Jan 22, 2013 - performance of serial entrepreneur backed startups and VCs funding these ... Lang Fellowship and the PSC-
Success is good but failure is not so bad either: serial entrepreneurs and venture capital contracting*
Raj Nahata Baruch College, CUNY One Bernard Baruch Way New York, NY 10010 Phone: 646-312-3473 Email:
[email protected]
January 22, 2013
Abstract: I analyze an important determinant – prior entrepreneurial experience – of financial contracting in U.S. based startups backed by venture capitalists (VCs). In companies founded by serial entrepreneurs, I find the contracts to be more startup-favorable in the following ways. Founders and other insiders retain not only greater board control but also suffer less dilution of equity in their dealings with VCs. Second, founders are more likely to retain their CEO positions. Third, startups extract higher valuations from the VCs, reflecting their greater bargaining power arising from prior entrepreneurial experience. Interestingly, these results obtain despite poorer performance of serial entrepreneur backed startups and VCs funding these startups earlier in their lifecycles. Finally, far from getting punished for previous failures, even unsuccessful serial entrepreneurs obtain better contracts than first-time entrepreneurs. This seems to suggest that entrepreneurial learning outweighs any stigma of failure associated with previously unsuccessful serial founders, a factor consistent with thriving entrepreneurship in the United States.
JEL Classification Code: G24
Keywords: Venture Capital; Financial Contracting; Serial Entrepreneurship
______________________ * I thank Markus Taussig and seminar participants at Baruch College and the Economics of Innovation and Entrepreneurship Conference at Queen‟s University for valuable feedback. Financial support from the Eugene Lang Fellowship and the PSC-CUNY Grant programs is gratefully acknowledged.
1. Introduction Capital constraints are generally regarded as one of the primary barriers to entrepreneurship (Evans and Leighton, 1989; Evans and Jovanovic, 1989; Holtz-Eakin, Joulfaian, and Rosen, 1994; Blanchflower and Oswald, 1998). At the same time, there exist many instances of entrepreneurs starting multiple businesses in their lifetime.1 Research suggests that founders with prior entrepreneurial experience, particularly, previously successful entrepreneurs, are more likely to receive venture capital funding (Hsu, 2007) and also succeed in their new businesses (Gompers, Kovner, Lerner, and Scharfstein, 2010). In this study, I empirically analyze the impact of serial entrepreneurship on one important dimension of capital-raising, namely the structure of financial contracting between the providers and recipients of venture capital (VC). Using U.S. data, I address two basic questions. First, what is the impact of prior entrepreneurial experience on the deal terms negotiated between the startups and the venture capitalists–are these terms less onerous for serial entrepreneur backed startups? And second, how are the terms different for previously unsuccessful serial entrepreneurs? Analysis of terms and financial contracts in the context of capital-raising by entrepreneurs is important for several reasons. First, not only is scarcely-available capital vital for cash-starved startups facing severe information asymmetry and adverse selection problems, but also the terms on which it is raised are extremely important. For example, access to slightly cheaper capital can significantly affect a fledgling company‟s survival and performance. Second, the analysis adds to a growing literature on VC contracting by empirically investigating an important determinant–prior entrepreneurial experience–of financial contracting between the entrepreneurs and venture investors.2 Finally, distinguishing serial entrepreneurs by their previous performance, the study highlights whether or not previously unsuccessful serial founders suffer in terms of the contractual terms they are able to negotiate for their new businesses. Conditional on receiving venture capital, if they do suffer, it is consistent with the so-called „stigma of failure‟ attached to unsuccessful entrepreneurship, a common notion at least outside the U.S. On the other hand, if they don‟t, it supports the view that regards entrepreneurship as more of a learning process, which in turn contributes to innovation and economic growth. “The secrets of serial success”, The Wall Street Journal, August 20, 2007 Sophisticated contracts are frequently employed to overcome the agency problems between outside investors and founders of early-stage companies whose assets are largely intangible and knowledge based. Some studies that discuss contracting mechanisms used to solve potential agency problems between investors and entrepreneurs, particularly in the context of venture capital financing include Admati and Pfleiderer (1994),Bengtsson and Sensoy (2011a, 2011b), Berglof (1994), Lerner (1995), Hellmann (1998), Casamatta (2003), Kaplan and Stromberg (2001, 2003, 2004), Kaplan, Martel, and Strömberg (2007), De Bettignies (2008), Cumming (2008), and Masulis and Nahata (2009). 1 2
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In this study, I specifically address the following questions in the context of VC financing. Are serial entrepreneurs able to retain more control rights and suffer less dilution of equity by virtue of their previous entrepreneurial experience? Second, are they more likely to survive as CEOs of their firms? Third, how does their prior experience affect the time it takes to raise VC capital? Fourth, are the startup share prices paid by VCs higher for serial entrepreneur-backed startups? And finally, what are previously unsuccessful serial entrepreneurs able to negotiate for their companies? These are issues that VCs and entrepreneurs alike often grapple with when deciding the terms of their financial contracts. Furthermore, pricing of shares, allocation of control rights, share ownership, and founder-CEO duality are likely to be central to their negotiations regarding VC investment terms. The key challenge to analyzing these questions is the lack of detailed publicly-available data on financial contracts. By circumventing this issue and focusing on VC-backed IPOs where public disclosure is required, I am able to hand-collect much cleaner and finer information such as the allocation of shareholdings among the company insiders (including founders) and outside investors including the VCs, distribution of board seats, founders‟ retention as CEOs (founder-CEO duality), and then relate them to prior entrepreneurial experience.3 I am also able to impute the average price paid by the VC syndicate for startup shares and relate it to prior entrepreneurial experience of the founders. While all these data allow me to undertake a much richer analyses that otherwise would not be possible, the downside is the constraint of only studying VC-backed IPOs, rather than all VC-backed companies, although doing so has the advantage of analyzing contractual arrangements in successful companies. To preview the results, I find that even after controlling for the size of VC investment, serial entrepreneurs suffer less dilution of equity and retain greater board control in their dealings with VCs. Furthermore, they are also able to survive more often as CEOs. Interestingly, all of these findings also hold for previously unsuccessful serial entrepreneurs. This indicates that prior entrepreneurial experience confers a distinct benefit (for instance, through better bargaining power) on account of reputation (for successful serial entrepreneurs) and learning (for both successful and not so successful founders) which enables serial entrepreneurs to negotiate better contracts with VCs. The results are also consistent with the notion that stigma of failure, relatively speaking, seems not to be as big of a barrier to entrepreneurship in the U.S. 3
Commercial databases do not report many of the variables used in this study or their coverage on some items is replete with errors. For example, VentureXpert reports no board seats for VCs in several of their portfolio companies (Bengtsson and Hsu, 2012), whereas Kaplan and Stromberg (2003) and Masulis and Nahata (2009) find that VCs almost always have some board representation.
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Next, I impute the valuation offered to startups when VCs buy startup shares. Theoretical work such as Koskinen, Rebello, and Wang (2011) suggests that startups should be able to extract higher valuations when they possess a greater bargaining power (through prior entrepreneurial learning and experience, for example). I find this to be the case: the average share price paid by the VC syndicate is significantly higher for serial entrepreneur backed startups. However, most of this effect comes from previously successful entrepreneurs. But interestingly, there is no differential share pricing between startups backed by previously unsuccessful and novice entrepreneurs. I also find that startups backed by serial entrepreneurs (including previously unsuccessful ones) are funded by VCs faster. Raising capital is a non-trivial exercise for startups and early access to capital is crucial for their progress and survival. It is also important for maintaining a first mover advantage, something that many startups critically depend on for tackling competition. A longer time spent in raising capital keeps scarce resources away from other crucial tasks (technology advancement, product and business development, human capital deployment, etc.) necessary for startups‟ progress. While not directly related to contract features, this result is interesting because although the serial entrepreneur backed startups obtain VC funding faster, yet they retain more influence (via more favorable contract terms) over their operations than other startups. In summary, serial entrepreneurs obtain better deals in their contracts by retaining more board control, suffering less dilution of equity, and by surviving more often as CEOs. Previously successful serial entrepreneurs also obtain higher valuations for their shares. This is despite obtaining VC funding earlier after the startups‟ founding. Given these findings, a natural question that arises is whether these results are an artifact of startups‟ performance. Better performing startups would confer more negotiating power on their founders resulting in better contractual terms. To shed light on this issue, I analyze three related metrics of industry-adjusted performance – profit margin, return on assets (ROA), and asset turnover ratio. Contrary to intuition, however, I find that serial entrepreneur-backed startups have poorer performance than novice entrepreneur-backed startups. This is especially true for companies backed by previously successful entrepreneurs. In particular, the profit margin (industry-adjusted) of startups backed by serial entrepreneurs is significantly lower than that of other startups. The industry-adjusted ROA and asset turnover ratios also obtain a similar pattern but they are not statistically different across the two types of startups. This implies it is something about serial entrepreneurship which results in better contractual terms for entrepreneurs and their companies. The learning, experience, and reputation amassed through prior entrepreneurship holds these repeat
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founders in good stead and enhances their bargaining power in negotiations even with sophisticated outside investors like VCs. Thus, the analysis offers new insights into the interaction between entrepreneurs and VCs by empirically assessing the importance of serial entrepreneurship and how it affects contracting terms. In the VC industry, characterized by severe asymmetric information problems, an enduring challenge remains the sorting of investments which entails pronounced search costs, time, and effort. A critical factor for VCs when they evaluate business plans is the founders‟ track record. Prior entrepreneurial experience, particularly successful, may significantly mitigate adverse selection problems and reduce to a large extent VCs‟ search costs. Thus, from a broader perspective, the study also contributes to the extensive literature on how VC firms overcome the informational problems associated with startup financing. The remainder of the paper is organized as follows. Section 2 reviews the related literature and develops testable hypotheses. Section 3 discusses data collection procedures and describes sample properties. Empirical results follow in Section 4. Section 5 reports some additional tests. Finally, Section 6 summarizes and concludes.
2. Hypothesis Development This study is related to several branches of corporate finance research. First is the research on capital-raising by startups or the burgeoning literature in entrepreneurial finance. Several studies characterize capital constraints as a primary barrier to entrepreneurship (Evans and Leighton, 1989; Evans and Jovanovic, 1989; Holtz-Eakin, Joulfaian, and Rosen, 1994; Blanchflower and Oswald, 1998). In surveys too, entrepreneurs often cite the difficulty in raising capital as one of the main challenges to their companies‟ survival and growth (Blanchflower and Oswald, 1998). While on one hand, banks are reluctant to fund risky startups, on the other, VC funding is too costly for many companies to afford. Thus, one of the primary issues related to seeking capital and also the focus of this study is the terms on which capital is raised since the contractual features directly affect the startups‟ survival likelihood and future performance. Indeed, investor favorable contracts can make funding very expensive for startups and are akin to harshly binding capital constraints. Anecdotal evidence suggests that many founders often overlook the proper negotiation of contracts or are not adept in specifics of contractual terms. These can make negotiations expensive and difficult. However, there are likely to be some entrepreneurs who are better than others at negotiating deals with the VCs. For example, experienced founders with the benefit of prior entrepreneurial experience are likely to be particularly well versed in their negotiations with external investors. A
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second branch of literature studies what MacMillan (1986) calls “habitual entrepreneurs” who generate multiple businesses in their lifetimes. While research on habitual or serial founders in the entrepreneurship literature is quite profound, this aspect has only now begun to receive attention in the finance literature. There is evidence that serial entrepreneurs, particularly previously successful ones, are more likely to raise VC funds (Hsu, 2007), are more skillful (Gompers et al. 2010), and also generate better performance in their following ventures. A potentially interesting question that arises thus is: do serial entrepreneurs by virtue of their experience and learning, accumulated through previous ventures, negotiate better terms with external investors? And how does previous success of serial founders affect the contractual features? These issues are the main focus in this study. In related research, Bengtsson and Sensoy (2011a) suggest that in companies founded by previously successful serial entrepreneurs, VCs obtain weaker downside protections whereas Gompers et al. (2010) find that serial successful founders do not receive more favorable valuations from VCs. Although the received evidence seems conflicting, contracting with serial entrepreneurs is not the main focus in those studies and also the contractual terms analyzed in those are different from this paper. Third, this paper adds to the empirical literature on VC financial contracting. Most financial contracting theories focus on the conflicts of interest between a principal (investor) and an agent (entrepreneur) and devise contracting mechanisms to mitigate those conflicts.4 Although conflicts are likely to be plentiful in risky startups, this study focuses more on relative bargaining power of insiders and outside investors. In so doing, it serves to enhance our understanding of VC financial contracting by investigating one important determinant–prior entrepreneurial experience–of financial contracts between entrepreneurs and venture investors. For example, one can think of previously successful entrepreneurs as having the benefit of both reputation and learning, which can positively affect the capital raising process. On the other hand, the novice entrepreneurs possess neither characteristic and their negotiations with VCs are likely to reflect their entrepreneurial inexperience that can adversely affect the terms they receive in their contracts. For the third subset of entrepreneurs, namely the previously unsuccessful entrepreneurs, their impact on capital raising process is not as straightforward. In his theory paper, Landier (2006) characterizes two types of equilibria for previously unsuccessful serial founders. First is the socalled “conservative equilibrium”, in which capital-raising is much more challenging for failed entrepreneurs. Failed entrepreneurs suffer from the so-called “stigma of failure” that adversely affects their reputation and entrepreneurial future. As the following quotes excerpted from Landier 4
See Hart (2001) for a relatively recent overview on the topic. Also, see footnote 2.
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(2006) point out, the stigma of failure is a real barrier to entrepreneurship in several countries around the world. The Economist, 1998: “If you start a company in London or Paris and go bust, you have just ruined your future; do it in Silicon Valley and you have simply completed your entrepreneurial training.” MITI, Japan, 2000: “There is also a Japanese stigma against failure, which discourages risktaking activities. It is often said that there is no second chance for Japanese; an American can fail two or three times before succeeding. There has been imbalance between big risk and little reward in Japan.” On the other hand, in the so-called “experimental equilibrium” of Landier (2006), capitalraising is only slightly more difficult for failed entrepreneurs. This equilibrium is consistent with a large literature in entrepreneurship that suggests that habitual entrepreneurs are more likely to view failure as a source of learning that contains lessons for improved performance in subsequent ventures (Politis, 2008; Politis and Gabrielsson, 2009) or that failure acts as a “stepping stone” to future success by providing entrepreneurs an instrument to learn “what works and what doesn't” (Sarasvathy and Menon, 2002).5 As well, some evidence exists of a more forward-looking outlook toward entrepreneurship in United States, particularly Silicon Valley, which is relatively more receptive of prior failure (Cardon, Stevens, and Potter, 2011). When it comes to contract negotiations, one of the primary issues entrepreneurs grapple with is how much equity and control to allocate to external investors. These decisions affect the startups in multiple ways. For instance, greater share ownership for VCs in the startups not only confers more leverage on VCs but also implies a higher cost of equity capital since insiders suffer higher dilution of equity. Similarly, allocation of board seats to external investors is a very contentious issue as relative board power affects important decisions that often determine the startups‟ strategic direction. If prior entrepreneurial experience and learning matter, they should affect contract negotiations with the VCs. Thus, relating the type of entrepreneur to allocation of ownership and control rights leads to the following two null hypotheses: H1N: Irrespective of their past performance, serial entrepreneurs suffer less dilution of equity in their startups by negotiating less share ownership for VCs than novice entrepreneurs. H2N: Irrespective of their past performance, serial entrepreneurs retain more control over their startups than first-time entrepreneurs.
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See also Sitkin (1992), Harvey and Evans (1995), Reuber and Fischer (1999), Zacharakis, Meyer, and DeCastro (1999), Savitsky, Epley, and Gilovich (2001), Cope (2005), and Cope (2011).
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Per the null hypotheses, all serial entrepreneurs have an advantage in contract negotiations compared to novice entrepreneurs. As discussed above, while previously successful entrepreneurs have the benefit of reputation and track record, the previously unsuccessful entrepreneurs benefit from their learning amassed through past entrepreneurial experience. The above two null hypotheses are thus consistent with the notion of accumulated learning through past entrepreneurial experiences and the “experimental equilibrium” of Landier (2006). On the other hand, the “conservative equilibrium” that stigmatizes serial founders for their past failures leads to the following two alternate hypotheses: H1A: Serial entrepreneurs that were unsuccessful in the past relinquish more share ownership in favor of VCs and suffer more equity dilution in their startups relative to other founders including first-time entrepreneurs. Previously successful serial entrepreneurs suffer the least dilution of equity in their startups. H2A: Serial entrepreneurs that were unsuccessful in the past retain less control over their startups relative to other founders including first-time entrepreneurs. Previously successful serial entrepreneurs retain the most control over their startups. In addition to equity ownership and board seats, yet another potent way for the founders to retain control over their firms is through their CEO positions (founder-CEO duality). An extensive literature in corporate governance argues that CEO-Chair duality (CEOs who are also the Chairpersons) is an important mechanism through which CEOs enhance their power in their firms. Retaining their CEO positions may also be important for founders because VCs are active investors and commonly replace founder-CEOs with outside CEOs during the time they are invested in the startups (Hellmann and Puri, 2002). Prior research also suggests that VCs‟ right to fire the founderCEOs is a common feature in contracts between the startups and VCs (Hellmann, 1998). Following the previous arguments that relate the type of entrepreneur to control rights, I have the following null and alternate hypotheses: H3N: Irrespective of their past performance, serial entrepreneurs are more likely to survive as CEOs than first-time entrepreneurs. H3A: Serial entrepreneurs that were unsuccessful in the past are less likely to survive as CEOs relative to other founders including first-time entrepreneurs. Previously successful serial entrepreneurs are most likely to survive as CEOs in their startups. For previously unsuccessful entrepreneurs, the null and alternate hypotheses are consistent with the “experimental” and “conservative” equilibrium respectively, as before.
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The arguments so far have focused on the allocation of ownership and control rights among VCs and startup insiders. I next turn my analysis to the valuations offered to VC investors when they buy startup shares. Standard bargaining models (for example, Koskinen et al, 2011) predict that entrepreneurs having greater negotiating power are likely to extract higher prices from external investors for their startup shares. From the VCs‟ perspective, an enduring challenge remains the sorting of investments which entails pronounced search costs, time, and effort. VCs choose a handful of risky companies to invest in from among hundreds of business plans. In the VC industry, characterized by severe asymmetric information and adverse selection problems, a critical factor for VCs when they evaluate business plans is the founders‟ track record. Prior entrepreneurial experience, particularly successful, may significantly mitigate adverse selection problems and such founders are likely to negotiate higher valuations for their startups. The valuation of startups backed by previously unsuccessful entrepreneurs would depend, as before, on the equilibrium obtained – experimental or conservative. The following null and alternate hypotheses capture the predictions of this analysis: H4N: Irrespective of their past performance, serial entrepreneurs are able to negotiate higher valuations for their startups. H4A: Serial entrepreneurs that were unsuccessful in the past fetch lower valuations for their startups. Previously successful serial entrepreneurs fetch the highest valuations for their startups. In related work, Hsu (2007) also finds that prior founding experience (especially financially successful experience) increases startup valuations. While that evidence is based on survey data from 149 early stage startup firms, my sample is larger and more representative, which enhances the power of tests and perhaps makes the findings more generalizable. Furthermore, I also analyze other contracting details. From a broader perspective, if VCs do consider prior entrepreneurial experience important in tackling their sorting problem, the study also contributes to the extensive literature on how VC firms overcome the informational problems associated with startup financing. In the following sections, I test the aforementioned hypotheses using a sample of VC-backed IPOs.
3. Data and Sample Characteristics 3.1. Data Sources and Sample Criteria The initial data are taken from the SDC VentureXpert database, which identifies VC-backed companies including IPOs. The sample comprises of privately-held US headquartered companies that go public between 1996 and 2007. Since the focus is on VC-backed companies and serial
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entrepreneurship, companies that were funded through recapitalizations and buyouts are excluded (also by carefully reading the prospectuses) from the purview of this study. The final sample comprises of 1,170 VC-backed IPOs for which all required and relevant company- and VC firm specific information are available. From the VentureXpert database, I also collect round-wise and total investments made by each VC in the startup, as well as the aggregate investment made by all VC firms in the startup. This information is used to determine the lead venture capitalist – the VC firm that participates in the initial funding round and makes the largest total investment in the company up to the IPO. In a few instances, if two or more VCs initiate funding at the same time, and also invest the same amount in the company, then the older VC is designated as the lead VC firm. The lead venture capitalist usually originates the deal and is among the most active members of the VC syndicate. Other data obtained from the VentureXpert database include size of the VC syndicate in each startup, number of funding rounds, startup‟s founding date, startup‟s developmental stage when it first attracted VC investment, and cumulative market capitalization of portfolio companies taken public by the VC firm prior to the year of its first investment in the startup, which is used to measure VC reputation (Nahata, 2008). When faced with missing information from VentureXpert, I supplement the data by obtaining additional information from the IPO prospectuses. Appendix 1 presents the construction and data sources of all variables used in this study. Majority of startup specific information is hand-collected from IPO prospectuses, which are the second major data source. From the IPO prospectuses, I collect aggregate VC shareholdings, aggregate outside investor shareholdings (including VCs), founder status (whether she is also the CEO) and the number of board seats allocated to startup insiders, VCs, and other outside investors. Startup insiders include CEOs, founders and other managers who are startups‟ executives. Aggregate outside investor shareholdings include shares owned by VCs and other investors that include proprietorships, consulting firms, non-VC arms of insurance companies, hedge funds, investment management firms, trusts, and retirement funds. To ascertain the background of the founder entrepreneurs, I read the management section in the prospectuses. This allows me to determine whether the entrepreneur has founded businesses before or not. Out of 1,170 companies in the sample, 317 are founded by serial entrepreneurs. The percentage of serial entrepreneurs is similar to that in Bengtsson and Sensoy (2011a) who report that 24% of the entrepreneurs in their sample are serial founders. On the other hand, the percentage of serial entrepreneurs is higher in my sample than in some other studies on serial entrepreneurship. For instance, Gompers et al. (2010) report that about 10% of their sample entrepreneurs are serial
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founders. There could be possibly two reasons for this difference. First, my sample comprises of all serial founders whereas Gompers et al. (2010) analyze a sample of repeat entrepreneurs whose previous businesses were also VC-backed. Since VCs fund only a tiny fraction of businesses and my sample includes all serial founders, their proportion may be higher. Second, if serial founders are more skillful (Gompers et al., 2010), they have a better likelihood of taking their companies public, thus increasing their proportion in the sample of IPOs. Sometimes, the prospectuses also mention what happened to the previous companies founded by serial entrepreneurs. If they were taken public or sold, I classify the serial entrepreneurs as previously successful. When the prospectuses make no mention of what happened to serial entrepreneurs‟ previous companies, I look for that information through Web searches (using Google and Factiva) to determine whether the companies were successful or not. Investors in privately-held companies (including VCs) generate most of their profits from the subsample of IPOs and acquisitions (also called successful exits), whereas the companies that remain private are generally considered unsuccessful. Of the 317 serial entrepreneurs, I determine that 244 were previously successful, which is evidence, at least in part, of their skill. However, as shown below, even previously unsuccessful entrepreneurs obtain better contractual terms than novice entrepreneurs. Thus even when skill is not proven when previous companies did not succeed, the entrepreneurial learning and experience gathered from them enable the serial founders to get more favorable contracts. One possible concern with the analysis is that VC-backed IPOs are non-randomly selected since firms going public are generally the most successful of VC investments. This raises the issue that the relation observed between serial entrepreneurship and the nature of their financial contracts could be because of a startup‟s performance, which can create a selection bias. In other words, superior performance of startups backed by serial entrepreneurs confers more negotiating power on the founders, leading to better contractual terms. One way to address this issue is to analyze the startup performance across serial and novice entrepreneurs. To do so, I analyze three related metrics of performance, namely profit margin, return on assets (ROA), and asset turnover ratio before the startup goes public. Since the startup characteristics such as equity ownership, board allocation, founder-CEO duality, and valuation are all measured at the IPO, the pre-IPO measures of performance are reasonable in determining whether they are responsible for differences in contracts across the startups. For obtaining the necessary financial information to study the pre-IPO performance I use the Compustat database.
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While a detailed analysis of the pre-IPO startup performance follows in section 4, it suggests that the contractual terms do not appear to be driven by the startup performance. Second, by examining only successful startups (IPOs) that have attracted VC investments and by controlling for cross sectional differences within the sample of VC-backed IPOs, I limit the concern that the relation observed between the entrepreneur type and the financial contracts is the result of startup performance. Third, the allocations of shareholdings and board seats, and the terms of share pricing are determined before it is known whether a startup is going public. Finally, the focus is on contractual terms and not on performance which is much more likely to be affected by selection biases. Hence although I cannot completely rule it out, I do not believe that selection bias in favor of more successful startups is likely to be a serious problem at least in the context of this study. On the other hand, absent a representative sample of detailed contracts (or term sheets), the data must be hand-collected from IPO prospectuses. Consequently, the resultant dataset is extensive, much cleaner, and conducive for richer analysis. It allows me to address important questions that would be much more difficult to answer otherwise.
3.2. Sample Properties and Descriptive Statistics Table 1A provides information on VC-backed IPOs in the 1996-2007 period. Over this eleven year period one in four companies were backed by serial entrepreneurs. The frequency of VCbacked IPOs peaks in 1999-2000 and is markedly higher than other sample years. However, there is a stable trend in serial entrepreneurship across the sample period. Table 1B reports serial entrepreneurship by most active industries. In absolute terms, most serial entrepreneurs are in software services (2-digit SIC: 73) followed by biological products and genetics (2-digit SIC: 28), electronic equipment (2-digit SIC: 36), manufacturing instruments (2digit SIC: 38), and communication services (2-digit SIC: 48). Combined, in these five industries, one in four companies were backed by serial entrepreneurs as well. Although there does not appear to be a significant industry impact on serial entrepreneurship, nevertheless we control for industry fixed effects in our analysis. Table 2A reports descriptive statistics on the distribution of shareholdings, board seats, and founder status. Pre-IPO equity of all outside investors (including VCs) averages 52.84% of shares outstanding. Apart from VCs, other outside investors include proprietorships, consulting firms, non-VC arms of insurance companies, hedge funds, investment management firms, trusts, and
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retirement funds. Total VC shareholding (including corporate VCs and venture arms of banks) averages 50.90%. The median board comprises of 7 members. The insiders – CEO and other company executives – hold 2 while the VCs hold 3 board seats. In terms of proportional board representation, the median board has 40% representation by the VCs and nearly 29% by the insiders. It is well known that the proportion of outside directors on boards of VC-backed companies is significantly higher than that for non-VC-backed companies. As Baker and Gompers (2003) show, this might have important implications for corporate governance practices in these companies. In 47% of startups, founders are also the CEOs at the IPO. That many of the founders are no longer the CEOs is consistent with earlier evidence that VCs exert considerable board control and frequently exercise their power to replace founder-CEOs with more experienced management to improve the companies‟ prospects. Table 2B presents other VC- and startup specific characteristics. The median company received 4 rounds of VC funding and had 6 firms in its VC syndicate although there is immense variation in each in the sample. About 66% of the companies received their first VC funding in the early developmental stage (seed or early stage as classified by VentureXpert). Finally, the median startup was an year old at the time of its first VC investment. Table 3 reports the sample statistics across different types of entrepreneurs. Comparing VC shareholdings across entrepreneur types in Table 3, we see that startups backed by serial entrepreneurs, whether previously successful or not, have significantly smaller VC shareholdings than novice entrepreneur backed startups. This evidence is consistent with the null hypothesis 1, which predicts that serial entrepreneurs suffer less dilution of equity in their dealings with VCs. This is all the more interesting given that VCs invest more in serial entrepreneur backed startups (see Tables 7 and 8 below). This result is also similar to the negative, though not significant, relation between serial founders and VCs‟ cash flow rights shown by Bengtsson and Sensoy (2011a). Turning to the board seat allocation, we observe that board seats held by insiders in startups founded by serial entrepreneurs are significantly higher. In fact even previously unsuccessful entrepreneurs retain more board control than novice entrepreneurs. This pattern of greater control over their companies is also evident in the founders‟ status at the IPO. In 63% of the companies serial founders retain their CEO positions while only 41% of the novice entrepreneurs manage to retain their CEO positions at their companies‟ IPOs. Previously unsuccessful entrepreneurs also retain their CEO positions in 59% of the companies. These results are also interesting in light of the
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fact that serial entrepreneur backed startups were younger when they received their first VC funding. Taken together, the evidence does not indicate that previously unsuccessful entrepreneurs are afflicted with a stigma of failure when they raise capital for their next ventures. In the next section, I employ multivariate analysis to address the concern that these univariate results may be driven by different deal and company characteristics.
4. Empirical Results In this section, I first present a detailed analysis of how entrepreneur type (serial or not) determines the allocation of equity and control rights among VCs and startup insiders. I follow it up with an analysis of founder status at IPO and finally relate serial entrepreneurship to the prices paid by the VCs for startup shares.
4.1. Total VC ownership To test Hypothesis 1 in a more rigorous multivariate framework, total VC ownership is regressed on a set of explanatory variables including an indicator variable denoting whether the entrepreneur is a serial founder or not. The control variables include an indicator denoting whether the startup received its first VC investment in early development stage, number of funding rounds, VC syndicate size, lead VC‟s reputation, an indicator denoting whether the CEO is also the founder, startup‟s age at the time of first VC funding, median market-to-book ratio in the startup‟s industry at the time of first VC investment, and total VC investment in the startup. The number of funding rounds, VC syndicate size, and startup age are measured in natural logs. As in Nahata (2008), VC reputation is measured by the (normalized) cumulative market capitalization of portfolio companies taken public as of the year-end prior to the VC‟s first investment in the startup. For calculating industry market-to-book ratios, firms are drawn from the Compustat universe based on their primary 2-digit SIC codes. The market to book ratio is measured by the sum of book value of assets plus market value of equity minus book value of equity, divided by book value of assets. I include industry fixed effects and the robust standard errors account for both heteroscedasticity and clustering by the lead VC firm. The industry fixed effects are based on the companies‟ 2-digit SIC codes. Table 4 reports estimates for four OLS regression models to test Hypothesis 1, which predicts a relation between total VC ownership and the type of entrepreneur. The first two models include all entrepreneurs with the second model also having the total VC investment in the startup as an
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additional independent variable. The introduction of total VC investment slightly reduces the number of observations. The third and fourth models exclude previously very successful entrepreneurs. This is to analyze whether previously unsuccessful entrepreneurs are afflicted by the stigma of failure and therefore part with more equity in their startups. An alternate way to analyze the issue is to introduce an indicator variable denoting whether previous ventures of serial founders were successful or not. However, this indicator is highly correlated with the indicator denoting serial entrepreneur leading me to adopt the former specification. The fourth model includes total VC investment also. In all four models, we observe a significantly negative coefficient on the serial entrepreneur indicator, which is consistent with the predictions of Hypothesis 1 that startups suffer less dilution of equity when their founders are serial entrepreneurs. As models 3 and 4 indicate, this holds true also when serial founders were unsuccessful in their previous businesses. Turning to the other explanatory variables in Table 4, the coefficient on number of funding rounds is positive and significant in models 1 and 3 indicating that total VC ownership increases with funding rounds. However, when total VC investment is controlled for in models 2 and 4, the number of funding rounds is no longer significant. As expected, the higher the VC investment, the larger the total share ownership of the VCs. VC syndicate size is also positively related to VC ownership and maintains its significance across all models. When founders are also the CEOs of their companies, they relinquish less equity to VCs. In a similar vein, the negative and significant coefficient on the startup‟s age suggests that insiders in relatively well established startups have greater leverage in their negotiations with VCs over the allocation of equity ownership. Finally, startups receiving their first VC investment when industry market-to-book ratios are high, relinquish less equity to VCs. This indicates insiders have more bargaining leverage when the startup‟s industry is faced with increased growth opportunities. Notably, not only are these results along expected lines and economically meaningful, they also explain about 20 percent variation in equity ownership of the VCs.
4.2. Insider board representation In this section I evaluate the prediction of Hypothesis 2 that insider board representation in a startup will be greater when a serial entrepreneur is involved. Directors in VC backed startups can be classified into three groups: VCs, insiders and independent directors. The insiders include the founder(s), CEO, and other executives. To test Hypothesis 2 in a multivariate framework which
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controls for other deal and company characteristics, we use the same framework as in the previous section. The dependent variable is insider board representation defined as the ratio of insiders‟ board seats to board size. Most explanatory variables used in this analysis are as defined earlier. One difference is instead of total VC investment, I include total VC ownership in the regression specification. As before, I include industry fixed effects and the standard errors are robust to heteroscedasticity and clustering at the lead VC firm level. I estimate four OLS regression models whose specifications are nearly the same as in Table 4. I exclude total VC ownership in two of the four specifications because of potential endogeneity concerns. As reported in Table 5, in all four models, the serial entrepreneur indicator has a significant positive coefficient, which indicates that insiders retain more control of the board when the startups are backed by serial entrepreneurs. Interestingly, this result also holds when previously successful entrepreneurs are excluded, again suggesting that previously unsuccessful entrepreneurs are valued for their amassed learning and not significantly stigmatized for their failure. Two other significant results are as follows. First, I find that VC syndicate size is negatively related to insider board representation which is similar in spirit to the findings on total VC ownership. Second, the higher the total VC ownership, the lower is the insider board representation.
4.3. Founder-CEO duality Apart from insider board representation, another important channel through which insiders, particularly the top executives, retain control of their firms is the so called mechanism of CEO duality. An extensive literature in corporate governance shows that CEOs who are also the Chairpersons of their Boards wield more power in their companies. A somewhat parallel concept applicable to private companies is the founder-CEO duality–arguably founders who manage to retain their CEO positions wield more control over their companies. In this section, I evaluate the relation between founder-CEO duality and serial entrepreneurship. One possible reason why serial founders may retain their CEO positions more often is because they are able to negotiate favorable contracts for their startups. Conversely, when contracts are more investor friendly, firing of founders from CEO positions may be easier. To test Hypothesis 3 in a multivariate framework, I employ a logit model. The dependent variable is whether or not founders were also the CEOs at the time of IPO. In Table 6, I present two models one of which excludes previously successful entrepreneurs. In both specifications, consistent with the univariate results, I strongly find that serial entrepreneurs are more likely to retain their CEO positions. This result is in line with the earlier findings on total
15
VC ownership and insider board representation. Taken together these findings also suggest that serial entrepreneurs, including previously unsuccessful ones, are able to negotiate contracts whose provisions strongly complement each other. The contract terms do not appear to be substitutes whereby, for example, in order to score better on insider board representation, serial founders sacrifice on equity ownership. This is also evident in the finding that the incidence of founder-CEO duality reduces with total VC share ownership. It is more difficult for the founders to survive in their CEO positions when VCs possess increased leverage through higher share ownership. Hellmann and Puri (2002) provide evidence that VCs are proactive investors and often replace founders with outside CEOs to professionalize their portfolio companies and improve their prospects.
4.4. Valuation of Startups Beyond the allocation of equity ownership and control rights, startup insiders also have some choice over the pricing terms they agree to in selling shares to VCs. According to Hypothesis 4, serial entrepreneurs are likely to extract higher valuations for their companies. In this section, I analyze the average purchase prices paid by VC investors for their shares relating them to the type of entrepreneurs. While VentureXpert identifies VC investments in different rounds of startup funding, it does not track the price paid per share in each funding round. However, since it does report the total VC investment in a startup, I can take that and divide it by startup shares held by the VCs at the IPO date to arrive at the average share purchase price paid by the VC syndicate. The number of shares held by the VCs is computed by multiplying VC equity ownership with the number of shares outstanding sourced from the CRSP database. In Table 7, we observe that the average purchase price paid per startup share is significantly higher for serial entrepreneur backed startups. On average, the VCs pay $5.65 ($5.00) per share for serial (novice) entrepreneur backed startups. The corresponding median numbers are $4.22 and $3.62 per share respectively. The differences in mean and median share purchase prices are statistically significant across the serial and novice entrepreneurs. However, part of this difference could be caused by differences in average IPO offer prices across the two samples. For a more meaningful comparison, we deflate our measure of VC share prices (average purchase price per share) by the startup‟s IPO offer price to control for differences in otherwise unobserved startup characteristics. On average, the ratio of average share price paid by VCs to IPO offer price is 0.49 for serial entrepreneur backed startups, which is significantly higher than the ratio of 0.44 for novice
16
entrepreneur backed startups. I also obtain a statistically significant (at the 4% level) difference in the median ratio of VC share purchase price to IPO offer price, which equals 0.33 for serial entrepreneur backed startups and 0.29 for novice entrepreneur backed startups. Finally, I measure the price paid by VC investors for each percent of the outstanding shares they receive and relate this variable to the type of entrepreneur. The purchase price per one percent of equity is akin to a startup‟s implied “post-money” valuation, a standard valuation measure in the VC industry. The so-called post-money valuation measures startup value based on the equity stake purchased by the investor, which is what my variable captures, albeit averaged across all funding rounds. Since VentureXpert does not report prices paid per share in individual funding rounds, I am unable to determine either the “pre-money” or the “post-money” startup valuations in a given funding round. I find that on average, VCs pay $1.43 million for each shareholding percentage in the startups founded by serial entrepreneurs, which is significantly higher than the $1.06 million for each shareholding percentage in novice entrepreneur backed startups. This represents an economically significant difference as well. One major difference from previous findings on ownership and control rights is that when previously successful entrepreneurs are excluded from the analysis, there is no difference between the valuations of the startups backed by novice and previously unsuccessful entrepreneurs. There is thus some cost for previously unsuccessful entrepreneurs, namely lower pricing for their startup shares, compared to previously successful entrepreneurs, although for most terms they are better off than the novice entrepreneurs. Table 8 presents regression estimates for share pricing using the entire sample of entrepreneurs. I use four specifications where the dependent variables are slightly different from each other. The independent variables remain identical and as before. While in the first model, the dependent variable is the average purchase price paid by the VC syndicate for their shareholdings, in the second, the average purchase price is inflation adjusted. In the third model, the dependent variable is the average purchase price paid by the VC syndicate, divided by the IPO offer price. And in the fourth, it is the price paid by the VC syndicate for each shareholding percentage. All prices are winsorsized at the 5 and 95 percentiles to adjust for outliers. In all four specifications, the coefficient on the serial entrepreneur indicator is positive and statistically significant. This indicates that startup insiders extract higher valuations from the VCs when founders have the benefit of previous entrepreneurial experience. Among other significant results, I find that number of funding rounds is positively related to startup share pricing. This is
17
expected given that our sample consists of successful IPO firms, in which later venture rounds are typically funded at higher purchase prices. The size of the VC syndicate is also associated with higher share pricing although the coefficient is statistically significant in three of the four models. Not surprisingly, older startups fetch higher share prices for themselves, but again the coefficient is statistically significant in three of the four models. Finally, startups receiving their first VC investment when industry market-to-book ratios are high have significantly higher valuations. Better industry conditions reflect increased growth opportunities and this improves the startups‟ bargaining power, which results in higher valuations of these companies.
4.5. Other startup characteristics Raising capital is a non-trivial exercise for startups and early access to capital is crucial for their progress and survival. It is also important for maintaining a first mover advantage, something that many startups critically depend on for tackling competition. A longer time spent in raising capital keeps scarce resources away from other crucial tasks (technology, product and business development, human capital deployment, etc.) necessary for startups‟ advancement. An oftrepeated quote goes as: “the first rule of entrepreneurship is: it takes twice as long and costs twice as much to achieve one‟s expectations.”6 Do serial entrepreneurs possess an advantage in raising capital faster than novice entrepreneurs? In Table 9, I model the startup‟s age when it first received VC funding. I find that startups backed by serial entrepreneurs (including previously unsuccessful ones) are funded by VCs faster. While not directly related to most contractual terms, this result is interesting because although the serial entrepreneur backed startups obtain VC funding faster, yet they retain more influence (via board seats, VC ownership, and founder-CEO duality) over their operations than other startups. The other significant result is that the startup is younger when the first VC investment takes place in company‟s seed/early development stage. Since VC-backed IPOs are not a random sample, one possible concern is that the relationships observed between entrepreneur type and the nature of their financial contracts could be a result of startup performance, which would create selection bias. For example, superior performance of startups backed by serial entrepreneurs confers more negotiating power on the
6
The chief technology officer of Hewlett-Packard (H-P) once highlighted the importance of speed-to-market, noting that getting a product to the marketplace one month earlier was typically worth more to H-P than its entire engineering and development cost. Reaching the market either six months earlier or six months later increased or decreased, respectively, a product‟s lifetime profits by one-third.
18
founders, leading to better contractual terms. In other words, we expect to see better performance for startups founded by serial entrepreneurs. To shed light on this issue, I analyze three related performance metrics, namely profit margin, return on assets (ROA), and asset turnover ratio before the startup goes public. Since the startup characteristics such as equity ownership, board allocation, founder-CEO duality, and valuation are all measured at the IPO, the pre-IPO measures of performance are reasonable in determining whether they are responsible for differences in contracts across the startups.7 For obtaining the necessary financial information to study the pre-IPO performance I use the Compustat database. The profit margin is defined as the ratio of earnings before interest, taxes, depreciation, and amortization (EBITDA) to revenues. ROA is the ratio of EBITDA to total assets. And asset turnover ratio is the ratio of revenues to total assets. All three performance metrics are industryadjusted and measured for the year before the IPO. In Table10A, I present the univariate comparisons. Surprisingly, I find that the median profit margin (industry-adjusted) for startups backed by serial entrepreneurs is -0.62 which is significantly lower than the median profit margin of -0.31 for startups founded by novice entrepreneurs. The profit margin of startups backed by previously unsuccessful entrepreneurs is also significantly lower than that for novice entrepreneur backed startups. I observe very similar patterns for other two performance measures, namely the ROA and the asset turnover ratio, although the differences across the entrepreneur types are not statistically significant in a consistent way. In Table 10B, I estimate the determinants of industry-adjusted profit margin in a multivariate framework with the primary variable of interest being the serial entrepreneur indicator. I use two specifications. In the first specification containing all entrepreneurs, I obtain a significant negative coefficient on the serial entrepreneur indicator whereas in the second that excludes previously successful entrepreneurs, the serial entrepreneur indicator is not significant in explaining the excess profit margin. This says that the performance of startups founded by previously successful serial entrepreneurs lags other companies‟ performance at the time of the IPO. Also, the startups founded by previously unsuccessful serial entrepreneurs do not perform any better than novice entrepreneur backed startups. These findings are interesting for the following two implications. First, it is not the companies‟ performance but something about the serial entrepreneurs themselves that leads to more favorable contracts for their startups. In fact, despite poorer (or similar) performance, startups founded by serial entrepreneurs manage to negotiate more favorable 7
When I include these performance measures as explanatory variables in regressions of contractual terms, none emerge significant and the indicator denoting serial entrepreneur continues to be robust. I don‟t report these regressions because I lose a few observations due to data unavailability on some of the performance metrics.
19
contract terms in their dealings with VCs relative to novice entrepreneurs. This mitigates concerns about selection that performance differences may be responsible for differential contracts. Second, relative to other entrepreneurs, when VCs fund previously successful serial entrepreneurs, the „jockey‟ (founder) is given more weight than the „horse‟ (startup). On the other hand, when previously unsuccessful serial entrepreneurs are considered for funding, VCs do not appear to rely on the founders to that extent; startup performance becomes important as well, which is consistent with Kaplan, Sensoy, and Stromberg (2009). At the very least, VCs seem to care that the performance of startups founded by previously unsuccessful serial entrepreneurs is not any worse than that of the startups founded by novice entrepreneurs. Overall, the evidence on performance of these startups suggests that the relations observed between entrepreneur types and the nature of financial contracts do not appear to be caused by differences in startup performance.
5. Additional tests In this section, I evaluate the robustness of the results to some more tests. One major difference from previous research (for example, Gompers et al., 2010; Bengtsson, 2008) is my dataset comprises of all entrepreneurs irrespective of whether they received VC funding in the past or not. If some of the serial entrepreneurs were VC-backed in the past then it is quite likely they were backed by the same VC firm that funded them in their most current venture. More importantly, does relationship investing – repeat entrepreneur-VC deals across more than one startup – have an impact on financial contracting? I find that 136 out of 317 (43%) serial entrepreneurs received VC funding for their previous startups. And 49 of the 136 (36%) startups were backed by the same VC firm that funded the serial founders in their most current venture as well; the 36% being remarkably similar to the evidence in Bengtsson (2008)8. I create two dummy variables denoting i) whether a serial entrepreneur received VC funding in the past, and ii) whether she received VC funding from the same VC firm. However, none of these indicators is incrementally significant in explaining any of the contract terms. Furthermore, all the earlier results and their statistical significance remain qualitatively similar. Second, for additional robustness, I substitute insider board representation with VC board representation defined as the ratio of VC board seats to total board size (on average, VCs control 40% of the board). Recall that I find that insiders retain greater board control in startups founded by
See also Wright, Robbie, and Ennew (1997) for evidence on VCs‟ repeated interactions with serial entrepreneurs including those that were funded by the same VC firm. 8
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serial founders. Does it automatically follow that VCs obtain lower board representation in such startups? (The correlation between insider and VC board representation is a relatively low -0.38.) Therefore, to provide further robustness, I replicate the analysis of Table 5 by having VC board representation as the dependent variable. Consistent with my hypotheses and previous results, I find that VC board representation is significantly lower in startups backed by serial entrepreneurs. Finally, I we use the Heckman correction procedure to generate consistent model estimates. In the first-step model, I estimate the determinants of being a serial entrepreneur using a probit regression framework. The instruments used in the first step selection equation (probit model) include the market to book ratio in the startup‟s industry in the year of its founding, the population of the state when the startup was founded and is headquartered, and industry fixed effects. I find that serial entrepreneurs display superior timing ability in terms of floating their startups in better industry conditions (see also Gompers et al., 2010) and they are also likely to come from more populous states.9 In the second-step regression, I include the inverse Mills ratio obtained from the first-step estimation as an additional regressor in our models of Tables 4-6 and 8. I find the second-step estimates to be statistically similar to those reported in these Tables after including the inverse Mills ratio. The inverse Mills ratio is statistically significant in a majority of specifications, indicating that adjustment for possible selection bias is important.
6. Discussion and conclusion In this study, I empirically investigate the impact of serial entrepreneurship on one important dimension of capital-raising, namely the structure of financial contracting between the providers and recipients of capital. Using U.S. data, I examine several questions. Are serial entrepreneurs able to retain more control rights and suffer less dilution of equity by virtue of their entrepreneurial experience? Are they also more likely to survive as CEOs of their firms? How does their prior experience affect the time it takes to raise VC capital? Do VCs pay higher share prices for serial entrepreneur-backed startups? And finally, what are previously unsuccessful serial entrepreneurs able to negotiate for their companies? The main findings are as follows. In companies founded by serial entrepreneurs, I find the contracts to be more startup-favorable in the following ways. Founders and other insiders retain not 9
In an alternate first-stage specification, instead of state population, I include an indicator variable denoting whether the startup was based in the states of California or Massachusetts – states most active in VC investments. This variable also significantly drives serial entrepreneurship consistent with these states having a thriving ecosystem that is much conducive to starting new businesses. I don‟t include the California-Massachusetts indicator and state population together in the first-stage specification because they are highly correlated (ρ=0.65).
21
only greater board control but also suffer less dilution of equity in their dealings with VCs. Second, founders are more likely to retain their CEO positions. Third, startups extract higher valuations from the VCs, reflecting their greater bargaining power arising from prior entrepreneurial experience. Interestingly, these results obtain despite poorer performance of serial entrepreneur backed startups and VCs funding these startups earlier in their lifecycles. Finally, far from getting punished for previous failures, even unsuccessful serial entrepreneurs obtain better contracts than first-time entrepreneurs. These results remain robust even after controlling for whether serial founders were VCbacked in their earlier ventures or received the funding from the same VC firm. In fact, relationship investing is not significant in explaining any of the contractual terms. Overall, the results indicate that prior entrepreneurial experience is an important determinant of financial contracting in U.S. based startups backed by venture capitalists (VCs). In reflecting on these findings, some issues merit discussion. First, it is possible that serial entrepreneurs, particularly successful, are wealthy and thus may not require the same amount of VC investment. Moreover, their deeper pockets may confer on them superior negotiating power in their discussions with VCs. If so, their contracts are likely to be less investor-favorable. While I do not have information on the personal wealth of entrepreneurs, it is worth noting that even previously unsuccessful entrepreneurs who may not have deep pockets negotiate better contracts than firsttime entrepreneurs. Furthermore, companies founded by serial entrepreneurs are younger when they receive their initial VC investment, which seems contrary to the expectation that wealthy entrepreneurs are likely to approach VCs later given the wealth at their disposal. Second, my findings are conditional on companies receiving venture capital. There may be serial entrepreneurs, particularly previously unsuccessful, who are simply unable to raise venture financing. This would run contrary to the assertion that unsuccessful serial entrepreneurs seem to be immune to the stigma of failure when trying to raise VC. While I do not observe unsuccessful serial founders who were unable to raise venture financing, some evidence suggests that even previously unsuccessful entrepreneurs are as likely to raise venture capital as novice founders (Hsu, 2007). Thus, although I can‟t analyze this issue further given the data constraints, the overall evidence suggests that entrepreneurial learning seems to outweigh potential stigma of failure associated with previously unsuccessful serial founders, which is consistent with some recent studies in entrepreneurship and also the outlook toward it in the United States.
22
Appendix 1: List of variables Variable
Explanation
Data sources
Average share purchase price
VC syndicate‟s average purchase price for startup shares measured as the total VC investment divided by total shares held in the startup by the VCs as of the IPO date Average share purchase price divided by the IPO offer price
IPO Prospectus VentureXpert Database CRSP
Average share purchase price to IPO offer price Early stage investment by VC
Founder-CEO Industry-adjusted asset turnover
Industry-adjusted profit margin
Industry-adjusted ROA
Industry market-to-book ratio
Insider board representation Lead VC reputation
Price paid per % of equity ownership Startup age at first VC funding Startup‟s total funding rounds Serial entrepreneur
Total VC investment Total VC share ownership VC syndicate size
An indicator variable denoting whether the startup first received VC investment in its seed/early developmental stage An indicator variable denoting whether a CEO is a founder Ratio of Sales to Total assets in the year prior to the IPO minus the median Sales/Total assets ratio in the startup‟s industry in the same year Ratio of EBITDA to Sales in the year prior to the IPO minus the median EBITDA/Sales ratio in the startup‟s industry in the same year Ratio of EBITDA to Total assets in the year prior to the IPO minus the median EBITDA/Total assets ratio in the startup‟s industry in the same year Median annual market-to-book in the startup industry at the time of initial VC investment in the startup Officer-director board seats divided by total board seats Reputation of the lead VC firm measured by the (normalized) cumulative market capitalization of portfolio companies taken public by the VC firm as of the year-end prior to the VC‟s first investment in the startup. (Nahata, 2008) Total investment by the VC syndicate divided by percent share ownership Age of the startup when the VC first invested in the startup Number of funding rounds received by the startup An indicator variable denoting whether or not the company founder is a serial entrepreneur. Serial entrepreneurs have founded businesses before Total investment by all VCs in the startup Total shareholdings (%) of all VCs in the startup Size of the total VC syndicate
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IPO Prospectus VentureXpert Database CRSP VentureXpert Database
IPO Prospectus Compustat
Compustat
Compustat
Compustat
IPO Prospectus VentureXpert Database SDC New Issues Database
VentureXpert Database IPO Prospectus VentureXpert Database IPO Prospectus VentureXpert Database IPO Prospectus
VentureXpert Database IPO Prospectus VentureXpert Database IPO Prospectus
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Harvey, M., Evans, R., 1995, Strategic windows in the entrepreneurial process, Journal of Business Venturing 10, 331–347. Hellmann, T., 1998. The allocation of control rights in venture capital contracts. RAND J. Econ. 29, 57-76. Hellmann, T., Puri, M., 2002. Venture capital and the professionalization of start-up firms: empirical evidence. J. Finance 57, 169–197. Holtz-Eakin, D., D. Joulfaian, H. Rosen, 1994. Entrepreneurial Decisions and Liquidity Constraints, Rand Journal of Economics 108, 604-631. Hsu, D., 2007. Experienced Entrepreneurial Founders, Organizational Capital, and Venture Capital Funding. Research Policy 36, 722-741. Kaplan, S., Sensoy, B., Stromberg, P., 2009. Should investors bet on the jockey or the horse? Evidence from the evolution of firms from early business plans to public companies. J. Finance 64, 75-115. Kaplan, S., Stromberg, P., 2001. Venture capitalists as principals: contracting, screening, and monitoring. Amer. Econ. Rev. 91, 426-430. Kaplan, S., Stromberg, P., 2003. Financial contracting theory meets the real world: an empirical analysis of venture capital contracts. Rev. Econ. Stud. 70, 281-315. Kaplan, S., Stromberg, P., 2004. Characteristics, contracts and actions: evidence from venture capitalist analyses. J. Finance 59, 2177-2210. Kaplan, S., F. Martel, P. Strömberg 2007, “How Do Legal Differences and Experience Affect Financial Contracts?”, Journal of Financial Intermediation 16, 273-311 Koskinen, Y., M. Rebello, J. Wang, 2011. Private information and bargaining power in venture capital financing. Working Paper. Landier, A, 2006. Entrepreneurship and the stigma of failure, Working Paper. Lerner, J., 1995. Venture capitalist and the oversight of private firms. J. Finance 50, 301-318. MacMillan, I., 1986. To really learn about entrepreneurship, let‟s study habitual entrepreneurs. Journal of Business Venturing 1, 241-243. Masulis, R., R. Nahata, 2009. Financial contracting with strategic investors: Evidence from corporate venture capital backed IPOs. Journal of Financial Intermediation 18, 599-631. Nahata, R., 2008, Venture capital reputation and investment performance. Journal of Financial Economics 90, 127-151. Politis, D., 2008, Does prior start-up experience matter for entrepreneur's learning? A comparison between novice and habitual entrepreneurs, Journal of Small Business and Enterprise Development 15, 472– 489. Politis, D., Gabrielsson, J., 2009, Entrepreneurs' attitudes towards failure: an experiential learning approach, International Journal of Entrepreneurial Behaviour and Research 5, 364–383. Reuber, A.R., Fischer, E., 1999, Understanding the consequences of founders' experience, Journal of Small Business Management 37, 30–45.
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Sarasvathy, S., Menon, A., 2002, Failing firms and successful entrepreneurs: serial entrepreneurship as a temporal portfolio, Darden Business School Working Paper Savitsky, K., Epley, N., Gilovich, T., 2001, Do others judge us as harshly as we think? Overestimating the impact of our failures, shortcomings and mishaps, Journal of Personality and Social Psychology 81, 44–56. Sitkin, S.B., 1992, Learning through failure: the strategy of small losses. In: Shaw, B.M., Cummings, L.L. (Eds.), Research in Organisational Behaviour 14, pp. 231–266. Wright, M., K. Robbie, C. Ennew, 1997, Venture capitalists and serial entrepreneurs, Journal of Business Venturing 12, 227-249. Zacharakis, A.L., Meyer, G., DeCastro, J., 1999, Differing perceptions of new venture failure: a matched exploratory study of venture capitalists and entrepreneurs, Journal of Small Business Management 37, 1–14.
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Table 1 Panel A: Annual frequency of VC-backed IPOs in United States Year
Number of VC backed IPOs
Number of Serial Entrepreneurs
Average number of Serial Entrepreneurs per IPO
1996
201
50
0.25
1997
117
24
0.21
1998
73
18
0.25
1999
241
73
0.30
2000
221
54
0.24
2001
27
9
0.33
2002
18
5
0.28
2003
24
4
0.17
2004
79
24
0.30
2005
42
12
0.29
2006
50
15
0.30
2007
77
29
0.38
Total
1170
317
0.27
The sample includes 1170 VC-backed IPOs by U.S. firms completed in the 1996-2007 period and listed on major U.S. stock exchanges.
27
Panel B: Industry distribution of VC-backed IPOs in United States 2-digit SIC
Number of IPOs
Number of Serial Entrepreneurs
73
417
109
28
142
37
36
131
36
38
113
33
48
68
22
87
61
15
35
37
11
59
36
9
80
28
6
Others
137
39
Total
1170
317
The sample includes 1170 VC-backed IPOs by U.S. firms completed in the 1996-2007 period and listed on major U.S. stock exchanges.
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Table 2 Summary Statistics for VC-backed IPOs Panel A: Shareholdings, Board representation, and Founder-CEO duality at IPO Mean
Median
Minimum
Maximum
Standard Deviation
Total VC shareholding %
50.90
51.85
5.60
96.60
22.09
Total outside investor shareholding % (including VCs)
52.84
54.25
6.00
96.60
22.26
Total VC board seats
2.76
3.00
0.00
8.00
1.43
Insider board seats
1.94
2.00
1.00
9.00
0.92
Total board seats
6.85
7.00
1.00
43.00
2.02
VC board representation (%)
40.28
40.00
0.00
100.00
17.82
Insider board representation (%)
29.53
28.57
9.09
100.00
14.14
Founder is the CEO (0/1)
0.47
0.00
0.00
1.00
0.50
Mean
Median
Minimum
Maximum
Standard Deviation
Number of rounds of VC funding
4.17
4.00
1.00
20.00
2.51
VC syndicate size
6.76
6.00
1.00
24.00
4.34
Early stage investment by VC (0/1)
0.66
1.00
0.00
1.00
0.47
Startup age at first VC investment (number of years)
3.09
1.00
0.00
94.00
5.36
Panel B: Other VC-specific characteristics
The sample of VC-backed IPOs comprises of completed offerings by U.S. firms that list on major US exchanges over the 1996-2007 period. Panel A presents shareholdings and board representation of the VCs, insider board representation, and an indicator variable denoting whether the founder is the CEO at the IPO. Apart from VCs, other outside investors include proprietorships, consulting firms, non-VC arms of insurance companies, hedge funds, investment management firms, trusts, and retirement funds. Shareholdings, board seats, and founder-CEO duality are measured at IPO and are taken from the IPO prospectuses. Panel B presents other VCspecific characteristics including number of funding rounds received by the portfolio company, VC syndicate size, startup age when it first received venture funding, and whether the startup received its first VC investment in its early stage of development. The data in Panel B are sourced from the VentureXpert database.
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Table 3 Venture capital funding and contracting categorized by portfolio company entrepreneurs Entrepreneurs
Total VC Shareholding % Mean Median
Insider board representation (%) Mean Median .
Founder-CEO duality Mean
Median
Startup age at first VC investment (years) Mean Median
All Serial Entrepreneurs (N=317)
47.30
47.60
32.25
30.00
0.63
1.00
1.91
1.00
Previously unsuccessful serial entrepreneurs (N=73)
46.21
48.60
34.76
33.33
0.59
1.00
2.14
1.00
Novice entrepreneurs (N=853)
52.24
52.60
28.51
25.00
0.41
0.00
3.54
2.00
0.00*** 0.00***
0.00***
0.00***
0.00***
0.00***
0.00***
0.00***
0.03**
0.00***
0.00***
0.00***
0.00***
0.00***
0.06*
Tests of equality (p-value) All serial entrepreneurs vs. Novice entrepreneurs Previously unsuccessful vs. Novice entrepreneurs
0.03**
The table presents shareholdings of the VCs, insider board representation, an indicator variable denoting whether the founder is the CEO at the IPO, and the startup age when it first received venture funding–classified by types of entrepreneurs. Serial entrepreneurs have founded businesses before. Previously unsuccessful serial entrepreneurs are founders whose previous businesses remained private, i.e. neither went public nor were acquired. Shareholdings, insider board representation, and founder-CEO duality are measured at the IPO and are taken from IPO prospectuses, while the startup age is sourced from the VentureXpert database. Information on whether entrepreneurs have founded businesses before is sourced from their biographies in the IPO prospectuses. Detailed Web searches inform us whether serial entrepreneurs were previously successful, i.e. their previous businesses were either acquired or went public. ***, **, and * indicate statistical significance at the 1, 5, and 10 percent levels respectively. The sample includes VC-backed IPOs completed in the 1996-2007 period by U.S. firms that list on major U.S. stock exchanges.
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Table 4 Total VC share ownership Determinants of total VC share ownership at IPO Total VC share ownership OLS All entrepreneurs Serial entrepreneur
Intercept
56.740*** [0.00]
-5.353*** [0.00] 0.662 [0.64] 2.061 [0.13] 5.028*** [0.00] -15.273 [0.81] -4.634*** [0.00] -3.121*** [0.00] -7.266*** [0.00] 1.877*** [0.01] 40.354*** [0.00]
Industry fixed effects Observations Adjusted R2
Yes 1170 19.00%
Yes 1155 19.00%
Early stage investment by VC ln startup‟s total funding rounds ln VC syndicate size Lead VC reputation Founder-CEO ln startup age at first VC funding Industry market-to-book ratio
-5.198*** [0.00] 0.711 [0.61] 2.705** [0.04] 6.477*** [0.00] -1.946 [0.98] -4.637*** [0.00] -3.372*** [0.00] -5.908*** [0.00]
ln Total VC investment
OLS Excluding previously successful entrepreneurs -4.891** [0.04] 0.069 [0.97] 2.966** [0.05] 6.950*** [0.00] -27.634 [0.64] -5.836*** [0.00] -3.302*** [0.00] -8.700*** [0.00]
57.755*** [0.00]
-3.932* [0.10] -0.155 [0.92] 1.922 [0.20] 5.041*** [0.00] -38.700 [0.50] -5.848*** [0.00] -3.033*** [0.00] -10.485*** [0.00] 2.493*** [0.00] 36.351*** [0.00]
Yes 926 20.01%
Yes 913 20.25%
The panel presents OLS estimation of total share ownership of VCs in the portfolio company. The key explanatory variable is an indicator variable denoting whether or not the company founder is a serial entrepreneur. Serial
entrepreneurs have founded businesses before. Previously unsuccessful serial entrepreneurs are founders whose previous businesses remained private, i.e. neither went public nor were acquired. The definitions of the other control variables are in Appendix 1. Robust p-values adjusted for lead VC firm clustering are in brackets beneath the parameter estimates. ***, **, and * indicate statistical significance at the 1, 5, and 10 percent levels respectively. The sample includes VC-backed IPOs completed in the 1996-2007 period by U.S. firms that list on major U.S. stock exchanges.
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Table 5 Insider board representation Determinants of insider board representation at IPO Insider board representation OLS All entrepreneurs Serial entrepreneur
Intercept
0.315*** [0.00]
0.037*** [0.00] -0.003 [0.72] -0.006 [0.52] -0.040*** [0.00] 0.111 [0.87] -0.008 [0.34] -0.001 [0.91] -0.010 [0.46] -0.002*** [0.00] 0.419*** [0.00]
Industry fixed effects Observations Adjusted R2
Yes 1170 11.06%
Yes 1170 17.61%
Early stage investment by VC ln startup‟s total funding rounds ln VC syndicate size Lead VC reputation Founder-CEO ln startup age at first VC funding Industry market-to-book ratio
0.047*** [0.00] -0.005 [0.64] -0.010 [0.22] -0.052*** [0.00] 0.115 [0.87] 0.001 [0.94] 0.006 [0.32] 0.001 [0.97]
Total VC share ownership
OLS Excluding previously successful entrepreneurs 0.063*** [0.00] -0.007 [0.54] -0.007 [0.43] -0.055*** [0.00] 0.559 [0.45] 0.012 [0.21] 0.004 [0.54] 0.004 [0.82]
0.315*** [0.00]
0.055*** [0.00] -0.007 [0.53] -0.002 [0.80] -0.043*** [0.00] 0.513 [0.48] 0.002 [0.80] -0.002 [0.77] -0.011 [0.53] -0.002*** [0.00] 0.411*** [0.00]
Yes 926 12.77%
Yes 926 18.14%
The panel presents OLS estimation of insider board representation in the company. The key explanatory variable is an indicator variable denoting whether or not the company founder is a serial entrepreneur. Serial entrepreneurs
have founded businesses before. Previously unsuccessful serial entrepreneurs are founders whose previous businesses remained private, i.e. neither went public nor were acquired. The definitions of the other control variables are in Appendix 1. Robust p-values adjusted for lead VC firm clustering are in brackets beneath the parameter estimates. ***, **, and * indicate statistical significance at the 1, 5, and 10 percent levels respectively. The sample includes VC-backed IPOs completed in the 1996-2007 period by U.S. firms that list on major U.S. stock exchanges.
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Table 6 Founder CEO Duality Determinants of Founder CEO Duality at IPO Founder CEO Duality Logit All entrepreneurs Serial entrepreneur Early stage investment by VC ln startup‟s total funding rounds ln VC syndicate size Lead VC reputation ln startup age at first VC funding Industry market-to-book ratio Total VC share ownership Intercept
Industry fixed effects Observations -Log Likelihood
Logit Excluding previously successful entrepreneurs
0.891*** [0.00] 0.071 [0.65] -0.218 [0.12] -0.080 [0.51] -7.047 [0.40] -0.010 [0.90] 0.468** [0.02] -0.012*** [0.00] -0.095 [0.92]
0.700*** [0.01] 0.128 [0.48] -0.293* [0.06] 0.006 [0.96] -3.966 [0.71] 0.027 [0.76] 0.258 [0.30] -0.015*** [0.00] 0.374 [0.72]
Yes 1170 734.65
Yes 926 577.05
The panel presents Logit estimation of Founder-CEO Duality at the company‟s IPO. The key explanatory variable is an indicator variable denoting whether or not the company founder is a serial entrepreneur. Serial entrepreneurs
have founded businesses before. Previously unsuccessful serial entrepreneurs are founders whose previous businesses remained private, i.e. neither went public nor were acquired. The definitions of the other control variables are in Appendix 1. Robust p-values adjusted for lead VC firm clustering are in brackets beneath the parameter estimates. ***, **, and * indicate statistical significance at the 1, 5, and 10 percent levels respectively. The sample includes VC-backed IPOs completed in the 1996-2007 period by U.S. firms that list on major U.S. stock exchanges.
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Table 7 Average startup share purchase price paid by the VC syndicate Entrepreneurs
Avg. share purchase price ($) Mean Median Obs.
Avg. share purchase price relative to IPO offer price Mean Median Obs.
Avg. price paid per % of share ownership Mean Median Obs. ($ Million)
All serial entrepreneurs
5.65
4.22
313
0.49
0.33
313
1.43
0.97
313
Previously unsuccessful serial entrepreneurs
4.97
3.32
73
0.43
0.32
73
0.98
0.62
73
Novice entrepreneurs
5.00
3.62
833
0.44
0.29
833
1.06
0.72
833
0.09*
0.04**
0.00*** 0.00***
0.93
0.80
0.50
Tests of equality (p-value) (All serial entrepreneurs vs. novice entrepreneurs) Tests of equality (p-value) (Previously unsuccessful serial entrepreneurs vs. novice entrepreneurs)
0.02*** 0.05**
0.95
0.62
0.27
The sample includes VC-backed IPOs completed in the 1996-2007 period by U.S. firms that list on major U.S. stock exchanges. The primary variable of interest is the average price per startup share paid by the VC syndicate across all funding rounds. This is calculated as the total investment made in the startup by the VC syndicate divided by the number of shares held as of the IPO date. The number of shares outstanding is sourced from the CRSP database. The next set of figures shows the
average share purchase price divided by the offer price at the IPO. Finally, the average price paid per percent of equity ownership (total investment by the VC syndicate divided by percent share ownership) comprises the last set of figures. All prices are winsorsized at the 5 and 95 percentiles to adjust for outliers. The entrepreneurs are segregated into three groups: all serial entrepreneurs, previously unsuccessful serial entrepreneurs, and novice entrepreneurs. Serial entrepreneurs have founded businesses before. Previously unsuccessful serial entrepreneurs are founders whose previous businesses remained private, i.e. neither went public nor were acquired. ***, **, and * indicate statistical significance at the 1, 5, and 10 percent levels respectively. The sample includes VC-backed IPOs completed in the 1996-2007 period by U.S. firms that list on major U.S. stock exchanges.
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Table 8 Startup valuation Determinants of average share purchase price paid by the VC syndicate
Serial entrepreneur Early stage investment by VC ln startup‟s total funding rounds ln VC syndicate size Lead VC reputation Founder-CEO ln startup age at first VC funding Industry market-to-book ratio Intercept
Industry fixed effects Observations Adjusted R2
OLS Average share purchase price ($)
All entrepreneurs OLS OLS Average share Average share purchase price ($) purchase price/ inflation-adjusted IPO offer price
OLS ln Price paid per % of equity ownership
0.593** [0.05] -0.420 [0.14] 1.588*** [0.00] 0.618*** [0.01] 5.844 [0.56] 0.090 [0.69] 0.378*** [0.01] 1.300*** [0.00] -0.099 [0.96]
0.724** [0.05] -0.568 [0.11] 2.235*** [0.00] 0.528* [0.07] 1.325 [0.91] 0.126 [0.64] 0.496*** [0.01] 1.351*** [0.01] -0.701 [0.71]
0.055* [0.06] -0.029 [0.31] 0.149*** [0.00] 0.034 [0.14] 0.874 [0.34] -0.012 [0.59] 0.041*** [0.01] 0.092** [0.05] -0.115 [0.30]
0.144** [0.02] -0.071 [0.26] 0.252*** [0.00] 0.502*** [0.00] 9.048*** [0.00] 0.065 [0.18] -0.033 [0.35] 0.659*** [0.00] 9.804*** [0.00]
Yes 1146 14.06%
Yes 1146 13.54%
Yes 1146 15.03%
Yes 1146 29.50%
The panel presents OLS estimation of average share price paid by the VCs in the portfolio company. The key explanatory variable is an indicator variable denoting whether or not the company founder is a serial entrepreneur.
Serial entrepreneurs have founded businesses before. Previously unsuccessful serial entrepreneurs are founders whose previous businesses remained private, i.e. neither went public nor were acquired. The definitions of the other control variables are in Appendix 1. Robust p-values adjusted for lead VC firm clustering are in brackets beneath the parameter estimates. ***, **, and * indicate statistical significance at the 1, 5, and 10 percent levels respectively. The sample includes VC-backed IPOs completed in the 1996-2007 period by U.S. firms that list on major U.S. stock exchanges.
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Table 9 Startup age at first VC funding
Determinants of startup age at initial VC funding ln Startup age at first VC funding OLS Excluding previously All entrepreneurs successful entrepreneurs OLS
Serial entrepreneur Early stage investment by VC Lead VC reputation Industry market-to-book ratio Intercept
Industry fixed effects Observations Adjusted R2
-0.291*** [0.00] -0.665*** [0.00] 3.412 [0.31] -0.009 [0.91] 1.514*** [0.00]
-0.221** [0.02] -0.712*** [0.00] 5.259 [0.23] -0.082 [0.36] 1.833*** [0.00]
Yes 1170 16.47%
Yes 926 15.42%
The panel presents OLS estimation of startup age at the company‟s initial VC funding. The key explanatory variable is an indicator variable denoting whether or not the company founder is a serial entrepreneur. Serial entrepreneurs
have founded businesses before. Previously unsuccessful serial entrepreneurs are founders whose previous businesses remained private, i.e. neither went public nor were acquired. The definitions of the other control variables are in Appendix 1. Robust p-values adjusted for lead VC firm clustering are in brackets beneath the parameter estimates. ***, **, and * indicate statistical significance at the 1, 5, and 10 percent levels respectively. The sample includes VC-backed IPOs completed in the 1996-2007 period by U.S. firms that list on major U.S. stock exchanges.
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Table 10 Company performance before the IPO
Panel A: Company‟s industry-adjusted profit margin, ROA, and asset turnover before IPO EBITDA/Sales Median
Obs.
EBITDA/Assets Median
Obs.
Sales/Assets Median
Obs.
All serial entrepreneurs
-0.62
265
-0.32
287
-0.33
286
Previously unsuccessful serial entrepreneurs
-0.61
61
-0.46
63
-0.34
63
Novice entrepreneurs
-0.31
698
-0.27
757
-0.15
753
Tests of equality (p-value) All serial entrepreneurs vs. novice entrepreneurs
0.00***
0.25
0.00***
Previously unsuccessful entrepreneurs vs. novice entrepreneurs
0.04**
0.07*
0.31
The panel presents summary statistics of company‟s industry-adjusted operating performance before its IPO. Company‟s industry-adjusted operating performance is measured on three key metrics: excess profit margin measured as industryadjusted ratio of operating profit (EBITDA) to sales, excess ROA measured as industry-adjusted ratio of EBITDA to total assets, and excess asset turnover measured as industry-adjusted ratio of sales to total assets. The data on sales, operating profit, and assets are sourced from Compustat. The key explanatory variable is an indicator variable denoting whether or not the company founder is a serial entrepreneur. Serial entrepreneurs have founded businesses before. Previously
unsuccessful serial entrepreneurs are founders whose previous businesses remained private, i.e. neither went public nor were acquired. ***, **, and * indicate statistical significance at the 1, 5, and 10 percent levels respectively. The sample includes VC-backed IPOs completed in the 1996-2007 period by U.S. firms that list on major U.S. stock exchanges.
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Panel B: Determinants of company‟s industry-adjusted profit margin in the year before IPO Company‟s industry-adjusted performance OLS OLS All entrepreneurs Excluding previously successful entrepreneurs Excess profit margin Excess profit margin Serial entrepreneur Early stage investment by VC ln startup‟s total funding rounds ln VC syndicate size Lead VC reputation Founder-CEO ln startup age at first VC funding Industry market-to-book ratio Total VC share ownership Intercept
Industry fixed effects Observations Adjusted R2
-0.005* [0.07] 0.001 [0.71] -0.004* [0.08] 0.001 [0.86] -0.074 [0.26] 0.003 [0.13] 0.003*** [0.01] -0.011*** [0.01] -0.000 [0.71] 6.928*** [0.00]
0.001 [0.91] 0.002 [0.25] -0.002 [0.20] 0.000 [0.98] -0.046 [0.43] 0.001 [0.36] 0.003*** [0.00] -0.009** [0.04] -0.000 [0.59] 6.919*** [0.00]
Yes 963 5.65%
Yes 759 9.37%
The panel presents OLS estimation of company‟s excess profit margin in the year before its IPO. Company‟s excess profit margin is measured as industry-adjusted ratio of operating profit (EBITDA) to sales. The data on sales and operating profit are sourced from Compustat. We use a logarithmic transformation of excess profit margin to adjust for outliers as follows: ln (1000 + excess profit margin). The key explanatory variable is an indicator variable denoting whether or not the company founder is a serial entrepreneur. Serial entrepreneurs have founded businesses before.
Previously unsuccessful serial entrepreneurs are founders whose previous businesses remained private, i.e. neither went public nor were acquired. The definitions of the other control variables are in Appendix 1. Robust pvalues adjusted for lead VC firm clustering are in brackets beneath the parameter estimates. ***, **, and * indicate statistical significance at the 1, 5, and 10 percent levels respectively. The sample includes VC-backed IPOs completed in the 1996-2007 period by U.S. firms that list on major U.S. stock exchanges.
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