Government Ownership and Venture Performance: Evidence from China*

Government ownership and venture performance: Evidence from China*

Jerry Cao† Singapore Management University & Asia Private Equity Institute

Mark Humphery-Jenner‡ UNSW Australia

Jo-Ann Suchard§ UNSW Australia

* This paper benefited from comments received at the Australasian Finance and Banking Conference (2013), and from seminar presentations at Singapore Management University and UNSW Australia. We also thank Vish Ramaswami, Hyacinthe Some and Melvyn Teo. † Singapore Management University. Email: [email protected] ‡ UNSW Business School, UNSW Australia. Email: [email protected] § UNSW Business School, UNSW Australia. Email: [email protected]

Government ownership and venture performance: Evidence from China

Abstract

We study the government's role in VC market in China. The impact of government depends on whether the fund is wholly or partially government-owned at central or provincial level. Partially government-owned VCs improve venture success, e.g., the likelihood of exit via an IPO and the likelihood of exit in mainland China. Investment from provincial government-owned VCs is associated greater exit-success, with such advantage diminishing with more funds. Government- owned funds exhibit worse performance at the fund-level. Our findings suggest that government VCs may benefit through political connections may help VCs, but that excessive government control leads to inefficiencies.

Keywords: Government Ownership, Venture Capital, Private Equity, China, IPO JEL Classification: G24, G34, G38

1 Introduction

In emerging economies, the government has significant influence over markets owing to political control and discretionary regulations. Government has widespread presence in the economic entities through direct ownership or via indirect vehicles. For example, Shleifer (1998) shows that government direct ownership is associated with inefficiency and value destruction in state owned enterprises (SOEs). On the other hand, research shows that government ownership conveys political connection, which can facilitate access to bank loans, government concessions or regulatory favors (Faccio, Masulis and McConnell, 2006; Claessens, Feijen and Laeven, 2008;

Li, Meng, Wang and Zhou, 2008). Most of these studies focus on SOEs in which government has direct ownership.

A relatively less explored area is the role of government indirect ownership through investment vehicles, such as venture capital (VC) funds. Dewenter, Han and Malatesta (2010) examine the value impact of sovereign wealth funds when they invest in listed firms. Unlike sovereign wealth funds, VC funds are an important financing source for entrepreneurial activity and innovation in both developed markets (Gompers and Lerner, 1999) and emerging economies

(Sapienza et al., 1996). The existent literature on the government’s role in VC has mostly focused on government support of VCs (e.g., via grants and subsidies) in developed markets

(Lerner, 1999; Leleux and Surlemont, 2003; Brander et al, 2014). The role of government ownership of VC funds remains relatively under-explored, especially in the context of emerging markets. The distinction between emerging markets and developed markets is especially important given the increased political and economic risks that are evident in those economies and the potential relevance of political connections in resolving them.

China is the largest emerging market in which the venture capital sector has become an important force in the country’s industrial transformation. China’s VC industry has grown rapidly during the past two decades, from virtually non-existent in 1991 to a peak of US$92.59bn in 2011, becoming the second largest global VC market next to the US. Unlike the US VC market,

China’s market features significant government involvement. For example, the first VC fund was established in 1985 by the central government when the State Science and Technology

Commission and the Ministry of Finance joined together to create the China New Technology

Venture Investment Corporation. This was followed by many provincial governments establishing their own VC funds.

Unlike in the VC industry in the U.S. and most developed markets, the Chinese government often has direct control of VC funds through whole or partial ownership. For example, Shenzhen Venture Capital Groups has the Shenzhen municipal government as its controlling shareholder; Yunnan Huili Equity Investment Fund Management Company is partially owned by Yunnan Industrial Investment Holding Group, which is wholly owned by the

Yunnan government. Government owned venture capital, as a percentage of domestic venture capital invested, varied between 25 to 34% in 2005-2008 (China Venture Capital Research

Institute, 2009). The purpose of this study is to analyze the impact of Chinese government ownership on the success of portfolio companies and the performance of the funds themselves.

Government owned VC funds have several advantages over other funds. They have preferential access to information and to companies because of government’s linkages with high- technology development zones and incubators. For firms, government connections can help obtain access to capital (Chen et al., 2013a), which is especially relevant if they have a high level of intangible assets (Zheng and Zhu, 2013). For entrepreneurial firms in emerging markets, one

3 advantage of having sponsorship from government VC funds is their ability to help establish connections with government agencies. This is especially important in China, where IPOs require prolonged government approval.1 We therefore hypothesize and test whether companies backed by a government owned VC fund are more likely to achieve a successful exit, especially through an IPO on domestic exchanges.

Despite the potential positives of government owned VCs, government ownership could lead to inefficiencies and misallocation of resources (both within the portfolio company and within the VC fund itself). We therefore distinguish between types of VC funds according to the amount of government ownership (wholly vs. partially owned) and its source (central government level vs. provincial government level). Due to the trade-offs between the advantages of government ownership (i.e., political connections) and the disadvantages (i.e., inefficiency, exposure to politically motivated decisions and misallocation of resources), we would expect that the benefits would mainly accrue in those situations where government does not have complete control over the fund. In this case, the fund could still obtain the benefits of political connections while attenuating the inefficiencies that would otherwise be overwhelming. Further, VC funds with provincial government stakes will behave differently when investing in local (that is, firms located within the same province as the government agency) vs. non-local entrepreneurial firms.

For example, the provincial government can provide their VC funds with better private information and access to regulators when investing locally. However, we expect that the benefits of provincial government owned VCs will decrease with the number of such VCs, as a

1 In China, companies that want to raise funds through domestic IPOs not only need government support but also approval from China Securities Regulatory Commission (CSRC). Chen et al., (2011) show that a government background can help firms to navigate the increasingly discretionary aspects of regulations. 4 preponderance of provincial government owned VCs would expose the company to an increased risk of politically motivated decision-making.

The impact of government ownership is also likely to vary with political and economic uncertainty. Specifically, if government ownership conveys benefits of political connections, government backed VC funds should be more able to achieve a successful exit during times of political uncertainty. We also expect that government VCs will be less sensitive to market conditions when deciding whether to exit a company. We therefore hypothesize that government owned VC funds, especially ones owned by the provincial government, should be more likely than other funds to exit investments in China at times of political uncertainty2or poor market conditions in China.

Although government ownership in VC funds is associated with benefits in accessing capital markets such as IPOs, government ownership in private companies could result in inefficiency. Thus, even if government-backed VC funds can provide some benefits to their portfolio companies, the government funds themselves could perform worse. Subsequently, we compare the performance of government-owned funds and other funds by examining the performance of all exited transactions. In particular, we examine the performance of government owned VC funds, as proxied by the fund’s average exit multiple and its success rate. We hypothesize government-owned VC funds achieve lower returns despite of preferential access to

IPO market.

We collect a comprehensive sample of 4700 Chinese venture-backed companies from

ChinaVenture, and supplement the data with hand-collected information on ownership of VC funds. We identify if the fund is wholly or partially government owned and if the government-

2 In this context, political uncertainty involves the risk of unexpected and significant changes in government regulation and the legal environment. 5 ownership is by the central government or by a provincial government. Our sample includes entrepreneurial companies based in mainland China, Hong Kong, and Taiwan (though is robust to focusing only on the companies in mainland China). Our sample is of firms that receive VC investment between 1988 and 2011.3 Our sample starts in 1988 and ends in 2011. 820 of the

4700 companies are exited either through an IPO or a takeover. The sample includes 691 companies exited via an IPO, 307 of which are in non-mainland markets.

We find that companies backed by government owned VC funds are significantly more likely to achieve an IPO, especially in mainland China, where the IPO process is discretionary and heavily government-regulated. This implies that government backing is important in accessing IPO markets since these funds are better navigating the discretionary laws that govern

IPO markets. We also find that companies backed by partially government owned VCs are more able to be exited at times of policy uncertainty, suggesting that government GPs can navigate political uncertainty. Similarly, government owned VCs have more exits during a market downturn, suggesting that government GPs are less sensitive to market conditions, especially adverse market conditions. When comparing VC fund performance in exited deals through IPOs, we find that government owned VC funds deliver lower returns measured the fund’s average exit multiple. The implication is that while the fund’s government connections might convey benefits to its portfolio companies, wholly government owned funds remain inefficient (in a similar manner to other government owned enterprises).

Our study extends the literature on government venture capital by analysing an emerging market in which government owned VC has played a pivotal role in the development of the VC market. While some prior studies have analysed government supported VC in developed

3 The government shut down the IPO market in October 2012, thus blocking the most common exit mechanism for VC backed firms. 6 markets, our analysis has several important differences from this literature, which enables our study to contribute to the literature. As compared with the preponderance of prior literature, we focus on government owned VC, rather than government supported VC, which allows us to analyse the impact of direct government involvement in the VC fund.4 Further, whereas the prior studies on government supported VC have focused on developed markets, we conduct this analysis using a sample from the world’s largest emerging market. The analysis of an emerging market allows us to examine the role of government VC in a market that is characterized by significant political risks and economic risks, which government connections might help to mitigate. In addition, most of the literature has analysed market level data and has examined whether government venture capital substitutes or complements private venture capital (Brander et al, 2010, 2014; Hood, 2000; Bertoni et al, 2014). Our study focuses on the firm level and provides insight into venture success as well as fund level performance. Considering the importance of VCs for financing growth and innovative companies, our study has important implications for policy makers, entrepreneurs, VC firms and capital markets.

The structure of this paper is as follows. Section 2 details the hypotheses and discusses the institutional background, where relevant. Section 3 describes the data. Section 4 presents the results and Section 5 concludes.

4 Brander et al (2014) find that 86% of their global sample is for government supported VC funds where the VC firms that are privately owned, but that obtain significant financing, tax credits, or other subsidies from government. 7

2 Background and Hypotheses

2.1 Government ownership and venture success

We expect that in China, companies backed by government owned funds will be more likely to succeed. Government owned funds tend to have more political connections.

Connections (in general) are often seen as a key value driver in venture capital and private equity investment (Hochberg et al., 2007, 2010; Bottazzi et al., 2008). Political connections can convey several advantages (see generally Faccio, 2006). Political connections are likely to particularly important in emerging markets for several reasons. First, emerging markets, including China, can feature arbitrary government decisions and limited recourse to the courts (He and Su, 2013), which the legal literature argues influences the investment decisions of private equity funds (Lin,

2013). For example, He and Su (2013) argue that a party’s access to resources significantly influences its access to the courts in China. Chen et al (2011) argue that political connections can help firms (in China) to protect against governmental rent-seeking, especially in areas where the government has more discretion. Berkman et al (2010) indicate that the government is less likely to enforce regulations against connected companies. Zhou (2013) finds that political connections significantly increase firms’ perceptions of property rights security. Such legal issues can deter non-government (i.e. private) investors from engaging with entrepreneurs (Bottazzi et al., 2009).

Overall, this suggests that political connections could help entrepreneurial firms to protect against commercially sub-optimal aspects of state intervention.

Second, political connections can help a company to navigate the politically influenced bureaucratic processes. The IPO process, and foreign listing-process, is bureaucratic and discretionary (Huang, 2011). Political connections are particularly important when navigating

8 discretionary regulations (Chen et al., 2011). Thus, government connections should help a fund to successfully exit a portfolio company.

Third, backing from a politically connected VC could also provide greater access to capital in a market, such as China, where capital access can be pseudo-political (Li et al., 2008). For example, Chen et al (2013a) argue that non-commercial factors determine a firm’s access to loans from all but the largest four-banks. Zheng and Zhu (2013) find that loans to politically connected firms (in China) are less sensitive to asset tangibility. This contrasts with the traits such as financial market development, tax reform, labor reform, and early-stage access to capital markets, which are often associated with improved entrepreneurial outcomes in developed markets (see e.g. Da Rin et al., 2006, 2010). This suggests that the connections derived from a government-backed VC investor would increase the firm’s access to credit, especially for entrepreneurial companies with significant levels of intangible capital. Fourth, firms with political connections can potentially obtain rents from the government, such as increased access to government subsidies (Wu and Cheng, 2011; Wu et al., 2012a), or preferential tax treatment

(Wu et al., 2012b).

The performance benefits of political connections should be highest for firms backed by a

‘partially’ owned VC fund as compared with a ‘wholly’ owned VC fund. Wu et al (2012a) show that privately owned firms with political connections benefit from those connections through increased access to subsidies, whereas wholly government-owned firms experience no such gains. Wu et al (2012b) make similar findings in relation to tax-treatment. The logic is that wholly government owned enterprises are under less competitive pressure, and are more susceptible to government interference. Further, Ma et al (Forthcoming) show that politically connected state owned enterprises are more prone to tunneling, suggesting that wholly owned

9 enterprises are worse-governed; and thus, that a wholly owned fund would provide fewer benefits to its portfolio companies. Subsequently, Chen et al (2012a) indicate that there is an inverted-U shaped relationship between connections and performance; some connections improve performance, but high levels of connections are associated with government interference and value-destruction. In the IPO market, Chen et al (2013b) find that state owned enterprises (SOEs) have worse underpricing problems than do other companies, suggesting that total government ownership can harm listing outcomes and performance. Thus, a partially government owned VC fund would be more likely to facilitate venture success than would a wholly owned one.

Hypothesis 1: Partially government-owned VC funds increase the likelihood of venture

success. Wholly government-owned VC funds do not increase the likelihood of venture

success.

2.2 Political ownership and political uncertainty

We expect that being backed by partially government-owned VCs will be even more beneficial during times of political uncertainty. In China, financial markets are vulnerable to political uncertainty. For example, the government maintains restrictions over the IPO process, leading to potential uncertainty surrounding IPO exits. Regulatory approval is ordinarily required for takeovers, rendering takeover-exits vulnerable to political uncertainty. The laws in relation to bankruptcy (Tomasic and Zhang, 2012), directors’ duties (Xu et al., 2013), anti-trust (Wei,

2013), takeovers (Cai, 2011), and securities litigation (Huang, 2007, 2010; Humphery-Jenner,

2012), have undergone significant changes and face significant uncertainty. Firms that are 10 backed by a government-owned VC should be better able to mitigate the aspects of such uncertainty where, as in China, regulation involves some regulatory discretion.5 These benefits should concentrate in partially government-owned VCs. This is because with wholly government-owned VCs, the portfolio company is further exposed to the driver of such political uncertainty – the government – thereby off-setting the benefits of government connections.

However, with partially government-owned VCs, the portfolio company gets access to government connections, with government intervention being moderated by the presence of an outsider. Thus, we make the following hypothesis.

Hypothesis 2: Partially government-owned VC funds mitigate the impact of political

uncertainty.

2.3 Government ownership and market conditions

We also anticipate that government owned VCs will be less sensitive to market conditions when deciding whether to exit a company. Government owned VC funds are not exposed to external market forces in relation to raising future funds. By contrast, for other non-government funds, prior performance can influence the ability to raise capital for future funds (Phalippou,

2010). Thus, we expect that government owned VC funds will be less concerned about the timing of their exits. Therefore we anticipate that government owned VC funds will be more willing to exit during weaker market conditions. We capture this in the following hypothesis.

5 For example, in China, the merits review approach to facilitating securities listings involves some government discretion (Huang, 2011; Humphery-Jenner, 2012). There is also discretion in the takeover context, for example in relation to the application of the mandatory bid rule (Cai, 2011). 11

Hypothesis 3: Firms backed by government owned VCs are more likely to be exited in

weaker market conditions.

2.4 Government ownership, location and firm performance

We expect that backing from a fund owned by the provincial government of the province in which the portfolio company is located will have a quadratic relationship with performance.

Geographic proximity between the fund and its backers can have some benefits in relation to monitoring, which can allow the VC-backer to add value to the portfolio company (Chen et al.,

2010; Humphery-Jenner and Suchard, 2013; Lutz et al., 2013).

Despite the benefits of geographic closeness, companies supported by their province’s government might not necessarily be more successful. First, these government-backed-funds might chose companies from the same province in order to achieve political outcomes, such as supporting local industries. In this case, the government selects companies who might not necessarily perform as strongly, but who are in government-favored sectors/industries. Second, support from the provincial government can tie the portfolio company to promoting the government’s interests. This can cause the company to make non-commercial decisions, which might impede venture success. Therefore, we expect that some backing from a provincial government-owned fund will improve exit-likelihood; however, exit-likelihoods might reduce when a high proportion of backers have government ownership from the company’s province.

Hypothesis 4: There is a quadratic relationship between the proportion of the company’s

VC backers6 who are owned by the provincial government in which the company is located

and venture success.

2.5 Government ownership and IPO exits

We anticipate that government-owned VC funds will be more able to facilitate an IPO exit and more able to facilitate a domestic IPO exit. Before 2005, China’s IPO process was government-controlled, featuring a quota system of allocating the right to undertake an IPO.

However, even after 2005, the IPO process and foreign listing process in China are both discretionary, featuring a merits review process whose criteria are open to regulatory interpretation (Huang, 2011). China’s IPO process has also featured quotas on the number of companies that can list on the stock market. Subsequently, recent Chinese evidence suggests that the political capital of underwriters can increase the likelihood of their clients’ IPO applications being approved by the regulators (Chen et al., 2012b). Further, companies who are politically connected have better access to IPO markets, often featuring lower underpricing and fewer costs during the IPO process (Francis et al., 2009), and a greater probability of IPO approval (Li, 2013;

Liu et al., 2013). Li et al (2012) hypothesize, but do not directly show, that backing from a politically connected fund might help a firm achieve IPO approval. These benefits are attributable both the signaling benefits of government connections (following the logic in

Ragozzino and Reuer, 2011), and the benefits of connections in navigating the discretionary nature of China’s IPO-approval regulations. By contrast, political connections would be less advantageous for other exit-types, such as M&As, where there is relatively less government

6 In this paper, we measure the proportion of backers with reference to the number of backers. Data on the percentage ownership of backers is unavailable. 13 intervention (Huang, 2005, 2008); and thus, less scope for political connections to become involved. Therefore, we expect that companies backed by a government-owned VC fund will both be more likely to exit via an IPO and more likely to be able to navigate the process to achieve a domestic listing.

Hypothesis 5a: Government owned VC firms are more likely to exit their investee firms

via an IPO

Hypothesis 5b: Government owned VC firms are more likely to exit their investee firms

via an IPO in mainland China than an IPO overseas.

2.6 Government ownership and investment returns

We expect that government owned VC funds will deliver lower returns than will non- government owned VC funds. While political connections can convey benefits to the fund’s portfolio companies, this need not imply that the VC fund is otherwise well run or is efficient.

Eesley (2009) argues that government backed VCs have both policy as well as financial objectives. The government, as the ultimate owner, can intervene in the operations of the firm and has an incentive to do so when pursuing political and social goals such as reducing unemployment (Wu et al., 2012a) . Government backed VCs often lack the business experience necessary to pick good investments and are not able to attract the most experienced or capable managers, so their ability to assess, monitor and intervene in new venture management is limited.

(Zhang et al, 2004; Eesley, 2009). We hypothesize that government owned funds will deliver lower returns than non-government owned funds for the investments which are exited via an

IPO. 14

Hypothesis 6: Government owned VC firms earn lower returns on their investments than

private VCs.

3 Data

The data is from a combination of hand collection and ChinaVenture. The sample contains

4700 venture-backed companies, with 1250 VC funds (of which, we can obtain performance data for 465). The dataset is cross-sectional, with each observation representing a separate company.

The companies are from mainland China, Hong Kong, and Taiwan. The results are robust to excluding Hong Kong and Taiwan from the sample. The companies receive their first investment from 1988 to 2011. 820 of those companies are exited through either an IPO or a takeover. 691 companies are exited via an IPO, 307 of which are in a non-mainland market.7 We also obtain data on various company-level and GP (fund manager) factors that might influence exit- outcomes and fund-performance. Many of these are designed to control for factors including investment risk, and the quality of the fund/company, thereby helping to mitigate concerns that any government-ownership/performance relationship might merely reflect some other unobserved factor.

We hand collect data on the government ownership of the fund manager and whether the fund manager is wholly or partially owned by the central government or by a provincial government. Each fund manager can be wholly or partially government-owned at the provincial or central level. A fund manager can be partially owned at both the provincial and central level.

7 The number of observations in each model depends on the required controls, including whether the model includes region and year fixed effects. 15

A company can be backed by any combination of funds whose managers are wholly or partially government owned at the central or provincial level (or both). In the data, few fund managers are government owned at both the central and provincial level. Few companies are backed by both centrally owned and provincially owned VCs. Subsequently, we do not separately analyze the interaction effect of having ownership at both the central and provincial level (as opposed to having backing from a fund owned at one of the two levels).

We collect data on economic policy uncertainty from the Economic Policy Uncertainty group.8 They compute an uncertainty index for most major countries, including China (Baker et al., 2013).9 These measures of uncertainty have featured in recent literature (see e.g. Pastor and

Veronesi, 2013). We use the political uncertainty measure within the context of a Cox hazard model, in which the time variable is the time between first investment and the earlier of when the exit occurs or 2012 (the last year for which we have exits). In these models, we measure policy uncertainty during the terminal year to capture the impact of policy uncertainty on exits.

We also collect fund-level data on factors that might influence the investment-success and the nature of the exit. For each company, we identify whether there VC investment at any investment-round, the average number of exits the GP has previously been engaged in, the natural log of the average capital under management (in USD) across all GPs, the fund is a PE or

8 The data is available from: http://www.policyuncertainty.com/index.html 9 They state that they compute the index as follows “First, we identify SCMP articles about economic uncertainty pertaining to China by flagging all articles that contain at least one term from each of the China EU term sets: {China, Chinese} and {economy, economic} and {uncertain, uncertainty}. Second, we identify the subset of the China EU articles that also discuss policy matters. For this purpose, we require an article to satisfy the following text filter: {policy OR spending OR budget OR political OR "interest rates" OR reform} AND {government OR Beijing OR authorities}} OR tax OR regulation OR regulatory OR "central bank" OR "People's Bank of China" OR PBOC OR deficit OR WTO. We use this compound filter because it outperforms simpler alternatives in our audit study. Third, we apply these requirements in an automated search over every SCMP article published since 1995. This automated search yields a monthly frequency count of SCMP articles about policy-related economic uncertainty. Fourth, we divide the monthly frequency count by the number of all SCMP articles in the same month. We then normalize the resulting series to a mean value of 100 from January 1995 to December 2011 by applying a multiplicative factor.”: http://www.policyuncertainty.com/china_monthly.html 16

VC fund, the number of investment rounds, and the average number of prior investments that the

GPs have made. In order to analyze fund-level performance, we collect data on the exit multiple earned on every IPO exit from ChinaVenture; this data is only available for IPO exits and not for

M&A exits. We also calculate each fund’s success rate (i.e., proportion of successful exited investments).

The summary statistics are in Table 1. Panel A contains summary statistics for the variables that are used in the company-level analysis of whether the company is successfully exited. These are based on the 4700 companies that receive venture backing. Panel B presents summary statistics for the variables that are used in the fund -level analysis of performance. This sample contains 465 VC funds (for which we have performance data).10 Of the funds for which we have the requisite data, around 9.4% are wholly government owned and 11% are partially government owned.

[Insert Table 1 About Here]

4 Analysis

This section contains the multivariate regression analysis. We start by analyzing whether government owned VCs increase the likelihood of a successful exit (within a Cox hazard model framework). Next, we look at the impact of being backed by a VC owned by the company’s provincial government. We then examine whether government-owned VCs increase the ability to list via an IPO, especially in a mainland market. Thereafter, we test the idea that even if

10 While our 4650 companies are backed by around 1250 VC funds, performance data is not available for all funds and not all funds invested prior to 2005, which we impose as the cut-off for inclusion in order to allow the fund at least seven years to exit the investment 17 government-owned VCs might increase the likelihood of a successful exit, they might perform worse due to inefficiencies associated with government ownership. Finally, we include several additional robustness tests.

4.1 Does government ownership in funds enhance the likelihood of venture

success?

We first analyze the impact of government ownership of venture success. We analyze a company-level cross-sectional sample of 4,700 VC-backed venture companies. In order to account for the time required to exit a company, and to avoid unfairly penalizing investments in the recent past, we use a Cox proportional hazard model (as in Humphery-Jenner and Suchard,

2013). We define the time variable as the time (in years) between the date the company first receives venture backing and the time it is exited (if the company is exited), or 2012 (if the company is not exited). 11 The end-condition is an indicator that equals one if the company is successful exited and equals zero otherwise. Because the model explicitly accounts for the time between the investment and present time, the model does not penalize companies who received their first investment recently and are not yet exited.

The results are in Table 2. Because we are using a Cox hazard model, the regression sample contains 4,650 observations. Columns 1-3 examine the government-ownership variables in isolation. Columns 4-6 control for other factors that might influence venture success. In all cases, backing by a partially government-owned GP increases venture success (usually statistically significantly). However, backing by a wholly government-owned GP reduces

11 The government shut down the IPO market in October 2012, thus blocking the most common exit mechanism for VC backed firms 18 venture success. These results highlight that a partially government-owned GP can convey benefits in the form of government connections. However, for a wholly government-owned GP, the disbenefits in terms of government-directed investments, can undermine venture success.

These results are consistent with the documented evidence in industrial-companies that complete government control can lead to inefficiencies (Wu et al., 2012a, 2012b; Ma et al., 2013), which might off-set the benefits that government connections might otherwise yield.

The signs on the control variables are largely consistent with expectations. Overseas GPs are negatively related to venture success. This is consistent with prior evidence on the difficulties monitoring portfolio companies at a distance (Humphery-Jenner and Suchard, 2013; Lutz et al.,

2013). The prior success of the companies backed, as proxied by Ave Num Exits, is positively related to venture success. This is consistent with prior evidence on performance persistence in venture capital and private equity (Phalippou, 2010). Companies who receive more rounds of funding are more likely to be successfully exited, potentially suggesting that there can be some benefits to staging venture investments. The number of GPs involved in the portfolio company is positively related to venture success, implying that there can be some benefits to the portfolio company of venture syndication. Interestingly, the average number of prior investments done by the GPs is negatively associated with venture success. However, it is important to note that this is after controlling for the number of prior successes the GPs have. Thus, the negative coefficient captures the potential effects of a ‘limited attention’ problem arising from the GPs investing in too many companies simultaneously.

[Insert Table 2 About Here]

4.2 Does government ownership help to mitigate political uncertainty?

We next analyze whether government backing helps to ameliorate the impact of political uncertainty. We expect that partially government owned GPs will be particularly helpful. Fully government owned GPs would represent an increased exposure to the source of political risk.

Partially government owned GPs could increase the firm’s exposure to political risk, but also convey the additional benefit of mixing government connections (from the government ownership) with the private-party’s incentives to ensure a successful exit. We run similar models to those in Section 4.1, namely Cox hazard models in which we include the interaction of the government-backing indicators with measures of political risk in China. The results are in Table

3 and are largely consistent with expectations. The coefficients on the interaction term Partial-

Gov GP x Uncertainty (Final Year) and Partial-Gov GP x Uncertainty (First Year) are positive and significant. By contrast, backing by a wholly government owned GP conveys no such benefit. This implies that backing by a partially government owned GP leads to a slight increase in the likelihood of a successful exit during times of political uncertainty.

[Insert Table 3 About Here]

4.3 Government ownership and market conditions

This section analyzes how backing by a government-owned VC influences the firm’s sensitivity to market-conditions. We expect that government VCs will be less sensitive to market conditions when exiting (as they are less exposed to market-discipline when raising future funds). We capture market conditions by obtaining the return over the exit year (or final year, if

20 the firm is not exited) on the SSE Composite index, or SZ 200 index. We test whether companies backed by government owned VC funds are more likely to be exited (through any method) at times of poor economic conditions than are private VC backed firms. We interact the index- return variables with our government-ownership variables.

The results are in Table 4. The returns on both indexes are positively associated with the likelihood of an exit (consistent with the idea that VC exits are easier to undertake in strong markets). The coefficients on the interaction terms are negative and significant. The coefficients are slightly larger and generally more statistically significant for the Partial-Gov GP interactions.

This implies that government GPs are less sensitive to market conditions when deciding to exit.

This is consistent with the idea that government GPs are not exposed to external market discipline that would arise if they had to go to the market to raise capital for future funds; and thus, are willing to exit in weaker markets.

[Insert Table 4 About Here]

4.4 Government ownership, location and firm performance

We next consider whether the location of the government owner of the VC fund influences venture success. One possibility is that geographic proximity (so backing from a fund with a government owner in the same province as the portfolio company) can reduce issues of information asymmetry and increase venture success (following Lutz et al., 2013). However, a government owned fund might make politically motivated investments within its own province, which might be designed to achieve political ends. These government-directed investments are

21 more likely to be problematic if a greater proportion of the firm’s VC backers are from the company’s province. Subsequently, in addition to examining an indicator for whether the company has a government backer with ownership from the company’s province, we also examine the proportion of backers with government ownership from the company’s province and the quadratic of this term. In the reported results, we do not restrict the sample based on the number of backers that the company has. However, we obtain qualitatively similar results if we restrict the sample to contain only firms who receive funding from more than one fund.

The results are in Table 5 and are consistent with our predictions. Columns 1-8 suggest that being backed by a provincial government owned fund is associated with reduced exit likelihood. However, Columns 9-12 test for a quadratic relationship. The main finding is that having some backers who are owned by the company’s provincial government is beneficial; however, a high proportion of such backers can reduce exit likelihood. This implies that some provincial backing could create monitoring benefits. However, ‘excess’ provincial backing could increase the prospect of government-directed investment in the portfolio company, be associated with the government VC making politically motivated investments (i.e. investing in less profitable companies for political reasons), and worse access to non-provincial markets.

[Insert Table 5 About Here]

We further explore the impact of a GP’s location by examining how the GP’s location (as opposed to the location of a government owner) influences exit likelihoods. To do this, we use data on a GP’s headquarters from ChinaVenture. We obtain the proportion of the portfolio company’s GPs who are headquartered in the company’s province. We then examine the impact

22 of the proportion of funds from the company’s province (split by whether the company is by backed by government owned VC funds). The results are in Table 6. The main finding is that geographic location only impacts companies that are backed by government owned VCs. That is, there is a quadratic relationship between exit likelihood and the proportion of GPs who are from the company’s province. Thus, having at least one local government GP can help with monitoring; however, excess numbers of local government GPs might reduce the company’s access to non-local markets. The results for nongovernment VCs are in contrast to developed markets, where geographic proximity can be beneficial (see e.g., Lutz et al., 2013).12

[Insert Table 6 About Here]

4.5 Do government owned funds increase access to IPO markets, especially in

mainland China?

We next analyze whether companies backed by government-owned VC funds have better access to IPO markets, especially in mainland China. Access to Chinese markets is regulated and involves a merits review process, which has discretionary elements. We expect that political connections will help companies to navigate these discretionary elements. We capture this by running logit models first to estimate the likelihood that a company is exited via IPO (conditional on the company being successfully exited) and second to estimate the likelihood that a company lists in a mainland market (conditional on it being exited via IPO).

12 There is some evidence that VC funds’ geographically distant investments can perform strongly (Chen et al., 2010); however, much of this strong performance is attributable to VC funds that are located in venture hubs, such as San Francisco, New York, and Boston. 23

We start by analyzing whether government-owned GPs increase the likelihood of an exit via IPO (as opposed to via M&A). 820 of our 4,700 companies are successfully exited. The regression sample contains 784 observations, with some observations being dropped due to the inclusion of controls and fixed effects. The results are in Table 7. The sample contains all companies that are successfully exited and the dependent variable is an indicator that equals one if the exit is via IPO (and equals zero otherwise). There is little evidence that government-owned

GPs increase the likelihood of an IPO in general.

[Insert Table 7 About Here]

We next consider more directly the (potential) benefits of government ownership in navigating China’s IPO-process by considering their impact on the likelihood of an IPO in mainland China. In these models, we restrict the sample to the set of firms that undertake an IPO

(in order to examine the location of that IPO). 691 of our companies undertake an IPO. However, since the models include year and region effects, and some regions have few IPOs, the regressions include 652 observations. The results are in Table 8. The results indicate that partially government-owned GPs increase access to the markets in mainland China. However, wholly government-owned GPs do not clearly increase access to mainland-listings (after including control variables in the models). This is an interesting result because it implies that the inefficiencies associated with complete government-ownership more than off-set the potential connection-related benefits that might otherwise concentrate in wholly government-owned GPs.

[Insert Table 8 About Here]

4.6 Do government-owned funds perform better?

We expect that government owned funds will perform relatively worse than private funds.

While government ownership, and the attendant political connections, can convey advantages for a fund’s portfolio companies, we expect such funds to perform worse in general. Government owned enterprises tend to perform worse than private enterprises, often being inefficient and subject to government intervention. We measure the fund’s performance by obtaining the average exit multiple on the fund’s investments and by computing the fund’s success rate. The exit multiples are obtained by using the company’s post money valuation (multiplied by the fund’s stake in the company) in addition to the amount invested in the company. We define the fund’s success rate in two ways. First, we divide the number of successful exits it has made by the number of investments it has made (irrespective of when those investments were made).

Second, we account for the possibility that recent investments have not yet been exited by dividing the number of successful exits by the sum of the number of exited investments and the number of unexited investments made prior to 2005 (we focus only on investments from 2005 or before so as to allow seven years for the portfolio company to be exited).

The results are in Table 9. All models are tobit models, with a lower bound of zero, and an upper bound of one when examining the success rate. The main finding is that there is weak evidence government owned VCs tend to generate worse performance, as proxied by the GP’s average exit multiple; however, the poor performance seems to concentrate in wholly owned

GPs. Further, both partially government-owned and wholly government-owned GPs exhibit worse success rates (using either of the success rate variables). This implies that even if government ownership might convey some benefits in terms of improving the portfolio 25 company’s success rate, this does not translate into improved performance at the fund level. It would appear that while backing from government owned VCs can help a company to achieve a successful exit, government GPs are generally worse at choosing portfolio companies (hence why government GPs improve the likelihood that a company is exited, but have an overall lower success rate at the fund level).

[Insert Table 9 About Here]

One possible concern with these results is that they might reflect the relative riskiness of government-owned versus non-government owned VCs. The issue is that government-owned

VCs might invest in less risky companies, resulting in a higher exit-likelihood, but a lower exit- valuation. This is unlikely to be a concern given that riskier investments often do not perform better in the venture space (Murmann and Sardana, 2013). That is, because there is no efficient market for venture investments, there is not always adequate compensation for investing in riskier companies; and thus, any tendency to assume less risk would not per se result in lower returns for government VCs. Nonetheless, in untabulated results, we find consistent results if we split the sample in halves based upon the total amount invested in the portfolio company (and thus, its size and riskiness). We also take steps to mitigate selection issues in Section 4.7.

4.7 Additional robustness tests

We address several types of selection issues. The general concern is that government- owned VCs might simply select companies that are more likely to achieve a successful exit,

26 rather than actually contributing to that successful exit. We address the selection concern in several ways.

First, one concern is that the benefits accruing to government-ownership merely reflect the government VC-funds investing at a later, less risky, stage when an exit is more likely. We address this concern by constructing a company-round sample in which we analyze the round in which government owned VC funds invest. Here, we run tobit models, and negative binomial models, where the dependent variable is the investment-round. We run separate ‘univariate’ models that model the investment-round as a function of government ownership and multivariate models that control for other relevant factors. We report the results for the multivariate models in

Table 10. The main finding is that government-owned funds are significantly more likely to invest in earlier rounds than are non-government-owned funds. This suggests the success of government-owned VC funds is not merely attributable to them investing at a later round in the company’s development.

[Insert Table 10 About Here]

Second, a related issue is that government owned VCs simply cherry pick companies without providing any guidance or influence. We address (in Table 11) this by removing from the sample any company who receives backing from a government-VC after the first round. That is, we only consider situations where the government-VC invests in the company’s first round.

While it is still possible that the government-VC could cherry-pick early-stage companies at the first round, cherry picking is less likely for this sample. Relatedly, we also find that where the

27 company is successfully exited, the government backed VC funds tend to invest at least two years prior to the exit.

[Insert Table 11 About Here]

Third, an additional concern is that the results might reflect systemic differences in the stage

(i.e. start-up, development, expansion, or late-stage) of the portfolio companies in which government funds invest. We address this by splitting the sample into the four types of investment-stage in our sample and analyzing whether the results hold for each stage. These results are unreported for brevity. However, we obtain qualitatively similar results across all investment stages. The impact of government-backed VC funds on exit-success is higher in development and expansion stage companies than in late stage companies or early stage companies.

5 Conclusion

This paper examines the impact of government ownership on the performance of VC funds and their portfolio companies in the world’s largest emerging economy, China. We distinguish between VC funds that are wholly government owned and those that are partially government owned. Partially government owned (though not wholly government owned) VC funds increase the likelihood of a successful exit, especially via an IPO in the Chinese mainland.

This result suggests that government ownership can help firms to navigate the discretionary nature of financial market regulations in China, but that excessive government control can lead

28 to inefficiencies. Further, government owned funds, especially wholly government owned funds, tend to show poorer performance. This evidence suggests that sole government ownership is associated with inefficiencies at the fund level even if the fund’s connections can benefit some individual portfolio companies.

We next show that better access to information rather than monitoring contributes to value by government in venture capital investment. Investment success increases with the presence of a provincial government owned VC, but the benefit decreases with the number of provincial government owned VCs. This suggests that while the presence of a provincial government backer can convey benefits (i.e., with navigating regulations at the provincial level), the marginal benefit of such connections decreases in the number of provincial government owned backers.

We further find that government owned VCs can convey benefits in the form of navigating political and economic uncertainties. Companies backed by a government owned VC are more likely to achieve an IPO exit during times of high political uncertainty and during periods of worse market performance. This suggests that government VCs are less sensitive to market timing, are more able to achieve an exit in worse market conditions. The result also points towards one reason for government VCs performing worse at the fund level: the ability (or willingness) to exit in less favorable market conditions.

This paper makes a significant contribution to the literature. We provide new evidence on the benefits and disadvantages of government-owned VCs. We highlight that while a degree of government ownership might benefit portfolio companies, wholly government owned VCs tend not to increase venture success. The results indicate that in emerging markets, a degree government ownership can convey value-creating connections; however, complete government

29 control can generate inefficiencies. Our research highlights the importance of institutional and political factors related to VC market in the emerging markets.

References

Baker S, Bloom N, Davis SJ, Wang X (2013) A Measure of Economic Policy Uncertainty for China (Working Paper). University of Chicago. Berkman H, Cole RA, Fu LJ (2010) Political Connections and Minority-Shareholder Protection: Evidence from Securities-Market Regulation in China. Journal of Financial and Quantitative Analysis 45(6): 1391–1417. Bottazzi L, Da Rin M, Hellmann T (2008) Who are the active investors? Evidence from venture capital. Journal of Financial Economics 89: 488–512. Bottazzi L, Da Rin M, Hellmann T (2009) What is the role of legal systems in financial intermediation? Theory and evidence. Journal of Financial Intermediation 18(4): 559– 598. Cai W (2011) The Mandatory Bid Rule in China. European Business Organization Law Review 12(4): 653–680. Chen CJP, Li Z, Su X, Sun Z (2011) Rent-seeking incentives, corporate political connections, and the control structure of private firms: Chinese evidence. Journal of Corporate Finance 17(2): 229–243. Chen CR, Luo D, Zhang T (2012a) Too Much Connection Can Harm Your Health: An Analysis of Political Connections and Firm Value (Working Paper). Chen D, Guan Y, Zhang T, Zhao G (2012b) Political connection of financial intermediaries: evidence from China IPO market (Working Paper). City University of Hong Kong. Chen H, Gompers PA, Kovner A, Lerner J (2010) Buy Local? The Geography of Successful Venture Capital Expansion. Journal of Urban Economics 67(1): 90–102. Chen Y, Liu M, Su J (2013a) Greasing the Wheels of Bank Lending: Evidence from Private Firms in China. Journal of Banking and Finance 37(7): 2533–2545. Chen Y, Wang SS, Li W, Tong WHS (2013b) Institutional Environment, Firm Ownership and IPO First-Day Returns: Evidence from China (Working Paper). Hong Kong Polytechnic University. Eesley CE (2009) Entrepreneurship and China: History of Policy Reforms and Institutional Development (Working Paper No. 7-10-2009). Stanford. Faccio M (2006) Politically Connected Firms. American Economic Review 96(1): 369–386. Francis BB, Hasan I, Sun X (2009) Political connections and the process of going public: Evidence from China. Journal of International Money and Finance 28(4): 696–719. Gompers P, Lerner J (1999) An analysis of compensation in the U.S. venture capital partnership. Journal of Financial Economics 51(1): 3–44. He X, Su Y (2013) Do the “Haves” Come Out Ahead in Shanghai Courts?. Journal of Empirical Legal Studies 10(1): 120–145. Hochberg YV, Ljungqvist A, Lu Y (2007) Whom You Know Matters: Venture Capital Networks and Investment Performance. Journal of Finance 62(1): 251–302. Hochberg YV, Ljungqvist A, Lu Y (2010) Networking as a Barrier to Entry and the Competitive Supply of Venture Capital. Journal of Finance 65(3): 829–859. Huang H (2005) China’s Takeover Law: A Comparative Analysis and Proposals for Reform. Delaware Journal of Corporate Law 30: 145–198. Huang H (2007) The Statutory Derivative Action in China: Critical Analysis and Recommendations for Reform. Berkeley Business Law Journal 42(1): 227–250.

Huang H (2008) The New Takeover Regulation in China: Evolution and Enhancement. International Lawyer 42(1): 153–175. Huang H (2010) Institutional Structure of Financial Regulation in China: Lessons from the Global Financial Crisis. Journal of Corporate Law Studies 10(1): 219–254. Huang RH (2011) The Regulation of Securities Offerings in China: Reconsidering the Merit Review Element in Light of the Global Financial Crisis. Hong Kong Law Journal 41(1): 261–284. Humphery-Jenner ML (2012) The Governance and Performance of Chinese Companies Listed Abroad: An Analysis of China’s Merits Review Approach to Overseas Listings. Journal of Corporate Law Studies 12(2): 333–365. Humphery-Jenner M, Suchard J-A (2013) Foreign VCs and Venture Success: Evidence from China. Journal of Corporate Finance 21(1): 16–35. Li G (2013) Political Connections and Access to IPO Markets in China (Working Paper). Central University of Finance and Economics. Li H, Meng L, Wang Q, Zhou L-A (2008) Political connections, financing and firm performance: Evidence from Chinese private firms. Journal of Development Economics 87(2): 283– 299. Lin L (2013) Private equity limited partnerships in china: A critical evaluation of active limited partners. Journal of Corporate Law Studies 13(1): 185–217. Liu Q, Tang J, Tian GG (2013) Does political capital create value in the IPO market? Evidence from China. Journal of Corporate Finance 23: 395–413. Li Y, Liu LX, Zhang Z (2012) Pre-IPO private equity investors and their impact on the IPO process under China’s compliance system (Working Paper). Lutz E, Bender M, Achleitner A-K, Kaserer C (2013) Importance of spatial proximity between venture capital investors and investees in Germany. Journal of Business Research 66(11): 2346–2354. Ma L, Ma S, Tian G (Forthcoming) Political connections, founder-managers, and their impact on tunneling in China’s listed firms. Pacific-Basin Finance Journal. Ma X, Tong TW, Fitza M (2013) How much does subnational region matter to foreign subsidiary performance? Evidence from Fortune Global 500 Corporations’ investment in China. Journal of International Business Studies 44(1): 66–87. Murmann JP, Sardana D (2013) Successful entrepreneurs minimize risk. Australian Journal of Management 38(1): 191–215. Pastor L, Veronesi P (2013) Political Uncertainty and Risk Premia. Journal of Financial Economics 110(3): 520–545. Phalippou L (2010) Venture capital funds: Flow-performance relationship and performance persistence. Journal of Banking and Finance 34(3): 568–577. Ragozzino R, Reuer JJ (2011) Geographic distance and corporate acquisitions: signals from IPO firms. Strategic Management Journal 32(8): 876–894. Da Rin M, di Giacomo M, Sembenelli A (2010) Corporate taxation and the size of new firms: Evidence from Europe. Journal of the European Economic Association 8(2-3): 606–616. Da Rin M, Nicodano G, Sembenelli A (2006) Public policy and the creation of active venture capital markets. Journal of Public Economics 90(8-9): 1699–1723. Sapienza HJ, Manigart S, Vermeir W (1996) Venture capitalist governance and value added in four countries. Journal of Business Venturing 11(6): 439–469.

Tomasic R, Zhang Z (2012) From Global Convergence in China’s Enterprise Bankruptcy Law 2006 to Divergent Implementation: Corporate Reorganisation in China. Journal of Corporate Law Studies 12(2): 295–332. Wei D (2013) Antitrust in China: An Overview of Recent Implementation of Anti-Monopoly Law. European Business Organization Law Review 14(1): 119–139. Wu J, Cheng ML (2011) The impact of managerial political connections and quality on government subsidies: Evidence from Chinese listed firms. Chinese Management Studies 5(2): 207–226. Wu W, Wu C, Rui OM (2012a) Ownership and the Value of Political Connections: Evidence from China. European Financial Management 18(4): 695–729. Wu W, Wu C, Zhou C, Wu J (2012b) Political connections, tax benefits and firm performance: Evidence from China. Journal of Accounting and Public Policy 31(3): 277–300. Xu G, Zhou T, Zeng B, Shi J (2013) Directors’ Duties in China. European Business Organization Law Review 14(1): 57–95. Zheng Y, Zhu Y (2013) Bank lending incentives and firm investment decisions in China. Journal of Multinational Financial Management 23(3): 146–165. Zhou W (2013) Political connections and entrepreneurial investment: Evidence from China’s transition economy. Journal of Business Venturing 28(2): 299–315.

Appendix: Variable Definitions

Variable Definition Wholly Gov GP An indicator that equals one if at least one if the GPs that backs the company is wholly owned by the government (either at the provincial level or at the central level) Partial Gov GP An indicator that equals one if at least one if the GPs that backs the company is partially owned by the government (either at the provincial level or at the central level) Overseas GP An indicator that equals one if at least one GP derives its capital from purely overseas sources Domestic GP An indicator that equals one if at least one GP derives its capital from purely domestic sources Venture Round An indicator that equals one if the company has at least one investment round that is classified as ‘start-up’ or venture. The four rounds in the data are ‘start-up’, development, expansion, and late. Ave Num Exits The average number of prior exits that the GPs have done. ln(Ave GP Cap Under Management USDm) The natural log of the average capital under management for the GPs. PE GP An indicator that equals one if at least one GP is in private equity (but not in venture capital) VC GP An indicator that equals one if at least one GP is in venture capital (but not in private equity) Num GPs The number of GPs invested in the portfolio company. Num Rounds The number of investment rounds that the company has. Ave GP Num Prior Investments The average number of prior investments that the GPs have made.

Tables

Table 1: Univariate statistics This table contains univariate statistics. Panel A contains the statistics for the companies in the sample. Panel B contains the statistics for the GPs in the sample. Sample All Wholly Gov GP Partial Gov GP Company Level Partial Gov GP 0.195 0.137 1.000 Wholly Gov GP 0.156 1.000 0.109 Overseas GP 0.369 0.146 0.156 Venture Round 0.724 0.765 0.723 Ave Num Exits 10.097 6.543 19.082 ln(Ave GP Cap Under Management USDm) 5.270 4.456 5.835 PE GP 0.303 0.339 0.354 VC GP 0.586 0.717 0.723 Num Rounds 1.357 1.454 1.471 Ave GP Num Prior Investments 21.401 14.462 35.221 Num GPs 1.656 1.973 2.055 Fund level Average Multiple 0.942 0.796 0.864 Success Rate 0.552 0.464 0.483 Success Rate (Pre 2005) 0.812 0.738 0.809 Wholly Gov GP 0.094 1.000 0.000 Partial Gov GP 0.116 0.000 1.000 Num Port Cos 11.809 12.136 14.907 Num Regions 4.116 2.909 4.352 ln(Capital Under Management) 3.206 3.000 3.347 Portfolio Spread 2.216 3.204 1.571

Table 2: Cox Hazard Models This table contains Cox proportional hazard models that analyze the likelihood of a company being exited (via M&A or IPO). The time-variable is the either (a) the time between first-investment and exit if the company is exited, or (b) the time between first-investment and 2012 if the company is not exited. The figures are coefficients (not hazard ratios). A positive coefficient on a variable indicates that a particular variable increases the likelihood of a company being exited. Brackets contain p-values and superscripts ***, **, and * denote significance at 1%, 5%, and 10%, respectively. [1] [2] [3] [4] [5] [6]

Partial-Gov GP 0.570*** 0.570*** 0.185* 0.153 [0.000] [0.000] [0.051] [0.111] Wholly-Gov GP -0.056 -0.005 -0.254** -0.228** [0.564] [0.961] [0.018] [0.036] Overseas GP -0.289*** -0.382*** -0.339*** [0.003] [0.000] [0.001] Venture Round -0.173* -0.195* -0.177* [0.100] [0.062] [0.091] Ave Num Exits 0.024*** 0.025*** 0.023*** [0.000] [0.000] [0.000] ln(Ave GP Cap Under Management USDm) -0.002 -0.001 -0.003 [0.909] [0.950] [0.867] PE GP 0.611*** 0.642*** 0.624*** [0.000] [0.000] [0.000] VC GP 0.244** 0.291*** 0.262** [0.018] [0.004] [0.011] Num Rounds 0.188*** 0.196*** 0.191*** [0.000] [0.000] [0.000] Ave GP Num Prior Investments -0.022*** -0.022*** -0.022*** [0.000] [0.000] [0.000] Num GPs 0.119*** 0.139*** 0.132*** [0.000] [0.000] [0.000] Year Fixed Effects Yes Yes Yes Yes Yes Yes Region Fixed Effects Yes Yes Yes Yes Yes Yes Observations 4,650 4,650 4,650 4,645 4,645 4,645 Likelihood Ratio Chi2 46.49 0.34 46.50 522.24 524.30 526.80

Table 3: Impact of political uncertainty This table analyzes the relationship between political uncertainty, government backing, and the likelihood of a successful exit. The models are Cox hazard models. The time-variable is the either (a) the time between first- investment and exit if the company is exited, or (b) the time between first-investment and 2012 if the company is not exited. The figures are coefficients (not hazard ratios). A positive coefficient on a variable indicates that a particular variable increases the likelihood of a company being exited. Brackets contain p-values and superscripts ***, **, and * denote significance at 1%, 5%, and 10%, respectively.

VARIABLES [1] [2] [3] [4] [5] [6] Partial-Gov GP -1.871* -1.865* -3.212*** -3.248*** [0.083] [0.084] [0.000] [0.000] Wholly-Gov GP 0.928 0.859 -0.238 -0.402 [0.495] [0.525] [0.832] [0.720] Log Uncertainty (First Year) -4.464** -4.345** -4.433** [0.017] [0.020] [0.018] Partial-Gov GP x Log Uncertainty (First Year) 0.445* 0.436* [0.056] [0.061] Wholly-Gov GP x Log Uncertainty (First Year) -0.257 -0.236 [0.382] [0.419] Log Uncertainty (Final Year) -5.452*** -5.295*** -5.476*** [0.000] [0.000] [0.000] Partial-Gov GP x Log Uncertainty (Final Year) 0.681*** 0.690*** [0.000] [0.000] Wholly-Gov GP x Log Uncertainty (Final Year) 0.055 0.096 [0.806] [0.670] Overseas GP -0.289*** -0.382*** -0.338*** 0.184* 0.151 0.202* [0.003] [0.000] [0.001] [0.065] [0.127] [0.050] Venture Round -0.168 -0.193* -0.174* 0.038 0.014 0.040 [0.110] [0.064] [0.098] [0.728] [0.894] [0.717] Ave Num Exits 0.025*** 0.026*** 0.024*** 0.010** 0.011** 0.011** [0.000] [0.000] [0.000] [0.025] [0.016] [0.023] ln(Ave GP Cap Under Management USDm) -0.001 -0.000 -0.002 -0.023 -0.022 -0.023 [0.931] [0.983] [0.883] [0.165] [0.183] [0.166] PE GP 0.608*** 0.635*** 0.619*** 0.268*** 0.283*** 0.265*** [0.000] [0.000] [0.000] [0.005] [0.003] [0.005] VC GP 0.242** 0.283*** 0.256** -0.012 0.011 -0.015 [0.019] [0.005] [0.013] [0.912] [0.913] [0.885] Num Rounds 0.190*** 0.194*** 0.192*** -0.002 0.006 -0.003 [0.000] [0.000] [0.000] [0.975] [0.912] [0.954] Ave GP Num Prior Investments -0.023*** -0.023*** -0.023*** -0.009*** -0.008** -0.009*** [0.000] [0.000] [0.000] [0.006] [0.012] [0.006] Num GPs 0.119*** 0.142*** 0.133*** -0.009 -0.013 -0.012 [0.000] [0.000] [0.000] [0.788] [0.687] [0.712] Year Fixed Effects Yes Yes Yes Yes Yes Yes Region Fixed Effects Yes Yes Yes Yes Yes Yes Observations 4,625 4,625 4,625 4,645 4,645 4,645 Likelihood Ratio Chi2 510.05 509.62 515.43 2572.24 2557.93 2572.84

Table 4: Government funds and sensitivity to market conditions This table contains Cox Hazard models that examine the sensitivity of government-owned GPs to IPO market conditions. The focus is on whether the government-owned GPs are more willing to exit in a market-downturn. The marked-index returns are measured as at the time of the exit (if applicable) or in the final year (2012, for unexited investments). The figures are coefficients (not hazard ratios). A positive coefficient on a variable indicates that a particular variable increases the likelihood of a company being exited. Brackets contain p-values and superscripts ***, **, and * denote significance at 1%, 5%, and 10%, respectively. [1] [2] [3] [4] [5] [6] Partial-Gov GP 0.303*** 0.275*** 0.303*** 0.274** [0.002] [0.006] [0.004] [0.010] Wholly-Gov GP -0.169 -0.143 -0.143 -0.127 [0.129] [0.206] [0.222] [0.285] SSE Composite Return 2.071*** 1.766*** 2.136*** [0.000] [0.000] [0.000] Partial-Gov GP x SSE Composite Return -1.229*** -1.188*** [0.000] [0.000] Wholly-Gov GP x SSE Composite Return -0.625* -0.537 [0.083] [0.124] SZ200 Return 2.075*** 1.926*** 2.103*** [0.000] [0.000] [0.000] Partial-Gov GP x SZ200 Return -0.689*** -0.642*** [0.000] [0.000] Wholly-Gov GP x SZ200 Return -0.405** -0.299 [0.044] [0.135] Overseas GP -0.322*** -0.409*** -0.362*** -0.382*** -0.439*** -0.415*** [0.001] [0.000] [0.000] [0.000] [0.000] [0.000] Venture Round -0.206* -0.255** -0.221** -0.246** -0.307*** -0.261** [0.050] [0.015] [0.036] [0.022] [0.004] [0.015] Ave Num Exits 0.023*** 0.022*** 0.022*** 0.021*** 0.020*** 0.020*** [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] ln(Ave GP Cap Under Management USDm) -0.002 0.001 -0.002 -0.008 -0.005 -0.008 [0.890] [0.971] [0.888] [0.618] [0.771] [0.620] PE GP 0.564*** 0.599*** 0.565*** 0.498*** 0.533*** 0.502*** [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] VC GP 0.267*** 0.319*** 0.286*** 0.285*** 0.355*** 0.305*** [0.009] [0.002] [0.006] [0.007] [0.001] [0.004] Num Rounds 0.171*** 0.189*** 0.176*** 0.166*** 0.180*** 0.170*** [0.001] [0.000] [0.001] [0.002] [0.001] [0.001] Ave GP Num Prior Investments -0.021*** -0.020*** -0.021*** -0.019*** -0.018*** -0.019*** [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] Num GPs 0.121*** 0.129*** 0.132*** 0.123*** 0.127*** 0.135*** [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] Year Fixed Effects Yes Yes Yes Yes Yes Yes Region Fixed Effects Yes Yes Yes Yes Yes Yes Observations 4,645 4,645 4,645 4,608 4,608 4,608 Likelihood Ratio Chi2 668.86 651.69 674.80 1016.12 1001.81 1021.71

Table 5: Government backers in the same province

This table contains Cox hazard models that examine the impact of being backed by a VC fund whose government ownership is from the same province as the portfolio company. Here, the main variables of interest are ‘Any GP from same prov’ (an indicator that equals one if the portfolio company is backed by at least one GP with ownership from that company’s province’, and ‘Prop GP from same prov’ (the proportion of the company’s GP backers who have ownership from the same province as the portfolio company. The figures are coefficients (not hazard ratios) and a positive coefficient indicates an increased likelihood of a successful exit. Brackets contain p-values and superscripts ***, **, and * denote significance at 1%, 5%, and 10%, respectively. Cox Hazard Model [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] ANY Gov-GP from same prov -0.401*** -0.221* -0.474*** -0.247* [0.002] [0.088] [0.000] [0.073] Prop Gov-GPs from same prov -0.629*** -0.410** -0.766*** -0.499*** 0.922 1.551** 0.886 1.673** [0.000] [0.015] [0.000] [0.005] [0.203] [0.035] [0.226] [0.025] Squared Prop Gov-GPs from same prov -1.697** -2.135*** -1.800** -2.348*** [0.030] [0.007] [0.022] [0.003] Overseas GP -0.341*** -0.259** -0.294*** -0.206* -0.353*** -0.273*** -0.305*** -0.219** -0.342*** -0.260** -0.297*** -0.208* [0.001] [0.013] [0.006] [0.054] [0.001] [0.009] [0.004] [0.040] [0.001] [0.012] [0.005] [0.051] Domestic GP 0.253*** 0.234** 0.210** 0.207** 0.249** 0.236** 0.211** 0.214** 0.237** 0.224** 0.200** 0.205** [0.010] [0.017] [0.036] [0.040] [0.010] [0.015] [0.034] [0.032] [0.015] [0.021] [0.044] [0.041] Venture Round -0.255** -0.226** -0.202* -0.189* -0.253** -0.224** -0.196* -0.185* -0.257** -0.227** -0.202* -0.189* [0.011] [0.024] [0.055] [0.069] [0.012] [0.026] [0.062] [0.075] [0.011] [0.024] [0.054] [0.070] Ave Num Exits 0.015*** 0.027*** 0.013*** 0.024*** 0.015*** 0.026*** 0.012*** 0.023*** 0.015*** 0.027*** 0.012*** 0.024*** [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.001] [0.000] [0.000] [0.000] [0.001] [0.000] ln(Ave GP Cap Under Management USDm) 0.009 0.015 0.009 0.015 0.006 0.014 0.006 0.013 0.003 0.010 0.002 0.009 [0.581] [0.336] [0.591] [0.339] [0.685] [0.378] [0.721] [0.401] [0.835] [0.515] [0.884] [0.558] PE GP 0.845*** 0.745*** 0.812*** 0.718*** 0.829*** 0.737*** 0.792*** 0.708*** 0.810*** 0.713*** 0.776*** 0.687*** [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] VC GP 0.419*** 0.366*** 0.428*** 0.368*** 0.410*** 0.362*** 0.416*** 0.362*** 0.392*** 0.338*** 0.400*** 0.340*** [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.001] [0.000] [0.001] Num Rounds 0.211*** 0.266*** 0.225*** 0.282*** 0.204*** 0.260*** 0.218*** 0.277*** 0.194*** 0.250*** 0.209*** 0.265*** [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] Ave GP Num Prior Investments -0.011*** -0.022*** -0.011*** -0.022*** -0.011*** -0.022*** -0.011*** -0.021*** -0.011*** -0.022*** -0.011*** -0.021*** [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] Year Fixed Effects No Yes No Yes No Yes No Yes No Yes No Yes Region Fixed Effects No No Yes Yes No No Yes Yes No No Yes Yes Observations 4,650 4,650 4,645 4,645 4,650 4,650 4,645 4,645 4,650 4,650 4,645 4,645 Likelihood Ratio Chi2 233.26 415.98 319.12 506.95 238.51 419.32 327.46 512.12 242.95 426.08 332.40 520.13

Table 6: GP location

This table contains Cox hazard models that examine the impact of being backed by a GP located in the same province as the portfolio company. Here, the main variable of interest is ‘Proportion GPs from Co's prov, which is the proportion of the company’s GP backers who located in the same province as the portfolio company. The figures are coefficients (not hazard ratios) and a positive coefficient indicates an increased likelihood of a successful exit. Brackets contain p-values and superscripts ***, **, and * denote significance at 1%, 5%, and 10%, respectively. Sample Full sample No Gov GP At least one Gov GP [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] Proportion GPs from Co's prov 1.243*** 1.389*** 1.305*** 1.423*** -0.052 0.048 0.390 0.434 2.010*** 2.158*** 1.884*** 2.002*** [0.005] [0.002] [0.004] [0.002] [0.944] [0.948] [0.606] [0.561] [0.001] [0.000] [0.002] [0.001] Squared proportion GPs from Co's prov -1.958*** -2.025*** -2.026*** -2.066*** -0.526 -0.612 -0.995 -1.019 -2.735*** -2.881*** -2.605*** -2.721*** [0.000] [0.000] [0.000] [0.000] [0.504] [0.434] [0.209] [0.195] [0.000] [0.000] [0.000] [0.000] Overseas GP -0.442*** -0.367*** -0.387*** -0.304*** -0.169 -0.129 -0.123 -0.083 -0.724*** -0.546*** -0.633*** -0.438** [0.000] [0.000] [0.000] [0.004] [0.217] [0.355] [0.379] [0.559] [0.000] [0.002] [0.000] [0.018] Domestic GP 0.231** 0.222** 0.193* 0.201** 0.420*** 0.452*** 0.360*** 0.398*** -0.033 -0.076 0.091 0.007 [0.018] [0.022] [0.055] [0.046] [0.001] [0.001] [0.007] [0.003] [0.846] [0.660] [0.619] [0.968] Venture Round -0.231** -0.198** -0.190* -0.169 -0.058 -0.132 0.012 -0.070 -0.484*** -0.286* -0.495*** -0.295* [0.022] [0.049] [0.069] [0.105] [0.658] [0.313] [0.928] [0.612] [0.003] [0.093] [0.003] [0.090] Ave Num Exits 0.015*** 0.028*** 0.013*** 0.025*** 0.015*** 0.038*** 0.016** 0.036*** 0.017*** 0.025*** 0.014*** 0.021*** [0.000] [0.000] [0.000] [0.000] [0.009] [0.000] [0.010] [0.000] [0.000] [0.000] [0.007] [0.000] ln(Ave GP Cap Under Management USDm) -0.003 0.004 -0.003 0.004 -0.015 -0.004 -0.013 -0.003 0.022 0.026 0.018 0.020 [0.843] [0.771] [0.834] [0.784] [0.439] [0.819] [0.486] [0.858] [0.444] [0.365] [0.564] [0.497] PE GP 0.758*** 0.662*** 0.737*** 0.637*** 0.772*** 0.747*** 0.742*** 0.718*** 0.730*** 0.500*** 0.722*** 0.460*** [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.001] [0.000] [0.003] VC GP 0.393*** 0.335*** 0.406*** 0.339*** 0.461*** 0.491*** 0.523*** 0.525*** 0.171 0.164 0.165 0.154 [0.000] [0.001] [0.000] [0.001] [0.000] [0.000] [0.000] [0.000] [0.301] [0.329] [0.339] [0.375] Num Rounds 0.171*** 0.230*** 0.180*** 0.245*** 0.155** 0.190*** 0.186*** 0.230*** 0.188*** 0.242*** 0.212*** 0.269*** [0.000] [0.000] [0.000] [0.000] [0.012] [0.002] [0.003] [0.000] [0.002] [0.000] [0.001] [0.000] Ave GP Num Prior Investments -0.012*** -0.023*** -0.011*** -0.023*** -0.008** -0.021*** -0.008** -0.020*** -0.014*** -0.027*** -0.013*** -0.026*** [0.000] [0.000] [0.000] [0.000] [0.024] [0.000] [0.021] [0.000] [0.000] [0.000] [0.001] [0.000] Year Fixed Effects No Yes No Yes No Yes No Yes No Yes No Yes Region Fixed Effects No No Yes Yes No No Yes Yes No No Yes Yes Observations 4,650 4,650 4,645 4,645 3,114 3,114 3,110 3,110 1,536 1,536 1,535 1,535 Likelihood Ratio Chi2 269.77 453.04 352.64 544.05 111.33 213.54 183.88 283.58 172.26 259.63 211.49 306.54

Table 7: Logit models predicting the likelihood of an IPO This table contains logit models that estimate the likelihood that a company is exited via an IPO (as opposed to a takeover) conditional on the company being exited. The sample is cross-sectional and contains only companies that are successful exited. The models contain year dummies. Brackets contain p-values and superscripts ***, **, and * denote significance at 1%, 5%, and 10%, respectively. [1] [2] [3] [4] [5] [6] Partial-Gov GP 0.471* 0.492* -0.038 -0.028 [0.079] [0.068] [0.902] [0.930] Wholly-Gov GP 0.468 0.498 0.089 0.084 [0.146] [0.124] [0.804] [0.816] Overseas GP -0.629** -0.600** -0.609** [0.026] [0.029] [0.038] Venture Round 0.417 0.426 0.423 [0.190] [0.181] [0.185] Ave Num Exits 0.043** 0.043** 0.043** [0.012] [0.012] [0.012] ln(Ave GP Cap Under Management USDm) 0.041 0.042 0.042 [0.350] [0.344] [0.342] PE GP -0.020 -0.018 -0.016 [0.947] [0.952] [0.958] VC GP -0.010 -0.015 -0.012 [0.974] [0.963] [0.970] Num Rounds 0.251 0.248 0.248 [0.138] [0.142] [0.142] Ave GP Num Prior Investments -0.033*** -0.033*** -0.033*** [0.000] [0.000] [0.000] Num GPs 0.285** 0.278** 0.280** [0.024] [0.027] [0.028] Constant 1.611 1.645 1.658 2.195 2.200 2.196 [0.239] [0.228] [0.225] [0.145] [0.144] [0.145] Year Fixed Effects Yes Yes Yes Yes Yes Yes Region Fixed Effects Yes Yes Yes Yes Yes Yes Observations 784 784 784 784 784 784 Pseudo R-squared 0.12 0.11 0.12 0.18 0.18 0.18 Likelihood Ratio Chi2 80.67 79.70 83.21 122.84 122.89 122.89

Table 8: Logit models predicting whether a company issues shares in the mainland This table contains logit models that estimate the likelihood that a company does an IPO in a mainland market, conditional on the company being exited via an IPO. The models contain year dummies. Brackets contain p- values and superscripts ***, **, and * denote significance at 1%, 5%, and 10%, respectively. [1] [2] [3] [4] [5] [6] Partial-Gov GP 0.937*** 0.974*** 1.057*** 1.130*** [0.000] [0.000] [0.001] [0.001] Wholly-Gov GP 0.785*** 0.851*** 0.331 0.520 [0.003] [0.002] [0.340] [0.147] Overseas GP -2.925*** -3.123*** -2.819*** [0.000] [0.000] [0.000] Venture Round -0.053 -0.153 -0.014 [0.886] [0.673] [0.969] Ave Num Exits -0.015 0.002 -0.014 [0.341] [0.889] [0.364] ln(Ave GP Cap Under Management USDm) -0.093* -0.074 -0.087* [0.076] [0.157] [0.099] PE GP 0.271 0.337 0.267 [0.376] [0.265] [0.383] VC GP 0.240 0.324 0.215 [0.475] [0.330] [0.522] Num Rounds -0.010 0.012 -0.027 [0.951] [0.943] [0.872] Ave GP Num Prior Investments -0.009 -0.013 -0.010 [0.417] [0.231] [0.385] Num GPs -0.159 -0.087 -0.202* [0.145] [0.414] [0.078] Constant -0.489 -0.407 -0.644 0.223 0.223 0.129 [0.280] [0.359] [0.160] [0.722] [0.718] [0.838] Year Fixed Effects Yes Yes Yes Yes Yes Yes Region Fixed Effects Yes Yes Yes Yes Yes Yes Observations 652 652 652 652 652 652 Pseudo R-squared 0.21 0.19 0.22 0.44 0.43 0.45 Likelihood Ratio Chi2 182.58 172.10 192.80 395.03 384.75 397.19

Table 9: GP performance This table contains models that examine the drivers of GP performance. The dependent variable in Columns 1-3 is the average exit multiple achieved across all portfolio companies that have been successfully IPOed by one of the GPs funds. The exit multiples are winsirozed at 1%. The models are tobit models with a lower bound of zero and. Brackets contain p-values and superscripts ***, **, and * denote significance at 1%, 5%, and 10%, respectively.

Dependent Variable Average Multiple Success Rate Success Rate (Pre 2005) [1] [2] [3]

Wholly-Gov GP -0.143* -0.201*** -0.224** [0.062] [0.001] [0.013] Partial-Gov GP -0.096 -0.139** -0.048 [0.266] [0.011] [0.585] Num Port Cos -0.004*** 0.000 -0.003 [0.006] [0.881] [0.200] Num Regions 0.025** -0.034*** -0.021** [0.011] [0.000] [0.024] ln(Capital Under Management) -0.010 -0.047*** -0.052*** [0.375] [0.000] [0.000] Portfolio Spread 0.000 -0.015*** -0.014** [0.898] [0.008] [0.013] Constant 0.941*** 0.980*** 1.430*** [0.000] [0.000] [0.000] Observations 465 465 465 Pseudo R-squared 0.01 0.28 0.19

Table 10: Looking at investment round This table contains models that examine the determinants of the investment round. The dependent variable is the round of investment. The data is a the deal level (c.f. the company level). In this sample, a GP can make multiple investments in multiple rounds. Thus, the sample is not a company/GP panel. Columns 1-7 contain tobit models with a lower bound of zero and columns 8-14 contain negative binomial models. Brackets contain p-values and superscripts ***, **, and * denote significance at 1%, 5%, and 10%, respectively. Tobit Negative Binomial [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] Wholly Gov -0.242*** -0.268*** -0.203*** -0.230*** -0.242*** -0.268*** -0.149*** -0.167*** [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] Partial Gov -0.161*** -0.190*** -0.152*** -0.180*** -0.161*** -0.190*** -0.107*** -0.125*** [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] ln(GP's Num Prior Investments) -0.116*** -0.116*** -0.107*** -0.077*** -0.077*** -0.071*** [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] ln(GP's Amt Prior Investments USDm) 0.038*** 0.039*** 0.037*** 0.026*** 0.026*** 0.025*** [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] ln(GP Capital Under Management USDm) 0.015*** 0.018*** 0.015*** 0.010*** 0.012*** 0.010*** [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] PE -0.082*** -0.081*** -0.065** -0.056*** -0.056*** -0.044** [0.003] [0.003] [0.017] [0.003] [0.003] [0.017] VC 0.018 0.019 0.034 0.013 0.013 0.023 [0.424] [0.387] [0.122] [0.398] [0.381] [0.122] Constant 1.502*** 1.499*** 1.528*** 1.396*** 1.375*** 1.398*** 1.502*** 1.499*** 1.528*** 0.333*** 0.319*** 0.335*** [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] Observations 8,900 8,900 8,900 8,896 8,896 8,896 8,900 8,900 8,900 8,896 8,896 8,896 Pseudo R-squared 0.003 0.002 0.005 0.009 0.008 0.011 0.003 0.002 0.005 0.004 0.004 0.005

Table 11: Sample where government invests in first round This table contains Cox hazard models that restrict the sample to exclude any government-backed companies who do not receive government backing in the first round. That is, the company is in the sample only if it is either not government backed or is government backed and receives investment in the first round. The figures are coefficients (not hazard ratios). Brackets contain p-values and superscripts ***, **, and * denote significance at 1%, 5%, and 10%, respectively.

[1] [2] [3] [4] [5] [6]

Partial-Gov GP 0.383*** 0.378*** 0.134 0.117 [0.000] [0.000] [0.234] [0.301] Wholly-Gov GP -0.143 -0.125 -0.225* -0.214* [0.207] [0.272] [0.078] [0.095] Overseas GP -0.244** -0.324*** -0.293*** [0.021] [0.002] [0.007] Venture Round -0.175 -0.193* -0.182 [0.123] [0.087] [0.108] Ave Num Exits 0.024*** 0.024*** 0.023*** [0.000] [0.000] [0.000] ln(Ave GP Cap Under Management USDm) -0.006 -0.005 -0.006 [0.735] [0.765] [0.721] PE GP 0.614*** 0.627*** 0.618*** [0.000] [0.000] [0.000] VC GP 0.226** 0.257** 0.238** [0.044] [0.020] [0.034] Num Rounds 0.248*** 0.250*** 0.250*** [0.000] [0.000] [0.000] Ave GP Num Prior Investments -0.023*** -0.023*** -0.022*** [0.000] [0.000] [0.000] Num GPs 0.114*** 0.126*** 0.122*** [0.002] [0.001] [0.001] Year Fixed Effects Yes Yes Yes Yes Yes Yes Region Fixed Effects Yes Yes Yes Yes Yes Yes Observations 4,336 4,336 4,336 4,331 4,331 4,331 Likelihood Ratio Chi2 14.88 1.65 16.12 437.40 439.22 440.28