Endogeneity

Table 21.6 presents regression models on the determinants of exit outcomes that are similar to those in Table 21.5 but with one major exception. In Table 21.6, we examine the effect of endogeneity of control rights on exits. We use two-step instrumental variable estimates. Step 1 of Models 3 and 4 accounts for the factors that affect the extent of VC control. Step 1 of Model 3 considers binomial logit estimates for majority board seats and the right to replace the CEO. Step 1 of Model 4 considers ordered logit estimates of the control rights index for the sum of dummy variables for drag-along, redemption, and antidilution rights. Step 2 of Models 3 and 4 estimates the multinomial logit model of exit outcomes. In Table 21.6 , we use the exogenous variables that are included in step 1 and excluded in step 2 of Models 3 and 4. These variables are the La Porta et al. (1998) indexes for creditor rights and antidirector (shareholder) rights. These instruments are intuitively related to contract terms, as confirmed by all of the correlations that are reported in Table 21.7 . We do not expect to find a relation between creditor rights and exit outcomes, unless the efficiency of bankruptcy law is related to write-offs. Table 21.7 indicates that creditor rights are not statistically related to any of the exit outcomes, which confirms the suitability of that instrument for the data. Antidirector rights may be positively related to the probability of an IPO (La Porta et al., 1998), but the data here indicate the opposite. The correlation between antidirector rights and IPO exits is 0.18. This negative correlation can only be explained by independent factors driving the IPO exits, and by little or no direct relation between IPOs and antidirector rights. In contrast, the antidirector rights index is significant and negatively related to the contract terms. This finding is consistent with the view that as shareholders, VCs use contracts as substitutes for the absence of strong legal protection (Lerner and Schoar, 2005). Creditor rights are positively and significantly related to contract terms, which is intuitive, because when decisions have be made in times of financial distress, VCs as shareholders want priority over and above creditors. Also, we use the industry market/book value at the time of first investment as an instrumental variable. This is a valid instrument because the second-step regressions use the industry market/book value at the time of exit. The results of the second step regressions are similar when we use the different instruments and different specifications for the first-step regressions and are available on request. In Table 21.6 , the step 1 evidence in Models 3 and 4 indicates that creditor rights are statistically and positively related to the extent of VC control and to the right to replace the CEO, but not statistically related to majority board seats. A one-point increase in the creditor rights index (on the scale of zero to four) increases the probability of the VC acquiring the right to replace the CEO by 31.6%. We note that although the creditor and antidirector rights are negatively correlated ( 0.42 for this sample), the statistical and economic significance of the regressions is not materially affected by the inclusion or exclusion of these variables. For instance, excluding antidirector rights in step 1 of Model 3 in Table 21.6 increases the economic significance of creditor rights from 31.6 to 34.3% for the right to replace the CEO without changing the statistical significance. A one-point increase in the creditor rights index also increases the probability of an extra control right (drag-along, redemption, or antidilution) by on average approximately 3%. The economic significance of a one-point increase in creditor rights is 4.9% to move from two to three, and 2.6% to move from three to four in step 1 of Model 4. In contrast, antidirector rights are more closely tied to majority board seats. An increase of one point in the index (on the scale of 0 to 6) reduces the probability of VC majority board seats by 12.6%. The step 1 regressions in Table 21.6 further indicate that VCs are more likely to have a majority on the board and to have greater control rights for those firms in industries with higher market/ book ratios (high-tech industries). VCs are less likely to take majority board seats, have the right to replace the CEO, and to have other control rights for earlier-stage investments. VCs are also less likely to have the right to replace the CEO and other control rights when the entrepreneur has a higher experience ranking. The step 2 regressions in Models 3 and 4 in Table 21.6 are consistent with those reported for Models 1 and 2 in Table 21.5 . Majority board seats lead to a 22.3% increase in the probability of an acquisition exit (Model 3), and each additional control right increases the probability of an acquisition by 14.5% (Model 4). The one result that differs from Models 1 and 2 is that the right to replace the CEO is statistically insignificant in Model 3. In general, the alternative specifications for the step 1 and 2 regressions in Table 21.6 invariably support at least one of the VC control right variables as being significantly related to acquisition exits. The instrumental variables regressions are not completely robust to alternative specifications, but nevertheless indicate support for the central proposition in the chapter that VC control influences the IPO versus acquisition choice, even after controlling for endogeneity.

Additional Robustness Checks

In this subsection we describe the results from six additional robustness checks (Models 5 –10) that are presented in Table 21.8 . As well, we discuss a number of additional robustness checks that were carried out but not explicitly reported. So that we can include dummy variables for exit years, Models 5 –10 exclude buyback and non exits from the sample. Model 5 presents a standard specification without buybacks and nonexits that is comparable to Model 1 without such exclusions. The regression results are similar and continue to support our central hypothesis. Model 6 provides a similar regression, but excludes investment years 1995 to 1998, because we want to check if contracts are related to exits in a way that is driven by the time period spanned by the data. For instance, if VCs in Europe were less sophisticated in the mid-1990s, and thus wrote less detailed contracts, and since market conditions enabled different exit opportunities in the Internet bubble period, then contracts might be connected to exits for reasons unrelated to the hypotheses discussed in subsection 21.2.1. However, the estimates in Model 6 indicate that the data do not support this alternative explanation for the results. The relation between VC control rights and acquisitions continues to hold for the subsample that excludes investment years 1995 to 1998. The results also hold for other subsamples that exclude other periods that are not explicitly presented here. These results are available on request. Regression Models 5 –8 in Table 21.8 indicate a negative relation between the right to replace the CEO and write-offs. That is, detailed VC contracts tend to enable the VC to prevent“ bad ” outcomes. In Model 7, for example, the right to replace the founding entrepreneur specifically reduces the probability of a write-off by 31.7%, and each additional control right studied (drag-along, redemption, and antidilution) reduces the probability of a write-off by 18.2%. This finding is consistent with Lerner (1995) and Gompers and Lerner (1999a). It is also consistent with the Kaplan et al. (2007) result that international VC funds that do use contracts with strong VC control rights are more likely to survive the Internet bubble crash after 2000. Our results suggest that strong VC rights are more likely to protect a VCs interest and force an acquisition. Weak control rights are more often associated with IPOs, but are also associated with write-offs and a non-covered invest- ment. For instance, there were 15 pure common equity investments in the data with absolutely no control rights above and beyond those held by the entrepreneur. Among those, six were IPOs, six were write-offs, and three were not yet exited in 2005. We also note that the trend in the European data is more often toward using convertible securities, both in the data introduced in this chapter (Table 21.2 ) and in the Kaplan et al. (2007) data. These trends also are consistent with the use of greater downside protection after the crash of the Internet bubble on April 14, 2000, which caused a major downturn in the market. To control for the possibility of endogeneity of contracts vis-à-vis exits, Model 7 excludes the preplanned exits in the data. In the full sample of 223 investments, 70 of the investments (31.4%) indicate a degree of preplanned exit behavior at the time of investment (and do not necessarily indicate such plans to the investee); 55 of the 70 (79%) are exited investments in our sample as of 2005. This evidence on preplanning behavior suggests the possibility of endogeneity vis-à-vis contracts and exits, although the VCs indicate that the preplanned exit outcome was by no means certain at the time of investment. Among the preplanned exits, the investors indicate that their (preplanned) strategy turned out to have the desired result only 53% of the time. Regression Model 7 in Table 21.8 indicates that the results are robust to excluding preplanned exits. This finding is strongly consistent with alternative controls for endogeneity in Table 21.6 . In Models 8 and 9, we examine the subsample of only seed investments i.e., start-ups at the time of first VC investment, and seed and expansion investments, respectively. These are important to show that the results are not driven by investments that were close to exiting at the time of first investment. 6 Model 10 examines only the funds that provided all of their investments as of 2002, which means we had to reject the observations of 15 funds. This robustness check is important to show that the results are not affected by VCs withholding information on some of their investments, such as the poorer performing ones. All of the estimates consistently support the central propositions that relate contracts to exits. In other models (not reported but available on request), we consider dummy variables for funds, rather than countries. The results show that fund effects are not driving the results. However, we note that we could not use dummy variables for 12 funds because of collinearity problems. Further, in other models, which are available on request, we consider different definitions of certain variables to show that the results are not driven by the model specifications. These models use dummy variables for seed, expansion, and late stages. At the time of the first VC investment, there are 69 investments, 82 expansion investments, 32 late investments, and 40 buyouts in the data. The models also use a dummy variable for entrepreneurs with rankings of seven or more (as an alternative to the other models with the ranking variable on the one-to-ten scale) and a second VC dummy for both captive and non-captive VCs. (We suppress the captive bank VC dummy for reasons of collinearity). Because there are 28 exits of foreign investments and nine unexited foreign investments, we also include a variable for the exits in which the investment is initially in a foreign firm. Also, we consider the use of different contract terms, which we include as right-hand-side variables. When we use common equity as a proxy for weak VC control rights, we find that it is associated with a 12.3% greater chance of an IPO and a 30.1% smaller chance of an acquisition. These findings are consistent with the comparison tests in Table 21.3. In a similar specification, we find that drag-along rights are more important in effecting an acquisition than are redemption or antidilution rights. Drag-along rights are associated with a 15.8% reduction in the probability of an IPO and a 31.5% increase in the probability of an acquisition. We also considered other robustness checks, such as Heckman (1976, 1979) sample selection corrections to control for the non-random selection of an exit event versus an ongoing investment in the portfolio. 7 The results are robust. These checks are not reported here but are available on request.

Valuation, Returns and Disclosure

Entrepreneurial firms typically do not have significant cash flow to pay dividends on equity or interest on debt. Therefore, venture capital fund investments are valued primarily on the basis of a capital gain upon an exit event. Exits typically occur two to seven years after the initial investment, so it is crucial that venture capital fund managers accurately value a firm, or its potential, prior to initial investment in view of the resources to be expanded by the venture capital fund manager over the investment life. Unlike more traditional investments, the valuation of the initial investment depends primarily on an expected exit value, which is rather challenging to predict in view of information asymmetries and potential agency costs. The purpose of this chapter is to shed light on a typical methodology used in valuing venture capital investments by venture capital fund managers. As well, we present evidence on how returns to venture capital investment vary depending on the structure of the investment, with consideration to the characteristics of the venture capital fund, the characteristics of the entrepreneurial firm, the contractual relation between the venture capital fund and entrepreneurial firm, market conditions, and different legal settings across countries. It is noteworthy that over the life of the venture capital fund, venture capital fund managers are required to regularly report valuations of unexited investments, and returns of exited investments, to their limited partner institutional investors. As shown by Cumming and Walz (2004), the reported returns on unexited investments, however, tend to be biased upward (Phalippou and Zullo, 2005, confirm this finding). In this chapter we explain factors that lead to reports being biased upward with reference to an international dataset from Cumming and Walz (2004) from 39 countries around the world. The valuation of unexited investments has been a frequently debated issue in the media since the CalPERS lawsuit in 2002 (see Chapter 7) and an issue that has negatively influenced venture capital fund-raising on an industry-wide level. In this chapter we will do the following:
● Review the mechanics underlying the venture capital valuation method
● Present evidence on venture capital fund returns to show ways in which the discount rate or cash flows considered in valuations might be adjusted depending on the characteristics of the venture capital fund, characteristics of the entrepreneurial firm, structure of investment, market conditions, and legal conditions
● Present evidence that shows how returns are disclosed to institutional investors prior to an exit event

Venture Capital Valuation Method

There are numerous ways to value a firm. There are even more books written on how to value a firm than there are valuation methods. 1 A review of different valuation methods is therefore understandably beyond the scope of this book. We will, in this section, describe the venture capital valuation method only. 2 Normally, when carrying out a business valuation, it is appropriate to use a few different methods to assess robustness of the valuation figure to different methods. 3 As well, within any given valuation method, it is normal to consider the robustness of the valuation result to assumptions underlying the method. In the end, it is important to be transparent about the sensitivity of the valuation results to alternative assumptions used in arriving at the valuation and to different valuation methods. The difficulty with valuing venture capital –backed entrepreneurial firms lies in the variability of the returns associated with venture capital investments. As shown in Chapters 19 –21, for example (see also Cumming and MacIntosh, 2003a,b; Cumming and Walz, 2004; Cochrane, 2005; Cumming et al ., 2006; Cumming, 2008), a significant percentage (often 20 to 30%) of investments are written off. Hence, there is huge variability in returns and a massive scope for valuation error. At best, therefore, valuation of venture capital investments is an art and not a science. One valuation method commonly used by venture capital fund managers is known as the venture capital method. This method involves assumptions that may on the surface seem rather arbitrary. A typical successful venture capital – backed entrepreneurial firm has negative cash flows in the early years of the life of the firm and thereafter positive cash flows (Chapter 1, Figure 1.2). The venture capital fund manager first determines the life of the investment before the exit event and the price at which the investment will be sold at that future exit date. For example, if there is a projection about the firm’s earnings in the exit year, then the sale price might be determined in reference to the price earnings multiple of a typical firm in the same industry. The sale price or “ terminal value ” is then discounted back to the day of first investment with the formula in equation 22.1.

Discounted Terminal Value = Terminal Value / (1 + target rate)^years (22.1)

The target rate is the discount rate required by the venture capital fund. This discount rate is critical to the valuation of the investment and varies depending on various factors that are explained following. In practice, the discount rate can be as large as 75%. Venture capital funds do not own 100% of the firms in which they invest. The venture capital fund’s valuation of the entrepreneurial firm must therefore be adjusted to account for the fact that it will hold less than 100% ownership. In the first step in making this adjustment, the venture capital fund calculates the eventual ownership percentage that it will have at the time of exit, or the “ Required Final Percent Ownership, ” as in equation 22.2.

Required Final Percent Ownership = Investment / Discounted Terminal Value (22.2)

The second step in this adjustment accounts for the fact that over successive financing rounds, investment syndication, and changes in the entrepreneurial firm’s management team’s ownership percentage (e.g., through the issuance of stock options), and so on, the venture capital fund’s ownership will get diluted. The required current percentage ownership depends on the venture capital fund’s retention ratio, or percentage of the investment that will be retained from first investment round to final investment round. Consideration of the retention ratio enables the venture capital fund to figure out what percentage of the firm the venture capital fund must own at the date of initial investment to maintain the required final ownership percentage at the date of exit so the venture capital fund maintains enough equity in the firm to achieve the desired rate of return. The calculation for the required current ownership is given by equation 22.3.

Required Current Ownership Percent = Required Final Percent Ownership / Retention Ratio (22.3)

Consider the following example. Suppose you are employed at the Soprano Venture Capital Fund, a hypothetical venture capital fund in New Jersey. Your first assignment is to value the price per share for a$10 million investment in a start-up green technology venture and to decide on what share of the firm you should demand. You project the firm will have net income in Year 6 of $ 40 million. Similar profitable green ventures listed on stock exchanges are trading at an average price-earning ratio of 15. The firm currently has 400,000 shares outstanding. Tony, your boss, tells you that the Soprano Venture Capital Fund requires a target rate of return of 80%. What is the appropriate price per share, and how many shares do you require? The answer is obtained by following the steps in equation 22.3. Notice in the preceding example that there is a problem associated with using the average price-earnings ratios of existing publicly trading green technology firms. Private firms are illiquid relative to publicly listed firms on stock exchanges, and typically an adjustment needs to be made downward (e.g., possibly by 20%) depending on the expected illiquidity of the private firm. More generally, the main difficulty in this venture capital valuation method involves the choice of discount rate. One justification for placing an arbitrarily high discount rate is the value-added advice provided by the venture capital fund manager. Empirical evidence has shown that more prestigious venture capital funds in fact charge higher discount rates (Hsu, 2004). Entrepreneurs are typically more than willing to accept inferior valuations from more prestigious venture capital funds because of the better advice they expect to receive, as well as the access to better networks of legal and accounting advisors, investments bankers, and other individuals and firms that will help the firm succeed. Therefore, in the next section we present evidence on returns and discuss how returns to venture capital fund investment vary systematically depending on the characteristics of the venture capital fund, entrepreneurial firm, transaction-specific issues, and legal and market conditions.

Factors That Affect Venture Capital Realized Returns and Reported Unrealized Returns 1

  In this section we examine returns because an ex-post analysis of returns provides guidance as to how discount factors in valuations might vary depending  on the characteristics of the investment. To begin, it is important to point out that performance statistics vary widely in terms of data quality. Performance indicators are generally not made available to the public, and therefore large representative samples are hard to obtain. Details vary depending on the number of transactions, the years of the transactions, and the different variables in the dataset examined.
  Cochrane (2005) examines the VentureOne database from its beginning in 1987 to June 2000, which consists of 16,613 financing rounds, with 7,765 investee firms. That data enable one to compare market returns to venture capital fund returns while controlling for selection biases in terms of which realized returns are observed. Cochrane estimates that the average log return is 15% per year and finds a beta (the covariance between market returns and venture capital fund returns divided by the variable of market returns) to be 1.7 and the alpha (the performance of venture capital fund returns above that which would otherwise be predicted by the Capital Asset Pricing Model [CAPM], which accounts for systematic risk) to be 32%.
  The statistics in reference to venture capital fund returns presented by Cochrane are interesting, but the dataset used cannot account for features of venture capital that are central to what it is that makes venture capital fund investment distinct from other types of investment. That is, the dataset used provides scant details in terms of venture capital fund characteristics, entrepreneurial firm characteristics, and investment structure characteristics. To be able to value a venture capital fund investment, ideally we would like to analyze more than alphas and betas in a CAPM framework. Venture capital funds hold a small nondiversified portfolio of entrepreneurial firms and pay great attention to the structure of their investment by writing detailed contracts to
mitigate agency costs and idiosyncratic risks. It is worthwhile to assess how returns vary pursuant to evaluating these details to come up with a more accurate portrayal of value drivers.
  Arguably the most comprehensive and detailed venture capital and private equity dataset collected to date is the CEPRES (Center for Private Equity Research) dataset, which is based out of Goethe University of Frankfurt, Germany. The dataset has been described in prior work, including Cumming et al. (2004), Cumming and Walz (2004), and Nowak et al. (2004). The sample contains cash flow information at the level of the individual investment for 5,038 portfolio firms in 221 private equity funds spanning a time period of 33 years (1971 to 2003). The data indicate very detailed information including all cash flow between venture capital funds and entrepreneurial firms,  4 fund characteristics (such as age, fund number, portfolio size per fund manager), entrepreneurial firm characteristics (such as stage of development at the time of first investment and industry), and investment characteristics, such as whether the fund returns are observed by the lead venture capital fund investor in a syndicate, the presence of syndicated investors, co-investment from the same fund managers operating a different fund, board seats, the use of convertible securities, amounts invested, and the standard deviation of cash flows
  Based on the CEPRES data, Cumming and Walz (2004) identified a number of factors that potentially influence the performance of venture capital and private equity investments. The data are presented for internal rates of return (IRRs) that are fully realized versus IRRs that are yet to be realized but reported to institutional investors, are summarized in Table 22.1 .
5 Table 22.1 further indicates differences in mean and median IRRs for realized and unrealized IRRs for different funds, entrepreneurial firm and investment characteristics, and differences across countries and in different economic conditions. Part A summarizes all of the investments in the dataset. Part B considers differences for across different market conditions and legal standards in different countries. Part C considers fund-specific characteristics, Part D considers entrepreneurial firm characteristics, Part E considers investment characteristics, and Part F considers country differences.

  Although venture capital fund managers are obliged to periodically provide reports of the value of the unexited investments to their institutional investors, it has to be noted that by the very fact that the investments that are to be valued as“ unrealized, ” their valuation by the venture capital fund managers are by all accounts subjective and extremely difficult to corroborate. Venture capital fund managers therefore may have an incentive to misreport valuations to their institutional investors for various obvious reasons, most notable of which is to attract more capital for investment.
  Hege et al. (2003), Cumming and Walz (2004), and others focus on IRRs in performance measurement of venture capital investments, despite the fact that IRRs are subject to manipulation (see, e.g., Damodaran, 2006),  6 for a number of reasons. Cumming and Walz explain that perhaps the most important reason is that the venture capital and private equity funds in the CEPRES sample do report IRR for realized and unrealized investments. As Cumming and Walz show, the fund managers do at times manipulate unrealized IRRs in their reports to institutional investors. Hence, it is appropriate to consider IRR because this is what is reported to the institutional investors. It is likewise particularly important to assess robust in regress estimates of factors that influence IRRs, by considering alternative adjusted metrics of performance and various causal mechanisms that
influence performance, as well as multistep selection effects (Cumming and Walz, 2004). Herein we do not go into details beyond summarizing the CEPRES data, since we believe this is an area of evolving research. We do, however, summarize factors that plausibly influence performance that are present in the CEPRES data, as well as discuss in the next subsection other factors that could be considered in valuation and performance that are not present in any current dataset.
  The data reported in Table 22.1 indicate that realized IRRs are significantly higher when the country-specific Morgan Stanley Capital International ( “ MSCI ” ) index returns over the contemporaneous investment period have been higher. Accounting for selection biases as to which firms are fully exited, Cumming and Walz estimate the beta to be approximately 1.45 for all venture capital and private equity investments, which is slightly less than Cochrane’s (2005) beta estimate of 1.7 for venture capital fund investments in the United States. The data in Table 22.1 indicate that the average (median) realized IRR is 58.07% (20.21%) when MSCI returns over the contemporaneous period have been greater than 3.5%. When MSCI returns are less than 3.5%, the average (median) realized IRR is 108.24% ( –10.99%). For unrealized investments, the average (median) IRR is 76.88% (9.32%) when MSCI returns over the contemporaneous period have been above 3.5%. When MSCI returns are less than 3.5%, the average (median) realized IRR is 59.07% (0.00%). It is noteworthy that with the very high-standard deviations in IRRs, differences in average values are statistically insignificant. However, differences in medians are statistically significant. Median realized IRRs are higher in times of better market conditions, but median unrealized IRRs are higher in times of worse market conditions. In other words, venture capital fund managers tend to overreport the value of their unexited investments in times of worse market conditions relative to what one might otherwise expect given existing market conditions (Cumming and Walz, 2004).
  It is interesting to note that a variety of fund characteristics are related to fund IRRs. Based on the Venture Economics data from 1980 to 2001, Kaplan and Schoar (2005) estimate that U.S. fund managers with better performance by 1% on a prior fund achieve a 77-basis-point better performance on the subsequent fund, demonstrating persistence in private equity performance over time. Given this persistence in performance, entrepreneurs tend to prefer financing from more reputable venture capital fund managers. Based on a hand-collected sample (from a dataset collected by MIT) of 148 entrepreneurs, Hsu (2004) estimates that entrepreneurs are three times more likely to accept a financing offer from a high-reputation venture capital fund manager, and these high-reputation venture capital fund managers acquire equity from the investee entrepreneurial firms at a 10 to 14% discount. As well, Lerner et al.(2007) find that different institutional investors tend to be systematically better at selecting fund managers that achieve superior performance results (or have better access to such fund managers).
  In Table 22.1 , Part C, we present the data from Cumming and Walz (2004) by fund characteristics. The data do not indicate specific trends in performance based on the age of the fund manager or the number of funds operated by the fund manager. The data do, however, indicate that the fund manager is much more likely to perform better where portfolio size in terms of the number of investee entrepreneurial firms per fund manager is smaller. The regression estimates in Cumming and Walz (2004) are consistent in showing portfolio size per manager as a very important factor in explaining realized IRRs. A change in portfolio size per manager from 10 to 20 investee entrepreneurial firms, for example, is associated with an expected reduction in realized IRRs by 10%. This evidence is consistent with the findings presented in Chapters 16 and 18 (as well as the theoretical work of Kanniainen and Keuschnigg, 2003, 2004; Keuschnigg, 2004b; and Bernile et al., 2007) that venture capital fund managers with larger portfolios provide less advice to the investee entrepreneurial firms.

Factors That Affect Venture Capital Realized Returns and Reported Unrealized Returns 2

  Part D of Table 22.1 indicates differences in IRRs depending on stage of development and industry. Recall the development stages that were defined in Chapter 1.  Earlier-development stages are associated with lower median realized IRRs but higher average IRRs, which means that there is much greater variance in IRRs and higher potential upside with earlier stages of investment.  Similarly, for high-tech investments (in industries with higher market/book values), average IRRs are higher but median IRRs are lower, which likewise reflects greater variance in IRRs and greater upside potential in high-tech industries. In the dataset there are 14 realized investments from firms that are publicly listed, and their IRRs are very high. The investments appear to be IPO
allocations to venture capital funds for which the fund managers were able to flip the investment shortly after the IPO for a substantial capital gain (see Chapter 19 on IPO underpricing). Notice that start-up stage investments tend to have the greatest unrealized valuations. Valuation standards (Chapter 7) typically suggest that valuations not deviate from zero for recent investments, particularly at the seed stage.  But where it is possible to indicate an appreciation in investment values, this is often done at the start-up stage. Both average
and median valuations of start-up and early-stage investments are significantly larger than the realized IRRs for those investment stages.
  Part E of Table 22.1 indicates differences in IRRs depending on specific investment characteristics. IRRs of realized investments tend to be higher where unaffiliated funds syndicate, while co-investments by affiliated funds tend to show lower IRRs. Recall from Chapter 5 that funds often prohibit co-investment of fund capital in firms which have obtained prior funding from affiliated funds managed by the fund manager because fund managers may have an incentive to use new capital from recently raised funds to bail out the bad investments of prior affiliated funds (e.g., a low IRR buyback exit would look better than a write-off). Regression analyses in Cumming and Walz (2004) show that syndicated investments tend to yield 73% higher IRRs than on syndicated investments, while co-investments tend to yield 33% lower IRRs than non-co-investments. The relation between IRRs and board seats and convertible securities that enable periodic cash flow back to the venture capital fund prior to exit tends to be sensitive to the econometric specification in Cumming and Walz (2004). One explanation is that the use of the convertibles and board seats is endogenous to expected exit outcomes.  Convertible securities with periodic cash flow tend to be positively associated with IRRs, but only for positive IRRs; in other words, cash flows back to the venture capital fund periodically where the entrepreneur is expected to be able to pay back the investor. Board seats tend to be associated with IRRs that are less than zero; in other words, venture capital fund managers are more likely to sit on boards of firms that are performing poorly. Finally, smaller initial investment amounts tend to be associated with lower IRRs. The econometric evidence in Cumming and Walz (2004) shows that an increase in the initial investment from US $ 1 million to US $2 million tends to be associated with an increase in IRRs by 3%, while an increase in the initial investment from US $19 million to US $ 20 million tends to be associated with an increase in IRRs by 0.2%.
  Part F of Table 22.1 reports the data by country and legal origin. IRRs may also vary depending on legal standards in different countries, although it is difficult to predict the relationship between IRRs and legal conditions    On one hand, given risks are more pronounced in countries with inferior legal standards, IRRs may be greater in countries with inferior legal standards in order to compensate for such risks. On the other hand, higher legal standards are associated with lower information asymmetry and lower agency costs that
enhance the efficiency of advice provided by venture capital fund managers to entrepreneurs and mitigate venture capital fund -entrepreneur conflicts (see also Chapter 16). As such, we might expect a positive relation between legal standards and IRRs. The data indicate that English legal origin countries have experienced the highest median realized IRRs (17.49%), while German legal origin countries experienced the lowest median realized IRRs (10.95%).
Tests for differences in medians (rows 96 –101), however, are statistically significant for differences in medians between English and French legal origin.
There are no statistically significant differences in means across legal origins, and this finding is explained by the high variability in returns, consistent with Cochrane’s (2005) evidence for the United States. There are no statistically significant differences in medians across legal origins for unrealized returns.
Mean unrealized returns are highest in German legal origin countries (89.97%), but differences in mean unrealized returns are not significant for German legal origin relative to other legal origin countries (and again, this is due to the high variance). Mean English legal origin unrealized returns are 54.25%, and significantly higher than mean French legal origin unrealized returns (19.10%) and mean Scandinavian legal origin unrealized returns (14.10%). Further, it is noteworthy that for all legal origins, median unrealized returns are lower than median realized returns. Overall, therefore, Part F of Table 22.1 indicates legal origins and country-specific factors do not appear to play as great a role in driving differences in means and medians, at least relative to market and legal factors (Part B of Table 22.1 ), fund characteristics (Part C), portfolio firm characteristics (Part D), and investment characteristics (Part E). In particular, it is noteworthy that the differences in Legality and accounting standards (Part B, rows 6 –11) appear to be stronger drivers of differences in realized and unrealized returns than the legal origins variables in Part F of Table 22.1 .
  The available evidence to date in fact indicates that IRRs are positively correlated with legal conditions. Cumming and Walz (2004) show that median realized IRRs are higher in countries with Legality indices above 20, but mean IRRs are higher in countries with Legality indices below 20. In other words, there is greater variability in IRRs in countries with lower legal standards. Cumming and Walz (2004) show a positive relation between IRRs and legal standards with a dataset from 39 countries and over 5,000 transactions, even after controlling for selection effects and other factors in multistep multivariate regression analyses. Similarly, Lerner and Schoar (2005) analyze 210 investments in 25 developing countries and show a positive relation between post money valuation and legal conditions. Cumming et al. (2006) show a positive relation between legal conditions and the probability that a venture capital–backed firm will exit via an IPO rather than a private sale or write-off, and this effect is robust to statistical selection effects.
  It is also noteworthy in Table 22.1 that the mean unrealized IRRs are higher in countries with lower legal standards (while the median unrealized IRR is slightly higher in countries with Legality indices above 20). Cumming and Walz (2004) show that unrealized IRRs tend to be higher than what we would otherwise expect based on factors that drive realized IRRs. As well, for a subsample of their data, Cumming and Walz (2004) can compare actual realized IRRs with previously reported unrealized IRRs and find legal conditions are a
key factor in explaining venture capital fund managers tendency to overvalue unrealized IRRs when reporting to their institutional investors.
  It is also noteworthy that Cumming and Walz (2004) find evidence that the structure of the investment tends to influence the propensity to overreport valuations on unexited investments. Valuations tend to be overreported for nonsyndicated investments and for co-investments. The intuition is that fund managers are less prone to exaggerate unexited investments when there is a syndicated investor that is potentially independently valuing the investment. By contrast, co-investments involve the same venture capital fund manager and, as discussed, there are agency problems with co-investment that would be consistent with a tendency to overvalue the investment. Convertible securities with periodic cash flows are less likely to be overvalued because the stream of cash flow does in fact make it easier to value the investment (since the valuation does not strictly rest on the estimate of the exit value). Finally, larger investments tend to have a shorter investment horizon until exit and valuations are less opaque. InTable 22.1 we note that the valuation average IRRs of unexited investments of less than US $2,500,000 are 91.8%, while average realized IRRs of exited investments of less than US $2,500,000 are 63.5%, and average IRRs of unexited investments of more than US $2,500,000 are only 34.6%, while average realized IRRs of exited investments of more than US $ 2,500,000 are 75.6%.

Summary and Concluding Remarks

  Venture capital and private equity funds hold small portfolios of entrepreneurial firms that are not well diversified, although this enables fund managers to take their time carrying out extensive due diligence before investments are made and to sit on boards of directors, monitor management, and add value to the enterprise by providing strategic, financial, marketing, human resource, and other advice during the investment life. However, because such funds are  not diversified, idiosyncratic risk matters; because idiosyncratic risk matters, agency costs matter, and thus the design of financial contracts matters.   This book is the first of its kind in the literature on venture capital and private equity to focus its theme specifically on the financial contracting between  parties in venture capital and private equity. One of the primary reasons for the existence of specialized venture capital and private equity funds is the occurrence of information asymmetries and agency costs. If idiosyncratic risks could  be diversified away and/or information asymmetries and agency costs were not present, there would be little scope for venture capital and private equity fund managers to provide value in ways that extend beyond that which banks or other sources of capital do for private and entrepreneurial firms. Part I, Chapter 2 provided an extended review of agency theory in the context of financial contracting with a focus on security design. With the empirical and international focus of this book, Chapter 3 reviewed institutional and legal differences across the countries considered and reviewed the empirical methods  used in the data analyses in each of the chapters of this book.   In Part II we showed that contracts are extremely important for limited partnership funds that act as financial intermediaries between institutional investors and their investee entrepreneurial firms (Chapter 5). As well, public policy that gives rise to“statutory contracts ” matters a great deal for venture capital and private equity fund-raising efforts (Chapters 7 and 9) and the performance of government-created funds (Chapter 9). Further, we showed that compensation is a significant element in venture capital and private equity fund structure  and explained the ways in which compensation varied across different countries (Chapter 6). We also addressed related issues of specialized fund mandates and style drift (Chapter 8) and considered the factors that are important  to institutional investors when they invest in venture capital and private equity funds (Chapter 4).     Part III focused on the relationship between fund managers and investee entrepreneurial firms. We addressed in detail issues relating to financial contracts design in terms of security choice (Chapters 10 and 11), adverse selection  (Chapter 12), corporate venture capital contracts (Chapters 11 and 13), and the use of specific veto and control rights in venture capital contracts (Chapter 14). Part IV started with Chapter 15 with an overview of factors that affect the extent of value-added provided by the investor and the impact of venture capital and private equity investment on innovative activity. We specifically considered the impact of financial contracts on the advice and monitoring provided by venture capital fund managers, as well as scope of disagreement with the investee (Chapter 16). Financial contracts by themselves are incomplete, and as such  other factors matter for investor value-added, including location (Chapter 17) and portfolio size (Chapter 18). Finally, in Part V we explained the central role of divestment or “ exit ” to the venture capital and private equity investment process. We overviewed factors that affect the extent of exit and duration of investment in Chapter 19.  Contracts that inefficiently govern the structure of funds have negative consequences for the exit performance of the fund (Chapters 20 and 21). Contractual structures affect the returns to venture capital and private equity investments, which in turn impacts investment valuations (Chapter 22). We also reviewed evidence (Chapter 22; see also Chapter 7), which showed that the ways in which valuations of unexited investments are reported to institutional investors depend significantly on contractual structures between the fund and its investee entrepreneurial firms. In short, all aspects of venture capital and private equity investment involve idiosyncratic risks and a central role for financial contracts. A striking feature about the venture capital and private equity market is the international differences in the size of markets around the world (Chapter 1; see also Armour and Cumming, 2006; Jeng and Wells, 2000). We had documented international differences in fund structures (Part II), contracts between funds and entrepreneurs (Part III), differences in value-added (Part IV), and differences in exit performance (Part V). International differences in venture capital markets are largely consistent insofar as poor legal conditions are associated with less efficient limited partnership contracts, less efficient managerial compensation, less efficient financial contracts with entrepreneurs, and less successful exit outcomes and financial returns. We may expect that countries with weaker venture capital and private equity markets will continue to lag behind with a poor supply of capital as long as poor legal conditions with weak shareholder rights and enforcement conditions persist in those countries. As well,  there is evidence that law impacts the demand for venture capital: Countries with entrepreneur-friendly bankruptcy laws are more likely to have a greater demand for venture capital (Armour and Cumming, 2006) and a greater rate of self-employment (Armour and Cumming, 2008). (For more generally on public policy toward venture capital, see Chapter 9; see also Kanniainen and Keuschnigg, 2003, 2004; Keuschnigg, 2003, 2004a,b; Keuschnigg and Nielsen, 2001, 2003a,b, 2004a,b,c.) Summary and Concluding Remarks 725 There has been some work on the real effects of venture capital and private equity, which we had reviewed in Chapter 15 (for a more detailed survey, see Cumming et al., 2007). Further research could consider international differences in the real effects in relation to contractual structures employed in different countries. International differences in venture capital may become blurred over time as markets become increasingly integrated. As we showed in Chapters 4 and 7, many institutional investors invest internationally in venture capital and private equity funds. Evidence on international contract structures, such as U.S. venture capital investment in Canadian entrepreneurial firms (Chapter 11) and crossborder European venture capital investment (Chapter 14) shows contracts are  written in ways that are very similar to those between entrepreneurs resident in those countries and domestic investors. Additional data on topic across other countries might, however, shed further light on topic. Finally, it is noteworthy that there is evidence that venture capital and private equity funds relocate their investee entrepreneurial firms to other countries after investment. For instance, Cumming et al. (2004a) show that Asia-Pacific venture capital funds often relocate their investee entrepreneurial firms to the United States after they invest but before they exit. Relocations yield higher returns than keeping the investee entrepreneurial firms in their respective country of origin. These differences can be explained by the improvement in legal conditions in the United States relative to the country of origin, as well as the increased size of the product market. Further work on transnationals in entrepreneurial, venture capital, and private equity markets would be a fruitful avenue for future work, particularly in relation to contract structures. As Meggingson (2004) predicts, it appears likely that there will be a growing trend toward a more global venture capital and private equity market around the world and greater internationalization of entrepreneurial ventures in the coming years. How and why venture capital and private equity contracts evolve in different countries will likely have significant implications for the performance and growth of venture capital and private equity markets.