is an executive. The founder serves as executive The founder does not serve as executive (1) (2) (3) (4) Monetary private Non-monetary Monetary private Non-monetary Variables benefits private benefits benefits private benefits OVR 0.022 0.002*** 0.064** 0.003* (0.99) (2.79) (2.12) (1.79) Control Variables Yes Yes Yes Yes Constant 12.002*** 0.275*** 12.269*** 0.263*** (13.84) (5.21) (14.02) (2.84) Year Dummy Yes Yes Yes Yes Industry Dummy Yes Yes Yes Yes Obs# 853 853 605 605 a dj-R 0.297 0.195 0.276 0.178 note: f or definitions of the variables, please refer to appendix. ***, **, * indicates significance levels of 1%, 5% and 10% respectively. a long tenure (Power3), and three single variables, respectively, to replace the managerial power index number (Power_N). The results are consistent with the main results; therefore, due to space limitations, the results are not tabulated here. 5. Conclusions Excessive financing has become common in China’s IPO market and leads to holding exces- sive free cash, which will result in the opportunistic behaviour of management and will increase the agency costs of management. This paper has analysed the situation of the excessive financing of companies listed from 2006 to 2011, researching the relation between excess funds and the private benefits of executives within three years after the listing, and has found that the executives of listed companies with excessive financing obtain higher monetary and non-monetary private benefits. Further analysis of the company’s internal governance shows that the greater the managerial power, the higher the monetary and non-monetary private benefits received by executives, with this phenomenon mainly occur - ring in non-state-owned enterprises. In addition, the market can identify the behaviour of companies with excessive financing providing their executives with excess monetary com- pensation payment, which produces a negative reaction and reduces the company’s value. However, there is no significant negative reaction to the distribution of excess non-monetary income. This paper does not distinguish whether the management of privately operated enterprises includes family members or the number of family members involved. Such a clear distinction would help us validate the inferences and provide directions for future development. In view of the above situation, how can we prevent and control for the agency costs of management due to excessive financing? First, the regulatory authorities should regulate the use of excess funds. At present, only No. 1 GEM specifies the use of excess funds, mainly for the GEM, with a lack of related specifications for excessive financing for the main board and small and medium enterprise boards. Therefore, regulators need to develop specifica- tions suitable for the excessive financing of the main board and small and medium enterprise boards. Second, we need to supervise the opportunism of executives and limit their power. According to Feltham and Ohlson (1995), if IPO companies introduce strict inspections and CHINA JOURNAL OF ACCOUNTING STUDIES 97 reward and punishment mechanisms, restrict executive powers, especially in privately oper- ated enterprises, and strengthen the construction of an external system environment, behav- iour that leads to excessive private benefits for the executives of companies with excessive financing would be effectively curbed. Acknowledgements This research is supported by grants from National Social Science Fund of China (No. 16BJY018), the National Natural Science Foundation of China (No. 71402198), Beijing Social Foundation of China (No. 15JGC176), Beijing Municipal Commission of Education ‘Joint Construction Project’, Beijing Municipal Commission of Education ‘Pilot Reform of Accounting Discipline Clustering’, ‘121 Talent Project for PHD Youth Development 2014’ of Central University of Finance and Economics, and Program for Innovation Research of the Central University of Finance and Economics. Disclosure statement No potential conflict of interest was reported by the authors. References Bebchuk, L.A., Fried, J.M., & Walker, D.I. (2002). Managerial power and rent extraction in the design of executive compensation. University of Chicago Law Review, 69, 751–846. Bebchuk, L.A., & Fried, J.M. (2005). Pay without performance: Overview of the issues. Journal of Applied Corporate Finance, 17, 8–23. 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Variable definitions Variables Variables definition Overpay t he difference between the natural logarithm of executives’ salaries and the natural logarithm of the expected normal salary Overperk t he difference between executives’ actual perks and expected normal perks OVR t he actual amount of financing minus the amount of planned financing, divided by the amount of planned financing HOV d ummy variable that equals one if the proportion is greater than or equal to the median and zero otherwise Power_N = Power1+Power2+ Power3 Power_D =1 if Power1 + Power2 + Power3 ≥ 2 and 0 otherwise Size t he logarithm of a company’s total assets at the end of the year Leverage t he company’s long-term asset liability ratio ROE t he company’s return on net assets RET t he stock returns MB t he book-to-market ratio for listed companies Top10 =1 if the underwrites rank in the top 10, and 0 otherwise Indep_R t he proportion of independent directors Zerosalary =1 if the executives do not receive remuneration, and 0 otherwise Option =1 if the company has an equity incentive, and 0 otherwise Manage share t he number of shares held by management, the unit of this measure is millions of shares SOE =1 if the firm is state-owned enterprise, and 0 otherwise BHAR Buy-and-hold abnormal returns in the first/two years after the iPo Overpay_#year t he top executives’ monetary private benefits in a company in number of years Overperk_#year t he top executives’ non-monetary private benefits in a company in number of years Size_IPO t he logarithm of a company’s total assets at the end of the iPo year Leverage_IPO t he asset-to-liability ratio for listed companies at the end of the iPo year ROE_IPO t he return on equity for listed companies at the end of the iPo year MB_IPO t he book-to-market ratio for listed companies at the end of the iPo year MRET_3month t he cumulative rate of return on the market for the three months prior to the listing of the company Size_BIPO t he average logarithm of a company’s total assets before iPo Leverage_BIPO t he average asset liability ratio before iPo ROE_BIPO t he average return on net assets before iPo CR_BIPO t he average current ratio before iPo Growth_BIPO t he average sales revenue growth rate before iPo
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