Weaknesses and strengths of GVCs with international evidence
Cumming et al. (2017) summarise three weaknesses of GVCs as follows when explaining why GVCs are expected to perform worse than PVCs.
Firstly, GVCs are established by statute instead of negotiation among contracting parties. Contacts between the limited partners (who provide funding resources but do not participate in the management of VC funds) and the general partners (who manage VC funds) help to mitigate the agency problems in funds management and facilitate the maximisation of returns7. However, GVCs do not have effective governance under the statute designed by governments and, therefore, fail to provide efficient performance. Cumming & MacIntosh (2007) explore the establishment of Canadian Labour-Sponsored Investment Funds and provide the evidence.
Secondly, the compensation scheme of GVCs is less efficient than that of PVCs. The former rely on base salary and bonuses, while the latter are motivated by management fees plus carried interests8 that are directly related to investment performance. As a result, GVCs face greater problems in the retention of talent.
Thirdly, interference by government officials leads to less independence for GVCs in decision-making. The political pressure and other non-financial goals distort the GVCs’ ability to invest in the most promising projects regardless of the locations or stages.
Cumming & MacIntosh (2007) provide evidence of this in Canada, and Sunley et al. (2005) find similar features in UK and Germany.
Cumming et al.(2017) point out that GVCs do have strengths from having better access to government contracts and being able to help their portfolio companies to obtain faster regulatory approval when needed. The GVCs’ network with government-related suppliers and customers can also benefit their investees.
Performances of GVCs and PVCs with international evidence
A large body of literature documents the underperformance of GVCs compared to PVCs in getting successful exits, providing value-added activities and bringing social benefits.
Successful exits rate through IPO/M&A
One of the most common metrics for evaluating the performance of VC firms is to look at the success rate of exiting from their portfolio companies. Cumming et al. (2017) show that enterprises financed by GVCs underperformed those backed by PVCs on the likelihood of achieving IPO and M&A in European countries. Brander et al. (2008) find a similar result for VC investments in Canada.
Value-added activities of GVCs in their portfolio companies
Compared to PVCs, GVCs are reported to be less effective in providing value-added activities to their investees. GVCs are reported to be less active in helping their investees to recruit managers and to raise funds (Bottazzi et al., 2008), and are less valuable in helping their portfolio companies to change management teams, find board members, or find acquirers in a trade sale (Luukkonen et al., 2013). Firms backed by a sole GVC achieved slower growth in sales (Grilli & Murtinu, 2014b) and productivity (Alperovych et al., 2015).
Social benefits brought by GVCs
Since GVCs have multiple goals besides generating financial returns, it is meaningful to look at the performance of GVCs in promoting innovation and boosting employment. Bertoni Tykvová(2015) find GVC-backed companies underperform those backed by PVCs in innovation measured by patents applications and citations. When measured by employment creation, Standaert & Manigart (2018) find GVCs are less effective than PVCs in promoting the growth of employment for SMEs.
Other researchers investigate the overall effect of GVCs on the whole VC industry and obtain mixed findings. Cumming & MacIntosh (2006) find a “crowding out” effect of GVCs on PVCs in Canada. In contrast, Guerini & Quas (2016) find that the GVC funding in the first round in a portfolio company increases the likelihood that the company will receive PVC investment in later rounds. They argue that GVCs provide the signal to PVCs that the investees are perceived as being able to obtain privileged support from the government, so more PVCs are encouraged to invest.
The endogeneity problem is one of the biggest challenges in the VC literature. The match between portfolio companies and VC firms is never randomly determined. If different VCs intentionally choose different companies to invest in, then the regression results based on the direct comparison of different investees would be biased.
Researchers apply several methods for mitigating the concern of potential endogeneity problems. The first method—propensity score matching—is to ensure that the comparison is only within investees with similar observable characteristics. Dai et al. (2012) include the investment stage, industry and country-level control variables to calculate the likelihood (the propensity score) of being backed by a certain VC type for each portfolio company, and then compare the likelihood of achieving IPO/M&A for each subgroup of companies with the nearest propensity scores. A similar method is also employed by many other researchers, for example, Faccio & Hsu (2017), Cumming et al.(2017) and Guerini & Quas (2016).
Another effective method is to find a proper instrument variable that is related to the likelihood of being backed by a certain type of VC firm while not being directly related to the performance of the portfolio companies. Brander et al. (2015) use the percentage of investments participated in by governmental sponsored VC firms in a country in a given year as the instrumental variable of whether a specific investment is backed by governmental sponsored VC firms. In comparison, Cumming et al.(2017) use a bundle of instrumental variables 9 that capture the characteristics of VC firms on an industry-level or a country-level.
Furthermore, some researchers augment the utilisation of instrumental variables by applying the Heckman two-step procedure to take into account endogeneous selection. The inverse Mills ratio is calculated in the first stage regression and is inserted into the second stage regression (the main regression) as an additional regressor. Examples can be found in Chemmanur et al.(2011) and X. Tian (2012).
Syndication between GVCs and PVCs
Reasons for syndication
Much of the extant literature discusses syndication among venture capital firms. Jääskeläinen (2012) provides a comprehensive literature review on the motivations for VC syndication. The main motivations include enjoying better resources in screening and nurturing portfolio companies, diversifying risk across investments, building up the network with other VCs firms and better managing inter-VC relationships. Jääskeläinen calls for more research on the contingency of syndication, i.e. how the characteristics of VC firms affect their syndication strategies and performances.
Reasons for mixed syndication
In addition to the general benefits of syndication, researchers find mixed syndication particularly appealing. According to Cumming et al. (2017), mixed syndication between GVCs and PVCs can offset the shortcomings of GVCs. They argue that because PVCs and GVCs are substitutable for choosing and growing entrepreneurial firms, PVCs in mixed syndication can mitigate the agency problems caused by the inefficient compensation terms and the political pressure on GVCs. Furthermore, mixed syndication can still enjoy the favourable policies and networking from GVCs.
Cost of mixed syndication
To syndicate with other VC firms, the venture capitalists need to balance the costs and benefits of syndication between different VC firms (Verwaal et al., 2010). The size of VCs matters when taking into consideration the cost of syndication. Large VCs enjoy scale advantages by setting up a decision-making system through repetitive and specialised routines. At the same time, large VCs may find it is harder to adjust their decisions on coordination with other VCs. As a result, larger VCs have less motivation to syndicate with others.
The cost of syndication does not only increase with the size of VC firms; it also increases when the syndicate partners are more diversified. Du (2016) argues that co-investing with similar VCs reduces transaction costs due to less information asymmetry among syndication partners. In contrast, syndication between VCs with different characteristics is expected to have higher coordination costs.
Performance of mixed syndication
Empirical research on the performance of mixed syndication supports the favourable views on mixed syndication. Brander et al. (2015) found that mixed syndication between GVCs and PVCs leads to higher successful exit through IPO/M&A than pure GVCs or pure PVC investments, using data on 25 countries, including China. However, they compare investment by mixed syndication with both investments by a sole PVC (or a sole GVC) and those by syndication among PVCs (or syndication among GVCs). When they control for the number of investors and the total amount of investments, the outperformance of mixed syndication disappears.
Cumming et al. (2017) improve the analysis and control for the number of VC firms that have invested in the portfolio companies by the end of each year (i.e. including all VC firms no matter which rounds of financing they have been involved in with the portfolio company). They use data on seven European countries and find no significant difference between the likelihood of achieving IPO or M&A for companies backed by mixed syndication and those backed by pure PVCs, although the magnitude of the coefficient for mixed syndication is larger than that of pure PVCs investments.
Bertoni & Tykvová(2015) use patents granted and patent citations to measure the impact of mixed syndication on young biotech firms in Europe and find that mixed syndication outperforms pure PVC syndication, suggesting that GVCs serve as an effective complement to PVCs.
However, some researchers find that the positive impact of mixed syndication only occurs under certain conditions. Syndicated investments involving both GVC and PVC are found to have a positive and statistically significant impact on the firms’ growth rate, as long as the syndicate is led by PVCs (Grilli & Murtinu, 2014a). Du (2016) provides evidence that the heterogeneity in types among VC firms (private VCs, bank-affiliated VCs, corporate VCs, governmental VCs and angels) in a syndicate leads to a lower likelihood of exit through IPOs or M&A for their portfolio companies.
Similar to the literature on the performance of different types of VC firms, research on VC syndication also seeks to control for potential endogeneity issues. For example, X. Tian (2012) uses the industry concentration index of the lead VC firm in a syndicate as the instrumental variable for being backed by syndication rather than a sole VC firm. He finds that the more diversified a lead VC’s portfolio companies are in different industries, the stronger the lead VC’s need to form a syndicate with other peers in a new investment.
VC firms in China
There is a paucity of literature on the VC industry in China. Due to the unavailability of financial data on private companies in China, most research limits the samples to firms that have successfully got listed on the domestic stock exchanges—the main boards in Shanghai and Shenzhen, SME board and ChiNext. Beladi et al. (2017) document that VC firms in China were concentrated in pre-IPO investment and had very limited influence on the sales growth of their investees. They had also given very little help to improve the corporate governance of their portfolio companies. Q.Wang et al. (2017) find that VC-backed companies have more independent directors on boards compared to non-VC-backed companies, although the number of independent directors has an insignificant impact on firm performance.
Most researches on the impact of GVCs and PVCs in China also limit their samples to listed companies. Yu et al. (2014) use a sample of listed firms on the SME board and ChiNext to investigate the investment behaviour of GVCs compared to PVCs. They find that GVCs are less likely to undertake early-stage investment. However, the reason may lie in the fact that the early-stage investments by GVCs are less likely to achieve an IPO and, therefore, are not included in their sample of listed companies. Q. Wang et al.(2018) use a similar sample of companies listed on SME board and ChiNext. They find that companies backed by GVCs are more likely to manage their earnings to improve short-term performance around IPOs. However, they do not control for the characteristics of VC firms that may affect the VC firms’ earning management, for example, the reputation or experience of VCs.
Because the financial return on VC investment is exempt from disclosure, it is hard to measure the return performance of GVCs compared to PVCs. To deal with this limitation, Qian & Zhang (2007) hand collected the data for the financial returns on 56 successful exits from portfolio companies between 1999 and 2003 and found that portfolio companies backed by GVCs have a lower annual return rate than those backed by PVCs. However, they fail to take into consideration the impact of investment stage on return. The relatively smaller sample size and the short period of the sample coverage make it hard to generalise from their findings.
All the fore-mentioned research focuses on portfolio companies that have successful exits and therefore, provide only part of the picture in measuring the performance of GVCs and PVCs. They ignore the performance of those portfolio companies that have not achieved successful exit. One exception is Ke & Wang (2017) who use all the portfolio companies backed by VC firms in China as the sample. They define GVCs as VC firms with more than 50% of the funds raised within the first three months since establishment coming from government agencies or government-controlled business enterprises. They find that portfolio companies backed by GVCs are less likely to achieve a successful exit through IPO, M&A or secondary sales and are likely to have a smaller amount of patent application. Furthermore, they find that the GVCs fully financed by the government underperform those GVCs with a small proportion of funding resourced from private entities.
Summary of Chapter 3
This chapter reviews the literature on the weaknesses and strengths of GVCs, GVCs’ performance compared to PVCs on a variety of measures, GVCs’ syndication with PVCs, and the empirical findings of GVCs in China. I also throw light on how researchers deal with the typical endogeneity problem in the field of VC studies. The literature review provides the foundation for the three topics I am going to discuss in Chapter 4, Chapter 5 and Chapter 6.
Table of Contents
1.1. Chapter Four—the performance of governmental venture capital firms: a life cycle perspective and evidence from China
1.2. Chapter Five—Gain or pain? New evidence on mixed syndication between governmental and private venture capital firms in China
1.3. Chapter Six—Improving the performance of governmental venture capital firms: a case study of Shenzhen Capital Group
1.4. Main contributions
2. Institutional background
2.1. Definition of GVCs
2.2. Four stages of the regulatory and exit environment of the Chinese VC industry
2.3. Unique features of GVCs in China
2.4. Summary of Chapter 2
3. Literature review
3.1. Weaknesses and strengths of GVCs with international evidence
3.2. Performances of GVCs and PVCs with international evidence
3.3. Syndication between GVCs and PVCs
3.4. VC firms in China
3.5. Summary of Chapter 3
4. The performance of governmental venture capital firms: a life cycle perspective and evidence from China
4.2. Comparison of GVCs and PVCs in a VC life cycle
4.3. Methods and data
4.4. Regressions results
4.5. Endogeneity problems
4.6. Robustness check
5. Gain or pain? New evidence on mixed syndication between governmental and private venture capital firms in China
5.2. Related literature, institutional background and hypotheses
5.3. Model and data
5.4. Empirical results
5.5. Endogeneity and robustness tests
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Governmental Venture Capital Firms in China: performance and interaction with private peers