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Keywords:

  • Government ownership;
  • Investment bank;
  • Underwriting performance;
  • Earnings quality;
  • Long-term performance
  • G21;
  • G24;
  • G28

Abstract

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Institutional Background and Hypotheses
  5. 3. Data and Sample
  6. 4. Main Empirical Results
  7. 5. Additional Analyses
  8. 6. Conclusion
  9. References

This paper examines the effect of government ownership on investment banks’ underwriting performance in China. A large number of Chinese investment banks are owned and controlled by their respective regional governments. While regional governments may capitalize on their superior local knowledge and administrative power to help affiliated investment banks identify and land high quality local issuers, they may also leverage affiliated underwriters to facilitate the capital market access of those underperformed but socially and/or politically desirable local firms. Empirical evidence favors the latter hypothesis. Specifically, using a sample of regional IPOs, we find that issuers underwritten by their respective regional government-affiliated investment banks exhibit lower earnings quality and poorer long-term performance compared with those underwritten by unaffiliated investment banks. However, this difference is attenuated after the abolition of the IPO quota system. Examination of underwriting fees and issuers’ shareholder identity provides additional evidence supporting the latter hypothesis.


1. Introduction

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Institutional Background and Hypotheses
  5. 3. Data and Sample
  6. 4. Main Empirical Results
  7. 5. Additional Analyses
  8. 6. Conclusion
  9. References

While the relationship between government ownership and performance has been extensively studied for publicly traded companies and commercial banks (e.g. Chong et al., 1996; Cole and Mehran, 1998; Barth et al., 2000; Sapienza, 2004), relatively little attention has been given to government ownership of other financial institutions, such as securities firms, especially in emerging markets. In the present study, we examine the performance implications of government intervention in investment banks’ underwriting practices.1 Moreover, this study also tries to understand the motivations behind government ownership of securities firms in China.

A unique feature of China’s investment banking industry is that nearly all securities firms are government-owned entities and they dominate the domestic underwriting market (Chen et al., 2005).2 Moreover, the vast majority of these banks are regional firms whose ultimate ownership belongs to their respective regional governments.3 As controlling shareholders and regulatory authorities, regional governments have strong managerial and political influence over investment banks under their administrative regime. Regional authorities have the power to approve the appointment of senior management in affiliated investment banks, many of whom are current or former regional government bureaucrats and, hence, are under strong governmental influence (Chen et al., 2005).

This institutional arrangement provides us a unique setting within which to explore the potential conflict of objectives facing regional governments between shareholder wealth maximization and the pursuit of social and/or political gains, which leads to opposite predictions on the underwriting performance of affiliated securities firms.4Wang et al. (2008) note that regional governments in China have in-depth knowledge about the operation of firms under their regulatory regime because of intensive monitoring and supervision. We posit that as ultimate shareholders, regional governments might capitalize on their superior local knowledge and regulatory power to help affiliated investment banks identify and land high-quality regional issuers, thereby enhancing their underwriting performance. Hence, we expect regional issuers underwritten by their respective regional government-affiliated investment banks to exhibit higher quality at the time of IPO and better long-term performance compared with other regional issuers.

Above prediction hinges on the assumption that government participation in equity underwriting is conducive to shareholder value maximization and, hence, has a positive impact on the performance of affiliated investment banks. However, a number of prior studies (e.g. Sapienza, 2004) suggest that government involvement might actually distort the performance of financial institutions. Two theoretical explanations are offered. Lewis (1950) and Gerschenkron (1962), among others, propose a social theory that focuses on government ownership of financial institutions in promoting economic development and improving social welfare. Based on this view, we conjecture that regional governments in China might acquire control of securities firms to facilitate the capital market access of those underperformed but socially important firms under their administrative regime. Saich (2002) points out that the decentralization of government power and reduction in central government fiscal subsidies in China had pressured regional governments to engage in inter-jurisdictional competition for public capital to finance the region’s social welfare spending. One important mechanism for channeling public funds into the region is through the equity offerings of regional firms. Hence, regional governments have strong social incentives to support issuers in their administrative regime, especially underperformed ones, during the listing process. Consistent with this argument, Chen et al. (2008) find evidence that regional authorities in China provide financial subsidies to help regional firms in need of earnings management to surpass the regulatory threshold of rights offerings set by the central government. We posit that regional governments can conceal evidence of collusion and help those firms circumvent stringent underwriter scrutiny by delegating their underwriting tasks to acquiescent securities firms.

Although the social theory implies that government intervention might compromise the objectivity and performance of affiliated securities firms, it nevertheless assumes that governments are benevolent and act in the best interest of the region. By contrast, studies, such as Kornai (1979) and Shleifer and Vishny (1994), emphasize the political rather than the social motivations underlying government ownership of financial institutions. In this more pessimistic “political” view, government officials are self-interested individuals who maximize personal gains. Consistent with this view, Li and Zhou (2005) suggest that regional authorities in China have incentives to assist firms residing in the region during the listing process because more successful IPOs contribute positively to their political capital and increase their chances of promotion through the bureaucratic ranks.

Although social and political theories make very different assumptions about the motivation behind government ownership of investment banks, they both predict the same distortion effect from the perspective of banks’ shareholders. Specifically, regional government-affiliated investment banks likely underwrite lower quality regional issuers because they maximize regional authorities’ social and/or political objectives instead of business profits.

Our empirical results provide strong support for the adverse effect of government ownership on underwriter performance, suggesting that regional governments in China trade off their own shareholder wealth for social and/or political gains. Specifically, using a sample of regional IPO firms, we find that issuers underwritten by their respective regional government-affiliated investment banks exhibit greater earnings management at the time of public offerings than other issuers, as measured by the level of non-operating income, investment income, and abnormal accruals. To control for the potential endogeneity between underwriter choice and earnings management, we also use a simultaneous equation approach and the results remain qualitatively unchanged. Furthermore, we also find that issuers underwritten by affiliated investment banks exhibit poorer post-issue operating performance, as measured by return on assets (ROA) and return on equity (ROE) in the first three post-IPO years, even after controlling for the effect of earnings management and other confounding factors.

To provide further evidence on the social and political motives behind government ownership of securities firms, we perform several additional tests, each of which is designed to assess the validity of one or both theories. We first examine the effect of an institutional change, the abolishment of the IPO quota system, on the performance differential between regional government-affiliated and unaffiliated investment banks. Chen et al. (2008) suggest that the incentives in both regional governments and firms are particularly well aligned through the stringent IPO quota system because the ability to fulfill regional IPO quotas granted by the central government signals regional officials’ capability and directly affects their chances of promotion (Li, 1998). Abolishment of the quota system hence likely diminishes regional officials’ political incentives to help firms residing in the region and, consequently, results in less distortion of the performance of affiliated investment banks. Consistent with this conjecture, we find an attenuated difference in the earnings quality and post-IPO performance between issuers underwritten by their respective regional government-affiliated investment banks and their counterparts after the abolition of the IPO quota system.

In addition to examining the effect of government participation in equity underwriting on the quality and long-term performance of firms underwritten, we also explore whether regional governments’ social and/or political motives manifest in the amount of underwriting fees charged to issuers. Empirical results suggest that regional government-affiliated investment banks charge lower underwriting fees than their counterparts, even after controlling for the effect of information advantage and other confounding factors. This result provides further support for the adverse effect of government ownership on the welfare of affiliated investment banks.

Finally, using a subsample of firms underwritten by their respective regional government-affiliated investment banks, we explore differences in earnings quality between regional government-owned firms (regional state-owned enterprises, SOEs) and non-regional government-owned firms (regional non-SOEs). Prior studies (e.g. Li and Zhou, 2005; Chen et al., 2008) suggest that regional SOEs are more important to regional governments for both social and political reasons. Hence, we expect the collusion pressure exerted on affiliated investment banks to be greater when serving regional SOEs. Consistent with this conjecture, we find evidence that regional SOEs are more aggressive in their accounting manipulation than regional non-SOEs.

Our paper is related to a number of recent studies on the role of government in finance. As La Porta et al. (2002) point out, governments can participate in the financing of firms either through direct subsidies or through ownership of financial institutions. Although Chen et al. (2008) provide evidence on the existence of the former mechanism in China, our study provides supporting evidence for the latter mechanism.

Our paper is also complementary to the literature on investment bank independence. Prior studies suggest that commercial pressure compromises investment bank integrity and leads to biased analyst research (Dugar and Nathan, 1995; Lin and McNichols, 1998; Michaely and Womack, 1999). In this study, we show that government intervention might also compromise investment bank independence, as reflected in the lower quality of firms underwritten and lower fees charged.

This paper is also related to several other strands of literature. First, it provides new evidence for the debate concerning the role of government intervention in financial institutions, especially in emerging markets (Lewis, 1950; Myrdal, 1968; Shleifer and Vishny, 1998; Annisette and Macias, 2002). Second, it extends the literature documenting the inefficiency of government enterprises and the political motives behind public provision of services (e.g. Megginson et al., 1994; Frydman et al., 1999; La Porta et al., 1999). Third, it provides additional evidence on the earnings management and financial packaging of IPO firms in China (Aharony et al., 2000; Chen and Yuan, 2004; Haw et al., 2005). Fourth, it complements the finding of Jo et al. (2007) that firms with greater earnings management tend to use lower quality underwriters to avoid intense monitoring. Results of our study suggest that in China, regional firms that are aggressive in earnings manipulation, especially regional SOEs, might avoid underwriter scrutiny by hiring their regional government-owned investment banks.

The remainder of this paper proceeds as follows. Section 2 discusses the institutional background and develops our hypotheses. Section 3 describes the data and the sample. Section 4 presents the main empirical results. Section 5 provides several additional analyses. Section 6 concludes the paper.

2. Institutional Background and Hypotheses

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Institutional Background and Hypotheses
  5. 3. Data and Sample
  6. 4. Main Empirical Results
  7. 5. Additional Analyses
  8. 6. Conclusion
  9. References

2.1. Government Regulation and Ownership of Securities Firms in China

Since the establishment of the Shanghai Stock Exchange in 1990 and the Shenzhen Stock Exchange in 1991, China’s stock markets have experienced tremendous development and changes. The total number of listed firms on both markets had reached 1604 by the end of 2008, with a combined market capitalization of US$1685bn.5 The rapid increase in the number of public offerings had created substantial demand for investment banking services and forged the development of China’s financial institutions. Despite its intention and effort to promote the market economy, the Chinese Government remains in tight control of its financial services sector. On prudential regulation, the government has established laws similar to the US Glass–Steagall Act that call for the separation between commercial and investment banking businesses (Qian and Wu, 2000).6 Although commercial banks are monitored by the China Banking Regulatory Commission, securities firms are regulated by the China Securities Regulatory Commission (CSRC). Moreover, the Securities Law classifies securities firms into two categories: comprehensive securities companies and brokerage securities companies.7 Only the former are allowed to engage in equity underwriting.8

Although the financial services sector is regulated by the central government, many securities firms, especially regional banks, are owned and controlled by their respective regional governments. Regional governments’ equity shares are typically held by the regional finance bureau and the state asset management companies (Chen et al., 2005). As controlling shareholders and regulatory authorities, regional governments have strong managerial and political power over investment banks under their jurisdictions. In a recently enacted regulation on the risk management of securities firms in response to the global financial crisis, one of the provisions states that “when a securities firm has major risk, it can apply to securities regulatory authority under the State Council for administrative restructuring only if [it receives] support from [the] provincial people’s government”.9 Moreover, in many cases, regional government authorities are in charge of appointing the senior management of affiliated investment banks, many of whom are current or former regional government bureaucrats and, hence, are under strong governmental influence (Chen et al., 2005).

2.2. Regional Government Ownership and Underwriting Performance

We offer two competing explanations underlying regional government ownership of investment banks that yield opposite predictions on the performance of affiliated securities firms. On the one hand, we conjecture that as controlling shareholders, regional governments might pursue shareholder wealth maximization by capitalizing on their superior local knowledge and regulatory power to help affiliated investment banks identify and land high-quality regional issuers. Regional governments in China likely possess deep and reliable information about firms under their jurisdictions and have strong influence over them for several reasons. First, China’s economic reforms from the late 1970s resulted in a progressive decline in direct central government control over regional economy, with powers devolved from central government to regional authorities (Saich, 2002). Consequently, regional governments have become the primary regulator of business entities under their administrative regime and have accumulated in-depth knowledge about them through close monitoring and interaction. Second, regional authorities have control and discretion over resources for distribution to those within their jurisdictions (Saich, 2002). As a result, firms have strong incentives to curry favor with their regional governments in order to receive preferential treatment, such as getting IPO quotas and tax benefits (Chen et al., 2008), thereby vesting regional governments with the power to request information from them. Third, a significant number of regional firms are audited by auditors residing in the same region that have a close relationship with regional authorities (Tang, 1999; Wang et al., 2008). Hence, these auditing firms might serve as third-party information sources for regional officials. Fourth, many regional firms are owned by regional governments. As owners, regional authorities have direct control over these firms and have access to proprietary firm information.

We expect regional governments’ superior local knowledge and regulatory power to be important and beneficial to affiliated investment banks. First, regional authorities might share their superior local information with affiliated securities firms, thereby giving them a competitive advantage in identifying high-quality regional issuers. Second, regional governments might also exercise their regulatory influence to facilitate any additional information acquisition by affiliated investment banks, enhancing their selecting and monitoring capability. Third, in some cases, regional governments might directly intervene in regional issuers’ underwriter choice and pressure high-quality issuers to choose those underwriters preferred by the regional authorities. These arguments lead to our conjecture that regional issuers underwritten by their respective regional government-affiliated investment banks probably exhibit higher earnings quality at the time of public offerings and better post-issue performance compared with others.

The above prediction hinges on the assumption that the incentives between regional governments and affiliated securities firms are well aligned and that regional government involvement is intended to improve the performance of these banks. On the other hand, however, a number of prior studies (e.g. Stiglitz, 1993; Sapienza, 2004) suggest that government-owned banks probably underperform because they maximize broader social objectives rather than business profits. As Saich (2002) points out, abandonment of the central-planned economy and the decentralization of central government power in China have induced intense competition among regional governments and provided them with a range of positive incentives to foster regional economic prosperity. In addition, the relative decline in central government subsidies has left regional governments by and large on their own to finance social welfare projects in their regions. The increased revenue pressure has forced regional governments to seek public capital and incentivized them to facilitate the capital market access of firms residing in their regions. Consistent with this argument, Chen et al. (2008) find that in China, earnings manipulation by regional issuers involves collusion with their regional governments in the form of fiscal transfer. We posit that in addition to providing direct financial help, regional governments can also provide indirect assistance by acquiring control of financial intermediaries. An acquiescent underwriter is more likely to relax the due diligence process and allow those firms to engage in earnings management to meet the CSRC’s earnings targets for IPO (Aharony et al., 2000; Chen and Yuan, 2004).

Although the social view predicts that government ownership distorts the performance of affiliated investment banks, it nevertheless assumes that regional governments are social welfare maximizing agents that trade off their own shareholder wealth for the region’s economic growth. By contrast, a number of studies, such as Shleifer and Vishny (1994), propose a political theory of government intervention in finance. Fundamentally different, the political view is based on the assumption that politicians are self-interested individuals who pursue their own personal objectives and gains (Sapienza, 2004). Shleifer and Vishny (1994) note that the political motives behind ownership of financial institutions are the greatest in countries with underdeveloped financial systems and poorly protected property rights. Consistent with this view, Li and Zhou (2005) argue that regional authorities in China have incentives to assist the equity offerings of regional firms because taking more firms public enhances their political capital and increases their chances of promotion. As such, regional authorities might acquire control of investment banks as a vehicle to help achieve their personal objectives.

Although regional securities firms, in general, care about their reputation capital, they are likely to compromise their gate-keeping roles when serving clients that are important to their regional governments because: (i) as controlling shareholders, regional governments are able to exert strong collusion pressure on investment banks under their control; (ii) given their connection with the central government, regional officials can provide a certain degree of insurance to affiliated investment banks and bail them out if things go wrong; and (iii) just like other firms in the region, regional investment banks also have strong incentives to forge a good relationship with their regional authorities to enhance their chances of securing future underwriting deals with firms residing in the region.

Although the social and political views make very different assumptions about regional government objectives, both theories would lead to the prediction that issuers underwritten by their respective regional government-owned investment banks probably exhibit lower quality and poorer long-term performance compared with those underwritten by unaffiliated investment banks.

2.3. Institutional Change in IPO Regulation and Underwriting Performance

To further our understanding of the motivations behind regional government intervention in financial intermediaries in China, we examine how differences in the underwriting performance between regional government-affiliated and unaffiliated investment banks change with a regulatory reform in the IPO process, the abolishment of the IPO quota system.

Prior to 2001, the Chinese IPO market was under tight government control and the listing process was characterized by a unique quota system. The CSRC, on behalf of the central government, sets annual quotas on the number of IPOs and rations the quotas to each of the 32 regions. The main purpose of devising this mechanism was for the central government to maintain control over the size and stability of the stock markets (Fang, 1995). In its practical application, however, the quota system went far beyond an instrument to control access to public equity capital. It created a “carrot-and-stick” incentive structure for regional authorities, with direct implications with respect to their personal career advancement (Pistor and Xu, 2005). On the one hand, as the size of the IPO quota effectively determines the amount of public capital to be distributed into each region, regional governors are incentivized to engage in inter-jurisdictional competition for this scare resource through intense bargaining with the CSRC. Gaining more quotas for the region and being able to fulfill them are, hence, viewed as regional government officials’ political achievements and a sign of their superior capability. In turn, their chances of promotion increases (Li and Zhou, 2005; Chen et al., 2008). On the other hand, failure to meet the current year’s quota is punished in the form of reducing future quotas, which adversely affects regional authorities’ political capital. Therefore, to maximize quota allocation and to avoid the risk and negative political implications of a failed IPO, regional governments have strong incentives to ensure that firms that they de facto choose as their region’s IPO candidates meet the CSRC’s listing requirements, which heavily emphasize pre-IPO accounting performance (Wang et al., 2008). In addition to directly assisting candidates in earnings manipulation through financial subsidies (Chen et al., 2008), regional governments can provide an additional layer of protection to them by assigning their underwriting tasks to acquiescent investment banks who are more willing to cover up for them.

The IPO quota system was officially abolished in 2001, which effectively removed this “carrot-and-stick” performance metric that affects regional government officials’ chances of promotion (Chen, 2003). Even though the quantity of IPOs remains socially important to regional governments after 2001, its impact on regional officials’ career outlook has diminished. Moreover, as the supply of IPO is no longer constrained, the negative implication of a single failed public offering is attenuated. At the same time, there has also been a gradual improvement in the overall regulatory environment, which makes it more difficult and costly for regional governments to collude with investment banks and issuers residing in their jurisdictions.10 Hence, although regional government officials possess more or less the same amount of local knowledge and social incentives since the abolishment of the IPO quota system, their political incentives and the ability to collude with investment banks have diminished. As a result, we would expect to see a reduced difference in the quality of regional firms underwritten by their respective regional government-affiliated and unaffiliated investment banks in the post-regulation period.

3. Data and Sample

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Institutional Background and Hypotheses
  5. 3. Data and Sample
  6. 4. Main Empirical Results
  7. 5. Additional Analyses
  8. 6. Conclusion
  9. References

3.1. Data

Our sample construction begins with all public companies listed on China’s stock markets (either Shanghai or Shenzhen) between 1992 and 2008. We exclude firms owned by the central government because they are not considered as regional firms and have the most distant relationship with regional authorities (Chen et al., 2008). We also exclude firms that issue shares to foreign investors (B-shares or H-shares) because they exhibit different financial characteristics and face different listing requirements and regulatory environments (Wang et al., 2008). The resulting sample hence consists of regional firms that only issue domestic shares (A-shares).

Our empirical tests call for sample classification based on whether an issuer is underwritten by its regional government-owned investment bank. Following a number of prior studies (e.g. Chen et al., 2008; Wang et al., 2008), we define regional government at the provincial level (or region with provincial status; that is, autonomous administrative region or municipality under the central government). We first classify investment banks into two categories: government-owned investment banks and non-government-owned investment banks, and exclude firms underwritten by the latter group.11 Ideally, we would like to further partition government-owned investment banks into regional and central banks based on the identity of their ultimate government shareholders. However, two challenges prevent us from taking this approach. First, most investment banks in China are privately held entities whose ownership information is not readily available to the public. Second, as the institutional and regulatory environments change over time, many government-owned investment banks had experienced multiple rounds of ownership transfer between central and regional governments (Chen et al., 2005), making it difficult to identify the ultimate government shareholder at a given point in time.

To deal with these two challenges, we use an alternative criterion, securities firm’s business registration location, to measure its regional government affiliation. Specifically, a regional issuer is considered to have been underwritten by its regional government-owned investment bank (hereafter termed “local underwriter” or “local investment bank”) if the issuer and at least one of its lead underwriters are registered in the same region at the time of IPO.12 We argue that this is a reasonable proxy because: (i) nearly all regional government-owned investment banks in China are registered and located in their respective regional government administrative territories; and (ii) even if an investment bank located in a given region is owned by the central government, regional authorities might still have certain influence over them as they are the primary regulators of all business entities registered within their jurisdictions.

We obtain company background, ownership and financial information, as well as IPO-related information including the IPO date, offer size, underwriting fees, underwriter and auditor choices from the WIND financial database. For those observations with missing information in the database, we try to manually fill in the missing data values by searching through the company’s IPO prospectus and financial statements. The final sample consists of 1363 IPOs.

3.2. Descriptive Statistics

Table 1 reports the sample distribution by year, industry, and underwriter choice, respectively. Panel A reports the number of regional IPOs in our sample between 1992 and 2008, as well as their choices between local and non-local underwriters. Among 1363 IPOs in our sample, 413 firms (30.3%) choose a local underwriter. Moreover, the time-series distribution suggests that the percentage of firms choosing a local underwriter has decreased over time. There maybe many possible explanations for the observed time-series trend. One plausible explanation is that changes in regulatory policies and environments had diminished the incentives and benefits associated with hiring a local underwriter, thereby reducing the demand for their services.

Table 1.   Distribution of sample firms by year, underwriter choice, and industry Sample distribution by year, underwriter choice, and industry is presented. We start sample construction from all IPOs in the domestic A-share market between 1992 and 2008. We then exclude firms that also issue B-shares and/or H-shares, as well as those firms controlled by the central government. After further excluding firms with missing data, the final sample consists of 1363 IPO firms. Panel A reports the sample distribution by year and underwriter choice. An issuer is considered to have been underwritten by a local underwriter if the firm and at least one of its lead underwriters are registered in the same province (or region with provincial status) at the time of the IPO. Panel B reports the sample distribution by industry and underwriter choice. The industry classification scheme is provided by the China Securities Regulatory Commission.
 Local underwriters, n (%)Non-local underwriters, n (%)Total, n (%)Percentage choosing local underwriters (%)
Panel A: Distribution of sample by year and underwriter choice
19926 (1.45)3 (0.32)9 (0.66)66.67
199368 (16.46)32 (3.37)100 (7.34)68.00
199460 (14.53)30 (3.16)90 (6.60)66.67
19953 (0.73)17 (1.79)20 (1.47)15.00
199647 (11.38)127 (13.37)174 (12.77)27.01
199746 (11.14)110 (11.58)156 (11.45)29.49
199832 (7.75)58 (6.11)90 (6.60)35.56
199920 (4.84)61 (6.42)81 (5.94)24.69
200030 (7.26)97 (10.21)127 (9.32)23.62
200113 (3.15)57 (6.00)70 (5.14)18.57
200212 (2.91)52 (5.47)64 (4.70)18.75
20038 (1.94)50 (5.26)58 (4.26)13.79
200417 (4.12)70 (7.37)87 (6.38)19.54
20053 (0.73)10 (1.05)13 (0.95)23.08
200612 (2.91)38 (4.00)50 (3.67)24.00
200720 (4.84)83 (8.74)103 (7.56)19.42
200816 (3.87)55 (5.79)71 (5.21)22.54
Total413 (100)950 (100)1363 (100)30.30
Panel B: Distribution of sample by industry and underwriter choice
Agriculture6 (1.45)29 (3.05)35 (2.57)17.14
Resource Extraction4 (0.97)28 (2.95)32 (2.35)12.50
Manufacturing234 (56.66)582 (61.26)816 (59.87)28.68
Electricity, gas and water15 (3.63)34 (3.58)49 (3.60)30.61
Architecture10 (2.42)17 (1.79)27 (1.98)37.04
Transportation16 (3.87)36 (3.79)52 (3.82)30.77
Information technology19 (4.60)66 (6.95)85 (6.24)22.35
Wholesale and retail32 (7.75)52 (5.47)84 (6.16)38.10
Financial and insurance4 (0.97)6 (0.63)10 (0.73)40.00
Real estate25 (6.05)34 (3.58)59 (4.33)42.37
Society service16 (3.87)29 (3.05)45 (3.30)35.56
Broadcasting and culture5 (1.21)5 (0.53)10 (0.73)50.00
All others27 (6.54)32 (3.37)59 (4.33)45.76
Total413 (100)950 (100)1363 (100)30.30

Panel B in Table 1 reports the industry distribution of the sample using the classification scheme provided by the CSRC. Manufacturing firms account for more than half (59.9%) of total IPOs, followed by information technology firms (6.24%), and wholesale and retail firms (6.24%). Moreover, firms in the broadcasting and culture industry are most likely to be underwritten by local investment banks (50%), whereas firms in the resource extraction industry are least likely to be underwritten by local investment banks (12.5%).

4. Main Empirical Results

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Institutional Background and Hypotheses
  5. 3. Data and Sample
  6. 4. Main Empirical Results
  7. 5. Additional Analyses
  8. 6. Conclusion
  9. References

4.1. Earnings Quality, Long-Term Performance, and Underwriter Choice: Univariate Tests

To examine the net effect of regional government ownership on the underwriting performance of affiliated investment banks, we first conduct a univariate comparison of earnings quality and post-IPO long-term performance between issuers underwritten by local investment banks and issuers underwritten by non-local investment banks. We use three measures of earnings quality that have been shown in prior studies (e.g. Chen and Yuan, 2004; Haw et al., 2005) to capture the earnings management behavior of Chinese companies. Specifically, these three variables are: (i) ENOI, referred to as excess non-operating income, defined as after-tax non-operating income (or losses) divided by owners’ equity and adjusted by the industry median; (2) IVSTI, referred to as investment income, defined as gains (losses) from investment divided by owners’ equity and adjusted by the industry median; (iii) DA, discretionary accruals estimated based on the cross-sectional Jones model.13 For all three measures, a larger number indicates greater earnings management and lower earnings quality. We also use two accounting-based variables, ROE and ROA, to measure issuers’ long-term performance in each of the three post-IPO years. ROE is calculated as the operating income divided by the year-end shareholders’ equity. ROA is calculated as the operating income divided by the year-end total assets. To control for the industry effect, we follow Chen and Yuan (2004) and adjust both ROE and ROA by the industry median.14Table 2 summarizes the definitions of all variables used in our empirical analyses.

Table 2.   Definition of variables
VariablesDefinition
Variables on earnings quality
 ENOIExcess non-operating income, defined as after-tax non-operating income (or losses) divided by owners’ equity and adjusted by the industry median
 IVSTIInvestment income, defined as gains (losses) from investment divided by owners’ equity and adjusted by the industry median
 DADiscretionary accruals estimated based on the cross-sectional Jones model
Variables on long-term performance
 ROE_1Return on owners’ equity for the first year after the IPO, computed as operating income in post-IPO year 1 divided by year-end owners’ equity, adjusted by the industry median
 ROE_2Return on owners’ equity for the second year after the IPO, computed as operating income in post-IPO year 2 divided by year-end owners’ equity, adjusted by the industry median
 ROE_3Return on owners’ equity for the third year after the IPO, computed as operating income in post-IPO year 3 divided by year-end owners’ equity, adjusted by the industry median
 ROA_1Return on total assets for the first year after the IPO, computed as operating income in post-IPO year 1 divided by year-end total assets, adjusted by the industry median
 ROA_2Return on total assets for the second year after the IPO, computed as operating income in post-IPO year 2 divided by year-end total assets, adjusted by the industry median
 ROA_3Return on total assets for the third year after the IPO, computed as operating income in post-IPO year 3 divided by year-end total assets, adjusted by the industry median
Variables on underwriters, auditors, and ownership
 Und_LocalDummy variable that equals 1 if the underwriter is a local underwriter, and 0 otherwise
 Uud_FeeUnderwriting fees, computed as the natural logarithm of underwriting fees for IPO
 Uud_TopDummy variable that equals 1 if the underwriter is a Top-10 national investment bank, and 0 otherwise
 Big_AuditorDummy variable that equals 1 if the issuer is audited by a Big-4 international or a Top-10 national auditor, and 0 otherwise
 OCOwnership concentration, measured as percentage of controlling shareholders’ ownership at the time of IPO
 Regional_SOEDummy variable that equals 1 if it is a regional government-owned enterprise, and 0 otherwise
Variables on firm characteristics and other variables
 CRCurrent ratio, computed as current assets divided by current liabilities
 LeverageLeverage, computed as year-end total debts divided by year-end total assets
 AgeComputed as the number of years between the company founding date and the IPO date
 Off_sizeOffer size, measured as total capital raised during the IPO
 SizeComputed as the natural logarithm of total revenues during the IPO year
 LnTAComputed as the natural logarithm of total assets at the end of IPO year
 GrowthPre-IPO sales growth, computed as [(sales in year t − sales in year t − 1)/sales in year t − 1]. To alleviate outlier concerns, Growth is winsorized into the range of [−20%, 20%]
 STDStandard deviation of daily stock returns in the first post-IPO year
 ROA_0Return on assets in the year before IPO, computed as income before extraordinary items divided by total assets at the beginning of the year To alleviate outlier concerns, ROA_0 is winsorized into the range of [−1, 1]
 ΔROAROA change in IPO year, measured as ROA in the IPO year minus ROA_0. To alleviate outlier concerns, ΔROA is winsorized into the range of [−1, 1]
 Post2001Dummy variable that equals 1 if the firm is listed after December 31, 2001, 0 if before January 1, 2001

Panel A in Table 3 presents the results of univariate comparisons. The Wilcoxon rank-sum test is used to test for the difference in median earnings quality and long-term performance between issuers underwritten by local investment banks and issuers underwritten by non-local investment banks. As reported in Panel A, ENOI, IVSTI and DA all suggest that issuers underwritten by local investment banks exhibit greater earnings management and lower earnings quality than their counterparts.15 Moreover, long-term performance comparisons show that firms underwritten by local investment banks underperform other issuers in terms of both ROE and ROA in each of the three post-IPO years. This is consistent with prior research findings (e.g. Teoh et al., 1998a,b) that greater earnings management at the time of public offering is followed by poorer post-issue performance. Taken together, results from univariate comparisons appear to suggest that regional governments in China probably use affiliated investment banks as an instrument to achieve social and/or political objectives at the expense of these banks’ shareholder welfare.

Table 3.   Earnings quality, post-IPO performance, firm characteristics, and underwriter choice Results of univariate comparisons of earnings quality, post-IPO performance and firm characteristics between issuers underwritten by local investment banks and issuers underwritten by non-local investment banks are presented. An issuer is considered to have been underwritten by a local underwriter if the firm and at least one of its lead underwriters are registered in the same province (or region with provincial status) at the time of the IPO. Panel A reports the results of earnings quality and post-issue performance comparisons. Three earnings quality measures are: (i) ENOI, referred to as the excess non-operating income, calculated as after-tax non-operating income (or losses) divided by owners’ equity and adjusted by the industry median; (ii) IVSTI, referred to as the investment income, calculated as gains (losses) from investment divided by owners’ equity and adjusted by the industry median; and (iii) DA, referred to as discretionary accruals estimated based on the cross-sectional Jones model. Two long-term performance measures are return on equity (ROE) and return on assets (ROA), respectively. ROE_t (ROA_t) refers to ROE (ROA) in post-IPO year t, where t = 1, 2, 3. Panel B reports issuer and offer characteristics by underwriter choice. All variables are defined in Table 2. The Wilcoxon rank-sum test is used to test for the difference in the media The Z-stat is reported. Significance levels are defined at ***1, **5, and *10%.
 Local underwritersNon-local underwritersTest for difference
MeanMedianSDNMeanMedianSDN
Panel A: Earnings quality and long-term performance, by underwriter choice
ENOI0.010.000.034130.010.000.029501.79*
IVSTI0.010.000.033920.000.000.028702.68***
DA0.120.100.111830.110.080.106312.13**
ROE_1–0.02–0.010.123730.000.010.11845–3.60***
ROE_2–0.03–0.010.16368–0.030.000.22786–2.71***
ROE_3–0.04–0.020.14358–0.020.000.16763–4.01***
ROA_10.000.000.053730.010.000.05845–2.03**
ROA_2–0.01–0.010.063680.000.000.06786–1.82*
ROA_3–0.02–0.010.06362–0.01–0.010.06767–3.29***
Panel B: Firm and offer characteristics, by underwriter choice
Und_Fee6.837.020.973207.167.220.72860–5.23***
Und_Top0.300.000.464130.591.000.49950–9.96***
Big_Auditor0.501.000.504130.561.000.50950–2.11**
OC0.470.480.194130.460.460.229501.43
Regional_SOE0.821.000.384130.751.000.439502.78***
CR2.861.983.294132.872.073.86950–1.21
Leverage0.380.380.174130.360.360.169501.41
Age2.601.632.764133.573.113.04950–6.09***
Off_size9.929.921.1341310.1710.201.03950–4.47***
Size10.6210.551.1941310.6310.531.209500.34
Growth0.870.203.504130.300.151.709503.89***
STD2.181.582.043691.911.441.938382.88***
ROA_00.390.340.321980.370.300.29447–0.93
ΔROA–0.10–0.040.25195–0.08–0.040.234444.65***

4.2. Earnings Quality, Long-Term Performance, and Underwriter Choice: Multivariate Tests

To corroborate the findings of univariate comparisons and to control for potential confounding factors, we turn to regression analyses. Panel B of Table 3 presents a summary statistics of the control variables that are used in subsequent regression analyses, partitioned by underwriter choice. Compared with firms underwritten by non-local investment banks, firms underwritten by local investment banks are generally younger (as measured by the number of years between founding date and IPO date), riskier in terms of future cash flows (as measured by the standard deviation of first post-IPO year stock returns), composed of more regional government-owned enterprises (regional SOEs), and have higher growth. The fact that regional government-affiliated investment banks tend to underwrite more regional SOEs is consistent with the argument that taking regional SOEs public is of greater importance to regional authorities for both social and political reasons (Li and Zhou, 2005). Moreover, as many listed regional SOEs are typically restructured from a parent company immediately prior to the IPO (Wang et al., 2008), which explains the relative youngness and riskiness of these firms, they are more likely to be in need of earnings management to meet the listing requirements imposed by the CSRC. Regional governments can facilitate such behavior by allocating the underwriting tasks of these firms to acquiescent local underwriters who are more likely to collude with them. The summary statistics in Panel B also show that issuers underwritten by local investment banks are less likely to choose a Big-4 international or a Top-10 national auditor. This is consistent with the argument in Wang et al. (2008) that small regional auditors are more likely to allow their local clients to manipulate earnings due to regional governments’ political power over them. Comparison of underwriting fees suggests that issuers choosing local investment banks incur lower fees. Untabulated results show that the average underwriting fees charged by local underwriters are US$2.18m, compared with US$2.63m charged by non-local underwriters. The average fee differentials between the two groups are US$0.45m.

Table 4 reports the results of regressing each of the three earning quality measures on an underwriter choice indicator variable (Und_Local) and a set of control variables. Und_Local equals one if the issuer is underwritten by a local investment bank, and zero otherwise. Among the control variables, we include ownership concentration (OC) to capture the role of controlling shareholders in earnings manipulation because Chinese firms are typically characterized by their concentrated ownership structure. Following Chen and Yuan (2004), we also include current ratio (CR) and leverage ratio (Leverage) to control for the firm’s need for cash in the short term and in the long run, respectively. It is generally well accepted that young companies are exposed to greater bankruptcy risk due to the liability of newness and smallness. Therefore, they have stronger incentives to produce artificially high earnings numbers. Hence, we include firm age (Age) as an additional control variable. Finally, offer size (Off_size) and firm size (Size) are also included to control for the size effect.

Table 4.   Quality of firms underwritten by local and non-local investment banks OLS regression estimates of earnings quality on the choice of underwriter and firm characteristics are presented. The dependent variable is earnings quality, measured in three ways: ENOI, IVSTI, and DA. ENOI is computed as after-tax non-operating income (or losses) divided by owners’ equity and adjusted by the industry median. IVSTI is computed as gains (losses) from investment divided by owners’ equity and adjusted by the industry median. DA is discretionary accruals estimated based on the cross-sectional Jones model. Columns (1), (2) and (3) refer to regression models using ENOI, IVSTI, and DA as the dependent variable, respectively. Und_Local equals one if the issuer is underwritten by a local investment bank, and zero otherwise. All variables are defined in Table 2. The intercept term is included in each regression model but not reported. t-Statistics (in parentheses) are adjusted for heteroskedasticity. Significance levels are defined at ***1, **5 and *10%.
Independent variablesENOIIVSTIDA
(1)(2)(3)
Und_Local0.003** (1.93)0.004*** (2.74)0.015* (1.65)
OC–0.004 (–1.25)–0.008** (–1.95)0.002 (0.13)
CR0.000 (–1.10)0.000 (–0.80)0.003** (1.96)
Leverage0.024*** (3.61)0.017*** (2.47)0.073** (1.99)
Age0.000 (–1.30)0.000 (–1.41)–0.003** (–2.15)
Off_size0.000 (0.26)0.000 (0.37)–0.002 (–0.22)
Size–0.005*** (–4.30)–0.002** (–2.11)0.000 (–0.06)
Adjusted R20.0580.0330.005
Observations13631262814

Columns (1)–(3) in Table 4 refer to regression equations using ENOI, IVSTI, and DA as the dependent variables, respectively. Similar to univariate tests results, the coefficients on Und_Local in all three regression models are significantly positive, indicating that issuers underwritten by local investment banks tend to exhibit greater earnings management and lower earnings quality than others. Among the control variables, the coefficient on Leverage is significantly positive in all three model specifications, indicating that highly leveraged firms have stronger incentives to manage earnings to avoid debt covenant violations. The coefficient on Size is significantly negative in Models (1) and (2), suggesting that larger firms are less likely to engage in earnings management. In Model (2), the coefficient on OC is also significantly negative, implying that greater ownership concentration is associated with higher earnings quality. Finally, in Model (3), the coefficient on Age is significantly negative, consistent with our conjecture that younger firms have stronger incentives to overstate earnings.

Table 5 reports the regression results of long-term performance on the underwriter choice and control variables. Columns (1)–(6) refer to regression models using ROE_1, ROE_2, ROE_3, ROA_1, ROA_2, and ROA_3 as measures of long-term operating performance, respectively. The coefficient on Und_Local is significantly negative at the 5% significance level in all except Model (2), largely consistent with the univariate test results. This suggests that firms underwritten by local investment banks generally have poorer long-term performance compared with those underwritten by non-local investment banks.

Table 5.   Long-term performance of firms underwritten by local and non-local investment banks OLS regression estimates of long-term firm performance on the choice of underwriter and firm characteristics are presented. Models (1)–(6) refer to using ROE_t (ROA_t) as the dependent variable, where ROE_t (ROA_t) denotes return on equity (return on assets) in post-IPO year t, where t = 1, 2, 3. Und_Local equals one if the issuer is underwritten by a local investment bank, and zero otherwise. All variables are defined in Table 2. The intercept term is included in each regression model but not reported. t-Statistics (in parentheses) are adjusted for heteroskedasticity. Significance levels are defined at ***1, **5 and *10%.
Independent variablesROE_1ROE_2ROE_3ROA_1ROA_2ROA_3
(1)(2)(3)(4)(5)(6)
Und_Local–0.016** (–2.02)0.002 (0.12)–0.022** (–2.19)–0.006** (–1.93)–0.007** (–2.01)–0.009** (–2.43)
Big_auditor0.004 (0.58)0.000 (0.03)0.009 (0.91)0.001 (0.26)0.003 (0.81)0.001 (0.37)
Leverage–0.146*** (–4.30)–0.173*** (–2.87)–0.175*** (–4.29)–0.144*** (–12.42)–0.129*** (–10.08)–0.117*** (–8.49)
Size0.026*** (4.71)0.019* (1.85)0.021*** (3.26)0.015*** (7.46)0.013*** (5.64)0.011*** (4.94)
Growth0.000 (0.18)0.000 (–0.22)0.000 (–0.20)0.000 (0.20)0.000 (0.04)0.000 (–0.64)
STD0.008*** (5.02)0.006** (2.10)0.009*** (3.48)0.005*** (5.68)0.004*** (3.45)0.003*** (3.41)
Age0.002 (1.54)0.003 (0.94)0.005** (2.38)0.002*** (3.07)0.001** (2.19)0.002** (2.25)
Off_size0.003 (0.53)0.018** (2.02)0.015** (2.24)–0.005** (–2.21)0.001 (0.64)0.004* (1.77)
Adjusted R20.0890.0380.0740.1960.1380.125
Observations116011301105116011301113

Turning to control variables, the estimated coefficient on Leverage is significantly negative across all six model specifications, indicating firms that are financially vulnerable tend to have poor future performance. The estimated coefficients on Size are statistically positive in all six regressions, indicating that larger firms generally have better long-term performance. Firm age (Age) at the time of IPO is positively correlated with post-issue performance in Models (3)–(6). Finally, a larger offer (Off_size) is generally associated with superior post-issue performance.

Taken together, Tables 3–5 provide empirical evidence suggesting that in China regional government participation in equity underwriting has a negative impact on the performance of affiliated investment banks. However, care must be taken in interpreting these results as the choice between issuers and underwriters might be endogenous. We address this issue using a three-stage least squares (3SLS) approach in Section 5. The inference remains qualitatively unchanged.

It is also worth noting that the empirical results documented above alleviate our concern regarding using investment bank registration location to proxy for regional government ownership. There are two potential problems with this proxy. First, it might introduce a location bias in the sense that the information advantage possessed by local underwriters might not come from their superior regional government affiliation but rather from their physical proximity to the issuing firms (or both). However, even if this is true, it should bias against our finding that firms underwritten by local investment banks exhibit lower earnings quality and poorer post-issue performance compared with those underwritten by non-local investment banks.16 Second, some securities firms registered in a given region might be owned by the central government. To the extent that these firms might have a distant relationship with regional governments and are not subject to their collusion pressure, including them in our sample of local underwriters should also bias against our empirical findings reported in Tables 3–5.

4.3. Institutional Change in the IPO Process: Abolition of the Quota System

To further explore the motivations behind regional government ownership of securities firms in China, we examine an institutional change that potentially diminishes regional officials’ political incentives to assist local firms in earnings management: the abolition of the IPO quota system in 2001. We predict that this regulatory change probably results in an attenuated difference in earnings quality and long-term performance between firms underwritten by local underwriters and firms underwritten by non-local underwriters.

Table 6 reports our empirical findings. Panel A presents the results of three regressions where we extend our base models in the first panel of Table 4 by adding a post-2001 indicator variable, Post2001, and an interaction term with the underwriter choice variable, Und_Local × Post2001. To remove any confounding effects surrounding the regulatory change, we exclude year 2001 from our analysis. Specifically, Post2001 equals one if the firm is listed on or after January 1, 2002, and zero if before January 1, 2001. Consistent with the results in Table 4, the coefficient on Und_Local in Models (1) and (2) remain significantly positive, indicating greater earnings management by firms underwritten by local investment banks. However, the coefficient on the interaction term Und_Local × Post2001 in both models is significantly negative. These results support our conjecture that the abolishment of the IPO quota system reduces regional government officials’ political incentives to assist underperformed local firms in earnings management by exerting collusion pressure on affiliated underwriters, thereby leading to a convergence in the quality of firms underwritten by local and non-local investment banks. Moreover, the coefficients on Post2001 in both Models (1) and (2) are significantly negative, suggesting that firms listed after 2001 generally engage in less earnings manipulation. This finding is consistent with the conjecture that there has been a gradual improvement in the institutional and regulatory environment in China, resulting in higher costs of collusion among regional governments, affiliated underwriters and regional issuers.

Table 6.   Effect of abolition of IPO quota system on differences in underwriting performance between local and non-local underwriters OLS regression estimates of earnings quality and post-issue performance on local underwriter dummy variable Und_Local, year indicator Post2001, the interaction term Und_Local×Post2001, and firm characteristics are presented. Und_Local equals one if the issuer is underwritten by a local investment bank, and zero otherwise. Post2001 equals one if the firm went public after December 31, 2001, zero if before January 1, 2001. Panel A presents regression results using each of the three earnings quality measures as the dependent variable. ENOI is computed as after-tax non-operating income (or losses) divided by owners’ equity and adjusted by the industry median. IVSTI is computed as gains (losses) from investment divided by owners’ equity and adjusted by the industry median. DA is discretionary accruals estimated based on the cross-sectional Jones model. Panel B presents regression results using each of the six long-term performance measures as the dependent variable. ROE_t (ROA_t) denotes return on equity (return on assets) in post-IPO year t, where t = 1, 2, 3. All variables are defined in Table 2. The intercept term is included in each regression model but not reported. t-Statistics (in parentheses) are adjusted for heteroskedasticity. Significance levels are defined at ***1, **5 and *10%.
Panel A: Earnings quality and underwriter choice
Independent variablesENOIIVSTIDA
(1)(2)(3)
Und_Local0.003* (1.62)0.004** (2.29)0.010 (0.72)
Und_Local×Post2001–0.005* (–1.74)–0.004* (–1.85)0.012 (0.64)
Post2001–0.004*** (–2.56)–0.004*** (–3.33)0.002 (0.19)
OC–0.005 (–1.31)–0.009** (–1.94)0.003 (0.21)
CR0.000 (–1.10)0.000 (–0.80)0.003* (1.78)
Leverage0.024*** (3.48)0.018*** (2.51)0.078** (2.05)
Age0.000 (–0.02)0.000 (–0.02)–0.003 (–2.54)
Off_size0.001 (0.87)0.001 (1.08)–0.003 (–0.38)
Size–0.005*** (–4.18)–0.002** (–2.10)–0.002 (–0.30)
Adjusted R20.0650.0420.007
Observations12931192752
Panel B: Post-issue performance and underwriter choice
Independent variablesROE_1ROE_2ROE_3ROA_1ROA_2ROA_3
(1)(2)(3)(4)(5)(6)
Und_Local–0.016* (–1.92)–0.007 (–0.48)–0.027** (–2.41)–0.008** (–2.16)–0.007* (–1.70)–0.011*** (–2.73)
Und_Local×Post20010.034* (1.81)0.073** (2.28)0.053** (2.08)0.018*** (2.46)0.026*** (2.48)0.021** (1.79)
Post20010.022** (2.39)0.045** (2.24)0.029* (1.73)0.009** (2.24)0.008 (1.54)0.011** (1.93)
Big_auditor0.002 (0.31)–0.000 (–0.05)0.008 (0.82)0.000 (0.12)0.002 (0.63)0.001 (0.30)
Leverage–0.145*** (–4.14)–0.177*** (–2.84)–0.177*** (–4.15)–0.144*** (–12.00)–0.129*** (–9.81)–0.117*** (–8.30)
Size0.026*** (4.58)0.019* (1.76)0.020*** (2.92)0.015*** (7.16)0.013*** (5.38)0.011*** (4.55)
Growth0.000 (0.25)0.000 (–0.10)0.000 (–0.18)0.000 (0.24)0.000 (0.08)0.000 (–0.67)
STD0.008*** (4.87)0.008** (2.28)0.010*** (3.72)0.005*** (5.54)0.005*** (3.54)0.004*** (3.66)
Age0.001 (0.78)–0.001 (–0.45)0.003 (1.44)0.001* (1.58)0.001 (0.99)0.001 (1.07)
Off_size–0.001 (–0.27)0.012 (1.33)0.012* (1.74)–0.006*** (–2.66)0.000 (–0.04)0.003 (1.29)
Adjusted R20.0990.0510.0810.2060.1420.135
Observations109010601036109010601043

Although the results of the first two regression models using ENOI and IVSTI as measures of earnings quality support our conjecture, the regression coefficient on the discretionary accruals, DA, is insignificant. This might be explained by prior research findings (e.g. Haw et al., 2005) that DA is less powerful in capturing the earnings management behavior of Chinese firms compared with ENOI and IVSTI. In addition, the insignificant coefficient on DA might also be induced by excluding sample firms between 1992 and 1998 from the regression as a result of the unavailability of cash flow statements required to calculate DA. However, regional governments’ incentives to take local firms public are likely to be high in these years. The sign and significance of estimated coefficients of control variables reported in Table 6 are largely consistent with those reported in Panel A of Table 4.

Panel B of Table 6 reports the results of six regressions where we separately regress ROE and ROA in each of the three post-IPO years on Und_Local, Post2001, their interaction term Und_Local × Post2001, and a set of control variables. The estimated coefficient on Und_Local is significantly negative in all but Model (5), which is largely consistent with the results in Panel B of Table 4. More importantly, the coefficient on Und_Local × Post2001 is significantly positive in all six model specifications, supporting our conjecture that the long-term performance differential between firms underwritten by local investment banks and non-local investment banks is attenuated after 2001. In addition, the coefficient on Post2001 is statistically positive in five model specifications, indicating that firms listed after year 2001 generally have better long-term performance than firms listed before 2001. Finally, the estimated coefficients on control variables are generally consistent with those reported in the second panel of Table 5.

In summary, empirical evidence reported in Table 6 provides support for the existence of political motivations behind regional government ownership of investment banks. However, care must be taken in drawing inferences from these results as they cannot completely rule out the social incentives of government participation in equity underwriting in China.

5. Additional Analyses

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Institutional Background and Hypotheses
  5. 3. Data and Sample
  6. 4. Main Empirical Results
  7. 5. Additional Analyses
  8. 6. Conclusion
  9. References

We now turn to several additional tests that further probe the performance implications and motivations of regional government ownership of securities firms in China. Specifically, we conduct the following four analyses: (i) the effect of government ownership on the amount of underwriting fees charged; (ii) differences in earnings quality between regional government-owned firms (regional SOEs) and non-regional government-owned firms (regional non-SOEs), given that both are underwritten by local underwriters; (iii) the 3SLS test to address the endogeneity issue; and (iv) fixed effects regressions to control for differences in regional characteristics.

5.1. Government Ownership and Underwriting Fees

In addition to examining the effect of government ownership on the quality of firms underwritten by affiliated investment banks, in this section we examine another dimension of government involvement in underwriting practices, the amount of underwriting fees charged to issuers. Specifically, we regress the natural logarithm of underwriting fees on the local underwriter dummy Und_Local and a set of control variables that potentially explain the variation in the amount of fees charged to issuers. As shown in Panel A of Table 7, the estimated coefficient on Und_Local is statistically negative in all three models, suggesting that firms using local investment banks incur lower underwriting fees compared with those underwritten by non-local investment banks. This finding is consistent with at least two explanations. First, local underwriters’ geographical proximity to the clients and/or their superior regional government connection might provide them an information advantage over non-local investment banks, thereby leading to lower underwriting costs and, consequently, lower fees. Alternatively, the above result could be another manifestation of regional governments’ incentives to facilitate the public listing of financially weak local firms.

Table 7.   Underwriting fees charged by local and non-local investment banks OLS regression estimates of underwriting fees on the choice of underwriter and firm characteristics are presented. Panel A presents results of the base models. The dependent variable is the natural logarithm of underwriting fees. Und_Local equals one if the issuer is underwritten by a local investment bank, and zero otherwise. ENOI is computed as after-tax non-operating income (or losses) divided by owners’ equity and adjusted by the industry median. IVSTI is computed as gains (losses) from investment divided by owners’ equity and adjusted by the industry median. DA is discretionary accruals estimated based on the cross-sectional Jones model. Panel B reports the regression results by adding the year 2001 dummy variable Post2001 and its interaction term with the local underwriter indicator variable Und_Local × Post2001. All variables are defined in Table 2. The intercept term is included in each regression model but not reported. t-Statistics (in parentheses) are adjusted for heteroskedasticity. Significance levels are defined at ***1, **5, and *10%.
Independent variablesEarnings quality = ENOIEarnings quality = IVSTIEarnings quality = DA
(1)(2)(3)
Panel A: Underwriting fees and the choice of underwriter
Und_Local–0.186*** (–5.05)–0.190*** (–4.91)–0.061* (–1.90)
Earnings quality–0.401 (–0.41)–1.787*** (–3.16)–0.066 (–0.57)
OC–0.269** (–2.38)–0.191** (–1.96)–0.183** (–2.03)
Und_Top–0.121*** (–4.30)–0.150*** (–5.21)–0.030 (–1.22)
Leverage–0.117 (–0.97)0.024 (0.21)–0.150 (–1.41)
Growth–0.047*** (–3.90)–0.042*** (–3.76)–0.013 (–0.76)
Off_size0.741*** (22.65)0.767*** (22.92)0.513*** (20.74)
Size0.043* (1.58)0.020 (0.76)0.116*** (6.91)
Adjusted R20.7150.7310.713
Observations11801083795
Panel B: Effect of abolition of the IPO quota system
Und_Local–0.126*** (–2.99)–0.130*** (–2.99)0.016 (0.59)
Und_Local×Post20010.145*** (2.80)0.145*** (2.57)0.004 (0.11)
Post20010.506*** (21.37)0.449*** (17.46)0.424*** (17.04)
Earnings quality0.794 (0.83)–0.538 (–0.92)–0.122 (–1.30)
OC–0.048 (–0.99)–0.037 (–0.73)–0.022 (–0.56)
Und_Top–0.029 (–1.20)–0.051** (–1.96)0.047*** (2.50)
Leverage–0.038 (–0.38)0.023 (0.25)–0.024 (–0.32)
Growth–0.045*** (–3.64)–0.043*** (–3.60)–0.031*** (–3.91)
Off_size0.715*** (22.75)0.735*** (22.41)0.602*** (31.25)
Size–0.007 (–0.25)–0.016 (–0.58)0.033** (2.30)
Adjusted R20.8030.7960.832
Observations11141017729

To further distinguish between these two alternative explanations, in Panel B we introduce into the regression models the post-2001 indicator variable, Post2001, and its interaction with the local underwriter dummy, Und_Local × Post2001. We posit that although the information advantage possessed by local underwriters remains more or less the same after the abolition of the quota system, regional officials’ incentives to help underperformed local issuers probably diminish. Hence, a convergence in the underwriting fees charged by local and non-local underwriters after 2001 would provide support for the second explanation.

Panel B of Table 7 reports the regression results. Consistent with our conjecture, while the coefficient on Und_Local in Models (1) and (2) remains negative, the coefficient on the interaction term Und_Local × Post2001 is significantly positive, even after controlling for issuer and underwriter characteristics. Although we cannot completely rule out the information advantage explanation, this result provides further support for the adverse effect of regional government ownership of securities firms. It is also worth pointing out that the coefficient on the year indicator variable Post2001 is significantly positive, indicating that there is an overall increase in the underwriting fees charged to IPO issuers after 2001.

5.2. Regional Government-Owned Firms (Regional State-Owned Enterprises) Vis-à-vis Non-regional Government-Owned Firms (Regional Non-State-Owned Enterprises)

To corroborate our prior finding of a distortion effect of regional government intervention on the performance of affiliated underwriters, in this section we focus on the subsample of firms underwritten by local investment banks and compare the earnings quality between regional government-owned enterprises (regional SOEs) and non-regional government-owned enterprises (regional non-SOEs). Regional SOEs are more important to regional governments for both social and political reasons (Li and Zhou, 2005). They typically bear greater social responsibilities, such as providing relief for the region’s unemployment problems and providing financial support for regional government infrastructure projects (Chen et al., 2008). In addition, Li and Zhou (2005) note that the main purpose of setting up the stock markets in China is to facilitate the privatization of government-owned enterprises. Therefore, the successful listings of regional SOEs contribute more to regional officials’ political careers than regional non-SOEs. The above arguments lead to our conjecture that regional governments probably exert greater collusion pressure on affiliated investment banks when serving regional SOEs and allow them to engage in more earnings manipulation.

Table 8 reports the results of regressing each of the two earnings quality measures, ENOI and IVSTI, on a regional SOE dummy variable, Regional_SOE, and control variables. As expected, the coefficient on Regional_SOE is significantly positive in both models, indicating greater earnings management by firms owned by regional governments. This result provides additional evidence supporting the social and political motives behind government intervention in securities firms.

Table 8.   Earnings quality and firm type OLS regression estimates of earnings quality on firm type and other firm characteristics are presented. The sample consists of firms that are underwritten by local investment banks. The dependent variable is earnings quality, measured in two ways: ENOI and IVSTI. ENOI is computed as after-tax non-operating income (or losses) divided by owners’ equity and adjusted by the industry median. IVSTI is computed as gains (losses) from investment divided by owners’ equity and adjusted by the industry median. Regional_SOE is a dummy variable that equals one if the firm is a regional government-owned enterprise, and zero otherwise. All variables are defined in Table 2. The intercept term is included in each regression model but not reported. t-Statistics (in parentheses) are adjusted for heteroskedasticity. Significance levels are defined at ***1, **5, and *10%.
Independent variablesENOIIVSTI
(1)(2)
Regional_SOE0.009*** (2.54)0.005* (1.90)
OC0.005 (1.15)0.001 (0.37)
CR0.004 (0.45)0.031** (2.42)
Leverage0.037*** (2.48)–0.001* (–1.61)
Age0.000 (–0.38)0.001 (0.44)
Off_size–0.001 (–0.51)–0.003** (–2.03)
Size–0.006*** (–2.95)0.005** (1.90)
Adjusted R20.0870.044
Observations311376

5.3. Endogeneous Relationship Between Earnings Management and Underwriter Choice

Jo et al. (2007) suggest that the relation between earnings management and underwriter choice is endogenous because issuing firms choose underwriters and their reporting strategies simultaneously. Underperformed regional issuers with greater earnings management incentives probably prefer regional government-affiliated underwriters for the ease of collusion. Conversely, regional government-affiliated underwriters probably serve underperformed regional firms and tolerate their earnings management behavior due to regional government pressure. Hence, ignoring this endogenous relationship and using OLS regression models might lead to biased and inconsistent estimates. To confirm the validity of previous results and inferences, we use a 3SLS estimation approach to address the endogeneity issue described above.

Table 9 reports the results of 3SLS models. Models (1) and (2) are based on ENOI and IVSTI, respectively. As shown in column (2) of Model (1), the coefficient on ENOI is significantly positive, suggesting that issuers with stronger earnings management incentives have a higher tendency to choose an underwriter that is affiliated with their regional government. Moreover, as the results in the first column of Model (1) indicate, the coefficient on Und_Local remains significantly positive at the 1% level. This result suggests that the association between underwriter choice and issuer’s quality exists even after controlling for the endogeneity problem. As shown in Model (2), this inference remains valid when we use IVSTI to replace ENOI as the measure of earnings management.

Table 9.   Three-stage least squares estimation of the relation between earnings quality and underwriter choice Results of the three-stage least squares estimation of the following systems of equations are reported: EQ = α0 + α1 × Und_local + α2 × Big_auditor + α3 × CR + α4ΔROA + α5 × Leverage + α6 × Growth + α7 × Age + α8 × LnTA + ɛ (a) Und_local = β0 + β1 × EQ + β2 × Big_auditor + β3 × ROA_0 + β4 × Growth + β5 × Off_size + β6 × LnTA + ɛ (b) In this system of regression models, EQ is earnings quality measured by ENOI and IVSTI, respectively. In this table, Models (1) and (2) refer to the regression results based on ENOI and IVSTI, respectively. ENOI is computed as after-tax non-operating income (or losses) divided by owners’ equity and adjusted by the industry median. IVSTI is computed as gains (losses) from investment divided by owners’ equity and adjusted by the industry median. Columns (1) and (3) report the regression results of equation (a). Columns (2) and (4) report the results of equation (b). All variables are defined in Table 2. The intercept term is included in each regression model but not reported. t-Statistics (in parentheses) are adjusted for heteroskedasticity. The chi-squared statistic is based on the three-stage least squares estimation. Significance levels are defined at ***1, **5, and *10%.
Independent variablesModel (1)Model (2)
Dependent variable = ENOI (1)Dependent variable = Und_Local (2)Dependent variable = IVSTI (3)Dependent variable = Und_Local (4)
Und_Local0.061*** (5.61) 0.049*** (4.65) 
ENOI 14.148*** (4.22)  
IVSTI   22.318*** (4.72)
Big_auditor0.006*** (3.26)–0.096*** (–3.53)0.005*** (2.74)–0.098*** (–3.28)
CR0.000 (–0.65) 0.000 (–0.32) 
ROA_0 0.088 (0.58) 0.169 (1.00)
ΔROA–0.002 (–0.21) 0.004 (0.62) 
Leverage0.006 (1.39) 0.002 (0.61) 
Growth–0.003*** (–3.63)0.051*** (4.43)–0.002*** (–2.46)0.037*** (3.04)
Age0.000 (0.48) 0.000 (0.48) 
Off_size 0.004 (0.14) 0.012 (0.42)
LnTA–0.002*** (–2.63)0.022 (0.93)0.000 (0.62)–0.023 (–0.81)
χ2-statistic76.1978.7986.26105.60
Observations12411144

5.4. Fixed Effects Regressions

All multivariate test results presented in Tables 4–8 are estimated with the OLS regression models. To control for differences in regional characteristics that might cause spurious results, we also use fixed effects regressions as a robustness check. Results remain qualitatively unchanged.

6. Conclusion

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Institutional Background and Hypotheses
  5. 3. Data and Sample
  6. 4. Main Empirical Results
  7. 5. Additional Analyses
  8. 6. Conclusion
  9. References

This paper examines the performance implications and motivations behind government ownership of securities firms in an emerging market like China. The fact that a significant number of investment banks in China are owned and controlled by their respective regional governments creates a unique opportunity for us to explore the potential conflict of objectives facing regional governments between shareholder wealth maximization and the pursuit of social and/or political gains. Empirical results suggest that regional government involvement has a distortion effect on the performance of affiliated investment banks. In particular, we find evidence that firms underwritten by their regional government-affiliated investment banks tend to exhibit greater earnings management and poorer post-issue performance compared with those underwritten by unaffiliated investment banks. This result remains valid after controlling for the endogeneity problem. Several additional tests provide further support for the social and/or political motivations behind regional government participation in equity underwriting. First, we examine the effect of the abolishment of the IPO quota system in 2001 and find that differences in the quality of firms underwritten by their respective regional government-affiliated and unaffiliated investment banks are attenuated in the post-2001 period. Second, we document that regional government-affiliated underwriters charge lower fees to issuers, even after controlling for the effect of information advantage. Third, using a subsample of regional issuers underwritten by affiliated investment banks, we find evidence that regional SOEs exhibit greater earnings management at the time of public offering than regional non-SOE firms.

The empirical results documented in this paper add new evidence relevant to the debate regarding government intervention in financial institutions, especially for countries with underdeveloped financial systems and poorly protected property rights. Our findings suggest that in China governments appear to acquire ownership of financial institutions to serve their social and political agendas, which has a distortion effect on the underwriting quality of affiliated investment banks.

Footnotes
  • 1

    In the rest of this paper, we use the terms “investment bank” and “securities firm” interchangeably.

  • 2

    Foreign investment banks are prohibited from providing independent underwriting services in China. Only a limited number of them have been allowed to set up joint ventures with “qualified” domestic brokerages under the approval of CSRC. For example, Goldman Sachs partnered up with Gao Hua Securities in 2004, while UBS gained access to the Chinese underwriting market through the purchase of part of Beijing Securities in 2005. However, under current rules, foreign investment banks may own no more than one-third of a Chinese joint venture.

  • 3

    For the purpose of this paper, we define regional government at the provincial level (or region with provincial status; that is, autonomous administrative region or municipality under the central government).

  • 4

    During an initial public offering, investment banks mostly work as brokers and lead the selling of shares to the public. The issuers often have the responsibility for unsold shares, although the shares are usually massively oversubscribed.

  • 5

    The statistics come from the World Federation of Exchanges at http://www.world-exchanges.org.

  • 6

    The Glass–Steagall Act was passed in 1933. Even though it was repealed in the USA in 1999, it nevertheless had a strong influence on China’s financial system.

  • 7

    A comprehensive securities company is required to meet the following conditions: (i) the company must have a registered capital of at least RMB500m; (ii) senior managers and officials must possess appropriate professional qualifications for employment in the securities industry; (iii) the company must have established business premises and satisfactory trading facilities; and (iv) the company must have a sound management system and standardized separate administrative systems to deal with operations on its behalf and in its brokerage operations. The requirements of a brokerage securities company are similar to those of a comprehensive securities company except that the minimum registered capital is set at RMB50m.

  • 8

    A comprehensive securities company may engage in the following business activities: (i) securities brokerage business; (ii) securities operations on its own behalf; (iii) securities consignment sales; and (iv) other securities business verified and approved by the CSRC.

  • 9

    Regulation on risk management of securities firms was passed in the sixth standing conference on April 23, 2008. Full disclosure is available at http://english.mofcom.gov.cn/aarticle/policyrelease/announcement/200805/20080505558547.html, accessed on August 20, 2009.

  • 10

    Chen (2003) notes that the private securities litigation in China start to surge after 2001.

  • 11

    Information on government-owned vis-à-vis non-government-owned investment banks is provided by Chen (2007), based on proprietary information from the CSRC. Non-government-owned investment banks only constitute a small fraction of the sample (<5%). In untabulated tests, we add regional firms underwritten by non-government-owned investment banks into the control sample. Empirical results remain qualitatively unchanged.

  • 12

    We choose to focus on lead underwriters because they assume the greatest responsibility in a public offering (Ellis et al., 2000).

  • 13

    We estimate discretionary accruals for each industry-year where the number of observations is more than five. Total accruals are computed as the difference between operating net income and operating cash flows. As cash flow statements are not available prior to 1998, we estimate discretionary accruals only for firms going public between 1998 and 2008.

  • 14

    We also conducted empirical analyses: (i) without making industry adjustment; and (ii) adjusting by the industry mean. In both cases the results remain qualitatively unchanged.

  • 15

    IVSTI might not be a proper measure of earnings management for firms in the financial industry because investment income is considered part of the core earnings for these firms. In untabulated tests, we also conducted analyses excluding financial firms from our sample. The results remain qualitatively unchanged.

  • 16

    Prior studies such as Bae et al. (2008) generally find a positive association between local information advantage and performance.

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  2. Abstract
  3. 1. Introduction
  4. 2. Institutional Background and Hypotheses
  5. 3. Data and Sample
  6. 4. Main Empirical Results
  7. 5. Additional Analyses
  8. 6. Conclusion
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