The effect of Corporate Venture Capital-backing on a venture’s post-IPO performance

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Master Thesis

The effect of Corporate Venture Capital-backing on a venture’s

post-IPO performance

University of Amsterdam

Faculty of Economics and Business Author: M.E.M. Brooijmans Supervisor: Dr. J.E. Ligterink

Msc Finance

Track: Corporate Finance Student Number: 11157186 Date: June 30, 2018

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2 Statement of Originality

This document is written by Student Michael Brooijmans who declares to take full responsibility for the contents of this document.

I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it.

The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.

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3

Introduction

New ventures generally depend on external investors’ capital and resources in order to exploit entrepreneurial opportunities (Stinchcombe 1965). Financial resources are often crucial for the survival and development of these young ventures, as they are used to acquire value-creating resources (e.g. Barney, 1986). New ventures rely a lot on Venture Capital (VC), specifically, for financing (Gorman and Sahlman, 1989; Sahlman, 1990; Gompers and Lerner, 2004). Different from traditional forms of financing, VCs can create and appropriate value for themselves in uncertain environments (Amit et al., 1998; Baum and Silverman, 2004; Kaplan and Strömberg, 2001). VCs create value through their screening, monitoring, and decision-support functions. VCs tend to focus their investments on specific industries and new venture development stages, and use their expertise and contacts to assist the new ventures in strategic, financial, and operational activities (Barry 1994, Gordon and Sahlman 1989, Macmillan et al. 1989, and Wright and Robbie 1998). VCs invest in start-ups, often in a syndicate with other VCs, and finally exit their investment preferably by either taking the venture public through an IPO, or by selling the venture to a strategic acquirer. According to Kaplan and Lerner (2010), roughly half of all Initial Public Offerings (IPOs) are VC-backed, while less than 0.25% of companies actually receive VC financing. Gornall and Strebulaev (2015) add to this that previously VC-backed public companies account for roughly 20% of the market capitalization of U.S. public companies. From the success of VC-backed companies can be concluded that VCs are effective at generating value, which is in line with Kaplan and Strömberg (2001) and Gompers and Lerner (2001), who argue that VCs connect entrepreneurs (with no financial resources) with investors (with financial

resources), effectively filling a gap in the market.

Traditionally, new ventures go to Independent Venture Capitalists (IVCs) for capital funding and advice (Gorman and Sahlman 1989, Sahlman, 1990, Gompers and Lerner 2004). IVCs are independent vehicles which have their own resources or are financed through limited partnerships (LPs).However, in the past decade, investments made by Corporate Venture Capitalists (CVC), another specific type of Venture Capitalists, are gaining share in the growing VC industry, as new ventures are looking to supplement IVC capital with more CVC capital. The National Venture Capital Association highlights this in their NVCA Yearbook (2017), stating that 44% of US VC capital raised had CVC

involvement in 2016.

Although previous literature has diverse definitions of CVC, in this research CVC refers to investments made in privately held companies by separate entities funded and managed by an established firm (Gompers and Lerner 1998, Anglin et al. 2017). As CVC is becoming increasingly important in the Venture Capital landscape, since more and more investments are being made by CVCs each year and research on the topic is gaining traction as well, knowledge about how CVC affects

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5 investee performance is becoming more crucial too. Extensive research has already been done on how IVC investments influence a portfolio company’s pre- and post-IPO performances (e.g. Barry et al. 1990, Jain and Kini 1991, Mikkelson 1997, Hellman and Puri 2002, Coakley et al. 2007), yet research on the effects of CVC, when compared to IVC, on post-IPO performance indicators is less complete. There are, however, a number of empirical studies that suggest that value-adding contributions made by CVC-investors to the commercial success of new ventures may be different from IVC-contributions (Gompers & Lerner, 2000a; Kelley & Spinelli, 2001; Maula, 2001; Hellmann, 2002; Maula & Murray,

2002; Maula et al., 2003)

The effect of VC on portfolio firm post-IPO performance is often underestimated, according to The Venture Capital Journal (March 1983). Their report states that most VC realize the largest returns by holding post-IPO equity positions in their portfolio companies, instead of by selling their equity share at IPO. Using empirical evidence, they show that more experienced VCs continue to hold an equity position through the rapid growth phase, after going public, in which the VC maintains board presence and project involvement. Furthermore, Jain and Kini (1995) find in their research that VC-backed IPO firms perform superior, relative to non-VC-VC-backed IPO firms, measured by operating return on assets and operating cashflow deflated by assets. Jain, and Kini (2000) build on their previous research of VC contribution to new ventures and show that VC involvement improves the post-IPO survival rate of firms, where higher research and development expenditures, greater analyst coverage, more prestigious investment banks, and more successful road shows are characteristic for VC-backed firms gone public. Ivanov et al. (2009) conclude from their research that more reputable VCs provide better advisory and monitoring services to their portfolio firms, as well as being able to select better investments in the first place, as they find that highly reputable VCs have a significant positive association with the long-run performance of ventures. Their research also shows that VCs with a better reputation tend to be more actively involved in the post-IPO performance of their portfolio firms. Because continued post-IPO VC-involvement positively influences a new venture’s performance, more reputable VC-investments are likely to benefit new ventures’ long-run performance.

Despite the fact that both types fall under the Venture Capital umbrella, CVCs differ from IVCs in a lot of aspects. These differences give me reason to believe that the resulting effects could possibly also express themselves in the new ventures’ development. Generally, CVCs are different from IVCs in their organizational structure, investment behaviour, and the range of services they provide to their investees (Gompers and Lerner, 2000). Diving a little deeper, CVCs generally pursue new ventures that offer possibilities for synergies between the venture’s innovative capabilities and the corporate parent’s existing operations as well as financial objectives (Dushnitsky and Lenox 2005, Wadhwa and

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6 Kotha 2006). On the other hand, VCs mostly seek more immediate capital gains by means of maximizing the venture’s market value. As a result of these discrepancies, the two types of VCs approach their investments in different ways, where the CVC’s broader goals potentially conflict with their IVC coinvestors’ more narrow goals (e.g. Hellmann 2002, Dushnitsky and Shaver 2009).

Previous literature has already shown, to a certain degree, how these structural differences in investment vehicles impact the ventures they invest in. For instance, Chemmanur et al. (2014) find that CVC-backed ventures are more innovative in terms of their patenting outcome than IVC-backed ventures and that CVC-investors have a greater tolerance for failure than IVC-investors. A higher degree of pre-IPO innovation within a company sets a stronger fundament for company survival, as Jain and Kini (2008) suggest that pre-IPO managerial commitment to R&D spending and the development of diversified product lines contribute to longer post-IPO survival time. CVC-backing also increases the new venture’s likelihood of going public or being acquired, when compared to exclusively VC-backing (e.g. Lerner 2000, Santhanakrishnan 2002). Santhanakrishnan (2002) also finds that CVCs are more likely to provide product market support to new ventures with a strategic fit, which increases the likelihood of a venture’s successful exit. As the new venture enjoys product market support from its CVC parent, from the moment of investment until (at least) the time of IPO, the new venture may have (partially) integrated the product market support it enjoyed into their core business, allowing the new venture to reap the related benefits even after the IPO. Ivanov and Xie (2010) find that CVCs add value to ventures, additional to that of VCs, only when a strategic fit is present between the venture and the corporate parent, where the added value is measured as higher valuations at IPO and higher takeover premiums in the case of an acquisition. As the aforementioned literature shows that investor type has a direct impact on pre-IPO performance, the structure of new ventures and possibly an indirect effect of new ventures’ post-IPO performance, it leads me to believe that these differences may continue to affect the new ventures long-term, post-IPO performance.

This leads to the primary goal of this research, which is to examine the role of CVC in the long-run performance of new ventures gone public. The central question of this research is: “Does CVC-backing affect a venture’s post-IPO performance differently than solely IVC-CVC-backing?”. As Ivanov et al. (2009) state, Post-IPO performance is of general importance to IPO-investors, to VC-investors that hold on to their investee’s stock after the lock-up period, to the respective new ventures seeking VC funding, and to investors who receive IPO shares when their investments go public. To measure a venture’s post IPO-performance, 4 measures are used in accordance with existing literature, which are well-known performance standards (e.g. Gompers et al. 2003, Moeller et al. 2004, Krishnan et al. 2008, Ivanov et al. 2009). The first measure is the industry-adjusted return on assets (ROA). The second measure is the company’s market-to-book ratio. Thirdly, the survival of

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7 the respective company in the long-run. Lastly, long-run abnormal stock returns according to Moeller, Schlingemann, and Stulz (2004), Gompers, Ishii, and Metrick (2003), and Field and Karpoff (2002).

This research contributes to a growing body of literature focussed on explaining the effects of external investors on new venture performance (e.g. Hellmann and Puri 2002, Hsu 2006, Hochberg et al. 2007). To be more precise, this research adds to a developing stream of literature exploring the effects of corporate investors on new ventures (e.g. Katila et al. 2008. Maula et al. 2009, Park and Steensma 2013), by offering new insights into the consequences of CVC on the development of new ventures, for which the number of funding sources keeps growing over time. This research takes the perspective of new ventures and thus contributes to the body of literature concerning corporate governance effects on new ventures. As external investors gain influential rights in new ventures at an early stage in the respective companies’ development, ownership and control over the new ventures get separated early on as well. Following this train of thought, this work also depicts the effects of path dependency of governance structures and how the implemented strategies coincided with these investor dependent governance structures affect new ventures’ performance. My findings quantify the value added by CVCs in the development of new ventures, measured in the long-term, independent performance of the respective ventures.

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Literature Review

As depicted in previous literature, the differences between the impact of IVC- and CVC-funding on new ventures is a topic that is being increasingly explored in recent years. The impact of IVC-funding on new venture pre- and post-IPO performance has already been investigated to a great extent. The impact of CVC-funding on new venture post-IPO performance, however, remains largely undiscovered. Additional to that is that there is no general consensus in the relevant literature, as previous research is both consonant as well as contradictory to each other. When looking at the organizational differences between the two types of investors as well as the differences in impact of both types of funding on pre-IPO performance of their investees, a post-IPO performance difference between both types of investments is potentially existing and awaits to be looked further into. This literature overview will start to explore how IVCs and CVCs differ from each other in the way they operate, followed by a closer look at how VCs in general impact their investees. Next ,I dive deeper into the differences of IVC-funding with CVC-funding on the performance of ventures pre-IPO, followed by a similar analysis for the post-IPO period. To conclude, I shall derive a number of hypotheses based on the combined results described in the previously described sections.

Structural differences between IVCs and CVCs

First of all, despite their similarities in activities, the way IVCs are set up differ largely from the way CVCs are set up. IVCs can be described as investment vehicles funded by large institutions and well-off angel investors (Gorman and Sahlman, 1989; Gompers and Lerner, 2004). CVCs are investment vehicles funded by a corporate parent. According to Gompers and Lerner (2000), CVCs differ from IVCs in organizational structure, objectives, investment behaviour and the services they provide to their venture investees. Therefore, CVCs have to procure the amount they invest with from their corporate parent and makes CVCs investment strategy subject to centralized resource allocation and parent company performance (Rajan, Zingales, and Servaes 2000; Scharfstein and Stein 2000). IVcs, however, have more freedom to allocate their funds once received from their investors and

operate independently from any controlling organizations.

Bluntly stated, the main objective of IVC investors is to realize capital gains by maximizing the market value of their investments and consecutively exiting their investments through an IPO or acquisition (Park and Steensma, 2013). Additionally, to simply capital gains, CVCs also seek to contribute to the overall value of their corporate parent (Dushnitsky, 2006; Hellmann, 2002; Park and Steensma, 2013). This second goal can be achieved in various ways, for instance by supplementing the corporate parent’s internal R&D processes, using investees’ products and innovations to stimulate demand for complementary products provided by the corporate parent (Kann, 2000; Chesbrough,

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9 2002) or even by bundling innovations from all involved parties to develop a robust ecosystem for the

corporate’s technology (Adler and Kapoor, 2010).

Managerial motivation for both types of funds is also stimulated differently as an effect of their organizational structure. IVC managers receive fees based on their fund size and return they obtain (Sahlman, 1990). Positive capital gains from their investments not only increase the respective managers’ compensation, it also acts as a signal for their success. These signals enhance future fundraising efforts and, in turn, increase future manager fees and the quality of ventures they can invest in (Gompers and Lerner, 2004). Thus, a cyclical process arises resulting in increased IVC manager wealth and motivates the managers to achieve the highest possible market value for their investments (Park and Steensma, 2013). The rewards received by CVC fund managers are usually restricted to corporate parent performance and less contingent on fund performance. This is why CVC funds have trouble motivating and retaining employees, according to Gompers and Lerner (2000).

General impact of VCs on pre-IPO venture performance

The effects of general VC-funding on new ventures up to IPO is well documented and conveys a largely positive message in favour of VC-funding. Chemmanur et al. (2011) take a close look at how VCs improve their investees. They state that VCs help firms hire competent management, provide better incentives to new venture management and employees and grant access to their network of contacts among potential suppliers and customers in the market of the new venture’s product or service. Additionally, new ventures receive better screening and monitoring with VC-backing (Chemmanur et al. 2011). VC-backed ventures receive assistance in strategic, financial and operational planning by using the knowledge, expertise and contacts from their VC investors planning (Barry, 1994; Gordon and Sahlman 1989; Macmillan et al., 1989; Wright and Robbie, 1998; Jain & Kini, 2000). Furthermore, Jain and Kini (1995) state that VCs ensure that their investee managers do not indulge in non-value

maximizing activities and minimize the present value of operating costs.

Regarding actual performance of VC-backed ventures, Purie and Zarutskie (2012) find through empirical analysis that VC-backed ventures, when compared to non-VC-backed ventures, have a smaller failure rate, a much higher chance of being acquired and an extremely higher probability of going public through an IPO. Additionally, Nahata (2008) finds that ventures’ time to exit is shorter and their probability of a successful exit (through an IPO or acquisition) is higher for ventures backed by more reputable VCs in terms of IPO capitalization share. Contrarily, Purie and Zarutskie (2010) also find that there are hardly any differences in measures of profitability between matched VC- and non-VC-backed ventures. Chemmanur et al. (2011) bring these findings in doubt with their empirical findings showing that labour productivity, return on assets (ROA) and operating efficiency are higher for VC-backed ventures. Chemmanur et al. (2011) continue their research and find an improvement

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10 in sales is a driving factor behind these improved performance measures. For ventures backed by highly reputable VCs, smaller increases in production costs help drive the venture’s performance as well, positively affecting the probability of a successful exit. Nahata (2008) also shows the importance of VC reputation as the author finds that these ventures have a higher asset productivity by the time they go public. All in all, the impact of VC on venture performance is present and mainly positive, which inspires me to further investigate the differences in this impact between both types of investors based on their significant differences.

Difference s in impact on pre-IPO performance of investees between CVCs and IVCs

IVCs deliver a range of services to their investees that are partially similar, such as aiding in the growth of their portfolio companies, yet partially different from the services delivered by CVCs. According to Warne (1988), IVCs mainly help companies recruit key employees, develop supplier and customer relations, and assist their investees in production and operational processes. Maula et al. (2005) adds that IVCs help raise additional finance and professionalize the venture. CVCs, on the other hand, also assist in setting up customer or supplier relations as well as assist in marketing, sales, distribution agreements and joint research or product development agreement. This helps CVCs’ investees gain quicker access to markets and product recognition (Ivanov and Xie, 2010). Additionally, using their corporate parent’s insider knowledge, CVCs could potentially better position their investee in the market and simultaneously deliver credibility to the investee due to the

corporate’s brand name (Ivanov and Xie, 2010; Maula et al. 2005). Resources provided by CVCs can be specifically tailored to the innovative activities of the investee and create synergies between investor and investee (Park and Steensma, 2013). However, by having an agreement with a corporate parent, a new venture can be constrained from obtaining resources from competitors (Park & Steensma, 2013). Also, a potential conflict of interest could arrive between a new venture and its CVC corporate parent due to similar or even competing products (Hellman, 2002). Thus, a corporate parent can exploit rather than nurture the venture invested in (Chemmanur et al. 2014). As CVCs mainly invest through syndicates with other IVCs, it is also important to understand how both types of investors deliver their services simultaneously. Maula et al. (2005) theorizes that the value added by both types of investors are complementary to each other and therefore, the addition of a CVC in the investing syndicate is beneficial to the new venture. From an investor-goal point of view, the focus of IVCs to realize maximum capital gains can conflict with CVCs broader goals (Hellmann, 2002; Dushnitsky and Shaver, 2009). The degree of influence a separate investor has within a syndicate depends, in part, on its reputation (Park and Steensma, 2013). Thus, a respectively more reputable CVC will be able to impact an investees performance more than a CVC with a lesser relative reputation.

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11 Resulting from the services delivered by both types of investors is the level of innovation within a venture. Chemmanur et al. (2014) find that CVC-backed ventures are more innovative in terms of a higher patenting outcome as well as a higher quality in patents. These results are even more prominent when a strategic fit is present between corporate parent and investee. Again, CVC reputation positively affects the level of innovativeness within the investee (Park and Steensma, 2013). A number of reasons for CVC-backed ventures being more innovative than IVC-backed ventures can be attributed to CVC-funds being more failure tolerant, having a greater industry knowledge, having a longer investment horizon, the lack of performance-based rewards for fund managers and the pursuit of not only financial rewards (Chemmanur et al. 2014; Park and Steensma, 2013).

Artz et al (2010) found empirical evidence for a negative relationship between patens and ROA and sales growth. They lagged R&D spending by three years, patents by two years, and product announcements by one year. Ravenscraft and Scherer (1982), however, found that there was a mean lag of four to six years between R&D investments and profitability. Song et al. (2008) state that innovation is only one of eight factors that enhance performance within a new venture. Rosenbursch et al. (2011) add to this that the importance of innovation is highly context specific. However, Jain & Kini (2008) have proven that pre-IPO managerial commitment to R&D spending and developing product lines improve the ability of ventures that go public to remain viable for longer periods of time. This finding leads me to believe that the impact of CVC-backing could possibly affect the post-IPO performance of a venture.

Regarding the impact of the value added by both types of investors, Ivanov and Xie (2010) find that CVC-backed ventures receive higher valuations at IPO as well as higher takeover premiums if acquired compared to IVC-backed ventures. The likelihood of a successful exit through IPO or acquisition is also higher for CVC-backed ventures compared to IVC-backed ventures. This could imply that the market expects CVC-backed ventures to outperform IVC-backed ventures in the long-run. If the market sentiment is correct and accurate, one expects stock price performances for both types of VC-backed IPOs to be similar. However, if the market is wrong, long-run stock price

performance should differ. This is another question I shall address in my research, as I also look at the post-IPO stock performance of both types of VC-backed IPOs.

Gener al impact of VCs on post-IPO venture operating performance

The impact of general VCs on the post-IPO operating performance of ventures is a widely discussed topic in previous literature, with very diverse findings. Because there is no overall consensus regarding this topic, it offers an opportunity for my research to fill fractioned area in VC literature. Starting with the literature claiming the positive influence of VCs in post-IPO venture operating

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12 performance, Krishnan et al. (2009) associate VC reputation with significant long-run venture performance measures, based on four well-known company performance standards. These performance measures comprise of, first, the industry-adjusted rate of return on assets (ROA), second, the market-to-book ratio (MTB), third, long-run listing survival, and fourth, the long-run abnormal stock returns (Moeller, Schlingemann, andStulz 2004; Gompers, Ishii, and Metrick, 2003; Field and Karpoff, 2002). Following from the pre-IPO performance analyses, more reputable VCs also exhibit more active post-IPO involvement (Krishnan et al. 2009). Thus, Krishnan et al. (2009) conclude that VC involvement has a positive influence on post-IPO firm performance. Jain and Kini (2000) further strengthen the case by finding that VC-backed IPOs exhibit an improved survival profile. The authors find that VC-backed IPOs have a higher probability to survive longer and the conditional probability of it surviving in the future given that it has survived until the present time is higher. They continue their research to find that higher levels of R&D expenditures, greater analyst coverage, more prestigious investment banks, and more successful road shows are at the cause of these positive post-IPO effects. Back in 1995, Jain and Kini (1995) already found empirical evidence for a superior operating performance of VC-backed IPOs and that proxies for the quality of VC involvement have a positive

impact on post-issue operating performance.

The theoretical evidence presented by Ber & Yafeh (2004) did not support any superior post-IPO performance for Israeli VC-backed post-IPOs between 1997 and 2002. The authors used the 36-month stock performance, accounting profitability and asset growth rates in the three years following the IPO as performance measures. Wang et al. (2003) also find empirical evidence for an inferior post-IPO operating performance for VC-backed IPOs.

Differences in impact on post-IPO performance of investees between CVCs and IVCs

All though hardly any research is done on the post-IPO venture performance of CVC-backed IPOs as opposed to their IVC-backed counterparts, Chemmanur et al. (2014) shed some light on the topic, with innovation output as a focal point for their research. The authors find empirical evidence for CVC-backed IPOs being more innovative in their post-IPO period. The measurements used for innovativeness are patenting outcome and spend on R&D. Artz et al. (2010) add to this that product announcements are positively associated with return on assets and sales growth. Furthermore, Chemmanur et al. (2014) continue to find that CVC-backed IPOs are younger and riskier and less profitable in the years immediately after IPO, yet catch up with their IVC-backed counterparts in the years thereafter.

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Hypotheses derivation

As mentioned above, previous literature has shown the differences between CVC-backed ventures and IVC-backed ventures, ranging from structure of the investment vehicle to the performance of the ventures. Not only the range of services and goals differ for both type of investors, CVC-investors can specifically tailor their offered resources to their investees needs. Because many services provided by CVCs to their investees differ from those offered by IVCs, yet both types of investors often operate in syndicates together, it leads me to believe that the value added by CVCs is complementary to that of solely IVCs, which is in accordance with previous literature (Maula et al. 2005). The impact of a single investor in a syndicate has proven to be subject to relative investor reputation (Nahata, 2008), which will impact the effectiveness of a CVC-investor in an investment syndicate. As mentioned in the sections above, previous research has proven the value added by CVC-investors to the innovativeness of their investees, which is even more present when both parties have a strategic fit (Chemmanur et al. 2014). Other research by Jain and Kini (2008) has shown that pre-IPO managerial commitment to R&D spending and developing product lines improve the ability of ventures that go public to remain viable for longer periods of time. Chemmanur et al. (2014) also find that CVC-backed ventures are more innovative in their post-IPO period. This, in turn, can translate into more product announcements which are positively associated with return on assets and sales growth (Artz et al. 2010). Finally, the higher take-over premiums and IPO valuations for CVC-backed ventures indicates the expected extra value held by CVC-backed ventures by the market, which motivates me

to find empirical evidence in favour or against this phenomenon.

Chemmanur et al. (2014) have delivered empirical evidence for the post-IPO ROA performance of CVC-backed ventures and find that these ventures are younger, riskier and less profitable immediately after their IPO than their IVC-backed counterparts, but catch up in profitability

in the years thereafter.

Combining the abovementioned arguments, I hypothesize that CVC-backed IPOs have a superior post-IPO performance measures when compared to their IVC-counterparts. I expect these superior performances to be concentrated around CVC-backed IPOs that have two characteristics, which are a strategic fit with their corporate parent, and a relatively high reputable CVC-investor. I shall use the four well-known performance measures to measure the ventures’ post-IPO performance for each year for a five-year period. These performance measures are ROA, MTB-ratio, long-run listing survival, and long-run abnormal stock returns (Moeller, Schlingemann, andStulz 2004;

Gompers, Ishii, and Metrick, 2003; Krishnan, 2009).

Innovation potentially increases the number of product announcements, which have a positive but lagged effect on ROA and sales growth. Chemmanur et al. (2014) delivered empirical

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14 analysis for a Therefore, I hypothesize that CVC-backed ventures that meet the three previously described circumstances, have a superior long-run (after 3 years) ROA and MTB-ratio performance

when compared to their IVC-counterparts.

As it is shown that CVC-backed IPOs exhibit more innovative activities than their IVC-backed counterparts, and innovativeness is linked to venture continuation, I hypothesize that CVC-backed IPOs remain listed for longer periods of time, when the CVC is relatively highly reputable in the

investment syndicate, than their IVC-backed counterparts.

Lastly, since CVC-backed IPOs receive higher valuations than IVC-backed IPOs, I theorize that the market hints at having incorporated added value by CVCs and thus I hypothesize that the long-run stock performance for CVC-backed IPOs is similar to that of IVC-backed IPOs.

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Methodology

Performance Measures

Following existing literature, I use four well-known performance standards. The four measures used to determine a company’s long-run post-IPO performance are return on assets, market-to-book ratio, survival indicator, and a factor-adjusted abnormal stock return (see, e.g., Moeller et al. (2004), Gompers et al. (2003), Field and Karpoff (2002), and Krishnan et al. (2009)). The first performance measure is return on assets (ROA). Return on assets is calculated by dividing the company’s net income by the book value of total assets. For companies that have gone defunct before the 12th_{quarter after IPO, the end of n}th_{- quarter (n<12) is used, where n is the maximum number of}

quarters for which data is available.

The second performance measure is the market value of equity divided by the book value of equity (M/B). This measure is often used to value a firm’s real options and operates as a good proxy for Tobin’s Q. As for the ROA measure, the nth_{quarter is taken for the companies that have gone}

defunct before the 12-th quarter, where n<12. The results are winsorized at the 1% and 99% levels to

minimize the effects of outliers, as a result of data errors.

The third performance measure is a dummy variable, indicating firms that survive on the NYSE, AMEX, or NASDAQ for three years following their IPOs or firms that have been merged or acquired with 1, and 0 for firms that have gone bankrupts, are defunct of have been liquidated (Survival). This measures a firms long-run financial strength, and is supposed to capture negative consequences of

window dressing, which are attempts to raise IPO investor demand.

Finally, the fourth performance measure is an issuer’s factor-adjusted abnormal stock return (Return). This is measured on a monthly basis, for the 36 months after the company’s IPO. The factors used to adjust return are the three Fama and French (1992) factors and the Carhart (1997) momentum factor. As for the first two performance measures, survivorship is accounted for by using the returns for the 36-month post-IPO period or until delisting, taking the value of whichever comes first. Also, results are winsorized at the 1% and 99% levels.

Empirical Models

Multivariate Panel Regression

The first analytical model I use to test the relationship between CVC-backing and post-IPO performance shall be a multivariate panel regression. The downside of this model is that it neglects any non-random effects causing ventures to receive CVC-backing and assumes. However, I am interested in the results it can provide me due to its the potential explanatory power. I shall look at the yearly post-IPO performance of CVC-backed IPOs with respect to their IVC-backed counterparts

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for a post-IPO period of five years.

To distinguish between the value added by the investor and the impact of the external characteristics on the venture’s post-IPO performance, I control for effects of the IPO and venture characteristics that are outside the control of the venture’s investors. However, because a venture receives VC-backing early on in its lifetime, I can never be completely sure that these control variables are fully outside the investors impact. On the other hand, these observable characteristics are largely incorporated in a VC’s selection procedure (Krishnan et al. 2009) and therefore are less likely to be

attributable to a VC’s advisory and development activities.

Based on the previous literature as discussed in the literature review section, I add the dummy variable CVC for ventures having received CVC-backing, which assumes the value of one for ventures that have received CVC-backing and zero otherwise. Next, to align with my hypotheses, I create two interaction variables to indicate the strategic fit between investee and CVC-investor (CVC*StrategicFit) and the relative reputation of the CVC-investor (Reputation). Strategic fit is calculated by aligning the first two digits of a venture’s SIC code with those of its corporate backer. If these digits overlap, a strategic fit is determined. Relative reputation is calculated by dividing the logarithmic transformation of the number of previous IPOs by the respective CVC-investor by the logarithmic transformation of the number of previous IPOs by the complete investment syndicate. When no investors in the syndicate have any prior IPO experience, I assign the value 0 to the Reputation variable (Park &

Steensma, 2013).

Previous studies have shown the importance of the impact lead underwriter reputation on post-IPO long-term returns (Carteret al., 1998), which is measured using the Carter Manaster (1990) ranking and can be found on Jay Ritter’s website (http://bear.warrington.ufl.edu/ritter/ipodata.htm). The underwriter control variable is a dummy variable and gives IPOs with Carter Manaster underwriter ranks of 7 and above the value of one and zero otherwise. This control variable is named URep. I also account for differences in IPO demand and issuer quality. Thus, I control for first day return, termed

Underpricing (Welch, 1989). I control for issuer market cap, calculated by multiplying the offer price

by the number of post-IPO shares and then taking its logarithmic transformation, termed LnMCap (Brav and Gompers, 1997; Krishnan et al., 2009; Loughran and Ritter, 2004). I also take the issuer’s market-to-book ratio into account, which is an indicator for venture growth opportunities (Brav and Gompers, 1997), termed MTB. Finally, I include industry and year fixed effects into my regression. All these control variables are in accordance with Krishnan et al. (2009), who look at the post-IPO

performance as an effect of VC-reputation.

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17 research, such as offer size and issuer age, because these are a direct result of CVC-backing, as other prior research has proven (Chemmanur et al. 2014).

The multivariate regression formula is:

𝑃 = 𝛽𝑦+ 𝛽𝐼+ 𝛽1𝐶𝑉𝐶 + 𝛽2𝐶𝑉𝐶 ∗ 𝑆𝑡𝑟𝑎𝑡𝑒𝑔𝑖𝑐𝐹𝑖𝑡 + 𝛽3𝐶𝑉𝐶 ∗ 𝛽4𝐶𝑉𝐶 ∗ 𝑅𝑒𝑝𝑢𝑡𝑎𝑡𝑖𝑜𝑛 + 𝛽5𝑈𝑅𝑒𝑝

+ 𝛽6𝑂𝑓𝑓𝑒𝑟𝑃𝑟𝑖𝑐𝑒𝑅𝑒𝑣𝑖𝑠𝑖𝑜𝑛 + 𝛽7𝑈𝑛𝑑𝑒𝑟𝑝𝑟𝑖𝑐𝑖𝑛𝑔 + 𝛽8𝐿𝑛𝑀𝐶𝑎𝑝 + 𝛽9𝑀𝑇𝐵

Additionally, I control for year and industry fixed effects. Thus, 𝛽𝑦 is a vector of year fixed effects and

𝛽𝐼 is the vector of the eight industry fixed effects (Gompers et al., 2006).

Propensity Score Matching

Due to the specific characteristics of CVC-financing, I recognize that obtaining this specific form of financing is not a random process for ventures and depends on the situation and circumstances the venture finds itself in. A venture will, to some extent, proactively select a CVC-investor from the financing opportunities the venture has to its availability. From the other side, CVCs also proactively select ventures to invest in and, in most cases, choose to invest in certain types of ventures. Resulting, CVC-backed IPOs might differ from IVC- and non-VC-backed IPOs, due to these selection effects, rather than due to nurturing by the CVC-investor. To address this case of endogeneity, I use a matching procedure to match CVC-backed IPOs with similar IVC-backed IPOs based on characteristics predicting the likelihood of receiving CVC-backing as opposed to IVC-backing. The matching procedure applied is based on propensity scores proposed by Dehejia and Wahba (1999, 2002) and applied in previous research by Drucker and Puri (2005), Ivanov and Xie (2010) and Villalonga (2004). The advantage of using this method is the ability to control for many observable characteristics, however, as most matching techniques, it neglects unobservable characteristics. The propensity score matching algorithm is based on three consecutive steps. First, I estimate a probit model in which the dependent variable is a dummy variable equal to one for ventures having received CVC-backing and a zero for ventures that have not received CVC-backing. Second, I compute the propensity score that indicates the probability of each venture receiving CVC-backing based on its coefficient estimates, resulting from the probit model. Next, CVC-backed IPOs are paired with IVC-backed IPOs with the closest propensity scores by using the nearest neighbourhood matching procedure. Additionally, to improve correctness of the model, the ventures that are matched together must operate within the same industry based on the first two digits of their SIC code. Finally, the ratios of all four performance measures of the CVC-backed venture to those of the IVC-backed venture are calculated for each year up until 5-year after their IPO or until delisting.

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18 The probit model used in my analysis is:

𝑌 = 𝛽1𝐿𝑜𝑐𝑎𝑡𝑖𝑜𝑛 + 𝛽2𝐸𝑎𝑟𝑙𝑦 𝑆𝑡𝑎𝑔𝑒 + 𝛽3𝐿𝑛𝑉𝐶 + 𝛽4𝐿𝑛𝑆𝑎𝑙𝑒𝑠 + 𝛽5𝐼𝑀𝑇𝐵

+𝛽6𝐸𝐵𝑆𝑎𝑙𝑒𝑠 + 𝛽7𝐶𝑉𝐶𝑆ℎ𝑎𝑟𝑒 + 𝜀

The dependent variable (Y), is the dummy variable indicating if the venture received CVC-backing or not. I control for a number of variables that are linked to receiving CVC-financing in accordance with Ivanov and Xie (2010) their similar probit model. According to Lerner (1995), the location of a venture can improve its chances of receiving VC-backing. This may also translate into geographically determined chances of receiving CVC-backing, for which I create the dummy variable

Location and is equal to one for ventures based in Massachusetts or California. To control for the

possible preference of CVC-investors to invest in ventures that are going through a specific development stage, I create the dummy variable Early Stage, which is equal to one for ventures residing in an early development stage at the time of receiving their first VC-investment. Regarding the relative reputation of each investor within a syndicate, I follow Nahata’s (2008) approach who finds that an investor’s proven record for leading its investees to successful outcomes will create a reputation for itself that depicts a signal of quality. I account for the possibility that CVCs tend to coinvest with IVCs with a high reputation and track record, by measuring the logarithmic transformation of the number of IPOs to the date of investment of the IVC-investor with the most IPOs under its belt with the variable LnVC. To control for a venture’s size, growth potential, and profitability at the time of receiving its first VC-investment, I use proxies for these variables based on their values around the time of the respective venture’s IPO (Ivanov and Xie, 2010). I recognize the bias of this approach by taking future values, however data constraints don’t allow me to gather these data points at the time of initial investment. I take the pre-IPO data to calculate the logarithmic transformation of the venture’s sales to determine size (LnSales), the industry average market-to-book-ratio (IMTB) to determine the venture’s opportunity for growth, and the venture’s EBITDA to sales ratio (EBSales) as a proxy for its profitability. In accordance with Ivanov and Xie (2010), I also estimate the availability of CVC-funding at the time each venture’s initial investment. This variable, CVCShare, is calculated by taking the percentage of CVC-investments in the total number of VC-investments. Finally, I add additional control variables to account for year and industry fixed effects. Since CVC-backed IPOs are now being compared directly to matched IVC-backed IPOs, the ratios for each performance measure indicates whether CVC-backed IPOs outperform their IVC-backed counterparts. If the performance for both types of IPOs is similar, the ratios should be equal to or near one. For an outperformance witnessed by CVC-backed IPOs, the ratios should be significantly greater than one and for and

underperformance vice versa.

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19 evidence related to a strategic fit or the relative reputation of the CVC-investor. To provide these insights, I break up the sample of CVC-backed IPOs separately for both conditions separately as well as for both conditions combined. In aligned with my hypotheses, I expect the ratios for ROA, MTB and

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20

Data & Descriptive Statistics

To increase the understanding of the effect of CVC-investors, I obtain CVC- and VC round-by-round investments from. To gather information on investors, I apply VentureXpert’s Investments database is. The VentureXpert database contains detailed information on funding rounds, such as a venture’s development stage and the identities of the investors. IPOs with unidentified investors are not excluded from the dataset. These IPOs are included based on the assumption that all investors involved in an IPO with a significant (5% or higher) equity stake are identified at IPO, as the venture is from then on publicly listed. Therefore, I make the assumption that unclassified investors can be

regarded as insignificant, with respect to the impact made by VCs.

CVC-funds funded by financial institutions, non-corporate partnerships, multiple corporate parents, foreign parents or unknown parents, are excluded from the dataset. A firm is marked as having received CVC-backing, if it has received backing from at least one CVC investor. Additional information regarding the corporate parent’s industry of operation is manually retrieved from CapitalIQ’s database. The SIC codes will be used to determine whether a strategic fit exists between the

CVC-investor and the investee.

I’ve gathered the required (pre-)IPO venture-level data by merging ThomsonOne’s VentureXpert IPO and Investments Database with its SDC New Issue Database. The VentureXpert IPO database and New Issue database both contain information regarding IPOs and investors and investments. IPOs classified as non-backed by the VentureXpert database, but classified as VC-backed by the SDC database, and vice versa, are double checked with ThomsonOne’s Investments database. The Investments database contains more elaborate information on VC-backed companies, regardless of an IPO and is often complementary to the VentureXpert and SDC databases. I downloaded the dataset with venture and investment information for IPOs between 2000 and 2012 from all three sources. Best efforts, financial institutions, regulated utilities companies, partnerships, reverse LBOs, issues with an offer price below $5, which is in line with literature conventions (Chemmanur et al, 2009; Ivanov and Xie, 2010). Furthermore, only IPOs that issue ordinary common shares are included, thereby excluding unit offerings, closed-end funds, real estate investment trusts (REITs) and American depository receipt (ADRs) (Chemmanur et al, 2009; Ivanov and Xie, 2010). Additionally, ventures not reported in the CRSP database within 6 months after the IPO are all

excluded from the dataset as well.

To get post-IPO data, I access Compustat for balance sheet items and CRSP for stock-related data. Compustat provides balance sheet data for North-American listed companies, which I need to construct post-IPO performance measures. However, Compustat comes with one large limitation as the database has many missing items for stocks that have changed ticker name or are currently not

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21 listed anymore. Originally, I am also interested in the survival distribution of IPO-ventures, however, due to the lack of information regarding currently non-listed ventures, I am forced to remove this

analytical element from my research.

The CRSP database provides me with monthly stock prices, which I use to compute the factor adjusted abnormal stock returns. To do so, I also obtain the four factors to a calculate the abnormal monthly stock returns following Carhart’s four factor model (1997):

𝑅𝑡 = 𝛼 + 𝛽1∗ 𝑅𝑀𝑅𝐹𝑡+ 𝛽2∗ 𝑆𝑀𝐵𝑡+ 𝛽3∗ 𝐻𝑀𝐿𝑡+ 𝛽4∗ 𝑀𝑜𝑚𝑒𝑛𝑡𝑢𝑚𝑡+ 𝜀𝑡

Here, 𝑅𝑡 is the excess return of an asset in month t, 𝑅𝑀𝑅𝐹𝑡 is the value weighted market return minus

the risk-free rate. 𝑆𝑀𝐵𝑡 (Small Minus Big), 𝐻𝑀𝐿𝑡 (High Minus Low) and 𝑀𝑜𝑚𝑒𝑛𝑡𝑢𝑚𝑡 are the returns

on zero-investment factor-proxy portfolios for month t, and account for size, book-to-market and

momentum effects.

After combining the ventures with their respective data, I create summary statistics to get a feel for the data (see table 1).

Table 1) Summary Statistics for IPOs with CVC-backing and IVC-backing

Table 1 shows the summary statistics for the dependent and independent variables used in the panel regression model. All variables are depicted based on the dataset parted by ventures’ type of backing. Both types of venture backing are mutually exclusive from each other.

Summary Statistics CVC vs. IVC

(1) (2) (6) (1) (2) (6)

Variable N Mean SD N Mean SD

Return on Assets 1115 -0.16 0.26 2180 -0.07 0.23

Market-to-Book Ratio 1081 4.80 6.82 2123 0.06 6.37

Abn. Stock Returns 203 0.01 0.08 2220 0.01 0.06

Strategic Fit 1127 0.36 0.48 2220 0.00 0.33

CVC Reputation 1127 0.19 0.25 2220 0.00 0.17

Underwriter Reputation Dummy 1127 0.61 0.49 2220 0.53 0.5

IPO Market Cap 1127 801.57 1541.91 2220 583.82 1086.41

IPO MTB-Ratio 1104 5.94 7.23 2148 0.93 94.68

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22

Table 2) Summary Statistics for IPOs with CVC-backing and IVC-backing

Table 2 shows how the dependent and independent variables vary for CVC-backed IPOs and non-VC-backed IPOs. Together with the sample of IVC-backed IPOs, the data represents the complete dataset of the ventures’ quarterly post IPO data for up to 5 years or until delisted.

The sample consists of 386 IPOs from 2000 to 2011, of which 65 are CVC-backed, 131 are IVC-backed and 190 are non-VC-IVC-backed. Of the 65 CVC-IVC-backed IPOs, 22 are strategic CVC-IVC-backed and 43 are non-strategic CVC-backed. Additionally, of the 65 CVC-backed IPOs, 31 have a prior track record of one or more successful IPO(s), giving them a value for CVC Reputation of higher than zero. The first thing that jumps in the eye is the inferior performance of CVC-backed IPOs when the focus is put on return on assets. Although return on assets is on average negative for all three types of IPOs, CVC-backed IPOs are appearing much worse than that of its counterparts. On the other hand, market-to-book ratio for CVC-backed IPOs appears to be much better than for IVC-backed and non-VC-backed IPOs. Abnormal stock returns remain similar for CVC- and IVC-backed IPOs, which is also the area where non-VC-backed IPOs relatively underperform, based on the first look at the summary statistics.

Table 3) Summary Statistics for CVC-backed IPOs based on investments with strategic fit and relative CVC experience

Table 3 compares dependent and independent panel regression variables for CVC-backed IPOs based on the cases where there is a strategic fit present between venture and investor as well as for CVC-investors with prior investment successes.

Summary Statistics CVC bvs. Non-VC

(1) (2) (6) (1) (2) (6)

Return on Assets 1115 -0.16 0.26 3198 -0.02 0.18

Market-to-Book Ratio 1081 4.80 6.82 3051 2.90 4.86

Abn. Stock Returns 203 0.01 0.08 563 0.00 0.10

Strategic Fit 1127 0.36 0.48 3271 0.00 0

CVC Reputation 1127 0.19 0.25 3271 0.00 0

Underwriter Reputation Dummy 1127 0.61 0.49 3271 0.01 0.08

IPO Market Cap 1127 801.57 1541.91 3271 1338.90 5850.93

IPO MTB-Ratio 1104 5.94 7.23 3174 10.52 88

CVC-backed IPOs Non-VC-backed IPOs

Summary Statistics

Return on Assets 394 -0.15 0.21 548 -0.18 0.28 Market-to-Book Ratio 393 3.46 2.56 524 4.9 7.27 Abn. Stock Return 72 0.02 0.09 93 0.02 0.09

Strategic Fit 402 1 0 556 0.49 0.5

CVC Reputation 402 0.25 0.24 556 0.38 0.23 Underwriter Reputation Dummy 402 0.25 0.24 556 0.63 0.48 IPO Market Cap 402 379.8 339.2 556 623.64 743.76 IPO MTB-Ratio 389 3.19 1.63 543 5.17 5.22

Strategic Fit CVC Reputation CVC-backed IPOs

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23 Table 3 shows, interestingly enough, that CVC-backed IPOs with experienced CVC-investors perform worse than for CVC-investors with no prior experience, when it comes to return on assets. Similar to the comparison of the full sample of CVC-backed IPOs to IVC- and non-VC-backed IPOs, the sample with worse average return on assets enjoys a much higher market-to-book ratio. At first sight, the summary statistics tend towards ambiguous results when related to my hypotheses. For return on assets, my hypotheses predicted a better performance for CVC-backed IPO when compared to its IVC- and non-VC-backed counterparts, especially for CVC-investors that enjoy a strategic fit or have prior experience with leading ventures to the market. However, first results show a tendency for an effect of opposite nature. When it comes to market-to-book ratio, however, first results are in line with my previously derived hypotheses. Factor adjusted abnormal stock returns seem relatively independent of investor type. These results raise interest for further investigation.

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24

Results

I start by analysing the performance measures of CVC- IVC- and non-VC-backed IPOs, based on monthly data up until five years post-IPO or, if n is smaller than 60, until month n of delisting. To evaluate the effect of CVC-backing, I use three main variables: CVC-backing dummy, strategic fit and

relative CVC-investor reputation.

Table 4) Panel regression results based on the three main performance measures ROA, MTB, and Factor adjusted abnormal stock returns

Results of panel regression where return on assets (ROA, market-to-book (MTB) and factor adjusted abnormal stock returns are dependent variables. Year and industry fixed effects are applied to control situational circumstances that effect the dependent variables.

Table 4 presents the main results found when regressing CVC-backing, strategic fit, CVC reputation, underwriter reputation, venture market capitalization at IPO and venture market-to-book ratio at IPO on return on assets, market-to-book ratio and factor adjusted abnormal stock returns for monthly

data over post-IPO period of 60 months or, if earlier, delisting time.

Pre-IPO CVC-backing has a negative effect on return on assets and is statistically significant at the 1% level. This finding, similar to that depicted by the summary statistics, goes directly against my first hypotheses as derived from previous literature. This extent of this negative impact can be explained by numerous reasons. First of all, previous literature has given evidence for the attribution of CVC-backing to venture investing in innovative activities. The investment going into these activities have a lag in return on investment for a number of years. However, due to having received influence early on and explicitly choosing to team up with an innovation-focused investor, a

CVC-Panel Data Regression

Variable (1) (2) (1) (2) (1) (2)

Coefficient Standard Error Coefficient Standard Error Coefficient Standard Error

CVC-backing -0.083*** (0.028) 0.772 (0.758) -0.005 (0.014)

Strategic Fit 0.044 (0.040) -1.822* (1.076) 0.005 (0.019)

CVC Reputation -0.161** (0.075) 2.194 (2.020) 0.026 (0.036)

Underwriter Reputation Dummy 0.004 (0.019) 0.734 (0.500) 0.009 (0.009)

IPO Market Cap 0.000 (0.000) 0.000 (0.000) 0.000*** (0.000)

IPO MTB-Ratio 0.000 (0.000) -0.001 (0.002) 0.000 (0.000)

Year fixed effects Industry fixed effects

N 6402 6187 6426

n 367 362 367

Adjusted R-Squared 0.08 0.075 0.0365

*** p<0.01, ** p<0.05, * p<0.1

Abnormal Stock Returns

Yes Yes Yes Yes Yes Yes

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25 backed venture can have a natural focus on innovative investments. Thus, return on these investments can become cumulative over time, as the returns can be reinvested. Perhaps this effect attributes to a more long-run performance of an IPO. Next, innovation-focused firms may not aim at achieving the highest return on assets, as their assets can be of more valuable nature due to the risk that coincides with innovativeness. Also, to increase chances of success in innovation, CVC-backed firms may tend to spread their investments over a range of activities, for which only a small fraction pay of in the long-run. Surprisingly, a CVC’s relative reputation to its investing syndicate seems to do more harm than good for a CVC-backed venture’s return on assets. Perhaps more experienced CVCs don’t pursue strictly financial goals and focus more on a broader range of value, such as new, innovative products. Their experience may contribute to a more efficient way to achieve this broader goal, thereby sacrificing the venture’s return on assets. As expected, strategic fit has a positive effect on return on

assets yet is statistically insignificant.

CVC-backing has a positive, but statistically insignificant impact on a CVC-backed venture’s post-IPO market-to-book ratio. Resulting from previous literature, I expected the positive effect, however it may not be substantial due to its insignificance. As for return on assets, this may imply that CVC-investors avoid pursuing prominently financial gains. Again, perhaps due to a broader focus, financial gains may be compromised and thus result in different forms of value for investors and stakeholders. However, as I shall discuss later on for factor adjusted abnormal stock returns, the market may have pre-calculated the added value of CVC-investors in an IPOs share price. This possible explanation results from the empirical findings of Chemmanur et al. (2014) supporting higher valuations for CVC-backed IPOs. Furthermore, it is surprising that the coefficient for the CVC-backing indicator variables are exactly the opposite for impact on market-to-book ratio as on return on assets. The impact of CVC-backing on factor adjusted abnormal stock returns is, as expected, small and insignificant. Relating to my hypothesis that the market has incorporated some positive impact of CVC-investors on IPO share price, the difference between CVC-backed factor adjusted abnormal

returns and its IVC- and non-VC counterparts is absent.

Due to the likely case that backing is a non-random event, I estimate the impact of CVC-backing on post IPO-performance by approach the situation with a probit analysis. First of all, I estimate the likeliness of a IPO-firm to have received CVC-backing. Therefore, I look at the pre-investment situational characteristics of ventures to create a robustness check for my earlier panel data results.

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26

Table 5) Shows regression results for the probit regression to determine the likelihood of an IPO-venture to have received CVC-backing.

In line with prior research (Ivanov and Xie, 2010), the independent variables are: Dummy variable indicating if the venture is located in Massachusetts or Califirnia, the logarithmic transformation of the number if previous IPOs by the lead investor (determined by most IPOs under its belt), the logarithmic transformation of the venture’s pre-IPO sales number, dummy variables indicating the venture’s company stage at the time of receiving its first investment, and the venture’s pre-IPO EBITDA/sales amount, market-to-book ratio and the general activity of CVC investors at the time of the venture receiving its first investment.

Most independent variables have a strong, significant impact on the likeliness of a venture received CVC-backing. First of all, if the venture is located in Massachusetts or California, the likeliness of receiving CVC-backing is significantly increased. As expected, CVC-investors invest in ventures with respectively smaller sales returns. The investment stages that are later in the business development cycle than the startup stage all negatively impact the chances of a venture receiving, indicating the

preference of CVC-investors to invest in ventures in the startup stage.

Next, I assign the estimated probabilities to each venture and match CVC-backed ventures to IVC-backed ventures using the nearest neighbour matching principle. Thus, I look at yearly, post-IPO performances to determine the kind of impact CVC-backing has on ventures relative to the post-IPO performance horizon. 2950 189.92 0 0.0508 Probit Estimator

Variable Coefficient Standard Error z P>|z|

Massachusetts / California 0.372*** 0.052 7.230 (0.000)

Lead VC Ln # of Successful IPOs -0.009 0.015 -0.610 (0.544)

Ln pre-IPO Sales -0.260*** 0.066 -3.950 (0.000) Early Stage -0.891*** 0.122 -7.300 (0.000) Expansion Stage -0.261*** 0.066 -3.950 (0.000) Later Stage -0.696*** 0.131 -5.330 (0.000) Other Stage -0.498*** 0.144 -3.450 (0.001) Startup Stage 0.099 0.062 1.600 (0.109) Pre-IPO EBITDA/Sales -0.001 0.001 -1.100 (0.270) Industry Market-to-Book 0.081*** 0.013 6.200 (0.000)

Market CVC activity at IPO -0.363 0.960 -0.380 (0.706)

*** p<0.01, ** p<0.05, * p<0.1

Number of observations

Likelihood of receiving CVC-backing LR chi2 (9) Pseudo R2 Prob > chi2

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27

Table 6) Yearly, post-IPO results for the impact of CVC-backing based on probit regression.

For each year, up until the fifth year of post-IPO performance, the impact of CVC-backing is regressed on post-IPO performance measures.

As previously also proven, the impact of CVC-backing on return on assets remains largely negative. It also remains statistically insignificant until the fourth and fifth post-IPO year. Here the negative impact does become statistically insignificant, possible substantiating the fact that CVC-backed firms and CVC-investors both pursue more innovative goals and tend to focus less on direct capital gains. Looking at the results, a venture’s post-IPO market-to-book ratio seems to be

Neireghst Neighbor Matching Coefficient: CVC / IVC

Coefficient z P>|z| _Observations

1 year post-IPO

ROA -0.015 -0.37 0.715 148

MTB -0.451 -0.46 0.645 148

Abn. Stock Returns -0.013 -0.51 0.613 148

2 year post-IPO

ROA -0.059 -1.18 0.238 143

MTB 0.303 0.22 0.823 143

Abn. Stock Returns -0.003 -0.22 0.826 144

3 year post-IPO

ROA -0.031 -0.65 0.518 145

MTB -0.820 -0.7 0.484 143

Abn. Stock Returns 0.005 0.4 0.693 147

4 year post-IPO

ROA -0.10244 *** -2.69 0.007 131

MTB 0.296 0.17 0.868 131

Abn. Stock Returns 0.022 * 1.78 0.075 133

5 year post-IPO

ROA -0.119 *** -2.58 0.01 122

MTB -0.329 -0.2 0.843 121

Abn. Stock Returns 0.016 1.27 0.203 122

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28 uncorrelated to it having received CVC-backing or not. The coefficient signs switch between positive and negative for each consecutive post-IPO year and are never significant, even at the 10 percent level. Much of the same can be said for CVC-backed IPOs’ factor adjusted abnormal stock returns, which only just become statistically significant for the fourth post-IPO year results. Naturally, observations decrease as the post-IPO year number increases, due to cases of delisting. My results are somewhat line with previous research by Chemmanur et al. (2014), who show that CVC-backed IPOs are less profitable than their IVC-backed counterparts in the years directly after IPO, however, according to my results, the CVC-backed IPOs do not catch up with their IVC-backed counterparts in the years thereafter. Regarding the research claiming complementary services provided by CVC-investors with regard to IVC-investors (Ivanov and Xie, 2010; Maula et al., 2005), my results fails to prove that these possible complementarities result in advantageous financial performance output. One might even go so far to state that the theory of Dushnitsky and Shaver (2009) and Hellmann (2002) are supported, who claim that the broader goals of CVC-investors can conflict with IVC-investors’ more financial goals. Then again, these complementary services might express themselves if other ways than positive performance that mainly benefit the venture’s stockholders.

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29

Conclusion

In this research, I investigate the impact of CVC-backing on post-IPO performance. I look at CVC-backed, IVC-backed and non-VC-backed IPOs in the US between 2000 and 2011. Derived from previous literature, I hypothesize that CVC-backing could have a positive effect on post-IPO return on assets, market-to-book ratio and factor adjusted abnormal stock return. Especially when a strategic fit between the corporate parent and investee is present and for a relatively highly reputable CVC-investor, I expect these hypotheses to be validated. After gathering the required data, I engage in statistical analysis to find empirical evidence for or against my hypotheses.

I analyse the data using panel regression, for IPO monthly data points until the fifth post-IPO year or the month of delisting, in case a delisting happens before the fifth post-post-IPO year. Due to CVC-backing being a largely non-random effect, I perform an additional robustness check in the form of a probit regression to account for a number of variables that impact the likelihood of a venture to receive a CVC-investment.

As far as the hypotheses that I derived in the literature review section go, they are far from supported. As my results suggest, CVC-backing tends to have a more negative than positive impact on post-IPO performance, and especially on return on assets. The impact of CVC-backing on a venture’s post-IPO market-to-book ratio are somewhat ambiguous, yet show no statistically significant results to support my hypotheses. My hypothesis regarding post-IPO factor adjusted abnormal stock returns are validated empirically, which substantiates the notion of the market incorporating the added value of CVC-backing into a venture’s stock price. Concludingly, this may mean that CVCs do add value to their investees, yet pursue different goals from the purely financial ones.

My research is just a beginning in the direction of the impact of CVC-backing on post-IPO performance. I was unable to acquire complete data on delisted companies, which removed some analytical power from my research. Furthermore, some independent variables are more proxies for what they claim to be, which may hamper results as well. For instance, determining a strategic alliance between a CVC-investor and its investee using only SIC codes is very limited, especially since strategic partnerships can form and prove efficient outside of similar industries. Another limitation of my research is the limited number of observations. The time frame of 2000 to 2011 had a number of good and a less good years in terms of IPO numbers. Also, the continued effect of CVC-backing on post-IPO performance can be largely impacted by post-IPO share retainment. My research doesn’t take this into account and therefore disregards its impact.

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30 My research shows unexpected and somewhat ambiguous results. Therefore, I hope to show the yet unexplored area of post-IPO performance impact of CVC-backing and how little is exactly known of how CVC-backing impacts a venture’s long-term performance.

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The effect of Corporate Venture Capital-backing on a venture’s post-IPO performance

Master Thesis