Do M&A exits have the same effect on venture capital reputation than IPO exits?

Journal of Banking and Finance 111 (2020) 105704

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Do M&A exits have the same effect on venture capital reputation than IPO exits?✰ Salma Ben Amor a, Maher Kooli b,∗ a

Université du Québec en Outaouais, Campus Saint Jerôme, 5 Rue Saint-Joseph, Saint-Jérôme, Québec, Canada J7Z 0B7 School of Management, CDPQ Research Chair in Portfolio Management, Université du Québec à Montréal, Department of Finance, 315 Rue Sainte-Catherine Est, Montréal, Québec, Canada H2X 3X2

b

a r t i c l e

i n f o

Article history: Received 27 November 2018 Accepted 19 November 2019 Available online 22 November 2019 JEL: G32 G34 Keywords: Initial public offerings M&A Venture capital Grandstanding

a b s t r a c t This paper examines whether merger and acquisition (M&A) exits have the same effect on venture capital (VC) reputation than initial public offering (IPO) exits? Using a large sample of U.S. IPOs and M&As for the period 1996–2015, we find that M&A exit strategy has the same importance as IPO exit strategy in explaining the incentives of young venture capital firms to grandstand. There is, however, no evidence that young VC firms exit from their portfolio companies closer to the next follow-on fund than older VCs. In addition, our results show that to build their reputation, young VC firms are willing to accept a lower premium in the case of M&A exits and to bear the cost of higher underpricing in the case of IPO exits. We also find that the presence of reputed VC affects significantly the probability of an IPO exit over an acquisition exit.

1. Introduction Experience and reputation are important factors in raising capital, especially for venture capital firms. A common concern of venture capitalists (VCs) is the need to deliver positive returns to maintain existing limited partners, to attract new investors, and to raise new funds. Prior research considers that the common indicator of VC firm reputation is its IPO success. Lerner (1994) and Gompers (1995) document that venture capital-backed companies yield the highest return for venture investors when they go public. Nahata (2008) finds that firms backed by more reputable VCs are more likely to exit successfully and can access public markets more quickly. Studies that infer the quality of the venture from the number of firms brought public, however, do not consider the case of M&As as an exit channel. Gompers (1996) argues that the most effective way for young venture capitalists to signal their ability to potential investors is to bring one of the portfolio companies

✰ We are grateful to an anonymous referee for insightful and constructive suggestions. We also thank seminar participants at the MFA 2018 and the EFMA 2018 for many helpful comments and suggestions. We gratefully acknowledge the financial support of the CDPQ Research Chair in Portfolio Management of the School of Management (UQAM). We are responsible for any remaining errors. ∗ Corresponding author. E-mail addresses: [email protected] (S.B. Amor), [email protected] (M. Kooli).

https://doi.org/10.1016/j.jbankfin.2019.105704 0378-4266/© 2019 Elsevier B.V. All rights reserved.

© 2019 Elsevier B.V. All rights reserved.

public in an IPO. According to Gompers (1996), young VCs have a strong reason to grandstand by bringing firms public earlier than older VCs to establish a reputation and raise capital for new funds. Lee and Wahal (2004) also confirm the grandstanding hypothesis. Butler and Goktan (2013) find that young VC firms have a comparative advantage at producing “soft information” about relatively opaque start-up companies.1 They conclude that the need for soft information production could be an explanation of why start-up companies would have a demand for young VC firms that are likely to grandstand. In this study, we extend this line of research by exploring the case of M&A exit. We investigate whether young VCs need to successfully sell privately held firms earlier than older VCs to establish a reputation.2 We also examine if VC reputation affects the exit choice between IPOs and acquisitions. Although an IPO is an attractive exit mechanism to realize returns, VC firms also have the alternative of cashing out via acquisition, a merger, or a trade sale. The appeal of M&As has become

1 According to Butler and Goktan (2013), the term “soft information” represents the type of information that VC firms generate about their portfolio companies through the use of their own network. 2 We should however mention that VC grandstanding is not the only means of reputation-building. For instance, holding directorships in mature public companies also increases VC firms’ reputation See Hasan et al. (2018) and Celikyurt et al. (2014) for further details.

2

S.B. Amor and M. Kooli / Journal of Banking and Finance 111 (2020) 105704

700 600 500 400 300 200 100 0

Total IPOs

Total M&As

Total IPOs and M&As

Fig. 1. IPOs and M&As activities between 1996 and 2015, according to the National Venture Capital Association (NVCA).

popular over the past decade. According to the National Venture Capital Association (NVCA) 2016 Yearbook, there were more exits by VCs through acquisitions than via IPOs for the period between 1996 and 2015 (see Fig. 1).3 This decline in venture-backed IPOs is in line with an overall decline in the IPO market. For example, Gao et al. (2013) report that in the U.S., the average of IPOs per year dropped from 310 IPOs per year during 1980–20 0 0 to only 99 IPOs per year during 2001–2012. Doidge et al. (2013) confirm that compared to other countries, the rate of small-firm IPO activity in the U.S. was low in the 20 0 0s. Furthermore, Bayar and Chemmanur (2011) and Bayar and Chemmanur (2012) note that an IPO is not always the best way to exit and that over the last decade, a privately held firm was much more likely to have been acquired than to go public. Masulis and Nahata (2011, p. 398) point out that “(…), while IPOs are generally viewed as the most profitable VC exit, acquisitions can also be very profitable, and can be the only profitable exits in periods when the IPO market is weak or effectively closed.” Smith et al. (2011) also confirm that IPO and M&A exits are of approximately equal importance. Specifically, in explaining VC fund financial performance, they find that M&A success is around 60% to 80% as important as IPO success. The popular press also highlighted many examples of the preference for M&As over IPOs as an exit route for venture-backed firms. For example, “Forget IPOs, firms want to get bought” (Wall Street Journal, November 2015, p. C1),4 and “Forget IPO. The new goal? Get acquired” (Inc., September 2012).5 According to Bayar and Chemmanur (2011), the upward trend in M&As exits indicates that the costs to private firms to go public via IPO rather than to get acquired have risen significantly in recent years. However, it is not only a matter of costs.6 Product market competition and firm’s quality could also explain the exit choice as later stage firms and better quality firms are more likely to go public, while earlier-stage firms and lower quality firms are more likely to be acquired. Bayar and Chemmanur (2012) also find that firms operating in less concentrated industries (with greater private benefits of control) are more likely to go public rather than to be ac-

3 For instance, acquisitions of venture-backed firms with disclosed values accounted, on average, for $25.43 billion between 2004 and 2014, while IPOs of venture-backed firms accounted for $10.25 billion. 4 “Forget Going Public, U.S. Companies Want to Get Bought” (Wall Street Journal, November. 29, 2015)http://www.wsj.com/articles/forget-goingpublic- u- s- companies- want- to- get- bought- 1448793190 5 “Forget IPO. The new goal? Get acquired” (Inc., September 2012)http://www.inc. com/eric- markowitz/forget- ipo- the- new- goal- get- acquired.html 6 We thank an anonymous referee for suggesting this discussion.

quired and Gao et al. (2013) retain the economies of scope hypothesis to explain the low level of IPOs vs. M&A.7 Our study contributes to the existing literature on how young VC firms grandstand and on the importance of VC reputation in several ways.8 First, previous work focuses mainly on IPOs despite the upward trend of M&A as an exit route. Nahata (2008, p. 141) notes that “although the ‘going public’ decision has been extensively studied both theoretically and empirically, limited research exists on the acquisitions of private firms, particularly those that are VC-backed.” Masulis and Nahata (2011) also point out that an analysis of VC-backed acquisitions is lacking. In this paper, we aim to fill this gap in the literature by examining whether M&A exits have the same effect on venture capital reputation than IPO exits. Second, Gompers (1996), considers a U.S. IPO sample between 1978 and 1987 and finds that young VC firms raise capital significantly sooner after the date of the IPO. The behavior of young VCs, however, could be due to the quality of the privately held companies they are financing rather than to their reputation. To address endogeneity concerns, we use Heckman’s (1979) correction procedure on a large dataset that covers the 1996–2015 period. We find that venture-backed acquisitions should be of the same importance as venture-backed IPOs in explaining the grandstanding of young venture capitalists. Further, using a Cox hazard analysis to control for the time between the M&A or the IPO exit and the next followon fund, we find that more experienced venture capitalists raise capital sooner after a successful exit by acquisition or IPO. Thus, unlike Gompers (1996)’s finding,9 VC reputation shortens the time of raising new capital. Indeed, while reputational concerns could be a driver for young VC firms to raise future funds quickly after the exit, experience, skills, and networks of well-established VC firms could help them to easily find capital providers as soon as possible after the exit. Third, our paper contributes to a growing literature that examines the role of VC.10 Much of this literature agrees on the fact that VCs do not only provide capital to young high-growth companies, they also provide screening, monitoring, certification, investment expertise, networking, and promoting innovation and growth. Thus, VC reputation is an important asset to carry out these objectives. According to Gompers (1996), for young VCs firms to build their reputation, they are willing to incur the costs of higher underpricing. We complement this result by examining the case of M&A exits. To make a parallel with the underpricing for IPOs, we investigate the effect of the VC reputation on the acquisition premium and find a positive and significant relation between the acquisition premium and the VC reputation. Thus, less reputed VCs could bear the cost of building their reputation by negotiating less and accepting a lower premium than more established VCs. Fourth, our paper contributes to the literature that examines the exit choice for private firms.11 Specifically, we explore whether

7 See Bayar and Chemmanur (2011) for a detailed discussion of private firm’s choice of exit mechanism and a proposition of several testable implications. In addition, in Section 3.5 of our study, we extend previous analyses by empirically examining the effect of VC reputation on the exit choice. 8 Our study also complements Krishnan et al. (2011). Nahata (2008) focuses on VC reputation and investment performance, while Krishnan et al. (2011b) focus on VC reputation and post-IPO long run performance. 9 Note that, to ensure that the different results are not driven by differences in methodologies it will be interesting to replicate Gompers (1996)’s study including M&A exits. However, we roll out this test due to data availability on M&As for the period 1978–1987. 10 For example, see Lerner (1995), Megginson and Weiss (1991), Hellmann and Puri (2002) Nahata (2008), Krishnan et al. (2011b), Hochberg, Ljungqvist and Lu (2007), and Chemmanur et al. (2011), Bernstein et al. (2016), and Gill and Walz (2016), among others. 11 Bayar and Chemmanur (2011) present a theoretical model to study the situation of an entrepreneur managing a private firm backed by a VC. Nahata (2008) examines whether VC reputation confers performance benefits to their portfolio compa-

S.B. Amor and M. Kooli / Journal of Banking and Finance 111 (2020) 105704

the most reputable VCs will choose to take their companies public rather than to sell them to potential acquirers. We find that VC reputation affects positively and significantly, the probability of an IPO exit over an acquisition exit. The remainder of this paper proceeds as follows. Section 2 describes our data and provides comparative and descriptive statistics. Section 3 describes our empirical tests and results. Section 4 provides further tests, and Section 5 concludes. 2. Data sources, sample selection, and descriptive statistics In this section, we present our data sources and highlight some descriptive statistics for our retained sample. We build this study on data, which come from different sources. First, we obtain our data on VCs from the Thomson One Private Equity Database provided by Thomson Financial. We focus on all U.S. venture capital exits by taking a firm public in an IPO or selling it to a public acquirer between January 1996 and December 2015. We exclude all exits for which venture capital firms could not be identified and collect data about dates and sizes of new funds by tracking the fundraising history of U.S. venture capital firms. To the extent that venture capitalists often syndicate their investments with other venture firms, we are interested in the lead venture capitalist. If the company is financed by more than one venture capital firm, we track the fundraising history for the lead investor. We identify the lead venture capitalist as the venture investor with the earliest and largest investment. If two firms provide the same amount of funding in the first round, we consider the firm with the largest investment by cumulating the amount invested across all financing rounds. We also eliminate venture-backed exits in which the size and date of the next fund raised could not be identified for the lead venture capitalist. Second, we crosscheck our data and complete the information on IPOs and M&As with the New Issues database (for IPOs) and M&A database (for acquisitions), also provided by Thomson Financial. Our final sample contains 609 U.S. VC-backed companies that exit through IPOs and 830 U.S. VC-backed companies that exit through acquisitions.12 Table 1 presents year distribution of exit by VC firms. During the 1996– 2015 period, approximately 58% of firms were acquired versus 42% of firms went public via IPOs. We also observe that after a significant peak during the internet bubble period of 1999–20 0 0, IPO activity slowed significantly, especially during the financial crisis. The number of IPOs fell from 40 during 20 05–20 06 to only 11 during 20 07–20 08. M&A activity also witnesses a decline from 135 during 20 05–20 06 to 94 during 20 07–20 08. To test the grandstanding hypothesis, we distinguish between companies backed by young venture capital firms and those backed by more established venture capitalists based on three measures of venture capital reputation. We form two groups of companies for venture-backed IPOs and venture-backed acquisitions. The first measure is the venture capital firm’s age. For comparison purposes, we follow Gompers (1996) and classify all lead venture capital firms under 6 years old at the exit date (by IPO or acquisition) as “young” and those 6 years old or more as “old”. We also classify all lead venture capital firms under 10 years old as young and those 10 years old or more as experienced venture capitalists.13 Sørensen (2007) argues, however, that VC age cannot nies and finds that companies led by more reputable VCs are more likely to exit successfully. Poulsen and Stegemoller (2008) conclude that VCs backing has an effect on the exit choice. Ball et al. (2011) find that the choice of an M&A exit over an IPO exit is negatively related to subsequent market returns and that acquirers may turn to M&A for lack of better alternatives. 12 Note that the number of observations varies in our empirical analysis depending on data availability. 13 The standard term of a typical VC limited partnership is 10–12 years. We also consider 12 years old as a cutoff and our results remain qualitatively unchanged.

3

Table 1 Year distribution of exit by VC firms. The sample consists of 609 VC-backed companies taken public by IPOs and 830 VC-backed companies exit through acquisitions between 1996 and 2015. Exit year

IPOs

M&As

Total exits

1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 1996–2015

111 61 39 110 94 11 13 12 33 18 22 9 2 4 18 15 7 16 14 0 609

24 24 39 51 87 61 59 46 73 66 69 60 34 26 32 34 20 11 10 4 830

135 85 78 161 181 72 72 58 106 84 91 69 36 30 50 49 27 27 24 4 1439

accurately distinguish between active and inactive investors. Therefore, we consider the number of previous IPOs or M&As conducted by the lead venture capital firm as a second measure of VC reputation. Specifically, we consider venture capitalists with the number of previous IPOs or M&As under the median as young and those with the number of previous IPOs or M&As equal to or over the median as old. Our third VC reputation measure is IPO/M&A market share and computed as VC’s dollar market share of all venturebacked IPOs or M&As in the preceding 3 calendar years. As noted by Krishnan et al. (2011a), this measure captures a VC’s IPO or M&A success rate relative to those of other VCs. It is also based on a 3-year moving window prior to the IPO. Thus, it avoids the strong bias against younger VC firms. Further, we follow much of the existing IPO and M&A literature by considering several control variables. See the appendix for more detailed variable definitions. According to the grandstanding hypothesis, young VCs have strong incentives to grandstand by taking their companies public too early than older VCs to build a reputation and to raise new funds. Thus, one of the predictions of the grandstanding hypothesis is that young VC firms exit their companies sooner than more established venture capitalists. As a preliminary data investigation, we report descriptive statistics for the IPO and M&A samples. Panels A and B of Table 2 present summary information for IPOs and M&As backed by young and old venture capital firms, using cutoff ages of 6 years old (panel A) and 10 years old (panel B), respectively.14 Our results show that young venture capital firms exit their companies sooner than more established venture capitalists, regardless of the measure of reputation used. For example, the time to exit by IPOs for lead venture capital firms under 6 years old is 3.3 years, compared to 4.6 years for old venture capitalists (see panel A of Table 2). The difference in means is statistically significant at the 1% level. The results for venture-backed acquisitions show that the average time from investment to exit is even shorter for young venture capi-

14 Our results remain qualitatively unchanged using the median number of previous IPOs and M&As as a reputation measure. These results are available from the authors upon request.

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S.B. Amor and M. Kooli / Journal of Banking and Finance 111 (2020) 105704

Table 2 Descriptive statistics of IPOs and M&As backed by young and old venture capital firms The sample consists of 609 VC-backed companies taken public by IPOs and 830 VC-backed companies exit through acquisitions between 1996 and 2015. Medians are reported below means. The number of observations varies depending on data availability. Variable definitions are provided in the Appendix. Panel A: VC smaller or greater than 6 years old IPO exit

Average time to exit Average time from exit to next follow-on fund Average size on next follow-on fund Average age of VC-backed companies at exit Average number of previous M&A Average number of previous IPO Average number of total exits Average syndicate size Average offering size

M&A exit

VC with 6 years old and greater at IPO

p-value of no diff test

VC less than 6 years old at the M&A

VC with 6 years old and greater at M&A

p-value of no diff test

VC less than 6 years old at the exit

VC with 6 years old and greater at exit

3.3 −2.15 18.1

4.6 −3.9 14.98

0.001 0 0.2

2.25 −1.8 18.51

4.9 −4.4 18.63

0 0 0.96

2.72 −2 18.31

4.77 −4.1 17.1

0 0 0

−7.5 288.03

−9.83 527.63

−0.16 0.02

−11.43 204.54

−11.98 529.75

−0.94 0

−9.3 244.09

−11 528.86

−0.004 0.83

−155.37 4.96

−270 7.36

−0.003 0

−118.02 6.14

−250 8.44

−0.29 0.01

−126.71 5.57

−259.89 7.98

−0.06 0

−4.19 16.5

−5.98 58.26

0 0

−3.75 12.08

−6.6 68.61

0 0

−4.02 14.17

−6.34 64.22

0 0.009

−9 10.29

−43 39.71

0 0

−6 4.15

−52 36.62

0 0

−7 7.06

−48 37.93

−0.012 0.033

−5 26.79

−24 95.24

0 0

−1 16.23

−22 100.28

0 0

−2 21.23

−23 98.17

−0.053 0

−14 7.65

−64 8.12

0 0.48

−7.5 4.45

−71 6.11

0 0

−10 5.96

−68 6.96

0 0.01

−7 90.91 −73.6

−7 146.51 −75.9

−0.67 0.56 −0.01

5

4

0

−5

−6

0.01

143.39

168.49

0.5

−73.16 0.62 −1 42.42%

−93 0.5 −1 26.91%

−0.04 0.04 −0.04

39.39%

48.26%

18.18%

24.83%

11.79 −5.99

19.58 −6.66

80

744

152

1281

Average M&A deal value Synergy % of stock-financed M&As % of cash-financed M&As % of cash- and stock-financed M&As Average underpricing

65.34 −34.7

48.22 −20.58

No. of observations

8

8.29

0.11

−8 72

−8.5 536

−0.17

Panel B: VC smaller or greater than 10 years old IPO exit

Average time to exit Average time from exit to next follow-on fund Average size on next follow-on fund Average age of VC-backed companies at exit Average number of previous M&A Average number of previous IPOs

p-value of no diff test

0.08 −0.04

Average premium IPO Underwriter prestige

All sample

VC less than 6 years old at the IPO

−0.41 −0.89

M&A exit

All sample

VC less than 10 years old at the IPO

VC with 10 years old and greater at IPO

p-value of no diff test

VC less than 10 years old at the M&A

VC with 10 years old and greater at M&A

p-value of no diff test

VC less than 10 years old at the exit

VC with 10 years old and greater at exit

p-value of no diff test

3.48 −2.6 19.01

4.69 −3.9 14.34

0 0 0.01

3.22 −2.9 18.73

5.07 −4.5 18.58

0 0 0.93

3.33 2.8 18.84

4.91 4.2 16.76

0 0 0.1

−10.21 293.8

−9.53 556.17

0.81 0.001

−12.01 235.96

−11.9 576.76

0.34 0

11.63 259.67

10.76 567.92

0.31 0

−150 5.6

−282.8 7.48

0 0

−126.33 6.89

−268.6 8.61

0 0.008

129.75 6.36

275 8.13

0 0

−4.62 9.75

−6.08 43.68

0 0

−5.35 15.15

−6.62 77.6

0 0

5.04 15.4

6.42 71.65

0 0

−5.5 15.77

−29 63.89

0 0

−10 5.28

−63 41.98

0 0

9.5 7.13

58 42.72

0 0

(continued on next page)

S.B. Amor and M. Kooli / Journal of Banking and Finance 111 (2020) 105704

5

Table 2 (continued) Panel A: VC smaller or greater than 6 years old IPO exit

Average number of total exits Average syndicate size Average offering size

M&A exit

VC with 6 years old and greater at IPO

p-value of no diff test

VC less than 6 years old at the M&A

VC with 6 years old and greater at M&A

p-value of no diff test

VC less than 6 years old at the exit

VC with 6 years old and greater at exit

−9 25.53

−50.5 104.19

0 0

−2 20

−27 113.74

0 0

3 22.26

28 109.64

0 0

−15 7.31

−75 8.28

0 0.07

−12 4.95

−86 6.25

0 0

14 5.92

81 7.12

0 0

−7 90.27 −70.75

−6 156.84 −77.62

0.07 0.38 0.03

−5

−4

0

−5

−6

0

162.22 −72.25 0.53 −1 34.46%

167.2 −99 0.51 −1 26.72%

0.84 0.04 0.7 0.7

42.57%

48.79%

22.97%

24.49%

12.65 −5.74

21.13 −6.28

190

634

322

1111

Average M&A deal Synergy % of stock-financed M&As % of cash-financed M&As % of cash- and stock-financed M&As Average underpricing

51.34 −22.42

34.3 −15

No. of observations

p-value of no diff test

0.006 0.03

Average premium IPO underwriter prestige

All sample

VC less than 6 years old at the IPO

7.93

8.06

0.35

−8 132

−8.01 477

0.56

tal firms. Specifically, we find that venture capital firms under 6 years old take on average 2.25 years to exit by acquisition, compared to 4.9 years for more experienced venture capitalists. The difference in means is also statistically significant at the 1% level. When we consider the full sample, we find that younger venture capital firms have an incentive to exit the firm in which they have invested through IPOs as well as through acquisitions as soon as possible (2.72 years for young VCs vs. 4.77 years for older VCs), confirming the grandstanding hypothesis. Unlike Gompers (1996), our results also show that there is no evidence that young venture capital firms exit companies closer to the next follow-on fund. Specifically, we find no significant differences between the average time from the IPO to the next followon fund for young and old venture capital firms when we consider a cutoff age of 6 years old (see Panel A of Table 2). Furthermore, when we consider a cutoff age of 10 years old, we find that, on average, older venture capitalists bring companies public 14 months prior to the next follow-on fund, compared to 19 months for younger venture capitalists. The difference in means is statistically significant at the 5% level (see Panel B of Table 2). In other words, our results show that young venture capital firms take more time to raise a new fund following their IPO exit. When we consider the acquisition sample, we find no significant differences in the time between selling companies to a public acquirer and the next follow-on fund. Our results show that it takes almost 18 months on average before venture capital firms succeed in raising a new fund, regardless of their age or the number of previous deals. Panels A and B of Table 2 also report average (median) maturity of companies at the exit date. When we consider the 10 years old cutoff age (see panel B of Table 2), for example, we find that the average age of the VC-backed company is 5.6 years at the IPO date for young venture capitalists and 7.48 years for more established venture capitalists. We also find that the average age of the VC-backed company is 6.89 years at the acquisition date for young venture capital firms and 8.6 years for old venture capitalists. Both

0.13 1.02

mean differences are statistically significant at the 1% level. These results support the grandstanding hypothesis for the IPO and acquisition samples. We also confirm these observations using a cutoff age of 6 years old (see panel A of Table 2). Further, our results show that experienced venture capitalists are able to raise more money immediately after their exit by IPO or acquisition. For example, taking the 10 years old cutoff age, we find that the average size of the next follow-on fund is $556.17 million for old venture capitalists versus $293.80 million for young venture capital firms when the exit strategy is the IPO. If venture capital firms choose to exit by acquisition, the average size of the next follow-on fund is $576.76 million for old venture capitalists, while it is $235.96 million for young venture capital firms (see panel B of Table 2). Panels A and B of Table 2 also show that young VC-backed IPOs are more underpriced than older VC-backed IPOs. For example, we find that the average (median) underpricing is 51.34% (22.42%) for IPOs backed by young venture capitalists, while it is 34.30% (15.00%) for IPOs backed by older venture capital firms (see panel B of Table 2). We also find that the average offering size is smaller for IPOs brought to market by young venture capitalists and that companies taken public by more established venture capital firms tend to engage more prestigious underwriters, although these results are not statistically significant. When VC exit through acquisitions, we find that the average deal value is smaller for transactions involving young venture capital firms. For example, we find that the average (median) deal value is $143.39 million ($73.16 million) for acquisitions involving young venture capitalists compared to $168.49 million ($93 million) for those involving old venture capital firms. The difference in means is not significant, but the difference in medians is statistically significant at the 5% level (see panel A of Table 2). Our results also show that the average acquisition premium is higher if an experienced VC firm is involved in the acquisition deal. For example, we find that the average acquisition premium is 19.58% for companies backed by more experienced VC firm compared to 11.79% for those backed by young VC firm, al-

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though those results are not statistically significant (see panel A of Table 2). To test the effect of the target company and the public acquirer being in the same industry, we use Synergy, a dummy variable taking the value of 1 if the company acquired is in the same three digits SIC code as the public acquirer, and 0 otherwise. Our univariate results also show that young venture capital firms are more likely to sell the company to a public acquirer who is in the same industry. We also report the payment method for our M&As sample. Overall, we find that older VCs prefer cash-financed acquisitions over stock-financed acquisitions.

lead VC after the IPO, VC fund type to control for VC characteristics, number of institutional investors, number of shares held by all institutional investors divided by all shares outstanding, and number of analysts following the company prior the exit date.16 Although not reported, we include industry and calendar fixed effects in all regressions. T-statistics appear in parentheses and are based on standard errors robust to heteroscedasticity and adjusted for industry clustering. Formally, we have: 1st step selection equation (Probit):

P rob(V C reputed = 1) = a0 + a1Control variables + ε

3. Empirical analysis To formalize our univariate analysis, we run a set of regressions using three different dependent variables: (1) IPO or M&A market share, (2) the logarithm of the size of the next fund raised by the lead venture capital firm, and (3) the time from the market exit to the lead venture capitalist’s next fund. We estimate regressions for both IPO and M&A samples. 3.1. VC reputation and grandstanding via IPOs Previous studies have confirmed that younger VC firms have strong incentives to exit earlier than older VC firms through IPOs to build their reputation. The behavior of young VCs, however, could be due to the quality of the privately held companies they are financing rather than to their reputation. To address endogeneity concerns, we use Heckman’s (1979) correction procedure. In the first step selection equation, we estimate the likelihood of reputable VCs making their investment in privately held companies. Thus, we consider an indicator variable denoting whether the lead VC is young or old (more established) as a dependent variable. As instruments, we consider IPO firm age, IPO firm total assets, number of companies lead VC has invested in, and VC investment stage. Let’s note that to be valid instruments these variables must be significant in the 1st step selection equation (but not significant in the 2nd step equation). In the second stage, we regress the size of the next fund raised by the lead VC on the VC reputation measure including a set of control variables and the inverse Mills ratios (IMR) obtained from the first step. As primary explanatory variables, we use VC age and the total number of previous IPOs conducted by the lead VC (VC previous IPOs). For the VC firm’s age, we consider the logarithm of the venture capital firm’s age in years (ln(VC age)).15 Following previous studies, we consider several control variables in the regressions. We include the total number of IPOs in the previous four months and the value-weighted CRSP market return for the year of the IPO as control variables related to the fundraising activity of venture capital firms and market conditions (Brau et al., 2003). We also control for the underwriter’s prestige using an updated of Carter and Manaster (1990) ranking. Gompers (1996) suggests that young venture capital firms are willing to incur the costs of higher underpricing to build their reputation. Underpricing is an indirect cost for VC firms. It represents a wealth transfer from existing shareholders (including VCs) to new ones. Lee and Wahal (2004) also confirm that VC firms are willing to bear the cost of underpricing and argue that IPO underpricing and IPO size are two measures by which venture capital firms can signal their reputation. Thus, we include these two variables in our regressions. Further, we include firm age to control for firm characteristics and VC syndicate size, fraction of equity held by the

2nd step:

Size o f the next f und raised by the lead V C f or IP Os/M&As = b0 + b1 (V C reputation measure f or IP Os/M&As) + b2Control variables + b3 IMR + n

We also consider as an alternative VC reputation proxy a dummy variable equals 1 if the lead venture capital firm is under 10 years old, and 0 otherwise. Our results remain qualitatively unchanged and available from the authors upon request.

(2)

Table 3 reports the results for the IPO sample. The results from the selection equation estimation show that VC reputation is significantly related to IPO size, to lead VC investment experience, and to VC investment stage. Specifically, we find that an investment by a reputable VCs is more likely in case of larger IPOs, if the lead VC has more investment experience measured by the number of companies it has invested in, and if the VC investment occurred when the portfolio company was not at an early/seed stage of development lifecycle. In models 1, 2, and 3, we separately include our VC reputation measures. Specifically, in model 1 of Table 3, we include IPO Market share as the first measure of VC reputation. We find that the coefficient of IPO Market share is positive and significant at the 10% level (0.045, t-statistic = 1.922). Thus, more experienced venture capital firms are able to raise more capital. In model 2, we include the logarithm of the venture capital firm’s age as the first measure of VC reputation and find that the coefficient of ln(VC age) is positive and significant at the 1% level (0.935, t-statistic = 3.096). Thus, more experienced venture capital firms are able to raise more capital. In model 3, we consider the number of previous IPOs by the lead VC firm as a measure of VC reputation. We also find that the number of previous IPOs by the lead venture capital firm is positively and significantly related to the size of the next fund raised after the IPO. The coefficient of VC previous IPOs is positive and significant at the 1% level (0.928, t-statistic = 3.124).17 This result confirms that the amount of capital raised by venture capitalists is sensitive to the number of previous IPOs, consistent with the grandstanding hypothesis. It also suggests that more experienced VC firms are able to raise more capital. The inverse Mills ratio derived from the specification equation is statistically significant at the 1% level, confirming the importance to control for the selection bias related to the VC’s choice of privately held companies. We also find that the coefficient of the fraction of equity held by lead VC after IPO is positive and significant at the 10% level. Thus, the commitment of lead VCs after IPO helps them to raise more capital. We also find that the coefficient of the fraction of shares held by institutional investors is positive and significant at the 1% level. Thus, institutional investors’ participation helps VC to raise more capital. In models 4, 5, and 5, we replace Underpricing by IPO size to avoid multicollinearity between both variables and confirm that lead VC reputation has a positive and significant effect on the size of the next fund. 16

15

(1)

We thank an anonymous referee for suggesting these control variables. In untabulated results, we exclude control variables in the second stage of the Heckman estimation and find that coefficients of IPO Market share, Ln(VC age), and VC previous IPOs are also positive and statistically significant. We thank an anonymous referee for suggesting these tests. 17

S.B. Amor and M. Kooli / Journal of Banking and Finance 111 (2020) 105704

7

Table 3 Regressions for the logarithm of the size of the next fund raised by the lead venture capital firm after IPO. The sample consists of 609 VC-backed companies taken public by IPOs and 830 VC-backed companies exit through acquisitions between 1996 and 2015. The dependent variable is the size of the next fund raised by the lead VC for IPOs. Variable definitions are provided in the Appendix. ∗ ∗ ∗ , ∗ ∗ , and ∗ indicate statistical significance at the 1%, 5%, and 10% level, respectively.

Constant

Pr(VC reputable = 1)

(1)

(2)

(3)

(4)

(5)

(6)

−3.257∗ ∗ ∗ (−6.791)

4.603∗ ∗ (2.253) 0.045∗ (1.922)

3.611 (1.504)

7.288∗ ∗ ∗ (3.055)

4.450∗ ∗ (2.021) 0.046∗ (1.932)

3.024 (1.204)

6.802∗ ∗ ∗ (2.688)

IPO Market share

0.935∗ ∗ ∗ (3.096)

Ln(VC age) VC previous IPOs Underpricing

0.018 (0.118)

0.099 (0.618)

0.928∗ ∗ ∗ (3.124) 0.284∗ ∗ ∗ (3.930) 0.059 (0.333)

IPO size Prestige Ln(IPO age) CRSP value-weighted return

0.175 (1.591) 0.070 (0.159)

Total IPOs in the previous four months Ln(syndicate size) Fraction of equity held by lead VC post-IPO Fund type Ln(1+number of inst. investors) Fraction of shares held by inst. investors Ln(1+number of analysts) Inverse Mills ratio Ln(IPO assets) Ln(1+number of companies lead VC has invested in) VC investment stage Industry and year fixed effect Wald test No. of observations

0.108∗ (1.918) 0.555∗ ∗ ∗ (7.815) −0.278∗ ∗ (−2.161)

457

To dig deeper our analysis, we next examine the likelihood and timing of raising money for follow-on funds after the date of the IPO using a Cox hazard model, proposed by Cox (1972), where the logarithm of the time from the IPO to the lead venture capitalist’s next fund is the dependent variable. The basic model assumes the following form:

hi (t ) = λ0 (t ) exp {β1 xi1 + · · · + βk xik }

(3)

Where hi (t) is the conditional hazard rate defined as the probability of raising money for follow-on funds after the date of the IPO. λ0 (t) is the baseline hazard function, and the second part of the equation is the exponentiated set of k covariates for firm i. The results of the estimated Cox proportional hazards models are reported in Table 4. Since the dependent variable is the logarithm of the hazard rate, a positive (negative) coefficient on an explanatory variable indicates that changes in that variable decrease (increase) the time from the IPO to the lead venture capitalist’s next fund. We find that VC reputation has a positive and significant impact on the time of raising capital for follow-on funds. In other words, VC reputation shortens the time of raising new capital. The coefficient of IPO Market share is positive and statistically significant at the 5% level. Thus, in contrast to Gompers (1996)‘s observation, more experienced venture capitalists raise capital sooner after the

0.286∗ ∗ ∗ (3.945)

0.198 (0.859) −0.022 (−0.096) −3.624 (−0.489) 0.001 (0.387) −0.292 (−1.628) 0.014 (1.408) 0.282 (0.844) −0.184 (−0.879) 0.357∗ ∗ ∗ (2.813) 0.136 (0.724) −1.041∗ ∗ ∗ (−3.309)

0.296 (1.316) −0.347 (−1.489) −1.296 (−0.173) 0.001 (0.317) −0.362∗ ∗ (−2.086) 0.016∗ (1.721) −0.051 (−0.152) 0.039 (0.170) 0.285∗ ∗ (2.156) −0.647∗ ∗ (−2.357) −1.941∗ ∗ ∗ (−5.065)

0.324 (1.301) −0.348 (−1.348) −2.802 (−0.338) 0.002 (0.436) −0.483∗ ∗ ∗ (−2.577) 0.011 (1.101) −0.217 (−0.591) 0.086 (0.339) 0.310∗ ∗ (2.131) −0.605∗ ∗ (−2.000) −2.145∗ ∗ ∗ (−4.724)

0.038 (0.183) 0.192 (0.828) −0.017 (−0.073) −3.366 (−0.443) 0.001 (0.387) −0.289 (−1.601) 0.014 (1.414) 0.285 (0.858) −0.205 (−0.821) 0.363∗ ∗ ∗ (2.779) 0.128 (0.667) −1.036∗ ∗ ∗ (−3.283)

Yes 51.28 443

Yes 64.54 457

Yes 62.04 457

Yes 51.30 443

0.155 (0.691) 0.277 (1.246) −0.330 (−1.428) −0.465 (−0.062) 0.001 (0.310) −0.348∗ ∗ (−2.016) 0.016∗ (1.744) −0.016 (−0.048) −0.015 (−0.061) 0.306∗ ∗ (2.258) −0.712∗ ∗ (−2.544) −1.916∗ ∗ ∗ (−5.048)

0.121 (0.488) 0.307 (1.250) −0.333 (−1.300) −2.139 (−0.258) 0.001 (0.430) −0.472∗ ∗ (−2.533) 0.011 (1.133) −0.198 (−0.552) 0.033 (0.119) 0.329∗ ∗ (2.194) −0.656∗ ∗ (−2.127) −2.115∗ ∗ ∗ (−4.690)

Yes 66.50 457

Yes 62.69 457

IPO. This observation is in line with Hochberg et al. (2007) who find that better-networked VC firms experience significantly better fund performance, as measured by the proportion of investments that are successfully exited through an IPO or a sale to another company. Further, we find a negative relation between the underwriter’s prestige and the time of raising capital for follow-on funds. The coefficient of Prestige is negative and statistically significant at the 5% level (models 2 and 5). Thus, prestigious underwriters help VCs to stay active. Again, the inverse Mills ratio derived from the specification equation is statistically significant at the 1% level, confirming the importance to control for the selection bias. We also find that the higher the underpricing, the longer time VC firms take after the IPO date to raise money for follow-on funds. The coefficient of Underpricing in models 1, 2, and 3 of Table 4 are positive and significant at the 5% level. Models 4, 5, and 6 also confirms our previous observations. Overall, our regression analysis results confirm that reputation affects VC future fundraising. 3.2. VC reputation and grandstanding via M&As The grandstanding hypothesis predicts that the amount of capital a VC firm can raise should also be positively related to the number of M&A exits. Table 5 presents regressions results of the

8

S.B. Amor and M. Kooli / Journal of Banking and Finance 111 (2020) 105704 Table 4 The Cox Hazard Model estimations for the time from IPO to the lead venture capital firm s next fund The sample consists of 609 VC-backed companies taken public by IPOs and 830 VC-backed companies exit through acquisitions between 1996 and 2015. The dependent variable is the logarithm of the time from the IPO to the lead venture capitalist’s next fund. Variable definitions are provided in the Appendix. ∗ ∗ ∗ , ∗ ∗ , and ∗ indicate statistical significance at the 1%, 5%, and 10% level, respectively. Pr(VC reputable = 1)

(1)

(2)

(3)

∗∗

IPO Market share

0.165∗ (1.739)

0.173 (1.802)

0.157∗ ∗ (2.127)

Underpricing

0.194∗ ∗ ∗ (2.740)

0.032 (0.595) 0.162∗ ∗ (2.295)

IPO size Prestige 0.156 (1.501) −0.090 (−0.231)

Total IPOs in the previous four months Ln(syndicate size) Fraction of equity held by lead VC post-IPO Fund type Ln(1+number of inst. investors) Fraction of shares held by inst. investors Ln(1+number of analysts) Inverse Mills ratio Ln(IPO assets) Ln(1+number of companies lead VC has invested in) VC investment stage

0.096∗ (1.801) 0.542∗ ∗ ∗ (7.251) −0.349∗ ∗ ∗ (−2.961)

Industry and year fixed effect Wald test Log likelihood No. of observations

size of the next fund raised by the lead venture capital firm immediately after the M&A exit. In models 1, 2, and 3, we separately include the three measures of VC reputation. In models 2, 4, and 6, we replace Acquisition premium by Ln(deal value). We consider the same set of control variables as for the IPO sample. We also include Synergy to control for the effect of the target company and the public acquirer being in the same industry. In addition, we use the Heckman correction procedure and include the inverse Mills ratio to control for the selection bias. In model 1, the coefficient of M&A Market share is positive and significant at the 1% level (0.438, t-statistic = 2776) and in model 3, the coefficient of the logarithm of venture capitalists’ age Ln(VC age) is positive and significant at the 1% level (1.563, tstatistic = 3.217). Thus, more reputable venture capital firms are significantly able to raise more capital after successfully selling the company to a public acquirer. In model 5 of Table 5, we find that the total number of previous M&As is significantly and positively related to the size of the next follow-on fund. This result confirms that each additional exit by M&A helps VC firms attain more reputation and succeed in raising more money for future in-

(6)

0.036 (2.308) ∗

VC previous IPOs

CRSP value-weighted return

(5) ∗∗

0.039 (2.518)

Ln(VC age)

Ln(IPO age)

(4)

∗∗

−0.204 (−1.418) −0.009 (−0.075) 0.135 (0.334) 0.002∗ ∗ (2.153) −0.035 (−0.359) −0.012∗ ∗ (−2.235) −0.001 (−0.005) 0.083 (0.708) 0.011 (0.139) −0.121 (−0.998) −0.467∗ ∗ (−2.547)

−0.277 (−2.035) −0.033 (−0.327) −0.089 (−0.233) 0.001∗ (1.901) −0.105 (−1.169) −0.008 (−1.622) 0.161 (0.886) −0.028 (−0.252) 0.078 (1.104) −0.103 (−0.949) −0.430∗ ∗ ∗ (−2.658)

−0.207 (−1.537) −0.041 (−0.420) 0.131 (0.354) 0.001∗ (1.854) −0.050 (−0.563) −0.005 (−1.004) 0.162 (0.895) 0.076 (0.690) 0.043 (0.611) −0.169 (−1.585) −0.350∗ (−1.832)

Yes 29.42 −1508 398

Yes 33.66 −1837 389

Yes 24.49 −1899 398

0.037 (0.687)

0.094 (0.821) −0.233 (−1.618) −0.039 (−0.337) 0.234 (0.565) 0.002∗ ∗ ∗ (2.609) −0.013 (−0.136) −0.012∗ ∗ (−2.286) 0.016 (0.079) 0.095 (0.652) 0.015 (0.187) −0.151 (−1.261) −0.415∗ ∗ (−2.282)

0.066 (0.594) −0.297∗ ∗ (−2.189) −0.068 (−0.686) −0.019 (−0.049) 0.002∗ ∗ (2.504) −0.062 (−0.714) −0.008 (−1.598) 0.176 (0.972) 0.033 (0.248) 0.069 (0.961) −0.116 (−1.086) −0.399∗ ∗ (−2.473)

0.061 (0.560) −0.234∗ (−1.735) −0.070 (−0.717) 0.198 (0.525) 0.002∗ ∗ (2.364) −0.018 (−0.199) −0.005 (−0.984) 0.168 (0.933) 0.123 (0.906) 0.040 (0.546) −0.183∗ (−1.746) −0.299 (−1.570)

Yes 26

Yes 27.40 −1840 389

Yes 20.04 −1901 398

vestments, once again supporting the grandstanding hypothesis.18 Furthermore, we find that the coefficient of Acquisition premium is negative but not significant. Thus, accepting a lower acquisition premium could help VCs to raise more capital immediately after the acquisition exit. Table 5 also shows that venture capital firms participating in large deals are significantly able to raise more capital. The coefficient of Ln(deal value) is positive and significant at the 5% level in model 4 and at the 10% level in model 6. Again, the coefficient of the inverse Mills ratio is statistically significant for all models indicating the importance of controlling for the selection bias. Overall, results in Table 5 show that the exit via acquisitions is as important as the exit via IPOs in explaining VC fundraising. We next estimate the time between the M&A exit and the next follow-on fund by lead VC. Table 6 presents our Cox hazard model estimations for the M&A sample. We find that VC reputation has a significant impact on the

18 In untabulated results, we exclude control variables in the second stage of the Heckman estimation and find that coefficients of M&A Market share, Ln(VC age), and VC previous M&As are positive and statistically significant. We thank an anonymous referee for suggesting these tests.

S.B. Amor and M. Kooli / Journal of Banking and Finance 111 (2020) 105704

9

Table 5 Regressions for the logarithm of the size of the next fund raised by the lead venture capital firm after acquisition. The sample consists of 609 VC-backed companies taken public by IPOs and 830 VC-backed companies exit through acquisitions between 1996 and 2015. The dependent variable is the size of the next fund raised by the lead VC for M&As. Variable definitions are provided in the Appendix. ∗ ∗ ∗ , ∗ ∗ , and ∗ indicate statistical. significance at the 1%, 5%, and 10% level, respectively.

Constant

Pr(VC reputable = 1)

(1)

(2)

(3)

(4)

(5)

(6)

−4.626∗ ∗ ∗ (−4.647)

11.179∗ ∗ (1.993) 0.438∗ ∗ ∗ (2.776)

3.533 (1.512) 0.144∗ ∗ (2.376)

−6.613 (−0.675)

3.536∗ ∗ (2.562)

11.301 (1.364)

2.146 (0.487)

1.633∗ ∗ ∗ (3.223)

0.781∗ ∗ (2.337) 1.042∗ ∗ ∗ (3.247) −44.649 (−1.498) −0.001 (−0.537) −0.177 (−0.598) −0.063 (−0.317)

0.387∗ ∗ (2.173) 4.838 (0.252) 0.001 (1.209) −0.117 (−0.733)

M&A Market share Ln(VC age) VC previous M&As CRSP value-weighted return

0.791 (1.126)

Total M&As in the previous four months Ln(M&A age)

−0.056 (−0.268)

Acquisition premium

−12.750 (−1.057) −0.002 (−0.990) −0.335 (−1.016) −0.153 (−0.746)

Ln(deal value) Synergy Ln(syndicate size) Fund type Ln(1+number of inst. investors) Fraction of shares held by inst. investors Ln(1+number of analysts) Inverse Mills ratio Ln(M&A assets) Ln(1+number of companies lead VC has invested in) VC investment stage

0.787∗ ∗ ∗ (7.325) 0.643∗ ∗ ∗ (3.721) 0.013 (0.047)

Industry and year fixed effect Wald test No. of observations

time between the M&A exit and the next follow-on fund. For instance, coefficients of M&A Market share and Ln(VC age) are positive and statistically significant. Thus, more experienced venture capitalists raise capital sooner after a successful exit by acquisition. In other words, VC reputation shortens the time of raising new capital. We also find that independent VCs are able to quickly raise new funds following the acquisition. The coefficient of Fund type is positive, however, not significant. Nahata (2008) points out that corporate VCs are generally less experienced in venture financing than traditional VCs. Chemmanur et al. (2014) also provide evidence that CVCs firms are younger, riskier, and less profitable than independent VC.19 Masulis and Nahata (2011) point out that CVC have weaker financial incentives, which make them more risk-averse and more worried to exit their investments. Again, the inverse Mills ratio derived from the specification equation is statistically significant at the 1% level, confirming the importance to control for the selection bias. Overall, we confirm that selling private firms to the public acquirer is as important as taking it public through an IPO to build VC reputation.

19 See Chemmanur et al. (2014) for a detailed comparison between CVC and independent VC and Ivanov and Xie (2010) for an examination of the added value of CVCs relative to independent VCs.

−3.647 (−0.672) 0.001∗ (1.752) −0.058 (−0.372)

0.377 (0.897) −0.907∗ ∗ ∗ (−2.803) −1.102 (−1.225) 0.107 (0.339) −0.981∗ (−1.873) −0.117 (−0.484) −1.264∗ ∗ ∗ (−2.696)

0.049 (0.612) 0.000 (0.000) −0.330∗ ∗ (−2.108) 0.827∗ ∗ (2.390) −0.027 (−0.269) 0.001 (1.040) 0.255∗ ∗ ∗ (2.959) −1.167∗ ∗ ∗ (−3.811)

Yes 70.97 434

Yes 134.55 434

22.352 (0.659) 0.001 (0.250) −0.595∗ (−1.913) −0.027 (−0.126)

−1.405∗ ∗ (−2.008) −0.000 (−0.447) 0.092 (0.515)

−0.025 (−0.067) −0.913∗ ∗ ∗ (−2.827) 0.598 (0.731) −0.001 (−0.003) −1.113∗ ∗ (−2.277) 0.335 (1.626) −1.038∗ (−1.698)

0.151∗ ∗ (1.965) −0.203 (−1.035) −0.510∗ ∗ ∗ (−3.133) 1.190∗ ∗ ∗ (3.219) −0.056 (−0.592) 0.001 (0.388) 0.278∗ ∗ ∗ (3.104) −1.917∗ ∗ ∗ (−4.989)

−0.108 (−0.281) −1.128∗ ∗ ∗ (−3.565) −1.300∗ (−1.881) −0.089 (−0.302) −1.175∗ ∗ (−2.389) 0.278 (1.315) −1.148∗ ∗ (−1.971)

0.155∗ (1.915) −0.203 (−0.992) −0.577∗ ∗ ∗ (−3.664) 0.678∗ (1.841) −0.114 (−1.153) −0.000 (−0.115) 0.295∗ ∗ ∗ (3.415) −1.179∗ ∗ (−2.479)

Yes 92.84 434

Yes 43.56 434

Yes 97.77 434

Yes 81.96 434

3.3. VC reputation and exit timing Our descriptive statistics reported in Table 1 show that the time between the first lead venture capital investment and the IPO or the M&A date is significantly shorter for young venture capitalists. We also find that companies backed by new venture capital firms are younger than those backed by more established venture capitalists. In this sub-section, we analyze the correlation between VC firm reputation and IPO or M&A timing. We consider (1) the time to exit and (2) the company age at the IPO or M&A exit as timing measures and run a set of regressions using VC reputation measures as independent variables. We use an accelerated failure time (AFT) model to test the relation between VC reputation and time to exit. One feature of this model is that the baseline hazard function follows an assumed density function based on prior expectations. Based on Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) results, we assume that the baseline hazard function follows a log-logistic density function. Hence, we estimate a log-logistic AFT model where the dependent variable is the number of years between the exit date and the first investment date by the lead venture capital firm. A positive (negative) coefficient on an explanatory variable indicates both a higher (lower) probability of survival as well as an increasing (decreasing) expected duration.

10

S.B. Amor and M. Kooli / Journal of Banking and Finance 111 (2020) 105704 Table 6 The Cox Hazard Model estimations for the time from M&A to the lead venture capital firm s next fund The sample consists of 609 VC-backed companies taken public by IPOs and 830 VC-backed companies exit through acquisitions between 1996 and 2015. The dependent variable is the time between the M&A exit and the next follow-on fund by lead VC. Variable definitions are provided in the Appendix. ∗ ∗ ∗ , ∗ ∗ , and ∗ indicate. statistical significance at the 1%, 5%, and 10% level, respectively. Pr(VC reputable = 1)

(1)

(2) ∗∗∗

M&A Market share

0.106 (2.674)

(3)

(4)

0.358∗ ∗ ∗ (3.178)

0.349∗ ∗ ∗ (3.108)

VC previous M&As −2.652 (−0.852) 0.000 (0.033) −0.028 (−0.302) −0.001 (−0.214)

0.006 (0.021)

Total M&As in the previous four months Ln(M&A age)

0.064 (0.593)

Acquisition premium Ln(deal value) Synergy Ln(syndicate size) Fund type Ln(1+number of inst. investors) Fraction of shares held by inst. investors Ln(1+number of analysts) Inverse Mills ratio Ln(M&A assets) Ln(1+number of companies lead VC has invested in) VC investment stage

0.132∗ ∗ (2272) 0.504∗ ∗ ∗ (5.361) −0.194 (−1.413)

Industry and year fixed effects Wald test Log likelihood No. of observations

Specifically, we estimate the following AFT model:

Ln(T ) = b0 + b1 (V C reputation measure f or IP Os/M&As) + b2Control variables + ε

(4)

where T is the duration of a VC-backed firm before the exit. The estimation results are reported in Table 7. Panel A of Table 7 reports regression results for IPOs. Following previous section, we also control for potential endogeneity concerns using Heckman’s (1979) correction procedure. Column 1 of Table 7 presents results of the first step selection equation, while columns 2–7 present regression results of the second step (Eq. (4)).20 We find that young venture capital firms take companies public earlier than old venture capitalists. Positive and significant coefficients of IPO Market share and Ln(VC age) suggest that more experienced VC take their time to bring companies to the market by IPOs than less established VCs. We also find that duration before the exit is positively and significantly related to VC previous IPOs, confirming again that more experienced VC take their time before the exit. Overall, these results support the grandstanding hypothesis. Further, we find that there is a positive, however,

20

We thank an anonymous referee for highlighting this point.

(6)

0.177∗ ∗ (2.163) −0.988 (−0.155) 0.000 (0.690) 0.032 (0.353) −0.006 (−0.930)

0.167∗ ∗ (2.046) −1.102 (−0.172) 0.000 (0.860) 0.038 (0.421)

0.105 (2.653)

Ln(VC age)

CRSP value-weighted return

(5)

∗∗∗

−2.718 (−0.876) 0.000 (0.045) −0.026 (−0.274)

−0.179 (−1.543) 0.074 (0.767) −0.531∗ ∗ ∗ (−2.580) 0.077 (1.506) 0.000 (0.140) −0.049 (−0.926) −0.327∗ (−1.815)

0.005 (0.089) −0.183 (−1.584) 0.074 (0.759) −0.537∗ ∗ ∗ (−2.632) 0.075 (1.287) 0.000 (0.148) −0.048 (−0.913) −0.325∗ (−1.792)

Yes 66.94 −1958 427

Yes 66.61 −1952 426

−2.928 (−0.469) 0.000 (0.840) −0.011 (−0.125) −0.003 (−0.504)

−2.875 (−0.460) 0.000 (0.950) −0.003 (−0.036)

−0.117 (−1.071) 0.045 (0.473) −0.246 (−1.317) 0.032 (0.649) −0.000 (−0.457) −0.008 (−0.149) −0.311∗ (−1.890)

0.017 (0.330) −0.129 (−1.189) 0.042 (0.448) −0.256 (−1.372) 0.024 (0.422) −0.000 (−0.449) −0.007 (−0.131) −0.310∗ (−1.883)

−0.091 (−0.824) 0.052 (0.548) −0.339∗ (−1.799) 0.038 (0.747) −0.000 (−0.691) −0.018 (−0.327) −0.287∗ (−1.729)

0.037 (0.715) −0.117 (−1.065) 0.046 (0.490) −0.353∗ (−1.878) 0.018 (0.304) −0.000 (−0.698) −0.018 (−0.330) −0.301∗ (−1.812)

Yes 74.02 −2225 480

Yes 73.62 −2219 479

Yes 72.62 −2154 465

Yes 71.94 −2148 464

not significant (except model 4), relation between Fund type and Time to exit, confirming that independent VCs do not rush their exit. As noted by Chemmanur et al. (2014), independent VCs are structured as limited partnerships and have full control over the capital committed by their limited partners. When we consider the company age at the exit as a dependent variable, we find a positive and significant relation between the IPO company age and the VC’s age. The coefficients of all our VC reputation measures are statistically significant, suggesting that companies backed by young venture capital firms are younger than those backed by more reputable VCs. Once again, these results favor the grandstanding explanation. The inverse Mills ratio derived from the 1st step equation is not statistically significant in the 2nd stage model, indicating that endogeneity issue does not significantly affect our results. Panel B of Table 7 reports regression results for M&As using the time to exit and the company age at the M&A exit as dependent variables. We find that the duration before the exit is significantly shorter for young venture capitalists than more established venture capitalists. The coefficient of IPO Market share is positive and statistically significant at the 10% level (0.058, t-statistic = 1.710). The coefficient of ln(VC age) is also positive and statistically significant at the 1% level (0.263, t-statistic = 4.736), suggesting that younger

S.B. Amor and M. Kooli / Journal of Banking and Finance 111 (2020) 105704

11

Table 7 Regressions on the time to exit and firm age at the exit The sample consists of 609 VC-backed companies taken public by IPOs and 830 VC-backed companies exit through acquisitions between 1996 and 2015. Dependent variables are time to exit and firm age at the exit. Variable definitions are provided in the Appendix. ∗ ∗ ∗ , ∗ ∗ , and ∗ indicate statistical significance at the 1%, 5%, and 10% level, respectively. Panel A: IPO regressions Time to exit Firm age at exit Pr(VC reputable =1) Constant

−2.438∗∗∗ (−6.019)

IPO Market share

(1)

0.014∗ (1.674)

Ln(VC age)

(2)

(3)

0.564 (1.519)

1.268∗∗∗ (3.824)

0.264∗∗∗ (4.055)

CRSP value-weighted return

−0.179 (−1.187) −0.014 (−0.033)

Total IPOs in the previous four months Ln(syndicate size) Fraction of equity held by lead VC post-IPO Fund type Ln(1+number of inst. investors) Fraction of shares held by inst. investors Ln(1+number of analysts) Inverse Mills ratio Ln(IPO assets) Ln(1+number of companies lead VC has invested in) VC investment stage

0.090∗ (1.654) 0.509∗∗∗ (7.683) −0.284∗∗ (−2.297)

Industry and year fixed effect Wald test No. of observations Panel A: M&A regressions Time to exit Firm age at exit Pr(VC Pr(VC reputable) =1 Constant

−2.703∗∗∗ (−10.240)

M&A Market share

Total M&As in the previous four months Ln(syndicate size) Fund type Synergy Ln(1+number of inst. investors) Fraction of shares held by inst. investors Ln(1+number of analysts) Inverse Mills ratio Ln(M&A assets) Ln(1+number of companies lead VC has invested in) VC investment stage Industry and year fixed effect Wald test No. of observations

0.148∗∗∗ (2.687) 0.589∗∗∗ (10.271) −0.151 (−1.469)

2.486∗∗∗ (5.726)

0.203∗ ∗ (2.003)

−0.045 (−0.543) −0.187 (−0.840) −0.003∗ ∗ ∗ (−6.525) 0.307∗ ∗ ∗ (4.801) 0.003 (0.775) 0.178 (1.578) −0.116∗∗ (−2.061) −0.011 (−0.311) −0.017 (−0.302) 0.186∗ (1.663)

Yes 78.63 409

Yes 95.12 409

Yes 79.35 409

Yes 31.74 474

(1)

(2)

(3)

(4)

(5)

(6)

1.124∗∗∗ (4.246) 0.058∗ (1.710)

0.320 (1.090)

0.284 (0.874)

1.824∗∗∗ (4.897) 0.056∗ ∗ (1.981)

1.131∗∗ (1.971)

1.182∗∗ (2.150)

0.263∗∗∗ (4.736)

0.596∗∗∗ (3.087) −0.0 0 0∗ ∗ ∗ (−2.853) 0.378∗∗∗ (6.972) 0.007 (0.058) 0.023 (0.329) −0.042 (−1.346) −0.002∗ ∗ ∗ (−4.052) 0.008 (0.221) 0.014 (0.125)

0.526∗∗∗ (2.869) −0.0 0 0∗ ∗ ∗ (−3.115) 0.454∗∗∗ (8.274) 0.031 (0.241) 0.055 (0.797) −0.047 (−1.520) −0.001 (−0.617) −0.012 (−0.325) −0.009 (−0.081)

0.157∗∗∗ (3.812) 0.534∗∗∗ (2.873) −0.0 0 0∗ ∗ ∗ (−2.769) 0.455∗∗∗ (8.267) 0.029 (0.237) 0.054 (0.799) −0.049 (−1.628) −0.001 (−0.406) −0.001 (−0.042) 0.187 (1.196)

Yes 262.9 374

Yes 116.7 374

Yes 109.8 374

VC previous M&As 0.095 (0.337)

(6)

2.020∗∗∗ (4.109)

−0.071 (−0.827) −0.163 (−0.705) −0.004∗ ∗ ∗ (−6.855) 0.295∗∗∗ (4.696) 0.004 (1.005) 0.186 (1.572) −0.124∗∗ (−2.150) −0.010 (−0.249) −0.017 (−0.278) 0.057 (0.538)

Ln(VC age)

CRSP value-weighted return

0.013∗ (1.722)

(5)

0.062∗ (1.797) −0.083 (−0.978) −0.177 (−0.768) −0.004∗ ∗ ∗ (−6.974) 0.293∗∗∗ (4.642) 0.004 (0.997) 0.183 (1.574) −0.115∗∗ (−2.055) −0.008 (−0.218) −0.018 (−0.296) 0.121 (1.007)

VC previous IPOs Prestige

(4)

−0.062 (−0.764) 0.566∗∗ (2.365) −0.001∗ (−1.909) −0.197∗∗ ∗ (−3.528) 0.001 (0.284) −0.208∗ (−1.864) 0.064 (1.029) 0.009 (0.204) −0.018 (−0.316) −0.188∗ (−1.852)

−0.113 (−1.441) 0.411∗ (1.775) −0.001∗ ∗ ∗ (−3.109) −0.113∗∗ (−1.991) −0.001 (−0.370) −0.100 (−0.836) 0.0 0 0 (0.003) −0.047 (−1.085) 0.005 (0.089) −0.059 (−0.544)

0.099∗ (1.741) −0.175∗ (−1.810) 0.372 (1.420) −0.002∗ ∗ ∗ (−2.997) −0.205∗∗∗ (−3.239) 0.002 (0.454) −0.108 (−0.800) 0.071 (0.979) −0.014 (−0.265) −0.042 (−0.587) −0.229 (−1.390)

Yes 90.14 474

Yes 89.65 474

0.301∗∗ (2.047)

0.793∗∗∗ (2.898) −0.0 0 0 (−0.669) 0.118∗ (1.683) −0.058 (−0.292) 0.065 (0.735) −0.040 (−0.990) −0.002 (−1.186) −0.008 (−0.183) −0.094 (−0.709)

0.425∗ (1.883) −0.0 0 0 (−0.093) 0.049 (0.757) −0.243∗ (−1.693) 0.111 (1.449) −0.053 (−1.501) −0.0 0 0 (−1.324) −0.009 (−0.261) 0.149 (1.163)

0.156∗∗ (1.969) 0.784∗∗∗ (2.807) −0.0 0 0 (−0.079) 0.157∗∗ (2.085) −0.355∗ (−1.883) 0.157∗ (1.679) −0.058 (−1.363) 0.0 0 0 (0.218) 0.001 (0.014) 0.162 (0.776)

Yes 19.28 434

Yes 20.07 689

Yes 24.92 434

12

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Table 8 Regressions on IPO underpricing and offering size The sample consists of 609 VC-backed companies taken public by IPOs and 830 VC-backed companies exit through acquisitions between 1996 and 2015. Dependent variables are level of underpricing and IPO offer size. Variable definitions are provided in the Appendix. ∗ ∗ ∗ , ∗ ∗ , and ∗ indicate statistical significance at the 1%, 5%, and 10% level, respectively. Panel A: IPO regressions

Constant IPO Market share

Underpricing

Offer size

(1)

(2)

(3)

(4)

(5)

(6)

−1.678∗ ∗ ∗ (−5.175) −0.625 (−0.548)

−0.756∗ ∗ ∗ (−3.595)

−0.842∗ ∗ ∗ (−4.094)

1.878∗ ∗ ∗ (6.156) −0.007 (−0.858)

2.216∗ ∗ ∗ (8.896)

2.248∗ ∗ ∗ (9.279)

Ln(VC age)

−0.051∗ (−1.895)

VC previous IPOs Prestige Ln(IPO age) CRSP value-weighted return Total IPOs in the previous four months Ln(syndicate size) Fraction of equity held by lead VC post-IPO Fund type Ln(1+number of inst. investors) Fraction of shares held by inst. investors Ln(1+number of analysts) Bubble dummy Tech dummy Industry and year fixed effects No. of observations Adjusted R2 Panel B: M&A regressions

−0.060 (−0.750) −0.145∗ ∗ (−2.221) 0.500∗ ∗ (2.214) 0.002∗ ∗ ∗ (3.402) 0.111∗ ∗ (2.104) −0.000 (−0.014) 0.048 (0.514) 0.476∗ ∗ ∗ (7.921) −0.022 (−0.524) −0.029 (−0.483) 0.471∗ ∗ ∗ (6.321) −0.060 (−0.889) Yes 411 0.367

M&A Market share

∗

2.651 (1.826) 0.133∗ (1.894)

(3) ∗∗

−2.540 (−2.579)

Total M&As in the previous four months Synergy Ln(syndicate size) Fund type Ln(1+number of inst. investors) Fraction of shares held by inst. investors Ln(1+number of analysts) Industry and year fixed effects No. of observations Adjusted R2

−0.813 (−0.803)

(4)

0.069∗ ∗ (2.222)

0.923∗ ∗ ∗ (2.353)

VC previous M&As

CRSP value-weighted return

0.035 (0.494) −0.032 (−0.476) −0.774∗ ∗ ∗ (−3.788) −0.001∗ ∗ ∗ (−2.857) −0.011 (−0.213) 0.002 (0.687) −0.006 (−0.072) 0.696∗ ∗ ∗ (13.108) −0.128∗ ∗ ∗ (−3.650) 0.169∗ ∗ ∗ (3.189) 0.048 (0.703) −0.049 (−0.775) Yes 411 0.574

−0.325 (−1.651) −1.737∗ ∗ ∗ (−3.161) 0.000 (0.340) 0.252 (1.034) 0.578∗ ∗ ∗ (3.369) −0.032 (−0.082) −0.275 (−1.614) −0.172∗ ∗ ∗ (−3.517) 0.079 (0.641) Yes 593 0.16

−0.008 (−0.143) −0.092∗ ∗ (−2.089) −0.736∗ ∗ ∗ (−4.539) −0.001∗ ∗ ∗ (−3.892) −0.050 (−1.340) 0.001 (0.458) −0.052 (−0.766) 0.710∗ ∗ ∗ (16.544) −0.133∗ ∗ ∗ (−4.429) 0.091∗ ∗ (2.105) 0.044 (0.804) −0.002 (−0.047) Yes 441 0.593

−0.010 (−0.497) 0.008 (0.135) −0.087∗ (−1.954) −0.708∗ ∗ ∗ (−4.322) −0.001∗ ∗ ∗ (−3.926) −0.055 (−1.440) 0.001 (0.426) −0.048 (−0.651) 0.707∗ ∗ ∗ (16.124) −0.127∗ ∗ ∗ (−4.144) 0.080∗ (1.826) 0.049 (0.897) −0.011 (−0.224) Yes 429 0.587

Ln (deal value)

(2)

Ln(VC age)

Ln(M&A age)

−0.019 (−1.193) −0.059 (−1.222) −0.003 (−0.088) 0.217 (1.571) 0.001∗ ∗ ∗ (3.126) 0.030 (0.946) −0.000 (−0.274) −0.048 (−0.780) 0.260∗ ∗ ∗ (6.977) −0.018 (−0.700) 0.020 (0.541) 0.341∗ ∗ ∗ (7.555) 0.025 (0.616) Yes 399 0.340

Acquisition premium (1)

Constant

−0.059 (−1.247) 0.005 (0.125) 0.221 (1.624) 0.001∗ ∗ ∗ (2.858) 0.025 (0.815) −0.000 (−0.145) −0.037 (−0.651) 0.257∗ ∗ ∗ (7.101) −0.010 (−0.423) 0.023 (0.638) 0.327∗ ∗ ∗ (7.329) 0.015 (0.378) Yes 411 0.337

−0.002 (−0.052)

−0.183 (−1.491) −1.328∗ ∗ ∗ (−3.012) 0.000 (1.287) 0.297 (1.596) 0.588∗ ∗ ∗ (4.257) 0.096 (0.330) 0.019 (0.174) −0.005∗ ∗ (−2.258) 0.028 (0.272) Yes 593 0.39

(5)

(6)

−0.623 (−1.468)

−0.478 (−1.216)

0.044 (0.540) 0.413∗ ∗ ∗ (2.477) −0.062 (−0.482) −1.475∗ ∗ ∗ (−3.155) 0.000 (0.757) 0.137 (0.731) 0.526∗ ∗ ∗ (3.518) −0.044 (−0.134) −0.023 (−0.208) −0.005∗ ∗ (−2.051) 0.035 (0.323) Yes 568 0.35

−0.094 (−1.183) −0.597∗ ∗ (−2.019) 0.001∗ ∗ ∗ (5.317) 0.299∗ ∗ ∗ (2.662) 0.173∗ (1.935) 0.185 (1.146) 0.539∗ ∗ ∗ (11.477) 0.001∗ ∗ (2.309) −0.028 (−0.511) Yes 461 0.29

−0.065 (−0.968) −0.360 (−1.360) 0.001∗ ∗ ∗ (5.599) 0.248∗ ∗ (2.485) 0.142∗ (1.785) 0.062 (0.444) 0.518∗ ∗ ∗ (11.990) 0.001∗ (1.828) 0.005 (0.109) Yes 810 0.29

0.121 (0.792) −0.050 (−0.742) −0.486∗ (−1.826) 0.001∗ ∗ ∗ (5.817) 0.270∗ ∗ ∗ (2.644) 0.151∗ (1.919) 0.054 (0.383) 0.476∗ ∗ ∗ (10.849) 0.001∗ (1.701) 0.042 (0.820) Yes 775 0.28

S.B. Amor and M. Kooli / Journal of Banking and Finance 111 (2020) 105704

and less reputed VCs exit through acquisitions earlier than older and more reputed VCs. Similarly, we find that the coefficient of VC previous M&As is positive and significant at the 1% level. Thus, the logged survival time (and hence, the expected duration) is an increasing function of the venture capital firm’s age. Using firm age at exit as a dependent variable, we find that coefficients of IPO Market share, ln(VC age), and VC previous M&As are all positive and significant at the 5% level, suggesting that VC’s reputation is associated with a higher company age at the acquisition date. Overall, these results are consistent with the grandstanding hypothesis. Again, the inverse Mills ratio derived from the 1st step equation is not statistically significant in the 2nd stage model, indicating that endogeneity issue does not significantly affect our results. 3.4. VC firms and the cost of building a reputation

Table 9 Logit analysis of IPO and M&A exits The sample consists of 609 VC-backed companies taken public by IPOs and 830 VC-backed companies exit through acquisitions between 1996 and 2015. The dependent variable is a dummy variable equals 1 if the private firm goes public and 0 if it is acquired. Independent variable definitions are provided in the Appendix. ∗ ∗ ∗ , ∗ ∗ , and ∗ indicate statistical significance at the 1%, 5%, and 10% level, respectively. (1) Constant IPO Market share

21 Following Loughran and Ritter (2004), we added to the previous set of control variables a bubble dummy variable to control for the internet bubble period, and a Tech dummy variable to control for technology IPOs.

(2) ∗∗∗

8.378 (7.209) 0.181∗ ∗ (2.564)

(3) ∗∗∗

8.910 (7.327)

Ln(Total previous IPOs and M&As ) Ln(firm age)

Fund type dummy VC investment stage Ln(syndicate size) Ln(1+number of inst. investors) Fraction of shares held by inst. inv Ln(1+number of analysts) Industry and year fixed effect No. of observations Adjusted R2

9.339∗ ∗ ∗ (8.050)

0.365∗ (1.744)

Ln(VC age)

CRSP value-weighted return

Earlier, we noted that venture capital firms are willing to incur the costs of higher underpricing to build their reputation. In this sub-section, to further examine this result, we run a set of regressions using underpricing and IPO size (for the IPO sample) and M&A premium and deal size (for the M&A sample) as dependent variables. We also separately consider different VC reputation measures as independent variables, and we control for IPO or M&A characteristics. Panel A of Table 8 reports regression results for the IPO exit.21 Using the logarithm of the venture capital firm’s age (model 2), we confirm that greater underpricing is significantly associated with younger venture capital firms. Our results imply that young venture capital firms could incur the cost of higher underpricing if they are looking to increase their reputation to raise more capital. Furthermore, the control variable Ln(IPO age) has a negative and statistically significant coefficient (−0.145, t-statistic = −2.221, model 1), confirming that younger IPO firms are more underpriced than older IPO firms. We also find in models 1, 2, and 3 that the underwriter’s prestige has a negative, however, not significant effect on the level of underpricing, while Bubble dummy coefficient is positive and significant at the 1% level, confirming the effect of the internet bubble period on IPO pricing. Using IPO size as an alternative measure of reputation signal does not alter our conclusions (models 4, 5, and 6). Our results are, however, not statistically significant. In panel B of Table 8, we examine the M&A sample. To make the parallel with the IPO sample, we consider M&A premium and deal size. We run a set of regressions using M&A premiums (models 1, 2, and 3) and M&A deal sizes (models 4, 5, and 6) as dependent variables. We also separately consider different VC reputation measures as independent variables, and we control for M&A characteristics. The results show that there is a positive and significant relation between M&A premium and VC reputation. Coefficients of M&A Market share, Ln(VC age), and VC previous M&As are positive and statistically significant. Thus, as young VCs are under strong pressure to establish a successful track record in venture investing, they are willing to accept lower acquisition prices to obtain profitable exits sooner. Further, we find that younger VCs participate in small deals to build their reputation (model 4). The positive coefficients of M&A market share is positive and statistically significant at the 5% level. Further, we find that Fund type has a negative and statistically significant coefficient, confirming Ivanov and Xie (2010)’s result that targets with CVC backing tend to receive higher takeover premiums than their counterparts with independent VC backing.

13

0.299 (1.265) 2.542∗ ∗ ∗ (2.888) 0.228 (0.626) −0.137 (−0.475) 1.214∗ ∗ ∗ (5.586) −2.864∗ ∗ ∗ (−10.033) −0.019∗ ∗ (−2.057) 1.057∗ ∗ ∗ (3.937) Yes 835 0.696

0.253 (1.115) 2.234∗ ∗ ∗ (2.890) −0.162 (−0.467) −0.145 (−0.544) 1.144∗ ∗ ∗ (5.914) −3.007∗ ∗ ∗ (−10.663) −0.049∗ ∗ ∗ (−6.189) 1.130∗ ∗ ∗ (4.374) Yes 953 0.695

0.014 (0.121) 0.283 (1.297) 2.496∗ ∗ ∗ (3.193) 0.055 (0.158) −0.289 (−1.092) 1.179∗ ∗ ∗ (6.144) −2.910∗ ∗ ∗ (−11.187) −0.047∗ ∗ ∗ (−5.794) 0.970∗ ∗ ∗ (3.996) Yes 951 0.685

3.5. VC reputation and the exit choice between IPOs and M&As In this subsection, we extend previous analyses by empirically examining the effect of VC reputation on the exit choice (IPOs vs. M&As). The exit likelihood is regressed on VC reputation along with the other independent variables used in previous tests. The dependent variable is a dummy variable equals 1 if the private firm goes public and 0 if it is acquired. Formally, we estimate the following logistic model:

P rob (1 i f IP O or 0 i f M&A) = b0 + b1V C reputation measure f or IP Os/M&As +b2Control variables + ε

(5)

The results are presented in Table 9. We find that the coefficient of IPO market share (model 1) is positive and statistically significant at the 5% (0.181, t-statistic = 2.564), the coefficient of Ln(VC age) (model 2) is positive and statistically significant at the 10% (0.365, t-statistic = 1.744), and the coefficient of total VC previous IPOs and M&As (model 3) is positive but statistically not significant (0.014, t-statistic = 0.121). Overall, VC reputation affects positively and significantly the probability of an IPO exit over an acquisition exit. These observations confirm the importance of VC reputation on the likelihood of exits via IPOs or acquisitions. We also find that market return has a positive and significant effect on the probability of an IPO exit over an acquisition exit. The coefficient of CRSP value-weighted return is positive and statistically significant at the 1% level (models 1, 2 and 3), confirming the “hotness” of the IPO market relative to the takeover market on the decision to go public versus to be acquired. Further, we find that firms with larger number of institutional investors are more likely to be acquired, while firms followed by more analysts are more likely to opt for an IPO. The coefficient of Ln(1+number of inst. investors) is negative and statistically significant at the 1% level, and the coefficient of Ln(1+number of analysts)

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S.B. Amor and M. Kooli / Journal of Banking and Finance 111 (2020) 105704

is positive and statistically significant at the 1% level (models 1, 2 and 3). Also, we find that the coefficient of Ln(VC syndicate size) is positive and statistically significant at the 1% level (models 1, 2, and 3). Thus, privately held companies that are backed by larger VC syndicates are more likely to go public than to be acquired. We also find that firms that receive their VC funding in the early/seed stage of development lifecycle are more likely to be acquired. The coefficient of VC investment stage is negative, however, not significant. This result is in line with Bayar and Chemmanur (2011)’s suggestion that later stage firms, more viable against product market competition are more likely to go public, while earlier-stage firms, less viable against product market competition, are more likely to be acquired.

Appendix. Definitions of the variables used in this paper

Variables VC reputation: IPO Market share

M&A Market share

Ln(VC age) VC previous IPOs or M&As IPO or M&A characteristics: Underpricing

4. Conclusion Previous literature on the venture capital industry has often considered that the most effective way for a VC firm to signal its quality is to conduct a successful IPO. However, the appeal of M&As has become popular over the last decade. Masulis and Nahata (2011) point out that on average IPOs occur in about 10% of VC investments, whereas M&As occur approximately in 20% of VC investments. Despite this upward trend of M&A as an exit route, studies on the role of VC on acquisitions of privately held firms remain scarce. We help fill this gap by examining the grandstanding hypothesis via IPOs as well as via M&As for VC firms from 1996 to 2015. Our results show that not only taking companies public by IPOs has an effect on young venture capitalists’ reputation and their ability to raise more capital but also succeeding to sell the company to a public acquirer is an important channel for young venture capital firms to easily access new investments and to build their reputation. Thus, the desire to grandstand is similar in young venture capital firms conducting IPOs or M&As. Our results are robust to different VC reputation measures and controlling for selection issue. We also find that for venture capital firms choosing to exit by IPOs, the size of the next fund raised depends on the number of IPOs previously financed by the VC and VC age. Similarly, for venture capital firms choosing to exit by selling the company to a public acquirer, the size of the next fund raised depends on the number of M&As previously financed and VC age. Furthermore, we find that IPO or M&A timing is associated with reputational concerns. The time it takes a company backed by a young venture capital firm to be acquired is even less than the time it takes to go public by IPO. This result suggests that an exit strategy by acquisition has the same importance as an IPO in explaining the incentives of young venture capital firms to grandstand. Unlike Gompers (1996), we find no evidence that young venture capitalists were able to raise more capital quickly after an IPO or an M&A than more established venture capitalists. While reputational concerns could be a driver for young VC firms to raise future funds quickly after the exit, experience, skills, and networks of well-established VC firms could help them to easily find capital providers as soon as possible after the exit (Hochberg et al., 2007). Moreover, we find that to build their reputation young VC firms are willing to bear the cost of higher underpricing in the case of IPO exits and to accept a lower premium in the case of M&A exits. We also find that independent VCs are significantly able to quickly raise new funds following the acquisition. In addition to testing the grandstanding hypothesis, this study illustrates the importance of considering both IPOs and M&As as exit channels for privately held firms. It also examines the effect of VC reputation on exit choice and confirms that the presence of a reputed VC significantly affects the probability of an IPO exit over an acquisition exit.

IPO size Prestige Ln(IPO or M&A age) Ln(assets) Acquisition premium

Ln(deal value) Synergy

Ln(1+number of inst. investors)

Fraction of shares held by inst. investors Ln(1+ number of analysts)

Bubble dummy

Tech dummy

Market conditions CRSP value-weighted return Total IPOs in the previous four months Total M&As in the previous four months VC characteristics Time to exit VC syndicate size Fund type Fraction of equity held by lead VC post-IPO Number of companies lead VC has invested in VC investment stage

Definitions

The VC’s dollar market share of all venture-backed IPOs in the preceding 3 calendar years The VC’s dollar market share of all venture-backed M&As in the preceding 3 calendar years The natural logarithm of the lead venture capital firm’s age in years Total number of previous IPOs or M&A conducted by the lead venture capital The difference between the first day closing price and the offer price given as a percentage of the offer price The natural logarithm of the total capital raised at the time of the IPO Dummy variable set to one if the IPO lead underwriter has an updated Carter and Manaster (1990) of eight or more, else zero. The natural logarithm of company’s age at the effective date of the IPO or M&A in years The natural logarithm of the total asset of the IPO or target firm A proxy defined as the total deal value divided by the total sales of the target before the announcement date. The natural logarithm of acquisition deal value Dummy variable taking the value of one if the company acquired is in the same three digits SIC code as the public acquirer, else zero. Logarithm of 1+ the number of institutional investors at the end of the first quarter following the exit date Number of shares held by all institutional investors divided by total shares outstanding Logarithm of 1+ the number of analysts following the company prior the exit date Dummy variable taking the value of one if the IPO occurred during 1999–2000, else zero Dummy variable taking the value of one if the IPO is in the technology business (according to Loughran and Ritter (2004)), else zero. The value-weighted CRSP market return for the year of the IPO or M&A. The cumulative number of IPOs in the previous four months The cumulative number of M&As in the previous four months The time between the first investment date by the lead venture capital firm and the exit date (IPO or M&A) The size of VC syndicate Dummy variable set to one if VC is independent and zero if it’s a corporate investor Fraction of equity held by lead VC post-IPO Number of companies lead VC has invested in Dummy variable set to one if VC invested at early/seed stage, else zero

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