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Adverse selection and capital structure: evidence from venture capital.

Venture capitalists (VCs) in all non-U.S. countries around the world have consistently reported the use of a variety of securities, including common equity, preferred equity, convertible preferred equity, debt, convertible debt, and combinations (in the U.S., VCs typically use convertible preferred equity, and there is a tax bias in favor of that instrument in the U.S.). The types of entrepreneurial firms that receive venture finance may be defined by a variety of characteristics, such as stage of development, type of industry, and capital requirements. Given this broad context observed in practice, previous research has not considered the extent to which different securities, among the complete class of forms of finance, attract different types of entrepreneurial firms. In this article, we investigate the empirical tractability of the adverse selection risks associated with capital structure from 4,114 first-round Canadian venture capital investments. We first characterize the nature of uncertainty (in terms of the risk of financing a lemon or a nut) facing investors for different types of entrepreneurial firms. We then show that VC syndication significantly mitigates problems of adverse selection.

Introduction

This article considers the screening of venture capitalist (VC) investments. In particular, this article investigates the issue of whether different financial instruments (including debt, common equity, preferred equity, and convertible securities) attract different types of entrepreneurial firms in terms of the adverse selection risks associated with financing low-quality firms in relation to the financial security used. A central contribution of this article is the assessment of whether syndication mitigates such adverse selection risks.

It has been well established that firm-specific characteristics affect the choice of financial security (e.g., Jensen & Meckling, 1976; Noe & Rebello, 1996; Rajan & Zingales, 1995). It has also been well established that offers of different forms of finance attract different types of entrepreneurial firms. Seminal research on selection effects and capital structure focused on debt and common equity (DeMeza & Webb, 1987, 1992; Stiglitz & Weiss, 1981). Consistent with the seminal work of Akerlof (1970) (and the related work of Stiglitz (see, e.g., Stiglitz & Weiss, 1981) and Spence (1973) for the joint award for the 2001 Nobel Prize in Economics), the theoretical literature shows that equity attracts firms with low expected returns (consistent with the language adopted in the literature, we hereafter refer to firms with low expected mean returns as lemons), whereas debt finance attracts firms with high variability in returns (hereafter referred to as nuts). Related research on adverse selection and capital structure has considered convertible securities; e.g., Brennan and Kraus (1987) show that firms with low variability in expected returns are attracted to convertible securities. The intuition linking these different securities to different types of adverse selection risks is explained in the next section of this article.

The VC market offers an interesting forum for empirically examining the relation between adverse selection and forms of finance. Risk management is particularly important for VC funds. VCs have enhanced screening and monitoring abilities, and are active value-added investors. (1) Because they finance early stage firms for which there is a comparative dearth of information, VCs take significant steps to try to avoid financing low-quality firms. Research on VC is consistent with the proposition that VCs are among the most sophisticated financial intermediaries with abilities to mitigate agency problems. (2) Therefore, in considering the VC market, we study not only pronounced problems of adverse selection, but also specialized investors that take active steps to mitigate such problems.

This article makes three main contributions. First, we introduce a new data set that indicates, consistent with VCs in Europe and in all countries (where data are available) other than the United States, VCs in Canada use a variety of forms of finance. Second, we introduce evidence that certain types of investors have a preference for financing certain types of entrepreneurial firms and syndicate with different degrees of frequency. Third, and perhaps most important, we empirically assess the relation between capital structure and adverse selection across a wide array of entrepreneurial firms with different characteristics for the complete class of forms of finance (debt, convertible debt, preferred equity, convertible preferred equity, common equity, and combinations thereof). We further provide new and unique tests of the effect of syndication on adverse selection costs pertaining to capital structure.

With regards to the link between adverse selection and capital structure, the most notable results in this article are as follows. We show that firms in the startup stage (with little or no track record) tend to select away from common equity and tend to select toward offers of debt finance. This indicates that the risk of financing startup stage firms is better characterized as a risk of financing a nut, and not a lemon. Similarly, we show that high-tech firms are more likely to select toward debt and are less likely to select toward convertible securities that provide the investor with upside potential and downside protection. This is consistent with the widely accepted view that high-tech firms are riskier than their nontech counterparts. Importantly, we further show that syndication significantly mitigates problems of adverse selection, consistent with research on why VCs syndicate their investments (Lerner, 1994; Lockett & Wright, 1999, 2001; Manigart et al., 2002b; Wright & Lockett, 2003). Our results on syndication complement this prior literature by providing a unique and new test of the role of syndication mitigating problems of adverse selection as they pertain to the use of different types of securities in venture finance.

This article is organized as follows. In the next section, we develop hypotheses pertaining to adverse selection in entrepreneurial finance. The Canadian Venture Capital Association (CVCA) data are then described. Empirical evidence is then presented, and the last section concludes.

Adverse Selection, Capital Structure, Firm Characteristics, and Syndication

In this section, we develop hypotheses relating problems of adverse selection among alternative forms of finance to entrepreneurial firms at different stages of development and in different industries. We also consider the effect of syndication on adverse selection. Our theoretical discussion in this section and empirical tests in the subsequent sections are focused on first-round VC investments only, and not on follow-on staged financing rounds.

Theoretical Principles on Adverse Selection and Capital Structure

To understand the link between adverse selection and capital structure, it is helpful to review the properties of the different types of securities. Common equity is analogous to a call option. Common equity holders have a claim to all of a firm's cash flows, but only after all other claimants have been satisfied. If the firm goes bankrupt, then equity holders are the last to be paid (debt holders have priority over preferred equity holders, who in turn have priority over common equity holders); however, common equity holders cannot lose more than their investment in the firm by virtue of the firm's limited liability. Common equity is therefore analogous to a call option on the firm, whereby exercising the option requires that the firm be liquidated and the face value of the debt (the option price) be paid off. The payoff function to common equity is bounded below by the cost of the common equity investment and by unlimited potential on the upside. The payoff to straight (nonconvertible) debt, by contrast, is limited to the present discounted value of all interest payments and to the principal on debt (similarly, the payoff to nonconvertible preferred equity is limited to the present discounted value of all prespecified preferred dividends). In the event of an entrepreneurial firm's failure to pay interest on debt, an investor can force a firm into bankruptcy. In the event of an entrepreneurial firm's failure to pay a prespecified preferred dividend, an investor cannot force a firm into bankruptcy, but all preferred dividends must be paid before any common dividends can be paid.

The well-known lemons principle (Akerlof, 1970), in the context of capital structure theory, is based on the idea that the form of finance offered by an investor attracts the worst possible type of firm for that form of finance. Theoretical research has well established the propositions that common equity attracts firms with low expected returns (lemons) (adverse selection costs of common equity) (DeMeza & Webb, 1987, 1992), straight debt and straight preferred equity attract firms with high variability in returns (nuts) (adverse selection costs of straight debt and straight preferred equity) (Stiglitz & Weiss, 1981), and convertible securities attract firms with low variability of returns (adverse selection costs of convertible securities) (Brennan & Kraus, 1987). Investors anticipate these problems and structure contracts accordingly (see, e.g., Brennan & Kraus, 1987). We review the intuition underlying these results in this subsection.

The intuition underlying the theoretical work of DeMeza and Webb (1987, 1992) linking common equity and lemons is as follows. A VC that finances an entrepreneurial firm with common equity receives significant upside potential in terms of obtaining an ownership interest in the entrepreneurial firm, but does not receive downside protection in terms of priority in bankruptcy. Entrepreneurial firms with lower expected mean returns have lower opportunity costs associated with giving up larger ownership interests to VCs through common equity contracts relative to entrepreneurial firms with high expected returns. Entrepreneurial firms with lower expected returns also have higher opportunity costs associated with giving up downside protection (in bankruptcy) to their VC investors. As such, VCs that offer common equity contracts to their entrepreneurial investee firms face a more pronounced adverse selection problem in terms of attracting entrepreneurial firms with lower expected average returns.

The intuition underlying the theoretical work of Stiglitz and Weiss (1981) linking nonconvertible debt (and similarly nonconvertible preferred equity) and nuts is as follows. A VC that uses debt to finance a firm does not receive any ownership interest and therefore does not derive the benefit of capturing the upside potential associated with an improvement in the quality of the firm (i.e., above and beyond an increase in the probability in being paid back the interest and principal on the debt contract). Entrepreneurial firms with high expected variability (standard deviation) of returns have higher opportunity costs associated with giving up larger ownership interests to VCs through equity contracts. The reason is as follows. If a risky venture happens to be successful, then the entrepreneur financed with debt captures 100% of the upside potential success. In the literature, this is sometimes referred to as a situation in which the entrepreneur thinks "Heads I win" in that the firm happened to do well, and the entrepreneur captured all of the benefits associated with winning the lottery. By contrast, if a risky venture happens to fail, then the entrepreneur financed with debt has not lost to the same degree as the investor that has not been repaid. In the literature, this is sometimes referred to as a situation in which the entrepreneur thinks "Tails you lose" in that the firm happened to fail, but the loss in capital provided to finance the firm is more heavily borne by the investor that provided such capital. In short, investors that offer debt contracts to their entrepreneurial investee firms face a more pronounced adverse selection problem in terms of attracting entrepreneurial firms with higher expected variability in returns.

Adverse Selection Risks in Venture Capital Finance

Adverse selection risks exist because of information asymmetry in that entrepreneurs have information that VCs do not have. In order to understand the extent to which entrepreneurs may have information that VCs do not have, it is necessary to identify and distinguish the entrepreneurial firm characteristics that are in fact known to VCs, such as the stage of development of the entrepreneur and the industry in which the entrepreneur operates. But not all entrepreneurial characteristics can be completely known by the VCs (such as the entrepreneur's intelligence, managerial abilities, planned work effort, scientific skills for developing patents, and technical processes for the firm, etc.). Hence, adverse selection risks will exist, and will exist to different degrees depending on the entrepreneurial firm characteristics that the VCs can identify.

Based on prior research, we may conjecture that, for entrepreneurial startup stage firms without a track record (or a significant track record) and for firms in high-tech industries, VCs are better able to screen the risks associated with financing a lemon relative to the risks associated with financing a nut. In other words, a "bad" firm is easier for a VC to screen than a "risky" one. The intuition is clear for four interrelated reasons. First, theoretical work (e.g., Hopenhayn & Vereshchagina, 2004; Landier & Thesmar, 2003) and empirical evidence (e.g., Moskowitz & Vissing-Jorgensen, 2002) consistently show that entrepreneurs bear substantial risk but do not earn a return that compensates for such risks. Most work in entrepreneurial finance is consistent with the view that entrepreneurs have significant risk tolerance and over optimism. This means that entrepreneurs downplay the risk of variance of potential outcomes associated with their startup firms. Second, entrepreneurs are not inclined to start a firm that they believe is a lemon due to the stigma of failure and the opportunity costs of not working elsewhere. Third, VCs can screen lemons through due diligence reviews based on the entrepreneur's track record in terms of leisure preference, (3) as well as managerial and technical competence that had been established before starting the particular firm seeking VC finance. (4) Fourth, while a VC can use past performance to mitigate the risk of financing a lemon, it would be much more difficult for a VC to ascertain whether an entrepreneur's latest idea is best characterized as nuts on the basis of the entrepreneur's past performance (i.e., it is easier to forecast the mean than the variance of expected value). Taken together, these four reasons suggest the following conjecture, which is tested in the subsequent sections of the article.

Hypothesis 1: The adverse selection risks associated with capital structure for financing risky nuts are more pronounced and difficult to mitigate through screening, relative to the adverse selection risks of financing low-quality lemons, for first-round VC financings of startup stage and high-tech entrepreneurial firms.

We further hypothesize that syndication reduces informational asymmetries and adverse selection costs through information sharing and improved screening. The intuition is based on the idea that due diligence is enhanced by bringing together complementary skills and stage and/or industry expertise from VC managers employed in different VC funds. The prediction that syndication mitigates adverse selection risks is consistent with analyses of syndication in different contexts (in the context of VC finance, see Dimov & De Clercq, 2006; Jaaskelainen, Maula, & Seppa, 2006; Lerner, 1994; Lockett & Wright, 1999, 2001; Manigart et al., 2002b; Wright & Lockett, 2003; for earlier work in a general context of syndication, see Leland & Pyle, 1977). We complement and build on this prior work by analyzing for the first time the effect of syndication on problems of adverse selection associated with different securities used in venture finance. With this literature that syndication facilitates due diligence and screening, we conjecture the following hypothesis:

Hypothesis 2: VC syndication in the first round of investment mitigates the adverse selection risks associated with capital structure decisions for financing startup stage and high-tech companies.

Further to H2, note that in Canada there are a variety of different types of investors, including private independent limited partnerships, corporate VCs, government VC funds, labor-sponsored venture capital corporations (LSVCCs), institutional investors, as well as foreign (U.S.) funds. In the empirical analyses in the next sections, we consider differences in the quality of the syndication among these different fund types. Our priority is to expect that U.S. VCs face greater hurdles in screening investments due to geographic distance. LSVCCs may also face greater difficulties in screening investments as a fund with statutory constraints that impose a time limit (from 1-2 years, depending on the jurisdiction in which they are incorporated) lot reinvestment of capital that has been contributed by investors (see, e.g., Cumming & Macintosh, 2003; Halpern, 1997; Osborne & Sandler, 1998 for the statutory details).

The data used to test these hypotheses are described in the next section. Then, empirical tests of the hypotheses developed herein are presented. We control for the different types of investors and make use of artificial regressions to explore problems of adverse selection for the complete class of forms of finance among different types of entrepreneurial firms. Limitations, alternative explanations, future research, and conclusion comprise the final sections of the article.

Data

To investigate problems of adverse selection in capital structure decisions, it is both necessary and interesting to consider a country in which VC investors finance a wide variety of different types of entrepreneurial firms and to use a heterogeneous mix of forms of finance. Research on the U.S. VC industry is consistent with the proposition that VCs rarely use forms of finance other than convertible preferred equity (Gompers, 1998; Kaplan & Stromberg, 2003; Sahlman, 1990); therefore, the U.S. VC market does not offer a useful forum to address problems of adverse selection in capital structure. Nevertheless, there are reasons why VCs use forms of finance other than convertible preferred equity, and data indicate a variety of forms of finance are employed by VCs in all countries around the world other than the United States. (see, e.g., Cumming, 2005a, 2005b; Hege, Palomino, & Schwienbacher, 2004; Lerner & Schoar, 2005).

The data used in this article comprise 4,114 first-round Canadian VC financing transactions from 1991 (Q1)-2003 (Q3) (source: Macdonald and Associates, Ltd., for the CVCA; see http://www.canadavc.com). All VC investors in Canada finance a wide variety of entrepreneurial firms and use a wide variety of financial instruments (see Table 1, panels A-G). The tables show that the use of a variety of forms of finance by VCs in Canada is not due to the definition of "venture capital" in Canada (e.g., early stage only, or early and expansion stage (5)). Given the heterogeneity in the types of firms and the use of different forms of finance, the Canadian VC market offers an excellent forum in which to study risks of adverse selection in capital structure. In fact, Canada is the only country in the world with industry-wide venture finance data to empirically study adverse selection and capital structure. For the purpose of analyzing adverse selection in venture finance, we control for changes in market conditions over the period considered, as subsequently described. Our focus is on first-round investments in the startup and expansion stage firms only in order to focus on the screening of new pure VC investments (and not later stage private equity investments). The data are summarized in Table 1.

There exist seven types of VC investors in Canada (see also Cumming, 2005a; Cumming & Macintosh, 2003): private independent limited partnerships, corporate, government, institutional, labor sponsored, foreign (U.S.), and "other." Private independent funds (Table 1, panel A) are similar to U.S. VC limited partnerships, but Canadian private independent VC funds generally have fewer and less restrictive covenants placed on the investment managers (Cumming & Macintosh, 2003). Canadian corporate VCs (Table 1, panel B) are analogous to U.S. corporate VCs (Gompers & Lerner, 1999), but tend to finance a somewhat more heterogeneous group of entrepreneurial firms (see Table 2). Government VC funds in Canada (Table 1, panel C) are managed by independent professional VC managers and finance a wide variety of different entrepreneurial firms. Institutional investors (Table l, panel D) are larger institutions that make direct VC investments. LSVCCs (Table 1, panel E) are significantly different than the other Canadian VC funds. These differences arise through statutory restrictive covenants placed upon LSVCC managers (Cumming & Macintosh, 2003; Osborne & Sandler, 1998). The tests below control for the fact that the constraints in which LSVCCs operate may influence not only their choice of types of firms in which they invest, but also the types of securities they employ, irrespective of the characteristics of their investees. Foreign investors (Table 1, panel F) are U.S. limited partnership investors that invest in Canadian entrepreneurial firms. The category of other (including "unknown") investors (Table 1, panel G) encompasses all other types of investors that less regularly appear in the CVCA data.

Table 1 panels A-G clearly show that convertible preferred equity has not been the most commonly used form of finance by Canadian VCs. This result is not due to the type of VC fund, or the type of firms being financed, as documented in Table 1 panels A-G. It is also not due to the definition of VC, as the results in Canada hold for the funds most similar to U.S. limited partnerships (the transactions for Canadian private independent funds are presented in Table 1, panel A). The 4,114 transactions in Table 1 panels A-G are used in the following section to test the hypotheses developed in section 2. Because the evidence in Table 1 panels A-G drastically differs from U.S. evidence on venture finance on the use of convertibles (e.g., Gompers, 1998; Kaplan & Stromberg, 2003; Sahlman, 1990), we exhaustively present the data by type of VC and entrepreneurial firm. The differences between the Canadian and U.S. evidence are consistent with a tax bias in favor of convertibles in the United States (Gilson & Schizer, 2003), and this tax bias is absent in Canada (Sandler, 2001 ; see also Cumming, 2005a for further details on tax aspects and security choice in Canada and in the United States).

The CVCA data consider syndication as more than one VC fund from different VC organizations that simultaneously fund the entrepreneurial firm in the first round of the investment. Consistent with Gompers and Lerner (1999), we do not consider "coinvestment" (different VC funds that are part of the same VC organization) as a syndicated investment.

The subsequent empirical analysis focuses on the standard financial instruments: debt, convertible debt, preferred equity, convertible preferred equity, common equity, and combinations of debt and common equity. A broader contract space does exist in practice. For example, convertible debt is a hybrid bond that allows its bearer to exchange it for a given number of shares of common stock anytime up to and including the maturity date of the bond. A broader contract space, however, is not considered herein for a number of reasons. Articles that do consider a broader contract space (e.g., Aghion & Bolton, 1992) yield optimal contracts that resemble the standard financial instruments. The fact that the standard instruments in corporate finance are used most frequently suggests that considerable gains arise from standardization, and greater transaction costs arise from designing contracts to mimic the standard forms of finance (Berglof, 1994; Macdonald, 1992). Regardless, the data used to test the hypotheses developed herein have been recorded such that if a contract was designed to mimic one of the standard forms of finance, then the standard form was recorded. (6)

The econometric analyses in the next section consider the entire sample of 4,114 first-round investments without segmenting the sample by type of VC fund. Different VC funds syndicate more than 50% of their investments (see Table l, panels A-G, and Table 2). Separating the data by sectors would fail to account for VC syndicates across different investor types (Table 2), and would therefore significantly bias the results. Table 2 in fact shows a massive degree of integration across different types of VC funds in Canada insofar as different types of investors syndicate with one another. The use of the full data set enables the richest array of results by accounting for interactions among different VC funds in Canada, while recognizing that the Canadian VC market is not segmented by sectors.

Empirical Evidence

The empirical evidence in this section is presented as follows. First, econometrics methods for the determinants of forms of finance used in prior work are discussed. Second, we consider the first step of a Durbin-Wu-Hausman (DWH) test for the purpose of setting up the test of adverse selection. Third, the test of adverse selection is provided with the second step of the DWH test. Finally, robustness checks are provided.

The Determinants of Forms of Venture Capital Finance. In the Canadian context (with the absence of the U.S. tax bias; Gilson & Schizer, 2003; Sandler, 2001), Cumming (2005a) considered the determinants of the selected form of finance by estimating multinomial logit regressions of the following form:

(*) Probability (security selected) = [alpha] + [[beta].sub.1] Startup + [[beta].sub.2] High-tech + [[beta].sub.3] Deal size + [[beta].sub.4] LSVCC + [[beta].sub.5] Capital gains tax + [[beta].sub.6] Toronoto Stock Exchange (TSX) + [[beta].sub.7] Trend + [epsilon]

The right-hand-side variables in equation * include a dummy variable for startup firms (a dummy for expansion-stage firms is suppressed for reasons of perfect collinearity; other later stage firms are excluded from the data herein), a dummy for high-tech firms, the capital required by the entrepreneurial firm (in real 2000 Canadian dollars and in logs), a dummy variable for LSVCCs, a variable for the capital gains tax changes, (7) a dummy variable for the Toronto TSX index, (8) and a trend term to account for changes over time. These variables are also used herein in the subsequent sections, particularly in regard to assessing the potential effect of potential endogeneity of the first three variables in equation *.

In the following subsections, we consider in more detail the nature of this adverse selection problem associated with different forms of finance and the presence of certain types of entrepreneurial firms in the market for VC finance. Adverse selection would exist with respect to hypothesis 1, where the variables startup and high-tech are endogenous in equation *. To consider this possibility, we proceed in two steps. In the first step, we consider instrumental variables that impact the types of firms that may exist in the market for VC. In the second step, we use the residuals from the first-step regressions to test the effect of endogeneity on the estimated coefficients in equation *. This artificial regression in the second step, a version of the DWH test, (9) is not a direct test for exogeneity, but does indicate the effect of endogeneity on the coefficient estimates in equation *, and therefore provides insight into the nature of adverse selection associated with different forms of finance and different types of entrepreneurial firms.

Do Different Types of Investors Select Different Types of Entrepreneurial Firms? VCs typically receive around 1,000 requests for financing each year (Sahlman, 1990). This may create noise in the matching of entrepreneurial firms to VC funds. But VC funds tend to have a preference for financing certain types of entrepreneurial firms according to their stage of development, required capital, and/or type of technology, among other things (Gompers & Lerner, 1999; Mayer et al., 2005). (10) Herein, we relate the presence of different types of firms in the VC market to geographic location of investees (11) and to the type of VC fund. We estimate the binary logit regression equations 1 and 2, and ordinary least squares regression equation 3 of the following form:

(1) Probability (Startup) = [Year fixed effects] + [[beta].sub.1] Corporate + [[beta].sub.2] Government + [[beta].sub.3] Institutional + [[beta].sub.4] LSVCC + [[beta].sub.5] LSVCC + [[bet].sub.6] Foreign investor + [[beta].sub.7] Other type of VC + [[beta].sub.8] British Columbia + [[beta].sub.8] Alberta + [[beta].sub.9] Saskatchewan + [[beta].sub.10] Manitoba + [[beta].sub.11] Ontario + [[beta].sub.12] Quebec + [[epsilon].Startup]

(2) Probability (High-tech) = [Year fixed effects] + [[beta].sub.1] Corporate + [[beta].sub.2] Government + [[beta].sub.3] Institutional + [[beta].sub.4] LSVCC + [[beta].sub.5] LSVCC + [[beta].sub.6] Foreign investor + [[beta].sub.7] Other type of VC + [[beta].sub.8] British Columbia + [[beta].sub.8] Alberta + [[beta].sub.9] Saskatchewan + [[beta].sub.10] Manitoba + [[beta].sub.11] Ontario + [[beta].sub.12] Quebec + [[epsilon].sub.High-up]

(3) Probability (Syndication) = [Year fixed effects] + [[beta].sub.1] Startup + [[beta].sub.2] High-tech + [[beta].sub.3] Log (Deal size) + [[beta].sub.4] Corporate + [[beta].sub.5] Government + [[beta].sub.6] Institutional + [[beta].sub.7] LSVCC + [[beta].sub.8] LSVCC + [[beta].sub.9] Foreign investor + [[beta].sub.10] Other type of VC + [[beta].sub.11] British Columbia + [[beta].sub.12] Alberta + [[beta].sub.13] Saskatchewan + [[beta].sub.14] Manitoba + [[beta].sub.15] Ontario + [[beta].sub.16] Quebec + [[epsilon].sub.Syndication]

In equations 1-3, a dummy variable for private independent limited partnerships is suppressed to avoid perfect collinearity problems; as such, the other coefficients are relative to the private independent funds. A dummy variable for the Maritime Provinces is suppressed to avoid perfect collinearity as well. Year fixed effects are used to account for the possibility of different types of firms (by stage of development, industry type, and capital requirements) present in the market for VC in different years due to market conditions. [[epsilon].sub.Startup], [[epsilon].sub.High-tech], and [[epsilon].sub.Syndication] are vectors of residuals for equations 1-3, respectively, and are used in the subsequent endogeneity tests. Diagnostic tests suggested in the main that the right-hand-side variables for equations 1-3 were orthogonal to the different forms of finance (see Table 3) and are therefore suitable instruments for the DWH tests of endogeneity subsequently described. (12) The main results are not sensitive to the choice of instruments (alternative regressions are on file with the author, as well as an earlier version of the article yielding similar results).

The estimates for equations 1-3 are presented in Table 4. Also, analogous to regression equation 3, Table 4 also presents regression equations 4-6 for syndications with LSVCCs only (regression equation 4 as specified in Table 4), foreign VCs only (regression equation 5 in Table 4), and for syndications for all other types of investors excluding foreign VCs and LSVCCs (regression equation 6 in Table 4).

There are two main results in Table 4. First, investments in certain types of entrepreneurial firms are related to overall investment activity in different geographic regions in Canada. In particular, VC-backed startups are less prevalent in Alberta and Saskatchewan, and high-tech VC-backed companies are more prevalent in British Columbia and less prevalent in Alberta, Saskatchewan, Manitoba, and Quebec. Second, there is support for the proposition that different types of VC funds often finance different types of entrepreneurial firms in Canada and display differences in the propensity to syndicate investments. Subsequently, we elaborate on this second result, as it is more generalizable to contexts in other countries where comparative work could be considered.

Table 4 indicates that corporate funds are 29.8% less likely to invest in startup stage firms and 30.0% less likely to invest in high-tech firms relative to private limited partnerships. Institutional investors are 34.3% less likely to invest in startup stage and 32.8% less likely to invest in high-tech firms relative to limited partnerships. LSVCCs are 19.2% less likely to invest in startup stage and 34.6% less likely to invest in high-tech firms relative to limited partnerships. By contrast, government funds are 5.7% more likely to invest in startup stage firms and 77% less likely to invest in high-tech firms relative to limited partnerships. Foreign (U.S.) VCs are 20.3% less likely to invest in startups, but are 12% more likely to invest in high-tech companies relative to limited partnerships.

Table 4 regression equation 3 indicates differences in the propensity of different types of VC funds to syndicate their investments. Relative to private independent limited partnerships, corporate VCs are 12.% more likely to syndicate, government VCs are 12% more likely to syndicate, institutional VCs are 12.8% less likely to syndicate, LSVCCs are 90% less likely to syndicate, and foreign (U.S.) investors are 12.2% more likely to syndicate. For all types of VC funds considered together (regression equation 3), we observe syndication 16.9% more frequently for startups and 16.5% more frequently for high-tech companies.

Syndication is also more likely the greater the total value of the deal. In regard to the economic significance of that effect, an increase in deal size from C$1,000,000 to C$2,000,000 increases the probability of syndication by 6.7%, whereas an increase in deal size from C$11,000,000 to C$12,000,000 increases the probability of syndication by 0.8. (13)

Table 4 regressions equations 4-6 consider the determinants of the propensity of LSVCCs to syndicate (regression equation 4), U.S. VCs to syndicate with Canadian VCs (regression equation 5), and all other types of VCs taken together (that is, all excluding LSVCCs and U.S. VCs; regression equation 6). LSVCCs are considered separately for reasons indicated earlier (see also Osborne & Sandler, 1998). U.S. VCs are considered separately because they are geographically distinct, if not in other ways as well.

Regression equations 4 and 5 in Table 4 do in fact indicate significant differences exhibited by LSVCCs and U.S. VCs. The propensity of LSVCCs to syndicate is invariant for startups and for high-tech firms, unlike other VCs (compare regression equation 4 with regression equations 3, 5, and 6). U.S. VCs, by contrast, are less 2.5% likely to syndicate with Canadian VCs for startup investments and 1.5% more likely to syndicate with Canadian VCs for high-tech investments.

In the next subsection, we use the vectors of residuals in regression equations 1-6 in Table 4 to construct artificial regressions and test for the effect of endogeneity associated with estimating equation * (the DWH test). That is, while the choice of form(s) of finance depends on the type of firm and the particular agency problems associated with the investment, are different types of firms more attracted to different forms of finance, and does syndication mitigate such adverse selection problems?

Adverse Selection, Forms of Finance, and Firm Characteristics: Empirical Evidence. In this subsection, we test for the effect of adverse selection associated with the choice of form(s) of finance by estimating a system of artificial regressions of the following form:

(7) Probability (Security selected) = [alpha] + [[beta].sub.1] Startup + [[beta].sub.2] High-tech + [[beta].sub.3] Log (Deal size) + [[beta].sub.4] LSVCC + [[beta].sub.5] Capital gains tax + [[beta].sub.6] TSX + [[beta].sub.7] Trend + [[beta].sub.8] [[epsilon].sub.Startup] + [[beta].sub.9] [[epsilon].sub.High-tech] + [[beta].sub.10] [[epsilon].sub.Syndication] + [epsilon]

Recall from the first subsection that different forms of finance may be more appropriate for different entrepreneurial firms (equation *); but the causal relation between type of firm and form of finance is not unidirectional. The key empirical insight is that where the residual vectors ([epsilon]) are not orthogonal in equation 7, different types of firms are attracted to different forms of finance. Statistically significant estimates indicate the residuals [[epsilon].sub.Startup], [[epsilon].sub.High-tech], and [[epsilon].sub.Syndication] are not orthogonal to the selected security; that is, they are endogenous, such that startups, high-tech, and syndicated investments are observed in the data because of the presence of the particular security that is part of the VC financing transaction. A positive coefficient is evidence of selection toward that security and vice versa for a negative coefficient.

Instead of providing the extended version of all of the multinomial logit regression coefficients of equation 7, we present only the marginal effects of such estimates. Only the marginal effects and statistical significance for [[beta].sub.8]-[[beta].sub.10] are reported in Table 5, as these coefficients are pertinent to the issue of adverse selection by virtue of the effect of endogeneity on the coefficient estimates of equation *. This has the benefit of conciseness, and shows economic as well as statistical significance.

Table 5 provides evidence relating selection effects to forms of finance for the different types of firms financed by Canadian VCs. Panel A of Table 5 considers all of the different types of VC funds that syndicate together. Panel B of Table 5 distinguishes syndication among LSVCCs and foreign VCs only from the rest of the types of VCs.

Three primary results are apparent from panels A and B of Table 5. The first primary result is that startup stage firms manifest adverse selection problems vis-a-vis debt finance. That is, startup stage firms are more likely to be attracted by offers of debt finance (Table 5, panel A). This result is statistically significant at the 1% level of significance, and the estimated economic significance is such that adverse selection problems are 4.3% more pronounced for startup stage firms (relative to expansion stage) in debt-financed transactions. Similarly, the data indicate that adverse selection problems for startup stage firms are 5.3% less pronounced for common equity finance and 1.7% more pronounced for mixes of debt and common equity finance (panel A). This evidence is consistent with the view that startup stage entrepreneurs do not like to "give up" common equity to their investors and would prefer to be financed by debt. Consistent with the prediction in section 2 (hypothesis 1), the data therefore indicate that startup stage firms manifest greater uncertainty as nuts as opposed to lemons. The economic and statistical significance of each of these effects are similar in panel B in Table 5, illustrating the robustness of the results.

The second primary result in Table 5 is that adverse selection problems are much more pronounced for firms in high-tech industries, as evidenced by the greater number of statistically and economically significant coefficients for high-tech firms. The data indicate that high-tech firms are attracted toward debt. In particular, adverse selection effects for high-tech firms are 5.3% more pronounced (relative to nontech firms) for debt finance (and similarly, they are more likely to select toward mixes of debt and common, and preferred and common). The economic and statistical significance is similar for panel B in Table 5 for high-tech investments. There is further evidence in both panels A and B that high-tech entrepreneurs are more inclined to select away from securities in which they would be required to give up equity ownership to their investors; for example, in support of theoretical research on adverse selection and convertible securities (Brennan & Kraus, 1987), the evidence indicates that high-tech firms are 9.2% more likely to select away from convertible preferred equity, and 4.1% more likely to select away from convertible debt. Overall, as with the evidence for startup stage firms discussed immediately above, this evidence for high-tech entrepreneurial firms is consistent with the conjecture in hypothesis 1 that the uncertainty associated with investment in high-tech firms is better characterized as uncertainty in the variability of returns (nuts) as opposed to uncertainty in average expected returns (lemons).

The third primary result in Table 5 is that, in support of hypothesis 2, adverse selection is more problematic for high-tech investments than for syndicated investments. That is, there are fewer statistically significant coefficients for syndication than for high-tech investments in Table 5, panel A. (Note that the number of significant coefficients for early stage and syndicated investments is similar in Table 5, but the evidence in the next subsection explores differences from a companion perspective in more detail.) Further, note in panel B of Table 5 that there are two statistically significant coefficients for syndication among LSVCCs, two for foreign VCs, and one for syndication among the other VC types. Overall, therefore, adverse selection appears to be slightly more problematic for LSVCCs and U.S. investors investing in Canada. As discussed earlier (see text accompanying hypothesis 2), these latter results are expected, since U.S. VCs face distance hurdles in carrying out due diligence and the screening Canadian investees. Likewise, LSVCCs face statutory covenants that require they invest capital within 1-2 years of receipt from investor (or risk paying a fine to the government, or even revocation of the opportunity to operate as a LSVCC; Osborne and Sandler [1998]); this statutory covenant on LSVCCs compromises the time that LSVCC managers have for carrying out their due diligence and hence exacerbates adverse selection problems for LSVCCs.

Robustness Cheeks on the Adverse Selection Tests. In this subsection, we carry out two robustness checks on the adverse selection tests. Robust check number 1 (Table 6) presents estimates similar to that in Table 5, but with syndicated and nonsyndicated investments treated separately as two different subsamples (we do not treat different types of investors in different subsamples for reasons previously indicated). The second robustness check (Table 7) again presents similar tests, but with the difference that the dollar value of the deal size is treated as a potentially endogenous variable as well. Overall, the tests in Table 5 yield quite similar results to these two alternative specifications, as explicitly shown in Tables 6 and 7, and as described subsequently.

In Table 6, panel A, the tests for the subsample of nonsyndicated investments show four statistically significant coefficients for startups; by contrast, Table 6, panel B, for the subsample of syndicated investments, shows only one statistically significant coefficient for startups. This reinforces the view that syndication facilitates screening such that the security does not "cause" the presence of the particular entrepreneurial characteristics; that is, syndication mitigates adverse selection problems associated with startups. Similarly, in Table 6, panel A, there are five significant coefficients for high-tech companies, but only four significant coefficients for high-tech firms in panel B. This latter difference in the number of significant coefficients for the syndication versus nonsyndication subsamples is less pronounced for high-tech companies, but again still illustrates a benefit to syndication with respect to mitigating adverse selection problems. As discussed, this evidence is consistent with prior work on the rationales underlying syndication (hypothesis 2; see also Lerner, 1994; Lockett & Wright, 1999, 2001; Manigart et al., 2002b; Wright & Lockett, 2003). Furthermore, note in Table 6 that the coefficients are significant in a way that is very similar to those in Table 5; as described in subsection 4.3, this supports the views that startups and high-tech companies are better characterized as nuts and not as lemons (hypothesis 1).

Table 7 carries out very similar tests as in Table 6. The difference in Table 7, relative to Table 6, is that for equation *, we also consider the possibility that Log(Deal size) is endogenous as well. In Tables 6 and 7, we did not consider that variable as endogenous since capital requirements to start a project are typically taken as exogenous in theoretical (e.g., Kanniainen & Keuschnigg, 2003, 2004; Keuschnigg, 2003) and empirical work (e.g., Manigart et al., 2002b). The estimates in Table 7 are presented separately for the first-round transactions that were not syndicated (panel A) and those that were syndicated (panel B), as in Table 6. The results in Table 7 are quite consistent with Table 6 in that for startup and high-tech firms, adverse selection problems are mitigated by syndication. Therefore, the results pertaining to hypotheses 1 and 2 previously described are not affected by the treatment of the deal size variable as either exogenous or endogenous.

As an aside, note that Table 7 indicates selection effects associated with a firm's capital requirements are not mitigated by virtue of syndication. Panel A (for nonsyndicated investments) indicates no statistically significant coefficients (even at the 10% level of significance) for capital requirements, while panel B (for syndicated investments) indicates two statistically significant coefficients (one at the 1% level and one at the 10% of significance). First-round syndicated investments naturally do tend to involve larger deal sizes (average deal size for first-round syndicated investments was $1,501,126, whereas average deal size for first-round nonsyndicated investments was $1,078,892). It is therefore not surprising that adverse selection problems vis-a-vis capital requirements are not smaller by virtue of syndication (unlike the role of adverse selection problems vis-a-vis startup stage and high-tech firms previously discussed) since syndication most often involves larger deals.

Finally, it is important to stress that we have consistently demonstrated in Tables 5-7 that syndication mitigates adverse selection problems for startups and high-tech companies. We have never claimed (and the data do not show) that syndication completely eliminates adverse selection. The view that agency problems can be mitigated but not eliminated has been well documented (see, e.g., Farmer & Winter, 1986).

Conclusion and Discussion

The Canadian VC market is a unique setting in which one may study nonsegmented financial intermediaries that are not restricted by the type of security they may employ. Within this setting, we build on previous research (e.g., Brennan & Kraus, 1987; DeMeza & Webb, 1987; Stiglitz & Weiss, 1981) by relating and tracking the presence of selection effects in capital structure to a variety of types of entrepreneurial firms and for the complete class of forms of finance. This article provided new tests of the empirical tractability in adverse selection in a nonsegmented market in which financial intermediaries use any number of different forms of finance and finance a variety of types of entrepreneurial firms. We controlled for changes in the economic environment over the 1991-2003 period both in regard to types of firms in the market for venture finance and in regard to selected securities.

The data introduced in this article indicated two primary results in terms of adverse selection and capital structure in the VC context. First, the evidence enabled a characterization of the type of uncertainty faced by investors in different types of entrepreneurial financing transactions in terms of the risk of financing a nut or a lemon. Canadian VC investors appear to face the greatest uncertainty among firms with high expected variability in returns (nuts) in financing startup stage and high-tech firms. Second, the evidence indicated strong support for the conjecture that syndication mitigates problems of adverse selection (consistent with earlier work on the rationales underlying the decision to syndicate; see Lerner, 1994; Lockett & Wright, 1999, 2001; Manigart et al., 2002b; Wright & Lockett, 2003). VC syndicates therefore facilitate an important role in screening potential investees and mitigating the risk of financing low-quality firms associated with different capital structure decisions.

As we are unaware of prior work that has carried out similar tests, we provide a few remarks about the robustness of our results and extensions to other contexts. First, we employed artificial regressions to test for the effect of endogeneity on the coefficient estimates in equation *. To the extent that equation * is not appropriate for other contexts, the implied adverse selection evidence may not be generally applicable.

Second, we do not consider transaction-specific relative price changes across different securities, among certain other factors; this may limit the extent to which the results are generalizable. Increasing the price of one security relative to another may lead some entrepreneurs to switch to an alternative source of finance (e.g., from the type of financial intermediary providing debt to the type of financial intermediary providing equity; see e.g., DeMeza & Webb, 1987, 1992; Stiglitz & Weiss, 1981). Given the limitation that our data do not indicate relative security prices for forms of finance in Canadian venture capital, we hold constant relative security prices and focus on adverse selection associated with the use of alternative forms of finance. (14) Similarly, our data do not indicate information pertaining to specific control rights (Gompers, 1998; Kaplan & Stromberg, 2003; Sahlman, 1990). To the extent that selection effects are associated with the allocation of specific control rights, there may be "noise" in our empirical evidence. Nevertheless, following DeMeza and Webb (1987, 1992), Myers and Mjluf (1984), Noe and Rebello (1992, 1996), Rebello (1995), and Stiglitz and Weiss (1981), among others, we suspect that selection effects are more broadly associated with form(s) of finance at the outset, and not the particular underlying terms of the financial contract determined pursuant to contractual negotiations and fine tuning.

Third, pronounced differences may exist among financial intermediaries other than VCs, as well as across countries, for institutional and legal reasons (see, e.g., Manigart et al., 1996; Manigart et al., 2002b, 2002c; Manigart et al., 2006; Mayer et al., 2005), for differences in governance, syndication, and returns across countries).

An important finding in this article is that problems of adverse selection are in fact context dependent and vary depending on firm characteristics and on the presence of investor syndicates. The context-dependent nature of our results suggests a number of avenues for future research. Further theoretical research could also incorporate different and/or broader contract spaces for alternative forms of finance, different types of entrepreneurial firms, and different financial intermediaries. Analyses of adverse selection in the context of work on team formation (e.g., in the spirit of Forbes, Borchert, Zellmer-Bruhn, & Sapienza, 2006; Ruef, Aldrich, & Carter, 2003) could be carried out with more detailed hand-collected data. Empirical work in different countries and/or among different financial intermediaries could also be fruitful in providing an improved understanding of adverse selection and capital structure among entrepreneurial firms.

I owe special thanks to Mary Macdonald for helpful comments and insights into venture capital in Canada. I owe thanks to seminar participants at the University of Alberta School of Business, the Schulich School of Business, York University, the University of British Columbia Sauder School of Business, the Center for Financial Studies, University of Frankfurt, the University of Cambridge Judge Institute of Management, the Universitita di Bologna Forli School of Business, and the Nottingham University Business School University of Nottingham Institute of Enterprise and Innovation Entrepreneurship Research Workshop. I have also greatly benefited from comments from an anonymous referee, as well as discussions and comments from Dirk De Clercq, Andy Lockett, Deniz Ucbasaran, and John Butler, and comments on an earlier draft from Varouj Aivazian, Paul Halpern, Mark Huson, Ted Liu, Frank Mathewson, Mary Macdonald, Randall Morck, Tom Ross, Barry Scholnick, and Ralph Winter. l am grateful for financial support from the University of Alberta Pearson Fellowship and the University of British Columbia Entrepreneurship Research Alliance Scholarship. Macdonald & Associates, Limited (Toronto) generously provided the data.

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(1.) See, e.g., Berger and Udell (1998), Bergmann and Hege (1998), Casamatta (2003), Casamatta and Haritchabalet (2003), De Clercq and Sapienza (2001), Gompers and Lerner (1999), Kanniainen and Keuschnigg (2003, 2004), Keuschnigg (2003), Manigart, Sapienza, and Vermeir (1996), Manigart et al. (2000, 2002a, 2002b, 2002c), Mayer, Schoors, and Yafeh (2005), Sapienza (1992), Trester (1998), and Wright and Lockett (2003).

(2.) See, e.g., references listed in footnote 1.

(3.) For example, at a Master of Business Administration lecture at the University of Alberta in 2003, a practicing VC described the due diligence process as including, but not limited to, meetings and barbecues with the entrepreneurs' family and spouse.

(4.) Technical competence can be assessed, e.g., from academic transcripts and peer reviews from practitioners.

(5.) Following the CVCA definitions, a startup stage firm is based on a concept without a product or any marketing, or it may have a product being developed, but not yet sold commercially. An expansion stage firm requires significant capital for plant expansion and marketing to initiate full commercial production and sales.

(6.) The inclusion/exclusion of less commonly used forms of finance was immaterial to the analyses and results.

(7.) In 1990, the effective capital gains rate in Canada was 36%. Because marginal income tax rates rose through the 1990s, the effective capital gains rate rose as high as 39.8% (in 1995) before falling back to 36.6% in 1999. In March 2000, the effective capital gains rate was reduced to 23.2%. The different capital gains tax rates can influence security choice in Canada as it directly affects the attractiveness of equity (capital gains) to investors (see Cumming, 2005a).

(8.) Different market conditions can influence security design, as investors and entrepreneurs change with changing market conditions (see Cumming, 2005a).

(9.) Davidson and MacKinnon (1993) discuss DWH tests for continuous variables. These specification tests have also been referred to as simply "Hausman specification tests" in various texts. Angrist (2001), Rivers and Vuong (1988), Wooldridge (2000, 2002), and others consider various ways to deal with endogeneity in limited dependent variable models. The problem of causal inference is not fundamentally different (see, e.g., Angrist, 2001, section 4), but limited dependent variables do present additional challenges in certain contexts, particularly for censored regression models. The DWH artificial regressions with (potentially endogenous) standard binary dummy variables in the context of this article are quite robust to alternative methods and specifications. The tests are also quite robust to various possible adjustments for multiple potential endogenous variables as described in, e.g., Maddala (2001, chap. 12).

(10.) See also mission statements from venture capital firms; links are available from http://www.vfinance.com and http://www.cvca.ca.

(11.) The location variables are included to account for the fact that different types of entrepreneurial firms may be more prevalent in different provinces in Canada due to regional economic differences.

(12.) Different types of VC funds in Canada are not restricted from using different forms of finance. Different types of funds may prefer to finance certain types of entrepreneurial firms, and different forms of finance may be more appropriate for different types of entrepreneurial firms, but there is generally no direct incentive for different types of funds to use different forms of finance. A possible exception is the case of LSVCCs (see Cumming, 2005a, for details); therefore, we include the LSVCC variable in the endogeneity tests.

(13.) The calculations are [log(12,000,000)-log(11,000,000)] x 0.224 = 0.008, and [log(2,000,000)--log(1,000,000)] x 0.224 = 0.067. Logs were used to account for a diminishing effect of deal size on the probability of syndication. Linear specifications did not materially change the results reported. Alternative specifications are available upon request.

(14.) But this may not be a significant limitation for two reasons. Since all types of VCs in Canada employ all forms of finance (see Table 1), relative security prices for entrepreneurs seeking venture financing in Canada are likely quite stable, especially compared with situations in which different forms of finance are only available from different types of financial intermediaries. Moreover, startups are hard to value, and investors and entrepreneurs therefore delay valuation to the second round, when more information is available. I owe thanks to an anonymous referee for this latter helpful comment.

Please send correspondence to: Douglas Cumming, e-mail: cummid@rpi.edu at Severino Center for Technological Entrepreneurship, Lally School of Management and Technology, Rensselaer Polytechnic Institute, Troy, New York.

Douglas Cumming is an associate professor and director at the Severino Center for Technological Entrepreneurship at the Lally School of Management and Technology, Rensselaer Polytechnic Institute, Troy, New York.
Table 1
Summary of Canadian VC Investment Data by Type
of Security, VC Fund, and Entrepreneurial Firm

Panel A. Private independent limited partnership venture capital funds

                                   Total
                                 number of                  Proportion
                                first-round   Proportion        of
Type of security                investments   of startup     expansion

Preferred equity                     91          0.769         0.231
Common equity and/or warrants       367          0.796         0.204
Convertible preferred equity        109          0.826         0.174
Debt                                 91          0.703         0.297
Convertible debt                    164          0.732         0.268
Debt and common equity               31          0.419         0.581
Preferred and common equity          18          0.722         0.278
Mixes of other securities           124          0.798         0.202

                                                Average
                                Proportion      amount      Proportion
                                    of         invested         of
Type of security                 high-tech      ('000)      syndication

Preferred equity                   0.857      1,437.808        0.648
Common equity and/or warrants      0.766        870.575        0.477
Convertible preferred equity       0.826        888.457        0.578
Debt                               0.659        647.483        0.308
Convertible debt                   0.774        753.058        0.390
Debt and common equity             0.452        638.415        0.516
Preferred and common equity        0.667        591.940        0.500
Mixes of other securities          0.855        757.091        0.605

                                Proportion    Proportion    Proportion
                                 in years         in            in
Type of security                 1991-1998     1999-2000     2001-2003

Preferred equity                   0.341         0.319         0.341
Common equity and/or warrants      0.529         0.302         0.169
Convertible preferred equity       0.404         0.330         0.266
Debt                               0.692         0.176         0.132
Convertible debt                   0.537         0.268         0.195
Debt and common equity             0.871         0.032         0.097
Preferred and common equity        0.667         0.056         0.278
Mixes of other securities          0.339         0.387         0.274

Panel B. Corporate venture capital funds

                                   Total
                                 number of                  Proportion
                                first-round   Proportion        of
Type of security                investments   of startup     expansion

Preferred equity                    27           0.593         0.407
Common equity and/or warrants       82           0.622         0.378
Convertible preferred equity        47           0.553         0.447
Debt                                80           0.313         0.688
Convertible debt                    43           0.628         0.372
Debt and common equity              26           0.346         0.654
Preferred and common equity          4           0.250         0.750
Mixes of other securities           77           0.662         0.338

                                                Average
                                Proportion      amount      Proportion
                                    of         invested         of
Type of security                 high-tech      ('000)      syndication

Preferred equity                   0.704       1,638.536       0.778
Common equity and/or warrants      0.671       1,411.269       0.646
Convertible preferred equity       0.809       1,715.965       0.766
Debt                               0.438       1,194.438       0.450
Convertible debt                   0.651         976.280       0.698
Debt and common equity             0.346       1,081.462       0.577
Preferred and common equity        0.750         739.335       0.750
Mixes of other securities          0.584         793.493       0.623

                                Proportion    Proportion    Proportion
                                 in years         in            in
Type of security                 1991-1998     1999-2000     2001-2003

Preferred equity                   0.333         0.296         0.370
Common equity and/or warrants      0.390         0.280         0.329
Convertible preferred equity       0.234         0.447         0.319
Debt                               0.325         0.538         0.138
Convertible debt                   0.302         0.372         0.326
Debt and common equity             0.577         0.269         0.154
Preferred and common equity        0.500         0.500         0.000
Mixes of other securities          0.065         0.234         0.701

Panel C. Government venture capital funds

                                   Total
                                 number of                  Proportion
                                first-round   Proportion        of
Type of security                investments   of startup     expansion

Preferred equity                    44           0.773         0.227
Common equity and/or warrants      284           0.824         0.176
Comrrtible preferred equity         49           0.796         0.204
Debt                                65           0.692         0.308
Convertible debt                    96           0.771         0.229
Debt and common equity              28           0.643         0.357
Preferred and common equity          8           0.750         0.250
Mixes of other securities           86           0.849         0.151

                                                Average
                                Proportion      amount      Proportion
                                    of         invested         of
Type of security                 high-tech      ('000)      syndication

Preferred equity                   0.909        780.352        0.795
Common equity and/or warrants      0.574        575.024        0.342
Comrrtible preferred equity        0.837        998.616        0.816
Debt                               0.523        537.813        0.492
Convertible debt                   0.615        505.848        0.615
Debt and common equity             0.607        606.096        0.536
Preferred and common equity        0.625        770.450        0.875
Mixes of other securities          0.651        579.790        0.547

                                Proportion    Proportion    Proportion
                                 in years         in            in
Type of security                 1991-1998     1999-2000     2001-2003

Preferred equity                   0.318         0.227         0.455
Common equity and/or warrants      0.718         0.120         0.162
Comrrtible preferred equity        0.265         0.163         0.571
Debt                               0.477         0.169         0.354
Convertible debt                   0.448         0.177         0.375
Debt and common equity             0.536         0.107         0.357
Preferred and common equity        0.750         0.000         0.250
Mixes of other securities          0.384         0.151         0.465

Panel D. Institutional investors

                                   Total
                                 number of                  Proportion
                                first-round   Proportion        of
Type of security                investments   of startup     expansion

Preferred equity                    31           0.323         0.677
Common equity and/or warrants      113           0.442         0.558
Convertible preferred equity        18           0.667         0.333
Debt                               144           0.438         0.563
Convertible debt                    56           0.429         0.571
Debt and common equity              47           0.404         0.596
Preferred and common equity          6           0.167         0.833
Mixes of other securities           53           0.661         0.340

                                                Average
                                Proportion      amount      Proportion
                                    of         invested         of
Type of security                 high-tech      ('000)      syndication

Preferred equity                   0.645       1,150.588       0.516
Common equity and/or warrants      0.575       1,813.993       0.372
Convertible preferred equity       0.778       1,471.400       0.722
Debt                               0.340         878.360       0.347
Convertible debt                   0.429       1,572.134       0.393
Debt and common equity             0.319       1,176.706       0.398
Preferred and common equity        0.667       1,805.777       0.500
Mixes of other securities          0.528       3,152.704       0.528

                                Proportion    Proportion    Proportion
                                 in years         in            in
Type of security                 1991-1998     1999-2000     2001-2003

Preferred equity                   0.419         0.161         0.419
Common equity and/or warrants      0.496         0.345         0.159
Convertible preferred equity       0.389         0.222         0.389
Debt                               0.306         0.292         0.403
Convertible debt                   0.429         0.321         0.250
Debt and common equity             0.447         0.383         0.170
Preferred and common equity        0.833         0.167         0.000
Mixes of other securities          0.321         0.377         0.302

Panel E. Labor-sponsored venture capital funds

                                   Total
                                 number of                  Proportion
                                first-round   Proportion        of
Type of security                investments   of startup     expansion

Preferred equity                     64          0.688         0.313
Common equity and/or warrants       289          0.578         0.422
Convertible preferred equity         85          0.741         0.259
Debt                                150          0.520         0.480
Convertible debt                    114          0.596         0.404
Debt and common equity               97          0.536         0.464
Preferred and common equity          30          0.600         0.400
Mixes of other securities           130          0.662         0.338

                                                Average
                                Proportion      amount      Proportion
                                    of         invested         of
Type of security                 high-tech      ('000)      syndication

Preferred equity                   0.609       1,666.579       0.516
Common equity and/or warrants      0.429       1,407.547       0.391
Convertible preferred equity       0.776       1,179.064       0.682
Debt                               0.360       1,658.972       0.273
Convertible debt                   0.658       1,408.740       0.518
Debt and common equity             0.320       1,075.662       0.278
Preferred and common equity        0.267         780.316       0.367
Mixes of other securities          0.585       1,182.964       0.523

                                Proportion    Proportion    Proportion
                                 in years         in            in
Type of security                 1991-1998     1999-2000     2001-2003

Preferred equity                   0.344         0.297         0.359
Common equity and/or warrants      0.561         0.232         0.208
Convertible preferred equity       0.282         0.271         0.447
Debt                               0.513         0.267         0.220
Convertible debt                   0.430         0.237         0.333
Debt and common equity             0.660         0.227         0.113
Preferred and common equity        0.400         0.467         0.133
Mixes of other securities          0.385         0.262         0.354

Panel F. Foreign (U.S.) venture capital funds

                                   Total
                                 number of                  Proportion
                                first-round   Proportion        of
Type of security                investments   of startup     expansion

Preferred equity                    17           0.765         0.235
Common equity and/or warrants       48           0.688         0.313
Convertible preferred equity        15           0.800         0.200
Debt                                 8           0.625         0.375
Convertible debt                     9           1.000         0.000
Debt and common equity               2           1.000         0.000
Preferred and common equity          3           0.000         1.000
Mixes of other securities           80           0.513         0.488

                                                Average
                                Proportion      amount      Proportion
                                    of         invested         of
Type of security                 high-tech      ('000)      syndication

Preferred equity                   1.000       2,460.133       0.824
Common equity and/or warrants      0.896       4,473.606       0.750
Convertible preferred equity       0.867       3,238.532       0.933
Debt                               0.750       2,048.213       0.875
Convertible debt                   1.000       2,096.885       0.889
Debt and common equity             0.500       1,121.992       0.500
Preferred and common equity        0.667         833.526       1.000
Mixes of other securities          0.975       6,348.063       0.900

                                Proportion    Proportion    Proportion
                                 in years         in            in
Type of security                 1991-1998     1999-2000     2001-2003

Preferred equity                   0.059         0.412         0.529
Common equity and/or warrants      0.333         0.375         0.292
Convertible preferred equity       0.200         0.467         0.333
Debt                               0.625         0.375         0.000
Convertible debt                   0.556         0.222         0.222
Debt and common equity             1.000         0.000         0.000
Preferred and common equity        0.667         0.333         0.000
Mixes of other securities          0.038         0.713         0.250

Panel G. Other types of investors

                                   Total
                                 number of                  Proportion
                                first-round   Proportion        of
Type of security                investments   of startup     expansion

Preferred equity                    24           0.667         0.333
Common equity and/or warrant       157           0.783         0.217
Convertible preferred equity        53           0.755         0.245
Debt                                50           0.720         0.280
Convertible debt                    62           0.710         0.290
Debt and common equity              20           0.800         0.200
Preferred and common equity         12           0.833         0.167
Mixes of other securities           86           0.767         0.233

                                                Average
                                Proportion      amount      Proportion
                                    of         invested         of
Type of security                 high-tech      ('000)      syndication

Preferred equity                   0.708       1,297.772       0.917
Common equity and/or warrant       0.662       1,346.061       0.873
Convertible preferred equity       0.736       1,138.705       0.925
Debt                               0.460       1,125.385       0.900
Convertible debt                   0.581         755.826       0.968
Debt and common equity             0.250         753.110       0.900
Preferred and common equity        0.667       2,701.023       0.750
Mixes of other securities          0.791       3,756.433       0.756

                                Proportion    Proportion    Proportion
                                 in years         in            in
Type of security                 1991-1998     1999-2000     2001-2003

Preferred equity                   0.250         0.375         0.375
Common equity and/or warrant       0.363         0.299         0.338
Convertible preferred equity       0.377         0.321         0.303
Debt                               0.640         0.180         0.180
Convertible debt                   0.452         0.306         0.242
Debt and common equity             0.450         0.200         0.350
Preferred and common equity        0.333         0.500         0.167
Mixes of other securities          0.093         0.372         0.535

Note: This table presents the number of first-round investments by
type of VC fund. entrepreneurial firm, and security. Different
securities over different years and by (non-) syndication are
presented. The proportions of startup and expansion sum to 1.0.
The proportion of nonhigh-tech is equal to I minus the proportion
of high-tech. The proportion of nonsyndication is equal to 1 minus
the proportion of syndication. The average amounts invested are in
real $2.000 Canadian dollars. The different types of VC funds are
indicated in each panel (A-G) separately.
VC, venture capitalist.

Table 2
Syndication and Integration among Different Types of VC Funds in Canada

                        (1) Total      (2) Number of    (3) Proportion
                        number of       first-round     of first-round
                       first-round       syndicated       syndicated
                           fund             fund             fund
                       investments      investments      investments
                                                           has been
                                                           invested
                                                         (all rounds)

Private independent         995              489            0.491
  limited
  partnership VCs
Corporate VCs               386              242            0.627
Government VCs              660              332            0.503
Institutional VCs           468              188            0.402
LSVCCs                      959              410            0.428
Foreign VCs                 182              155            0.852
Other types of VCs          464              405            0.873
Totals                    4,114            2,221            0.540

                        (4) Total        (5) Total      (6) Proportion
                        number of        number of       of different
                        different        different       companies in
                       companies in     companies in      which the
                        which fund       which fund      partnership
                      type has been    type fund type        VCs
                      invested as a     has invested     (all rounds)
                        syndicated          as a
                         investor        syndicated
                       (all rounds)       investor
                                        (all rounds)

Private independent       1,322             736             0.557
  limited
  partnership VCs
Corporate VCs               692             433             0.626
Government VCs              913             563             0.617
Institutional VCs           668             365             0.546
LSVCCs                    1,516             710             0.468
Foreign VCs                 279             257             0.921
Other types of VCs          840             770             0.917
Totals                    3,696 *         1,440 *           0.390

                        (7) Number       (8) Number       (9) Number
                       of different     of different     of different
                        companies        companies        companies
                        syndicated       syndicated       syndicated
                       with private    with corporate        with
                         limited            VCs         government VCs

Private independent         39
  limited
  partnership VCs
Corporate VCs              197               25
Government VCs             263              151               12
Institutional VCs          165              121              163
LSVCCs                     328              175              247
Foreign VCs                178              109              100
Other types of VCs         392              214              321
Totals                     736 *            433 *            563 *

                       (10) Number      (11) Number
                       of different     of different
                        companies        companies
                        syndicated       syndicated
                           with         with LSVCCs
                      institutional
                           VCs

Private independent
  limited
  partnership VCs
Corporate VCs
Government VCs
Institutional VCs           16
LSVCCs                     158               34
Foreign VCs                 68              116
Other types of VCs         155              379
Totals                     365 *            710 *

                       (12) Number      (13) Number
                       of different     of different
                        companies        companies
                        syndicated       syndicated
                       with foreign      with other
                           VCs          types of VCs

Private independent
  limited
  partnership VCs
Corporate VCs
Government VCs
Institutional VCs
LSVCCs
Foreign VCs                  7
Other types of VCs         134                8
Totals                     257 *            770 *

* Note: This table presents the total number of first-round fund
investments (column 1), the total number of syndicated first-round
fund investments (column 2), and the proportion of first-round
syndicated investments (column 3, which is column 2 divided by
column 1). In addition, to illustrate the extent of integration
among different fund types in Canada, this table presents, by
the number of investee companies for all investment rounds, the
following information: the total number of different companies
in which the fund type has been involved as a syndicated investor
(column 4), the number of different companies in which the fund
type has been involved as a syndicated investor (column 5), the
proportion of different companies in which the fund type has been
involved as a syndicated investor (column 6, which is column 5
divided by column 4), and the number of companies in which the
fund type has syndicated with different types of other VCs
(columns 7-13). Note that the * next to some of the totals
indicates the column does not add up to the total because multiple
syndications (i.e., syndications with more than two investors)
across different fund types give rise to double counting of companies.
VC, venture capitalist; LSVCC, labor-sponsored venture capital company.

Table 3
Correlations between Securities and Type of VC Fund and Location

                                              Common
                                              equity      Convertible
                               Preferred      and/or       preferred
                                equity       warrants       equity

Private limited partnership       0.04          0.05          0.04
Corporate VC                      0.00         -0.08          0.03
Government VC                    -0.01          0.10         -0.03
Institutional VC                 -0.01         -0.06         -0.07
LSVCC                            -0.01         -0.03         -0.01
Foreign (U.S.) investor           0.02         -0.03         -0.01
Other type of VC                 -0.03          0.01          0.03
British Columbia                  0.02         -0.03          0.12
Alberta                           0.01          0.04          0.02
Saskatchewan                     -0.03          0.01         -0.03
Manitoba                         -0.01          0.04          0.00
Ontario                           0.06          0.01          0.04
Quebec                           -0.05         -0.02         -0.11

                                                           Debt and
                                            Convertible     common
                                 Debt          debt         equity

Private limited partnership      -0.08          0.05        -0.07
Corporate VC                      0.06         -0.02         0.01
Government VC                    -0.06          0.02        -0.03
Institutional VC                  0.17         -0.01         0.06
LSVCC                             0.02         -0.02         0.09
Foreign (U.S.) investor          -0.06         -0.05        -0.04
Other type of VC                 -0.04          0.00        -0.03
British Columbia                 -0.05         -0.01        -0.05
Alberta                          -0.02         -0.03        -0.03
Saskatchewan                      0.07         -0.02         0.00
Manitoba                          0.00         -0.02         0.00
Ontario                          -0.10         -0.01        -0.07
Quebec                            0.11          0.04         0.10

                               Preferred     Mixes of
                              and common       other
                                equity      securities

Private limited partnership      -0.01         -0.05
Corporate VC                     -0.02          0.04
Government VC                    -0.02         -0.03
Institutional VC                 -0.02         -0.04
LSVCC                             0.05         -0.03
Foreign (U.S.) investor           0.00          0.17
Other type of VC                  0.02          0.03
British Columbia                 -0.02          0.03
Alberta                           0.00         -0.01
Saskatchewan                     -0.02         -0.01
Manitoba                          0.05         -0.03
Ontario                          -0.04          0.07
Quebec                            0.04         -0.08

Note: This table presents correlation coefficients across securities
and type of VC fund and location of entrepreneurial firms. Correlations
greater than 0.04 are statistically significant at the 5% level of
significance. Correlations are presented for first-round investments
only (4,114 observations). VC, venture capitalist.

Table 4
Logit Regressions for Startup, High-Tech,
and Syndication: First-Stage DWH Regressions

                                                             (3)
                                                         Syndication:
                           (1)              (2)           All types
                         Startup         High-tech          of VCs

Year fixed effects?        Yes              Yes              Yes
Startup                     --               --              0.169 ***
High-tech                   --               --              0.165 ***
Log (deal size)             --               --              0.224 ***
Corporate                 -0.298 ***       -0.300 ***        0.120 ***
Government                 0.057 **        -0.772 ***        0.102 ***
Institutional             -0.343 ***       -0.328 ***       -0.128 ***
LSVCC                     -0.192 ***       -0.346 ***       -0.869 ***
Foreign investor          -0.203 ***        0.120 **         0.122 **
Other type of VC          -0.037           -0.202 ***        0.390 ***
British Columbia           0.002            0.165 ***        0.132 **
Alberta                   -0.130 *         -0.167 **        -0.955
Saskatchewan              -0.268 ***       -0.499 ***        0.106
Manitoba                  -0.057           -0.333 ***        0.136 *
Ontario                   -0.073            0.810           -0.548
Quebec                    -0.084           -0.128 **         0.150 **
[chi square]             403.240 ***      897.314 ***    1,794.612 ***
Log likelihood        -2,114.683       -2.270.576       -1,941.212
Pseudo [R.sup.2]           0.077            0.165            0.316

                                            (5)              (6)
                                        Syndication:     Syndication:
                           (4)            Foreign         Non-LSVCCs
                       Syndication:        (U.S.)        and non-U.S.
                       LSVCCs only        VCs only         VCs only

Year fixed effects?        Yes              Yes              Yes
Startup                    0.003           -0.025 ***        0.155 ***
High-tech                  0.009            0.015 ***        0.116 ***
Log (deal size)            0.026 ***        0.004 ***        0.106 ***
Corporate                   --               --               --
Government                  --               --               --
Institutional               --               --               --
LSVCC                       --               --               --
Foreign investor            --               --               --
Other type of VC            --               --               --
British Columbia           0.042           -0.008 **         0.223
Alberta                   -0.003           -0.017 ***       -0.259
Saskatchewan               0.028             --              0.161 **
Manitoba                   0.139 *           --             -0.564
Ontario                    0.026           -0.020 ***       -0.119 **
Quebec                    -0.008           -0.046 ***        0.942 *
[chi square]             206.219 ***      159.099 ***      649.963 ***
Log likelihood        -1,231.203         -580.696       -2,447.950
Pseudo [R.sup.2]           0.077            0.120            0.117

*, **, and *** denote significance
at 10, 5, and 1% levels, respectively.

Note: This table presents logit regression estimates of the
determinants of startup stage (equation 1) and high-tech
(equation 2) investments, and the determinants of syndicated
investments (equation 3). Also, equations 4-6, respectively,
present regressions for syndications with LSVCCs only, foreign
VCs only, and other types of investors excluding foreign VCs
and LSVCCs. Year fixed effects for 1991-2003 are used. Dummy
variables for private limited partnerships and for the Maritime
Provinces are suppressed to avoid perfect collinearity. The marginal
effects are presented to explicitly show economic significance for
the logit regressions. Only first-round investments are considered
for a total of 4,114 observations. The variable "--" is excluded
because of collinearity in the syndication regressions, and because
it is not applicable in the startup and high-tech regressions. VC,
venture capitalist; LSVCC, labor-sponsored venture capital company;
DWH, Durbin-Wu-Hausman.

Table 5
DWH Tests of the Effect of Endogeneity vis-a-
vis Firm Characteristics and Forms of Finance

Panel A. All types of syndicated investments considered together

                                                   Convertible
                      Preferred      Common         preferred

Startup                -0.005       -0.053 **        0.022
High-tech              -0.013        0.013          -0.092 ***
Syndication
  (all types of VCs)    0.000       -0.058 **       -0.040 ***

                                   Convertible      Debt and
                       Debt           debt           common

Startup                0.043 ***     0.016           0.017 *
High-tech              0.053 ***    -0.041 **        0.030 ***
Syndication
  (all types of VCs)   0.026         0.024          -0.007

                       Preferred        Other
                          and       combinations
                         common     of securities

Startup                 -0.011       -0.029
High-tech                0.017 ***    0.033 **
Syndication
  (all types of VCs)    -0.003        0.057 ***

[chi square] = 948.8370 ***; log likelihood =
-7,162.593; pseudo [R.sup.2] = 0.062

Panel B. LSVCC, foreign and other syndications considered separately

                                                   Convertible
                      Preferred     Common          preferred

Startup                -0.006       -0.061 **        0.016
High-tech              -0.016        0.016          -0.088 ***
Syndication
  among LSVCCs         -0.040 *      0.027           0.026
Syndication among
  foreign VCs           0.014        0.012          -0.014
Syndication among
  other VCs            -0.011       -0.021           0.020 *

                                   Convertible      Debt and
                        Debt          debt           common

Startup                 0.046 ***    0.014           0.017 **
High-tech               0.048 ***    0.040 **        0.029 ***
Syndication
  among LSVCCs         -0.031        0.043          -0.018
Syndication among
  foreign VCs          -0.058       -0.085 **       -0.037
Syndication among
  other VCs            -0.012        0.009          -0.001

                       Preferred        Other
                          and       combinations
                         common     of securities

Startup                -0.010       -0.015
High-tech               0.017 ***    0.033 **
Syndication
  among LSVCCs         -0.005        0.052 *
Syndication among
  foreign VCs           0.016        0.179 ***
Syndication among
  other VCs             0.004        0.013

[chi square] = 989.935 ***; log likelihood =
-7,142.044; pseudo [R.sup.2] = 0.065

*, **, and *** denote significance at
10, 5, and 1% levels, respectively.

Note: This table presents DWH tests of the effect of endogeneity
vis-a-vis forms of finance and firm characteristics (stage of
development, industry). The regressions are multinomial logit
models of equation 7 described in the text of the article. The
multinomial logit regression coefficients are not presented;
rather, the marginal effects are presented to explicitly show
economic significance. The reported right-hand-side variables
are the residuals from the regressions reported in Table 4.
Other independent right-hand-side variables are not reported for
conciseness. Only first-round investments are considered. Panel
A considers all syndications among all types of VCs together.
Panel B considers separately syndications that involved LSVCCs,
foreign VCs, and all other different types of VCs. The full sample
of 4,114 first-round investments is used. VC, venture capitalist;
LSVCC, labor-sponsored venture capital company; DWH, Durbin-Wu-
Hausman.

Table 6
DWH Tests: Robustness Check Number 1

Panel A. Nonsyndicated first-round investments

                                             Convertible
              Preferred        Common         preferred

Startup         0.014          -0.082 **        0.016
High-tech      -0.021          -0.007           0.048 ***

                             Convertible      Debt and
                Debt            debt           common

Startup       0.055 **         -0.031           0.002
High-tech     0.089 ***        -0.013           0.052 ***

                                Other
              Preferred     combinations
             and common     of securities

Startup      -0.019 ***       0.045 ***
High-tech     0.018 ***      -0.069 ***

[chi square] = 459.326 ***; log likelihood
= -3.147.875; pseudo [R.sup.2] = 0.068

Panel B. Syndicated first-round investments

                                             Convertible
              Preferred        Common         preferred

Startup         0.003          -0.080           0.050
High-tech      -0.071 **        0.061          -0.092 **

                             Convertible      Debt and
                Debt            debt           common

Startup         0.022           0.021          -0.059 **
High-tech       0.079 ***      -0.001           0.021 *

                                Other
              Preferred     combinations
             and common     of securities

Startup         0.000           0.042
High-tech      -0.015           0.018

[chi square] = 482.706 ***; log likelihood
= -3,932.897; pseudo [R.sup.2] = 0.058

*, and *** denote significance at 10, 5, and 1% levels, respectively.

Note: This table presents DWH tests of the effect of endogeneity
vis-a-vis forms of finance and firm characteristics (stage of
development, capital requirements, and industry). The regressions are
multinomial logit models of equation 7 described in the text of the
article. The multinomial logit regression coefficients are not
presented; rather, the marginal effects are presented to explicitly
show economic significance. The reported independent variables are the
residuals from regressions analogous to those reported in Table 4 (for
the respective subsamples for syndicated and nonsyndicated investments).
Other independent variables are not reported for conciseness. Only
first-round investments are considered. Panel A considers 1,893
investments that were not syndicated. Panel B considers 2,221
investments that were syndicated. DWH, Durbin-Wu-Hausman.

Table 7
DWH Tests: Robustness Check Number 2

Panel A. Nonsyndicated First-Round Investments

                                                          Convertible
                           Preferred        Common         preferred

Startup                      0.007          -0.064 *         0.012
High-tech                   -0.017          -0.015          -0.046 ***
Log
  ($ deal size ['000])      -0.017           0.045          -0.010

                                          Convertible      Debt and
                             Debt            debt           common

Startup                     0.044 *         -0.036           0.011
High-tech                   0.093 ***       -0.011           0.047 ***
Log
  ($ deal size ['000])     -0.026           -0.012           0.023

                                             Other
                           Preferred     combinations
                          and common     of securities

Startup                    -0.019 **        0.044 *
High-tech                   0.018 ***      -0.069 ***
Log
  ($ deal size ['000])      0.000          -0.003

[chi square] = 466.027 ***; log likelihood
= -3,144.524; pseudo [R.sup.2] = 0.069

Panel B. Syndicated first-round investments

                                                          Convertible
                           Preferred        Common         preferred

Startup                      0.001          -0.075           0.047
High-tech                   -0.069 **        0.058          -0.091 **
Log
  ($ deal size ['000])      -0.004           0.017          -0.002

                                          Convertible      Debt and
                             Debt            debt           common

Startup                      0.026           0.028          -0.056 **
High-tech                    0.076 ***      -0.006           0.018
Log
  ($ deal size ['000])       0.012           0.025           0.017 *

                                             Other
                           Preferred     combinations
                          and common     of securities

Startup                      0.000           0.028
High-tech                   -0.015           0.029
Log
  ($ deal size ['000])      -0.001          -0.064 ***

[chi square] = 504.376 ***; log likelihood
= -3.922.062; pseudo [R.sup.2] = 0.060

*, **, and *** denote significance at 10, 5, and 1% levels,
respectively.

Note: This table presents DWH tests of the effect of endogeneity vis-
a-vis forms of finance and firm characteristics (stage of development,
capital requirements and industry). The regressions are multinomial
logit models of equation 7 described in the text of the article. The
multinomial logit regression coefficients are not presented; rather,
the marginal effects presented to explicitly show economic
significance. The reported independent variables are the residuals
from regressions analogous to those reported in Table 4 (for the
respective subsamples for syndicated and nonsyndicated investments),
and the residuals from an analogous regression explaining the log of
deal sizes. Other independent variables are not reported for
conciseness. Only first-round investments are considered. Panel A
considers 1,893 investments that were not syndicated. Panel B
considers 2,221 investments that were syndicated. DWH,
Durbin-Wu-Hausman.
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Author:Cumming, Douglas
Publication:Entrepreneurship: Theory and Practice
Geographic Code:1CANA
Date:Mar 1, 2006
Words:14756
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