Entrepreneurial Litigation and Venture Capital Finance*

Douglas Cumming York University - Schulich School of Business

4700 Keele Street Toronto, Ontario M3J 1P3

Canada +1-416-932-1500 ext 77942

http://ssrn.com/author=75390 douglas.cumming@gmail.com

Bruce Haslem Florida State University

821 Academic Way, 143 RBB Tallahassee, FL 32306

+1-850-644-8216 http://ssrn.com/author=104910

bhaslem@fsu.edu

April Knill Florida State University

821 Academic Way, 143 RBB Tallahassee, FL 32306

(850) 644-2047 http://ssrn.com/author=384290

aknill@cob.fsu.edu

* We owe thanks to the seminar participants at the University of Florida, Law and Entrepreneurship Conference, French Finance Association Conference, Washington State, Florida State, Southern Utah, EMLYON, Durham, York, and George Washington, as well as Vladimir Atanasov, Alexander Groh, Sofia Johan, Ari Pandes, Michael Robinson, Harry Turtle, Rick Sias and Gordon Smith for helpful comments and discussions.

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Entrepreneurial Litigation and Venture Capital Finance

Abstract

This paper empirically examines the interaction between entrepreneurial firm plaintiff

litigation and venture capital (VC). The data indicate (1) plaintiff firms are more likely to obtain

financing by less reputable VCs, (2) VCs provide more oversight of plaintiff firms relative to

non-plaintiff firms in their portfolio, (3) and plaintiff firms are more likely to exit by an IPO

(versus acquisition), and less likely to be defunct at the end of the investment period. For all

results, implications are less severe for litigants who begin their suit after VC suggesting these

entrepreneurial litigants have the backing of the VC.

JEL classification: G24, K4, L26

Key Words: Litigation, Venture Capital

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1. Introduction

For small, entrepreneurial firms, the decision to pursue litigation requires them to invest a

significant portion of their available cash resources into a project that has an uncertain payoff

and has the potential to generate significant reputational costs affecting their ability to raise

capital going forward. However, by not pursuing their rights in court, the small firm might be left

at a competitive disadvantage, which could make it more difficult for the firm to obtain

financing, more difficult for its investors to successfully exit the investment or more likely for

the firm to fail. For firms that are able to obtain venture capital (VC) financing, they may not be

able to access the largest, most connected VCs (i.e., Hsu, 2004). These tradeoffs give rise to the

following empirical questions considered in this paper: for those plaintiff firms that do obtain

financing, (1) does initiating litigation as a plaintiff effect the quality of VC financing a start-up

entrepreneurial firm is able to obtain, (2) is governance of the investor different than that for

other non-litigant investee firms, and (3) does the performance of plaintiff VC-backed firms

differ from non-litigant VC-backed firms?

In this paper, we analyze a large, unique dataset compiled from case information

collected by accessing over 900,000 case filings in the United States district courts through the

PACER Service Center. For cases that met our selection criteria (described in detail in section 2),

our final sample includes 13,057 portfolio company (PC)-to-VC matches with litigation,

compared to 169,165 similar PC to VC relationships for non-litigants, and spans the years 1994-

2006. While our dataset comprises cases on entrepreneurial firm plaintiff and defendant

litigation, our focus is on plaintiff litigation since its implications for external financing are not

obvious, as it depends on the relative expected benefits versus the costs and hence requires

empirical testing.

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The data herein indicate that there is in general a significant negative relationship

between corporate litigation and the availability of external financing through venture capital for

entrepreneurial firms, but the effect depends on the timing of litigation. On average, firms who

file litigation before receiving venture capital end up receiving funding from lower quality VC

firms in that they have less expertise and fewer assets under management (among other proxies

for VC quality; see Hsu, 2004; Nahata, 2008; Masulis and Nahata, 2010. Hochberg et al., 2010;

Masulis et al., 2010; Bengtsson and Hsu, 2010). These VC firms also had fewer prior PCs who

exited through initial public offerings, which also indicates lower quality. In addition, the

funding was given out in significantly more rounds, perhaps indicating that the PC is under more

scrutiny and given more expectations they must meet before the next round of funding.

Entrepreneurs that filed while receiving venture capital are less negatively impacted by

the litigation. Though these litigants are also associated with VCs that have had fewer previous

IPOs, as well as a greater number of VCs in the funding syndicate, they are also associated with

VCs with greater capital under management, expertise, and larger amounts of funding for the PC.

In addition, when litigation is filed while receiving VC financing, there is also a significant

decrease in the probability that funding will be stopped; which is the first indication that litigant

firms who are able to obtain VC end up with better post-VC outcomes. We also find that firms

who file litigation are significantly less likely to go defunct, and have a significantly higher

probability of exiting through an initial public offering (versus an M&A). These results are

consistent with the view that VCs are effective screeners of projects and/or a higher hurdle is

applied to firms who start litigation, thus making capital available to only the best litigant firms.

These results are likewise consistent with the view that firms who aggressively litigate their

rights improve their likelihood of long-term success by enforcing their rights, and because the

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CEOs of such firms are among the type with exceptional perseverance necessary for

entrepreneurial success.

Our empirical results relating litigation to VC financing and outcomes are not merely

statistically significant, but also economically large. Moreover, when we run two-step

econometric specifications to account for litigation as a choice variable, such as the use of

Heckman-like treatment regressions, our results remain statistically significant and the economic

significance is even larger.

Finally, in this paper we find that the type and outcome of the litigation has an effect on

VC investment; with firms filing contract, product liability or employment suits enjoying

significantly better funding outcomes than those filing antitrust and shareholder lawsuits in our

sample. Those firms filing intellectual property lawsuits see a decrease in VC quality, but there is

still a reduced probability of funding being stopped. It also appears that being willing to

compromise affects venture capital outcomes. Litigation in which the case is eventually settled is

associated with significant increases in VC expertise and capital under management, as well as

fewer financing rounds, smaller syndicates and greater funding amounts, while also decreasing

the probability of funding being stopped. Settlement is also associated with an increase in the

probability of the firm exiting through an initial public offering.

This paper stands at the intersection of several strands in the literature. First, our paper is

perhaps most closely related to concurrent work that examines lawsuits within the VC industry.

Atanasov, Ivanov and Litvak (2009) examine 296 lawsuits involving 221 VCs and find

defendant VCs raise significantly less capital than their peers, invest in fewer and lower quality

deals, and syndicate with fewer VC firms. Tian, Udell and Yu (2011) examine the reputational

impact of VCs failing to prevent fraud within their invested firms (as measured by those invested

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firms later becoming defendants in lawsuits). Our focus, by contrast, is on plaintiff litigation

among entrepreneurs for entrepreneurs that initiated suits both before and after obtaining VC

finance. We examine thousands of plaintiff lawsuits, and among impecunious plaintiffs for

whom the outcome of litigation is vital yet extremely costly relative to a start-up`s asset base.

Second, our paper is related to an extensive literature examining the effect corporate

litigation has on firm value. From the earliest studies to the present, the literature has been nearly

unanimous in documenting that corporate litigation creates significant deadweight losses for both

parties in a lawsuit. Beyond the damage payments that could potentially be transferred from the

defendant to the plaintiff, there are legal fees, and a loss of managerial focus and impaired

reputation that might result in higher contracting and financing costs. Early studies, such as

Cutler and Summers (1988) and Engelmann and Cornell (1988) analyze a small number of cases

involving large corporate plaintiffs and defendants to document that the combined losses in

market value at the start and conclusion of litigation, far exceeded the actual damages paid. Later

studies, such as Bhagat, Brickley and Coles (1994) and Bhagat, Bizjak and Coles (1998) use

larger samples to confirm those results, and demonstrate that the market reaction to litigation is

often affected by the prospect of financial distress for a firm. But again, these firms were large,

publicly traded firms with ready access to capital markets.

Third, there is a robust literature examining the effect legal protections have on the

ability of firms to attract outside financing. At the country level, La Porta, Lopes-de-Silanes,

Shleifer and Vishny (1997a, 1998, 2000) began a string of papers showing that the origin of legal

systems, and the level of protection they provide the firm’s investors, has a large effect on the

availability and cost of capital. And other papers consider factors that determine aggregate levels

of VC within a country. At the firm level, another strand of literature is developing which

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examines factors that affect the willingness of VCs to provide financing. For example, recent

papers, such as Mann and Sager (2007) and Hsu and Ziedonis (2008), have shown that having a

patent improves the valuation of entrepreneurial firms, the likelihood of obtaining venture

capital, the terms of financing (number of rounds and amount invested) and exit status of the

firm.

While it is clear that legal protections enhance markets and the ability of firms to attract

outside financing in general, these protections are costly to enforce and it is not clear that there is

a payoff to doing so. And like patents, litigation serves as a public and costly signal that will be

observed by sources of outside finance, but it has not been shown how they will react to that

signal.

There is very little research analyzing the effect litigation has on small firms, particularly

private firms who don’t have easy access to capital markets. The managers of such firms, when

facing the decision as to whether they should press their firm’s claims through legal action,

might find the existing empirical evidence to be daunting. Among all previous studies, only

Bizjak and Coles (1995), which focuses on antitrust suits, document a positive market response

to the filing of litigation for a plaintiff. The remaining literature is uniform in finding an

insignificant or negative market reaction to the filing of a plaintiff’s lawsuit; regardless of the

underlying nature of the lawsuit. And many papers, such as Karpoff and Lott (1993, 1999), have

documented a significant reputational penalty for firms in litigation.

After carefully weighing these previous results, as well as the limited access to external

capital, they suffer relative to the large firms in those studies; the management of small private

firms might be very reluctant to devote scarce financial resources to corporate litigation, even if

their claims are valid. At best, even with a positive litigation outcome, external capital sources

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might see them as too willing to devote precious capital and managerial focus on litigation rather

than the day to day operation of the firm. And at worst, a loss could lead to squandered financial

resources, a loss in managerial focus, and a weakened legal position in future litigation when the

company might have greater resources to devote to legal efforts.

On the other hand, small firms might see it as mandatory to defend their legal claims in

order to attract outside financing. For example, were they not to defend their intellectual property

rights, or not to prevent a former executive from starting a competing business, they might end

up in a weaker strategic and financial position, thus making it more difficult to attract future

financing. It may be that outside capital groups will appreciate their toughness in protecting their

legal rights, and it might attract outside capital groups who could provide expertise in protecting

and maximizing the value of these rights. This paper is the first to fill this gap in the literature by

examining the effect corporate litigation has on the quality and quantity of external financing at

the initial funding stage, as well as how it affects continued funding and the future exit outcome

for the entrepreneurial firm.

This paper is organized as follows. Section 2 introduces the new data. Section 3 explains

the empirical methods. The empirical results are presented in section 4. The last section

concludes.

2. Data

Our case information is collected by accessing case filings in the United States district

courts through the PACER Service Center. We download index information for cases filed

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between 1994-2006, for types1 of litigation that were most likely to have a business as a plaintiff

or defendant. The information downloaded includes the names of the first listed plaintiff, the first

listed defendant, the court where the case was filed, the case number, and the dates the case was

filed and closed. This initial sample includes over 900,000 cases. We focus on firms in the

plaintiff role, because unlike defendants, it is their decision whether or not to begin litigation.

Therefore, we match the plaintiffs in these cases against the nearly 49,000 firms listed in SDC

Platinum who had received venture capital financing and also had information for the expertise

variable used in our tests. Out of this matching process, we are able to identify a sample of 3,547

firms who were plaintiffs in litigation either prior to, or while receiving venture capital. Because

VC firms often syndicate to reduce their potential exposure to any one investment, the PC is

matched to the investment decisions of multiple VCs. Thus, our final sample includes 13,057

PC-to-VC matches with litigation, compared to 169,165 similar PC-to-VC relationships for non-

litigants. Finally, for each of the PCs in this initial sample, we examined additional case filings to

identify the case outcomes used in our study.

In our empirical analysis, we examine the effect that litigation has on the quality and

terms of VC investment (assuming the entrepreneur receives VC funding). We do not include in

our sample those entrepreneurs that are not able to obtain VC funding. To our knowledge, this

data is not available. We therefore concentrate on those that are able to obtain funding. Though

this is clearly a bias, we feel that our analysis is more conservative as a result. Including the

universe of entrepreneurial firms would certainly bias downward the results pertaining to PCs

that file before VC funding. Further, this bias does not affect our analysis on PCs that file during

VC funding. We are able to observe this population without bias.

1 These lawsuits had the following NOS values: 160, 190, 195, 245, 310, 315, 340, 345, 350, 355, 360, 365, 370,

380, 385, 410, 710, 720, 790, 820, 830, 840, and 850.

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There is wide variation in the quality of VCs, with some being more knowledgeable than

others due to experience and their gained skill set. These differences can have a significant effect

on the eventual outcome of its investment in the PC. To measure this, we use several variables to

proxy for VC skill: the VC’s expertise, the number of previous IPO’s for which the VC can

claim responsibility, and the amount of capital under that VC firm’s management. The first

variable, expertise, refers to the number of funds a VC has successfully raised. As the time

limited nature of VC groups requires them to finance repeatedly, the ability to do so is a strong

indicator of past success. This proxy implicitly assumes retention of VC management. This

assumption should not be problematic as long as venture capital firms are able to hire similarly

talented executives to lead their firms. The second variable measures the number of firms

financed by the VC that were eventually exited through an IPO. This is a good proxy for the

ability of VC firms to select, grow and position PCs in the post-VC period. The final variable,

VC capital under management, indicates the ability of the VC to attract investment. As this is

typically based on prior performance or reputation of the general partners in the fund, this will be

a good measure of VC quality.

We also consider the effect of litigation on the terms and structure of the VC investment.

In order to minimize risk, the venture capital will be given to the entrepreneurial firm in tranches,

with each round of financing contingent on the firm reaching agreed upon targets. Thus, we use

the number of rounds to measure how risky the VC views the investment in the PC. For similar

reasons, we also use the number of VCs invested in the PC, as the VCs attempt to minimize their

potential exposure to the PC firm.

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Lastly, we look at the effect of litigation on the amount of VC funding the entrepreneurial

litigant is able to access. For litigation filed while the firm is already receiving venture capital,

we also examine the effect on the likelihood of the VC firm stopping funding.

In each of our specifications, we control for a number of characteristics of the VC firms,

PCs and the investment environment. Whether the firm prefers to originate is included to control

for the VC’s preferred role in syndication as well as its influence on PC exit. Lerner (1994)

indicates that syndicating first-round venture investments improves due diligence and decision

making about whether to invest. This implies that VCs that lead (or even participate in) a

syndication will invest in higher quality PCs and the resulting probability of exit should be

higher. Corporate VC is a dummy variable that indicates whether a VC is corporate or not, and is

included to control for VC fund characteristics. Gompers and Lerner (1999) and Norton and

Tenenbaum (1993) explain that investment at early stages entails more risk. Similarly, there are

some industries that are riskier than others. Due to the different opportunity sets available in

these categories, we include the variable Risk, which is an index summing the two dummy

variables for the stage and industry perceived as riskier than the rest: 1) information technology

(IT Dummy) and 2) early stage investments (Early Stage Dummy). Since each dummy variable

can be at least zero and at most one, Risk is an index from zero to two. We include this index to

neutralize any additional motivation to diversify and to account for any fund effects.

For the PCs in which VCs invest, we control for their age, the investment term, years

since last investment and the industry market-to-book ratio. Age is calculated by subtracting the

company founding date from the date litigation was filed. Investment Term and Years since Last

Investment are included to control for the average length of investment. It is more likely that a

firm would have exited the venture capital cycle if the term is longer or if the last investment

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occurred less recently. Industry Market-to-Book is included to control for any cyclical effect

regarding the industry. Several papers, such as Cumming (2008) and Brau, Francis, and Kohers

(2003) find that this variable increases the propensity of a given PC to exit via M&A.

Finally, macroeconomic variables such as Number of Deals, S&P 500 Return, and

Bubble are included to control for the general state of the VC industry and the market. Number

of Deals provides a proxy for the general fundraising levels, while the S&P 500 return is

included to control for public market conditions. This variable will likely pick up the

countercyclical nature of the venture capital industry (Groshen and Potter, 2003). Following

several studies, such as Cumming (2008) and Nahata (2008), we use the dummy variable,

Bubble, to account for the increased probability of exit during the information technology bubble

period (1998-2000).

Definitions of all variables used in this analysis as well as their sources are provided in the

Appendix. Table I illustrates differences between litigation and non-litigation firms in our

sample. Overall, firms involved in litigation receive capital from larger VCs with less expertise

and fewer previous IPOs to their credit. Their funding will come in more rounds and from more

VC groups, suggesting greater scrutiny. Finally, we can see that firms in the litigation sample

enjoy a significantly greater likelihood of exiting through an IPO compared to the non-litigation

recipients of VC, and have a lower probability of becoming defunct.

INSERT TABLE I ABOUT HERE

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3. Methodology

In this study, we extend the implications of extant literature regarding costs imposed on

public firms due to legal fees, loss of managerial focus and reputation costs in litigation, to the

cost of financing for privately held firms. However, one of the inherent difficulties in studying

private, often small entrepreneurial firms is that there are no public reporting requirements, nor

observable valuations for the firm. To overcome this hurdle, we focus on a time when these firms

seek external financing and examine the relationship between litigation and the firm’s ability to

attract the highest quality VC firms, and to obtain financing on favorable terms. Therefore, our

tests are structured to analyze the effect that various aspects of litigation, such as case timing,

outcome or nature of suit, have upon our financing outcomes.

3.1. PCs with lawsuit before VC funding

In our first set of multivariate models, we examine whether the timing of the lawsuit

affects VC outcomes. A PC that has initiated a lawsuit prior to the initial VC financing could

result in a very different outcome than one in which the PC files litigation with the input of the

VC who is already providing financing. We analyze those lawsuits that are initiated before the

date of the first investment of the VC as follows:

VCTermsij = α + β0 Lawsuitj + β1 INVi,j + β3 VCi + β4 Yt + β5 Indt + εij,

(1)

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where VCTermsij refers to a variable that proxies for either the quality of VC firm i (i.e.,

expertise, number of previous IPOs or capital under management) or aspects of the funding

arrangement (number of rounds, number of VCs in syndicate, or fund amount invested in PC

firm j). The vector Lawsuitj includes the variable of interest, which is an indicator variable

stating whether a lawsuit during this time frame has occurred or not. In separate analyses, we

include specifics about the lawsuit such as type and outcome. Since entrepreneurial firms can be

involved in multiple lawsuits, Lawsuit type is a count of each type of litigation for which a given

litigant is involved: shareholder, contract, product liability, antitrust, employment and intellectual

property rights. Lawsuit outcome is likewise a count of the outcomes of all litigation for which a

given litigant is involved: win, lose, settle, and whether an injunction resulted from the lawsuit.

INVi,j is a vector of investment characteristics such as the age of the PC at the time litigation is

filed, the term of the investment (Investment Term) and the number of years since the last VC

investment (Years Since Last Inv). It also includes the average market–to-book ratio for firms in

the PC’s industry. VCj is a vector of VC firm characteristics including whether the firm prefers

to originate (PTO), a dummy indicating whether or not the VC is corporate or not (Corporate

VC), and Risk, which is an indicator of the level of risk the VC undertakes in its investments. Yt

is a vector of macroeconomic variables to control for things that papers such as Gompers and

Lemer (1998) have found may affect VC fundraising (Number of Deals), or factors that may

affect the probability of exit through M&A or an IPO, such as general market conditions (S&P

500 Return), or occurring in the IT bubble time period (Bubble). Cumming et al. (2005) and

Gompers et al. (2008) offer a rationale for VC investment changes in different IPO markets.

Finally controls are added for various industry effects and errors are clustered around PC to

allow for homogeneity within observations for a given PC.

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3.2. PCs with lawsuits during VC funding

We further analyze lawsuits that are initiated after the date of the first investment of the

VC (i.e., during VC investment). The empirical model remains the same except lawsuit is

defined as litigation that occurs after the first round of VC financing,2 but before the final round

of financing. For litigation during funding, an additional model is run to include an additional

dependent variable (Stopped Funding) to examine how litigation affects the likelihood that

funding will be discontinued before the final round.

3.3. PC Current Status

We examine how the PCs current status is impacted by litigation. We use a multinomial

logit model to regress the following:

Pr(Current Statusj) = Ψ(ά + γ0 Lawsuitj + γ1 INVi,j + γ2 VCi + γ3 Yt + γ4 Indi + ε)

(2)

where CurrentStatus is the current standing of the entrepreneurial (PC) company j.3 This proxy

takes on a value of one if the PC is defunct (i.e., out of business), two if the PC is private, three if

the PC goes public through merger and acquisition (i.e., M&A), and four if the PC goes public

through initial public offer (i.e., IPO). This hierarchy where IPO is a superior exit vehicle to

2 We acknowledge that if litigation begins after the first VC but before the second VC, the lawsuit would be defined

as during for the first VC and after for the second VC. We argue that the largest marginal effect on the quality and

terms of VCs would be on the first VC since subsequent VCs will arguably find the impact of such litigation as

negligible based on the continued-funding signal of the first VC. 3 PC outcome = private is the base outcome.

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M&A is well established in the literature by papers such as Nahata (2008) or Cumming (2008).

Ψ is the cumulative logistic probability distribution function. The explanatory variables are as

described above. Once again, errors are clustered around the PC.

3.4. Corrections for Potential Endogeneity

While the occurrence of an actionable claim may be exogenous, the decision to litigate

may not be. Rather, the entrepreneur must decide whether or not to pursue such an action. To this

end, we consider treatment regressions to control for the non-random decision to litigate. In our

sample, we know the outcome variables associated with firms that do and do not litigate;

therefore, it is inappropriate to use the traditional Heckman regressions, and instead appropriate

to the treatment regressions. We note that the treatment regression does not require the same

variables in the first-step regression as the second-step regression plus some additional

identifying variables, as in the traditional Heckman regression. Rather, a more parsimonious

specification may be used in the first step. The model is as follows with the re-examination of

equation (1), for example:

Lawsuitij= α + β1 Y’t + β2 Indt + ε (1a’)

VCTermsij = α + β0 (Lawsuit|1a’)j + β1 INVi,j + β3 VCi + β4 Yt + β5 Indt + ε

(1b’)

Where Y’t includes the market characteristics found in the equation (1), namely Number of VC

Deals, Market Return and Bubble, as well as the number of similar-type lawsuits that occurred at

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time t. In our empirical tests reported below (subsection 4.3), we consider robustness to different

specifications of the first and second stage regressions for inclusion or exclusion of different

factors that might explain the propensity to litigate, among other things.

Beyond the treatment model, we also use a propensity score matching technique, to

ensure that the nonrandomness of the sample does not bias results toward our conclusions. In

other words, since the relevant research question is what are the quality and terms of the VC

financing that the litigant would have received if it had not litigated, it is perhaps more relevant

to compare the litigant to firms that most closely resemble the litigant. Given the size of the

sample, a propensity score matching technique is well suited and the control variables, being

precisely measured and stable, are also appropriate. We use nearest neighbor matching given the

importance to match most closely characteristics of the litigant firm.4

4. Results

4.1. Main Results

Table II presents the results of specification (1), which regresses key measures of VC

quality and financing structure on a dummy variable that indicates pre-VC litigation on the part

of the PC, as well as other variables that control for other characteristics of the PC, the VC

group, general economy and industry effects. The data indicate that filing litigation prior to

obtaining VC has a deleterious effect on the quality of VC, as well as the structure of the deal.

Litigation prior to obtaining VC is negatively related to all three proxies for VC quality: VC

expertise (the number of successful funds the VC has closed), the VC`s number of previous

4 Other matching methods such as caliper matching, Mahalanobis metric matching and stratification matching have

been used and results are qualitatively identical. The results are not included but are available upon request.

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IPOs, and VC capital under management, with each of these effects being statistically significant

at the 1% level. The economic significance is such that entrepreneurial litigation before VC gives

rise to the entrepreneur obtaining financing from VCs that have on average raised 1 fewer funds

(rounded up from 0.663), from VCs that have had 3 fewer IPO exits (rounded down from 3.243),

and raised $1.089 Million less capital. The data further indicate that the VCs that finance

plaintiff investee companies provide on average 6 more staged rounds of financing (rounded up

from 5.645), and this effect is significant at the 1% level. This latter result shows that VCs

monitor their investees more often when there is risk of litigation (Gompers, 1995). These results

suggest that VCs do not want to transfer funds to litigants in case of unnecessary expenditure on

the suit itself as opposed to spending on R&D or other things to help the firm develop.

We do not, however, observe significant differences in the number of syndicated VCs for

plaintiff investee companies or significant differences in the amount of capital provided. The

results thereby indicate that although plaintiff investee companies that initiate lawsuits before

seeking VC finance obtain financing from less well established VCs and receive substantially

more monitoring in the form of staged financing rounds, litigation does not significantly hinder

the amount of VC funding they would have without litigation. The findings in Table II are robust

to controls for other investment characteristics, VC characteristics, market characteristics and

industry effects.

INSERT TABLE II ABOUT HERE

Table III considers whether the timing of litigation matters. In Table III, we maintain the

empirical specifications from Table II, with the exception that the litigation variable now

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indicates that litigation was filed by the PC during the time that it is receiving VC funding (i.e.,

the litigation began after the initiation of funding by a VC). Table III provides an additional

econometric specification under VC Funding which uses as its dependent variable a dummy

variable that takes on a value of one if funding is stopped prematurely. This additional model

allows us to measure whether the occurrence of litigation increases the probability that a VC will

drop future rounds of funding.

Overall, Table III indicates that entrepreneurial litigation filed while receiving venture

capital has a less severe (and in some cases positive) effect on venture capital outcomes relative

to entrepreneurial litigation prior to VC (i.e., Table II). Put more succinctly, timing matters. This

finding is intuitive because VC investors, which typically take substantial ownership and control

rights, have input into whether the firm will file litigation while receiving venture capital. Note

that the litigation variable is positive and significant at the 5% level for VC expertise

(specification 1), albeit the economic significance is close to 0 (rounded down from 0.138). Still,

this is a significant change since we saw a marginal effect of -0.663 in Table II.

We see a similar pattern when VC quality is proxied by the number of IPOs for which

the VC is responsible. While specification 2 displays a negative marginal effect for litigation in

both Tables II and III, the effect in Table II is three times larger. The third specification in Table

III shows that VCs that fund entrepreneurs who become plaintiffs after receiving VC funding

have on average $788,000 more capital under management, while in Table II, entrepreneurs who

initiate lawsuits prior to obtaining VC finance obtaining financing from VCs that have on

average $1.089 Million less capital. Table III further shows that there is no difference in staged

financing rounds for entrepreneurs that initiate lawsuits after obtaining VCs finance, while Table

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II showed on average 6 more financing rounds for entrepreneurs that became plaintiffs prior to

obtaining VC financing.

Table III also shows that there are on average 0.298 more syndicated VCs for

entrepreneurs that become plaintiffs after obtaining financing (this effect is significant at the

10% level) and these VCs invest on average $5.607 million more capital in the entrepreneurial

firm (this effect is significant at the 1% level), suggesting that perhaps the VCs are investing

even more in the PCs that they support in litigation. Finally, Table III shows that there is a 48.6%

reduction in the probability that funding is stopped for entrepreneurs that become plaintiffs after

they obtain VC financing.

INSERT TABLE III ABOUT HERE

Table IV considers the effects of litigation on PC outcomes for the timing of litigation

before and after VC finance. The data indicate that for plaintiff firms that become litigants prior

to obtaining VC finance, there is a negative effect that the firm will either become defunct,

remain private or be acquired (1.6%, 12.5%, and 2.9%, respectively), but there is a 17% increase

in the probability of an IPO. For firms that become plaintiffs after obtaining VC finance, results

are quite similar. Litigant firms who file during VC are once again less likely to go defunct,

remain private or be acquired (1.7%, 11.6%, and 2.7%, respectively). All marginal effects are

statistically significant at the 1% level.

The findings are robust to controlling for other variables that previous literature has

shown to be related to the likelihood of successful exits including investment characteristics, VC

characteristics, market characteristics and industry effects. These results are consistent with

20

multiple hypotheses. It may be that VCs are more willing to defend their most promising PCs

through the use of legal action; leading to the observed result of better funded PCs and those that

are the least likely to have funding stopped being associated with litigation. On the other hand, it

could be that the filing of litigation (or the perceived likelihood of such a necessity) leads VCs to

be more selective in choosing which litigation firms are selected ex ante for funding, which

results in better outcomes for litigation firms in that they are less likely to have funding stopped

and have a greater likelihood of exiting successfully.

Our large sample evidence does not indicate the sample of firms who sought but were

unable to obtain VC; therefore, we cannot directly test whether having litigation made affected

the probability of getting venture capital, nor whether only the best litigant firms were eventually

selected. What we do show is that litigant firms who receive venture capital have significantly

worse financing outcomes than other PCs, yet also have a higher probability of successfully

exiting the fund. However, the stronger relationship (i.e., Table IV between post-VC outcomes

for the PC and litigation being filed while receiving venture capital), in comparison to the same

relationship between outcomes and litigation filed prior to receiving VC, might be suggestive

that VCs are more willing to defend their best PCs through litigation. Further research with hand

collected data could explore these alternative explanations in greater detail.

INSERT TABLE IV ABOUT HERE

Beyond the timing of litigation, we examine whether characteristics of the litigation, such

as case type or outcome, affect the funding of PCs. It is possible that a PC can have several

lawsuits of various case types and with various outcomes in the sample. In such instances, the PC

is not necessarily always a winner or always a loser in litigation, and can’t be classified as such.

21

To control for the case type and outcomes given the potential for multiple cases per PC, we

include in Table V the count of each case type and outcome as independent variables in the

regressions. Doing so allows us to both control for these effects and to examine the effect of an

additional case on funding outcomes.

INSERT TABLE V ABOUT HERE

Looking first to Panel A of Table V, we find that that while firms who are involved in

contract suits receive their funding from VC firms who have had 0.149 fewer IPOs, they also

have improved outcomes in that they receive their funding from larger funds with $484,000 more

capital, and with 1.088 fewer rounds of funding, 0.320 fewer VC funds in the syndicate, and

$3.633 million more investment into the PC firm. A similar relationship exists for firms involved

in employment suits and those same funding outcomes, with the exception that the amount given

to the VC is not significantly different. Even after controlling for case types, however, the

coefficient on our pre-VC litigation variable indicates that litigation firms receive their funding

from lower quality VCs with an increase in the number of financing rounds and firms in the VC

syndicate with the statistical and economic significance similar to that discussed above. In Panel

B, we see that similar marginal relationships exist between case types and financing outcomes

when the litigation occurred while receiving venture capital. Again, employment, product

liability and contract suits are all associated with fewer VC firms in the financing syndicate and

few rounds of funding. Yet several case types, such as antitrust, intellectual property and

employment suits are also associated with a reduction in the quality of the VC. On the other

hand, case types and litigation in general are both still significantly related to a decreased

22

probability of the financing ending prematurely, with the economic and statistical significance

similar to that discussed above. .

INSERT TABLE VI ABOUT HERE

Table VI considers whether case outcomes have an effect on the financing arrangements.

Looking first to Panel A, we see that firms that settle receive their funding from VCs who have

had 0.12 fewer prior IPOs (significant at the 1% level), but they also receive it from larger VCs

with $174,000 more capital under management (significant at the 5% level) and more expertise

(0.04 more funds raised, significant at the 5% level), in 0.365 fewer rounds (significant at the 5%

level) and $2.047 million more invested (significant at the 1% level). And cases in which an

injunction is placed against the defendant are also associated with VCs who have lower expertise

(0.225 fewer funds raised, significant at the 10% level) and $1.402 million less capital under

management (significant at the 1% level), in smaller amounts by $5.534 million (significant at

the 5% level), and with 0.917 fewer VC firms in the funding syndicates (significant at the 5%

level). Surprisingly, additional losses have no significant effect of VC outcomes, while

additional wins have an ambiguous effect, with funding coming from larger VCs by $764,000

(significant at the 1% level), but with the risk being shared across larger syndicates with 0.618

more VCs on average (significant at the 10% level). These results are unchanged when the

litigation is filed while the venture capital funding is being received. Panel B shows these similar

relationships at roughly the same level of statistical and economic significance, and again

demonstrate that litigation is associated with a significantly lower probability of funding being

discontinued; regardless of the case outcome.

23

The results found in Table VI that PCs are more likely to exit with that exit being IPO

(i.e., the superior mode of exit as per Gompers and Lerner, 1999) are robust to adding specifics

on both type and outcome. The probability of the PC going defunct and exiting via M&A are

now statistically insignificant with statistical significance almost across the board for the

different case outcomes and types. In these cases, the outcome/type of case is more important

than the fact that the firm was involved in litigation. We see in the first specification that the

marginal effect of the number of wins is statistically insignificant, which suggests that as long as

the PC wins their lawsuit, their viability is not threatened. In specification (2), the positive

statistical significance of lawsuits regarding employment significantly increases the probability

of the PC going out of business by 1.5%. Though not economically huge, anything that increases

the probability of the PC going defunct could be useful information to both the PC and the VC.

Specifications (5) and (6) display analogous results in that the outcome and type of the

lawsuit overshadows the fact that the PC is simply involved in a lawsuit. Though we see fewer

statistically significant lawsuit types in these specifications, it is interesting to note that cases

resulting in injunctions increase the odds that a PC will exit via M&A (with all others

significantly reducing this probability).

Overall, the results suggest that regardless of the outcome or type of case, litigation

improves the efficiency of the entrepreneurial process without endangering the viability of the

entrepreneurial firm. The mode of exit supported is that which is considered the superior mode of

exit. This suggests that as long as the PC is not refused funding (see Table II) or cut off from it

(see Table III), the odds are in its favor that it will exit, and that the mode of exit will be IPO.

INSERT TABLE VII ABOUT HERE

24

4.2. Robustness Checks for Endogeneity

As endogeneity may be a concern, we provide checks for endogeneity using a Heckman-

like treatment model as well as a propensity score matching approach. Due to the time invariant

nature of the data (i.e., it is investment-level data), a difference-in-difference approach as well as

a Granger causality analysis are not possible.

The results of the treatment model, wherein we control for the nonrandomness of the

probability of a lawsuit, are qualitatively identical to those found in the rest of the paper. The

major difference in these results is the economic significance. We find that all of the results are

much stronger once we control for factors that may enhance (or diminish) the probability of a

lawsuit. Table VIII, Panel A shows the treatment model corollary to Table II (i.e., litigation

before VC) using our new model. When comparing the two sets of results, we find that the

economic effect is enhanced considerably but the qualitative results are identical. The statistical

significance is enhanced in those specifications where it was not already statistically significant

at 1% (Specifications 5 and 6).

Panel B displays the treatment model corollary to Table III (i.e., litigation during VC).

These results likewise show an enhancement in the economic effect. Indeed, the economic

significance is enhanced even more than those found in Panel A (save Specification 7 where the

economic significance actually falls a bit, though the sign remains as it was). We note also that

the statistical significance is enhanced in the VC Scrutiny specifications (i.e., Specifications 4

and 5). Our conclusions, therefore, not only remain the same, they are strengthened when we

consider selection effects. The data consistently indicate that entrepreneurs considering pursuing

25

a lawsuit that would like to obtain VC financing at some point in the future are best served by

waiting until they have secured the VC financing.

Regarding the control variables in Panels A and B, we note that the number of VC deals

has significantly less significance in Panel B relative to A. The data thus suggest that the number

of VC deals matters significantly for securing initial VC financing but not subsequent VC

financing. The other difference with the controls in Panels A and B is in respect of market

returns, which is positive and significant for first round deals but not necessarily for subsequent

deals, as different factors affect deal origination versus follow-on investment.

INSERT TABLE VIII ABOUT HERE

A final robustness check for endogeneity may be found in Table IX. A propensity score

matching approach is used for the sub-sample of entrepreneurs that litigate during the time in

which they are receiving VC funding. As can be seen in the table, the results are not only upheld,

they are strengthened. Not only is economic significance of the results strengthened

considerably, but also the statistical significance in three of the seven outcome variables is

strengthened (i.e., Expertise, # Rounds VC Invests and # of VCs Invested in PC). Using this

methodology, all are statistically significant at the 1% level. These results may be found in the

current analysis, which uses a nearest neighbor methodology, as well as results when one uses

alternative matching algorithms such as stratification, kernel or caliper & radius. Results using

alternative matching schemes are available upon request.

INSERT TABLE IX ABOUT HERE

26

4.3. Companion Analyses of IPO Underpricing

Because our prior results indicate that firms involved in litigation have a higher

probability of exiting through an IPO, we considered whether litigation has an effect on share

underpricing at the time of the IPO (see, e.g., Megginson and Weiss, 1991, for related work).

The results of this analysis are not explicitly reported but are available on request. The data

indicate that although the occurrence of litigation is not significantly related to underpricing of

the PC’s shares in an IPO (save one specification), the outcome of the litigation certainly is.

When examining the sample including PCs that begin litigation prior to VC financing,

there is a decrease in underpricing by 37.492% and 31.276% (both significant at the 1% level)

when the PC wins or loses the case, respectively. But for cases resolved through settlement,

underpricing is 5.788% greater (significant at the 5% level). These results are consistent with

those found in Haslem (2005) who finds that the market reacts positively to cases resolved by a

court decision, whether won or lost, and negatively to settlements. Cases involving shareholder

or contract suits are associated with greater underpricing by 42.982% (significant at the 1%

level) and 11.223% (significant at the 5% level), respectively, as expected since the material in

these cases is directly pertinent to the risk of the IPO. By contrast, product liability and

intellectual property suits are associated with less underpricing by 6.712% (significant at the 5%

level) and 3.824% (significant at the 10% level), respectively.

Looking to PCs that begin litigation during VC financing, results are even more

impressive. Underpricing is decreased by 44.369% and 32.190% when the PC wins or loses the

case, respectively. Increases in underpricing for cases that are either settled or that end in an

27

injunction are less extensive than those seen in cases where PCs being litigation prior to VC

financing. The results are available on request. Further research on topic is warranted.

Future research may likewise examine other questions that might be tractable with hand-

collected data on decision-making of venture capitalists that considered but decided not to

finance litigant entrepreneurs. One possibility from anecdotal evidence is that reputable VCs do

not like to finance litigant entrepreneurs as the litigation impacts the networks of the investors.

As well, further research could explore entrepreneurs that tried to obtain VC finance but were

unsuccessful and instead used other forms of finance. These types of datasets could shed

additional light on the topics we address in this paper regarding the interplay between litigation

and external capital and entrepreneurial success.

5. Conclusions

Deciding whether to enter litigation is a significant decision for small, private firms who

do not have ready access to capital markets. Previous literature has thoroughly established that

litigation imposes significant costs on firms; both directly and through increased costs of

financing. And these results were based on large, publicly traded firms who have superior access

to capital and a much larger pool of resources on which they can draw to finance litigation. In

this paper, we provide the first evidence on the effect entrepreneurial litigation has on small,

private firms as they successfully attempt to gain access to funding through VC. Based on our

results, it is clear that litigation has a major effect on their ability to attract future capital.

We show that firms who file litigation prior to receiving VC end up receiving capital

from inferior VC syndicates, and do so at less generous terms in the structure of the funding.

Specifically, we show that they receive their funds from VCs that are smaller, have had fewer

28

previous IPOs, and have less expertise. In addition, the funding will be provided in more

financing rounds, and as it appears that VCs find these firms more risky, they will spread the

financing across a larger consortium of VCs. We also find that the type of litigation and case

outcome does have a marginal effect on VC financing outcomes.

We find that the timing of entrepreneurial litigation makes a difference in its effect.

Entrepreneurial firms who filed litigation while receiving VC received their financing from VC

firms with more expertise and capital under management (albeit with a weaker history of

investees exiting via IPO). The amount of funding these PCs received was larger, and there was a

significant improvement in the probability that the funding was stopped before the final round of

funding. Again, these relationships were robust to controlling for other factors such as case type

and outcome. These results suggest one of two possibilities: 1) VC firms are able to effectively

screen out the weaker firms who have filed litigation, or 2) VC firms are more willing to commit

to litigation themselves to protect their most promising investments.

Regardless of the explanation, it is clear that entrepreneurial firms who file litigation have

significantly better outcomes following venture capital funding. They are less likely to become

defunct, while enjoying a significantly greater likelihood of exiting through an IPO or M&A,

particularly for lawsuits filed after venture capital has begun. When the litigation occurs before

receiving VC, the coefficient is only significant for the increased probability of an exit through

an IPO. After grouping all litigant firms together, and controlling for case type and outcomes, we

see that litigant firms still enjoy an increased likelihood of exiting successfully compared to other

firms who receive venture capital. However, the probability of becoming defunct is increased,

but this result is mitigated by a significant decrease in that probability when the firm settles

litigation or is able to impose an injunction against the defendant. Surprisingly, the losing

29

litigation also appears to decrease the risk of going defunct, although it also decreases the

likelihood of exiting through an IPO or acquisition. Controlling for endogeneity confirms and

strengthens results.

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Gompers, P., 1995, “Optimal Investment, Monitoring, and the Staging of Venture Capital,” Journal of Finance 50, 1461-1489. Gompers, P. and J. Lerner, 1999, The Venture Capital Cycle, 1st Edition, Cambridge, MA The MIT Press. Gompers, P., and J. Lerner, 1998, “What Drives Venture Capital Fundraising?” Brookings Papers on Economic Activity, Microeconomics, 149-204. Gompers, P., A. Kovner, J. Lerner, and D. Scharfstein. 2008. "Venture Capital Investment Cycles: The Impact of Public Markets." Journal of Financial Economics 87, 1-23. Groshen, E. and S. Potter, 2003, “Current Issues in Economics and Finance,” Federal Reserve Bank of New York, 9 (8), 1-7. Heckman, J., 1979. “Sample Selection Bias as a Specification Error,’ Econometrica 47, 153-161. Hsu, D.H., 2004. “What Do Entrepreneurs Pay for Venture Capital Affiliation?” Journal of Finance 59 1805-1844. Hsu, D, and R. H. Ziedonis (2008), “Patent as quality signal for entrepreneurial ventures” Academy of Management Best Paper Proceedings. Hochberg, Y.V., A. Ljungqvist, and Y. Yu, 2010. Networking as a barrier to entry and the competitive supply of venture capital” Journal of Finance 65, 829-859. Karpoff, J. and J. R. Lott, Jr., 1993, “The reputational penalty firms bear from committing criminal fraud” Journal of Law and Economics 36, 757-802. Karpoff, J. and J. R. Lott, Jr., 1999, “On the determinants and importance of punitive damage awards” Journal of Law and Economics 42, 527-573. La Porta, R., Lopez-de-Silanes, F., Shleifer, A., Vishny, R., 1997a. “Legal determinants of external finance” Journal of Finance 52, 1131–1150. La Porta, R., Lopez-de-Silanes, F., Shleifer, A., Vishny, R., 1998. “Law and finance” Journal of Political Economy 106, 1113–1155. La Porta, R., Lopez-de-Silanes, F., Shleifer, A., Vishny, R., 2000a. “Investor protection and corporate governance” Journal of Financial Economics 58, 141–186. Lerner, J., 1994, “The Syndication of Venture Capital Investments,” Financial Management 23(3), 16-27. Mann, R. J., and T. W. Sager, 2007, “Patents, venture capital and software start-ups” Research Policy 36(2), 193-208.

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Appendix A. Variable Definitions and Sources

Funding Quality and Outcomes

Expertise The number of successful funds VCi has closed. SDC Platinum

# Previous IPOs

The number of IPOs for which VCi is responsible. SDC Platinum

Capital under Mgmt

The total amount (in 000’s) VCi has invested in all PCs. SDC Platinum

# Rounds VC Invests

The number of rounds in which the VC funding was given to the PC. SDC Platinum

# of VCs Invested in PC

The number of VC firms in the syndicate providing funding to the PC. SDC Platinum

Fund Amnt Invested in PC

The amount of funding the PC gets from VC SDC Platinum

Stop Funding A dummy variable equal to one if the VC drops PC’s funding and zero otherwise SDC Platinum; own calculation

Current Status The current status of the PC: exit via IPO, exit via M&A, remain private, or defunct. SDC Platinum

IPO Return The percentage change in the price of the IPO from the offer to the close of the first trading day.

SDC Platinum

Investment Characteristics

PC Age Date of litigation claim – company founding date VentureXpert

Year Last Inv The year in which VCi last invested in PCj. SDC Platinum

Investment Term

The year VCi last invested in PCj minus year VCi first invested in PCj. SDC Platinum

Mkt/Book Ratio

The market-to-book ratio for the industry to which PCj belongs (Data Item 24*Data Item 25)/Data Item 60).

Compustat

VC Characteristics

Prefer to Originate

A dummy variable describing the preferred role VCi takes in syndications that is equal to one if the VC prefers to originate and zero otherwise.

Galante’s

Corporate VC A dummy variable that takes on a value of one where VCi is a corporate venture capitalist and zero otherwise.

SDC Platinum

Risk An index from zero (low) to two (high) which sums IT Dummy and Early Stage Dummy, indicators of whether VCi invests in the IT and/or Early Stage PCs, respectively.

Galante’s

Market Conditions

Number of VC Deals

The natural log of the number of VC deals (investments) at time t. VentureXpert

Market Return The return on the S&P 500 index. Standard & Poor’s

Bubble An indicator variable if the year of funding is 1998-2000.

33

Table I. Data Characteristics Expertise is the number of funds the venture capitalist has raised before time t. # Previous IPOs is the number of IPOs for which VCi has been responsible. Capital under Management is the total capital ($Mil) the fund manages. # Rounds VC Invests refers to the number of rounds of financing in the VC investment. # of VCs Invested in PC is the number of VCs in the funding syndicate. Fund Amnt Invested in PC is the amount the fund has invested in the PC ($Mil). *, **, *** indicate significance levels of 10, 5, and 1 percent respectively.

Characteristic N Mean Litigants – Non-litigants Panel A: VC Quality

1 VC Expertise All PCs 182,222 3.306 Litigants 13,057 3.216

-0.097** Non-litigants 169,165 3.313 2 VC No IPOs

All PCs 131,838 6.612 Litigants 9,727 4.128

-2.682*** Non-litigants 122,111 6.810 3 VC Capital Under Mgmt ($Mil)

All PCs 120,931 3.048 Litigants 8,945 4.041

1.072*** Non-litigants 111,986 2.969 Panel B: VC Scrutiny

4 VC Number of Rounds All PCs 139,726 15.183 Litigants 10,340 19.491

4.652*** Non-litigants 129,386 14.839 5 Number of VCs

All PCs 182,222 6.662 Litigants 13,057 8.030

1.474*** Non-litigants 169,165 6.556 Panel C: VC Funding

6 Fund Amnt Invested in PC ($Mil) All PCs 72,877 5.236 Litigants 4,754 11.195

6.375*** Non-litigants 68,123 4.820 Panel D: PC Outcome

7 Prob(Defunct) All PCs 182,222 0.085 Litigants 13,057 0.076

-0.009*** Non-litigants 169,165 0.086 8 Prob(Private)

All PCs 182,222 0.560 Litigants 13,057 0.364

-0.210*** Non-litigants 169,165 0.575 9 Prob(Subsidiary)

All PCs 182,222 0.203 Litigants 13,057 0.220

0.018*** Non-litigants 169,165 0.202 10 Prob(IPO)

All PCs 182,222 0.152 Litigants 13,057 0.339

0.201*** Non-litigants 169,165 0.137

Table II. Relationship between pre-financing litigation and venture capital quality and deal structure

The following OLS model is specified: VCTermsij = α + β0 Lawsuitj + β1 INVi,j + β3 VCi + β4 Yt + β5 Indt + ε. VCTerms is either Expertise, # Previous IPOs, Capital Under Mgmt, No Rounds VC invests, # of VCs invested in PC, or Fund Amnt Invested in PC. Expertise is the number of funds the venture capitalist has raised before time t. # Previous IPOs is the number of IPOs for which VCi has been responsible. Capital under Management is the total capital ($Mil) the fund manages. # Rounds VC Invests refers to the number of rounds of financing in the VC investment. # of VCs Invested in PC is the number of VCs in the funding syndicate. Fund Amnt Invested in PC is the amount the fund has invested in the PC ($Mil). Litigation Before is an indicator variable that takes on a value of one if PC litigation occurs before VC funding and zero otherwise. Investment Characteristics include PC Age, Yrs Since Last Investment and Mtk/Book Ratio. PC Age is the natural log of the number of years VCi has been in business. Years Since Last Inv is 2006 minus the year that the VC made its last investment in the PC. Mkt/Book Ratio is the market-to-book ratio of the industry to which PCj belongs. VC Characteristics include Prefer to Originate, Corporate VC and Risk. Prefer to Originate describes the VCs preferred role in a syndication. Corporate VC is a dummy variable that takes on a value of one if the VC is corporate and zero otherwise. Risk is an index from zero to two which sums IT Dummy and Early Stage Dummy, indicators of whether VCi invests in the IT and/or Early Stage PCs, respectively. Market Characteristics include Number of VC Deals, Market Return and Bubble. Number of VC Deals is the natural log of the number of deals (investments) in the VC industry at time t. Market return is the annual return of the S&P 500 index. Bubble is an indicator variable which is a one if time t is the year 1998, 1999, or 2000. Robust standard errors (clustered around PC) are given in brackets. *, **, *** indicate significance levels of 10, 5, and 1 percent respectively.

VC Quality VC Scrutiny VC Funding

Expertise # Previous IPOs Capital under

Mgmt # Rounds VC

Invests # of VCs

Invested in PC

Fund Amnt Invested

in PC 1 2 3 4 5 6 Litigation Before -0.663*** -3.243*** -1.089*** 5.645*** 0.415 4.158 [0.118] [0.430] [0.324] [1.482] [0.268] [3.858] Investment Characteristics: PC Age 0.220*** 0.194 1.196*** -1.429*** -0.560*** 6.150*** [0.070] [0.167] [0.084] [0.173] [0.045] [1.392] Yrs Since Last Inv -0.084*** -0.422*** -0.065*** 0.416*** 0.155*** -0.606*** [0.003] [0.013] [0.008] [0.032] [0.009] [0.093] Investment Term -0.053*** -0.494*** -0.035*** 1.942*** 0.634*** -0.297*** [0.009] [0.018] [0.011] [0.112] [0.016] [0.077] Mkt/Book Ratio -0.001 -0.266*** 0.020 1.227*** 0.372*** -0.016 [0.055] [0.072] [0.044] [0.283] [0.076] [0.182] VC Characteristics: Prefer to Originate 0.776*** -1.563*** 0.449*** -0.771*** -0.370*** 0.501* [0.032] [0.051] [0.080] [0.241] [0.045] [0.273] Corporate VC 0.175*** 19.113*** -2.018*** -0.454** -0.082 -0.832** [0.062] [0.387] [0.064] [0.212] [0.097] [0.374] Risk 0.109*** 0.464*** -1.033*** -0.208** 0.009 -0.921*** [0.030] [0.066] [0.037] [0.084] [0.022] [0.166] Market Characteristics: Number of VC Deals 0.055*** 1.015*** 0.345*** 1.348*** 0.336*** 0.515*** [0.013] [0.055] [0.047] [0.203] [0.022] [0.120] Market Return -0.069 -1.764*** -0.379*** -4.252*** -1.967*** -1.677** [0.074] [0.188] [0.116] [0.673] [0.176] [0.735] Bubble -0.029 -1.208*** 0.066 -1.587*** 0.085 0.887* [0.096] [0.081] [0.075] [0.468] [0.110] [0.476] Constant 3.088*** -0.555 -1.882*** -1.868 1.582*** -9.249*** [0.218] [0.498] [0.450] [2.599] [0.330] [2.238] Industry FE? Yes Yes Yes Yes Yes Yes Observations 182,222 131,838 120,931 139,726 182,222 72,877 R-squared 0.018 0.624 0.028 0.320 0.340 0.024

35

Table III. Relationship between post-financing litigation and venture capital quality and deal structure

The following OLS model is specified (except in specification 7, where probit is specified): VCTermsij = α + β0 Lawsuitj + β1 INVi,j + β3 VCi + β4 Yt + β5 Indt + ε. VCTerms is either Expertise, # Previous IPOs, Capital Under Mgmt, No Rounds VC invests, # of VCs invested in PC, or Fund Amnt Invested in PC. Expertise is the number of funds the venture capitalist has raised before time t. # Previous IPOs is the number of IPOs for which VCi has been responsible. Capital under Management is the total capital ($Mil) the fund manages. # Rounds VC Invests refers to the number of rounds of financing in the VC investment. # of VCs Invested in PC is the number of VCs in the funding syndicate. Fund Amnt Invested in PC is the amount the fund has invested in the PC ($Mil). Litigation During is an indicator variable that takes on a value of one if PC litigation occurs during VC funding and zero otherwise. Investment Characteristics include PC Age, Yrs Since Last Investment and Mtk/Book Ratio. PC Age is the natural log of the number of years VCi has been in business. Years Since Last Inv is 2006 minus the year that the VC made its last investment in the PC. Mkt/Book Ratio is the market-to-book ratio of the industry to which PCj belongs. VC Characteristics include Prefer to Originate, Corporate VC and Risk. Prefer to Originate describes the VCs preferred role in a syndication. Corporate VC is a dummy variable that takes on a value of one if the VC is corporate and zero otherwise. Risk is an index from zero to two which sums IT Dummy and Early Stage Dummy, indicators of whether VCi invests in the IT and/or Early Stage PCs, respectively. Market Characteristics include Number of VC Deals, Market Return and Bubble. Number of VC Deals is the natural log of the number of deals (investments) in the VC industry at time t. Market return is the annual return of the S&P 500 index. Bubble is an indicator variable which is a one if time t is the year 1998, 1999, or 2000. Robust standard errors (clustered around PC) are given in brackets. *, **, *** indicate significance levels of 10, 5, and 1 percent respectively.

VC Quality VC Scrutiny VC Funding

Expertise # Previous

IPOs Capital under

Mgmt # Rounds

VC Invests

# of VCs Invested in

PC

Fund Amnt Invested

in PC

Stop Funding

1 2 3 4 5 6 7 Litigation During 0.138** -0.752*** 0.788*** 0.164 0.298* 5.607*** -0.486*** [0.061] [0.119] [0.143] [0.682] [0.168] [1.349] [0.022] Investment Characteristics: PC Age 0.213*** 0.215 1.162*** -1.416*** -0.567*** 5.951*** -0.012** [0.070] [0.168] [0.085] [0.165] [0.045] [1.350] [0.005] Yrs Since Last Inv -0.084*** -0.423*** -0.064*** 0.414*** 0.155*** -0.603*** 0.012*** [0.003] [0.013] [0.008] [0.032] [0.009] [0.090] [0.001] Investment Term -0.054*** -0.494*** -0.037*** 1.945*** 0.633*** -0.304*** 0.005*** [0.009] [0.017] [0.011] [0.113] [0.016] [0.077] [0.001] Mkt/Book Ratio -0.004 -0.286*** 0.016 1.257*** 0.375*** 0.006 -0.023*** [0.055] [0.072] [0.044] [0.283] [0.076] [0.180] [0.005] VC Characteristics: Prefer to Originate 0.781*** -1.522*** 0.451*** -0.829*** -0.379*** 0.341 0.053*** [0.032] [0.050] [0.080] [0.235] [0.044] [0.291] [0.009] Corporate VC 0.178*** 19.108*** -2.015*** -0.464** -0.082 -0.820** -0.029* [0.063] [0.386] [0.064] [0.212] [0.096] [0.353] [0.017] Risk 0.113*** 0.484*** -1.030*** -0.244*** 0.006 -0.959*** 0.047*** [0.030] [0.066] [0.037] [0.084] [0.022] [0.157] [0.007] Market Characteristics: Number of VC Deals 0.051*** 1.021*** 0.328*** 1.361*** 0.333*** 0.440*** 0.044** [0.013] [0.056] [0.047] [0.198] [0.022] [0.111] [0.020] Market Return -0.066 -1.807*** -0.344*** -4.229*** -1.953*** -1.571** -0.100*** [0.075] [0.190] [0.117] [0.677] [0.177] [0.708] [0.010] Bubble -0.038 -1.196*** 0.033 -1.560*** 0.077 0.775 0.098*** [0.097] [0.080] [0.075] [0.466] [0.110] [0.471] [0.014] Constant 3.125*** -0.629 -1.711*** -1.951 1.620*** -8.487*** [0.216] [0.507] [0.454] [2.551] [0.330] [2.123] Industry FE? Yes Yes Yes Yes Yes Yes YesObservations 182,222 131,838 120,931 139,726 182,222 72,877 182,222 R-squared 0.018 0.623 0.028 0.319 0.34 0.026 Pseudo R-squared 0.089

36

Table IV. Effect of litigation on current status of firms following venture capital

The following multinomial logit model is specified: Pr(Current Statusj) = Ψ(ά + γ0 Lawsuitj + γ1 INVi,j + γ2 VCi + γ3 Yt + γ4 Indi + ε). Current Status is either Defunct, Private, Exit via M&A or Exit via IPO. Litigation Before (During) is an indicator variable that takes on a value of one if PC litigation occurs before (during) VC funding and zero otherwise. Investment Characteristics include PC Age, Yrs Since Last Investment and Mtk/Book Ratio. PC Age is the natural log of the number of years VCi has been in business. Years Since Last Inv is 2006 minus the year that the VC made its last investment in the PC. Mkt/Book Ratio is the market-to-book ratio of the industry to which PCj belongs. VC Characteristics include Prefer to Originate, Corporate VC and Risk. Prefer to Originate describes the VCs preferred role in a syndication. Corporate VC is a dummy variable that takes on a value of one if the VC is corporate and zero otherwise. Risk is an index from zero to two which sums IT Dummy and Early Stage Dummy, indicators of whether VCi invests in the IT and/or Early Stage PCs, respectively. Market Characteristics include Number of VC Deals, Market Return and Bubble. Number of VC Deals is the natural log of the number of deals (investments) in the VC industry at time t. Market return is the annual return of the S&P 500 index. Bubble is an indicator variable which is a one if time t is the year 1998, 1999, or 2000. Marginal effects are reported. Robust standard errors (clustered around PC) are given in brackets. *, **, *** indicate significance levels of 10, 5, and 1 percent respectively.

Pr(Defunct) Pr(Private) Pr(Exit via M&A) Pr(Exit via IPO)

1 2 3 4 5 6 7 8

Litigation Before -0.016*** -0.125*** -0.029*** 0.170***

[0.004] [0.015] [0.008] [0.012]

Litigation During -0.017*** -0.116*** -0.027*** 0.159***

[0.002] [0.006] [0.003] [0.005]

Investment Characteristics:

PC Age -0.033*** -0.032*** -0.047*** -0.045*** -0.005** -0.004 0.085*** 0.080***   [0.002] [0.002] [0.003] [0.003] [0.003] [0.003] [0.002] [0.002]

Yrs Since Last Inv 0.008*** 0.008*** -0.034*** -0.033*** 0.016*** 0.016*** 0.010*** 0.010***   [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000]

Investment Term -0.000** -0.000*** -0.015*** -0.014*** 0.003*** 0.003*** 0.012*** 0.012***

[0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000] [0.000]

Mkt/Book Ratio 0.005*** 0.004*** -0.081*** -0.082*** 0.071*** 0.071*** 0.005*** 0.006***

[0.001] [0.001] [0.002] [0.002] [0.002] [0.002] [0.002] [0.002]

VC Characteristics:

Prefer To Originate -0.001 0.000 -0.004 -0.002 0.005** 0.006*** 0.001 -0.004**   [0.001] [0.001] [0.003] [0.003] [0.002] [0.002] [0.002] [0.002]

Corporate VC -0.003** -0.003** 0.022*** 0.022*** -0.007*** -0.008*** -0.012*** -0.011***   [0.001] [0.001] [0.003] [0.003] [0.002] [0.002] [0.002] [0.002]

Risk 0.000 0.001 0.005** 0.006** 0.001 0.002 -0.007*** -0.008***   [0.001] [0.001] [0.002] [0.002] [0.002] [0.002] [0.002] [0.002]

Market Characteristics:

Number of VC Deals 0.024*** 0.024*** -0.052*** -0.050*** 0.042*** 0.043*** -0.014*** -0.016***   [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001] [0.001]

Market Return 0.014*** 0.013*** 0.004 -0.002 0.030*** 0.028*** -0.048*** -0.040***   [0.002] [0.002] [0.005] [0.005] [0.003] [0.004] [0.003] [0.003]

Bubble 0.058*** 0.059*** -0.182*** -0.180*** 0.053*** 0.054*** 0.071*** 0.066***   [0.002] [0.002] [0.004] [0.004] [0.003] [0.003] [0.003] [0.003]

Industry FE? Yes Yes Yes Yes Yes Yes Yes Yes

Observations 182,222 182,222 182,222 182,222 182,222 182,222 182,222 182,222

Pseudo R-squared 0.195 0.198 0.195 0.198 0.195 0.198 0.195 0.198

37

Table V. Relationship between types of financing litigation and venture capital quality and deal structure

The following OLS model is specified: VCTermsij = α + β0 Lawsuitj + β1 INVi,j + β3 VCi + β4 Yt + β5 Indt + ε. VCTerms is either Expertise, # Previous IPOs, Capital Under Mgmt, No Rounds VC invests, # of VCs invested in PC, or Fund Amnt Invested in PC. Expertise is the number of funds the venture capitalist has raised before time t. # Previous IPOs is the number of IPOs for which VCi has been responsible. Capital under Management is the total capital ($Mil) the fund manages. # Rounds VC Invests refers to the number of rounds of financing in the VC investment. # of VCs Invested in PC is the number of VCs in the funding syndicate. Fund Amnt Invested in PC is the amount the fund has invested in the PC ($Mil). Litigation During is an indicator variable that takes on a value of one if PC litigation occurs during VC funding and zero otherwise. Litigation type is either Contract, Product Liability, Antitrust, Employment or Intellectual Property. Investment Characteristics include PC Age, Yrs Since Last Investment and Mtk/Book Ratio. PC Age is the natural log of the number of years VCi has been in business. Years Since Last Inv is 2006 minus the year that the VC made its last investment in the PC. Mkt/Book Ratio is the market-to-book ratio of the industry to which PCj belongs. VC Characteristics include Prefer to Originate, Corporate VC and Risk. Prefer to Originate describes the VCs preferred role in a syndication. Corporate VC is a dummy variable that takes on a value of one if the VC is corporate and zero otherwise. Risk is an index from zero to two which sums IT Dummy and Early Stage Dummy, indicators of whether VCi invests in the IT and/or Early Stage PCs, respectively. Market Characteristics include Number of VC Deals, Market Return and Bubble. Number of VC Deals is the natural log of the number of deals (investments) in the VC industry at time t. Market return is the annual return of the S&P 500 index. Bubble is an indicator variable which is a one if time t is the year 1998, 1999, or 2000.

Panel A: Litigation Before VC Quality VC Scrutiny VC Funding

Expertise # Previous

IPOs Capital under

Mgmt # Rounds VC

Invests # of VCs

Invested in PC

Fund Amnt Invested

in PC 1 2 3 4 5 6 Litigation Before -0.620*** -3.034*** -1.156*** 6.414*** 0.635** 1.110 [0.122] [0.453] [0.358] [1.494] [0.281] [4.148] # of Contract Suits 0.048 -0.149** 0.484*** -1.088*** -0.320*** 3.633** [0.037] [0.058] [0.139] [0.366] [0.105] [1.424] # of Product Liability Suits 0.125 -0.380* 0.559* -1.309 -0.379 7.990 [0.155] [0.211] [0.336] [0.836] [0.230] [8.822] # of Antitrust Suits -0.176 -0.334 1.066 6.943 0.369 2.813 [0.166] [0.744] [1.124] [5.913] [0.646] [4.407] # of Employment Suits 0.260 -1.599*** -0.766 -3.206*** -1.054*** -6.471 [0.417] [0.563] [0.834] [1.114] [0.325] [5.168] # of Intellectual Property Suits -0.018 0.043 -0.093 0.082 0.008 0.587 [0.026] [0.100] [0.060] [0.289] [0.111] [0.641] Industry FE? Yes Yes Yes Yes Yes Yes Observations 182,222 131,838 120,931 139,726 182,222 72,877 R-squared/Pseudo R-squared 0.018 0.624 0.029 0.321 0.340 0.027

Panel B: Litigation During

VC Quality VC Scrutiny VC Funding

Expertise # Previous

IPOs Capital

under Mgmt # Rounds

VC Invests

# of VCs Invested in

PC

Fund Amnt Invested

in PC Stop

Funding 1 2 3 4 5 6 7 Litigation During VC 0.189*** -0.736*** 0.710*** 0.924 0.707*** 3.685** -0.290*** [0.068] [0.150] [0.178] [0.768] [0.200] [1.508] [0.029] # of Contract Suits -0.021 -0.047 0.286 -1.163*** -0.477*** 2.373 -0.261*** [0.045] [0.063] [0.182] [0.419] [0.138] [1.679] [0.025] # of Product Liability Suits 0.047 -0.262 0.336 -1.404 -0.539** 7.058 -0.139*** [0.154] [0.216] [0.354] [0.877] [0.251] [8.620] [0.047] # of Antitrust Suits -0.284* -0.535 0.801 7.328 0.274 1.505 -0.405*** [0.171] [0.694] [1.148] [6.066] [0.673] [4.360] [0.085] # of Employment Suits 0.176 -1.653*** -1.028 -3.045*** -1.177*** -7.092 -0.129 [0.400] [0.541] [0.822] [1.167] [0.343] [5.119] [0.092] # of Intellectual Property Suits -0.042*** 0.072 -0.151*** 0.077 -0.045 0.019 -0.194*** [0.012] [0.086] [0.031] [0.292] [0.082] [0.464] [0.028] Industry FE? Yes Yes Yes Yes Yes Yes Yes Observations 182,222 131,838 120,931 139,726 182,222 72,877 182,222 R-squared 0.018 0.623 0.029 0.320 0.341 0.027 Pseudo R-squared 0.097

38

Table VI. Relationship between outcomes of financing litigation and venture capital quality and deal structure

The following OLS model is specified: VCTermsij = α + β0 Lawsuitj + β1 INVi,j + β3 VCi + β4 Yt + β5 Indt + ε. VCTerms is either Expertise, # Previous IPOs, Capital Under Mgmt, No Rounds VC invests, # of VCs invested in PC, or Fund Amnt Invested in PC. Expertise is the number of funds the venture capitalist has raised before time t. # Previous IPOs is the number of IPOs for which VCi has been responsible. Capital under Management is the total capital ($Mil) the fund manages. # Rounds VC Invests refers to the number of rounds of financing in the VC investment. # of VCs Invested in PC is the number of VCs in the funding syndicate. Fund Amnt Invested in PC is the amount the fund has invested in the PC ($Mil). Litigation During is an indicator variable that takes on a value of one if PC litigation occurs during VC funding and zero otherwise. Investment Characteristics include PC Age, Yrs Since Last Investment and Mtk/Book Ratio. PC Age is the natural log of the number of years VCi has been in business. Years Since Last Inv is 2006 minus the year that the VC made its last investment in the PC. Mkt/Book Ratio is the market-to-book ratio of the industry to which PCj belongs. VC Characteristics include Prefer to Originate, Corporate VC and Risk. Prefer to Originate describes the VCs preferred role in a syndication. Corporate VC is a dummy variable that takes on a value of one if the VC is corporate and zero otherwise. Risk is an index from zero to two which sums IT Dummy and Early Stage Dummy, indicators of whether VCi invests in the IT and/or Early Stage PCs, respectively. Market Characteristics include Number of VC Deals, Market Return and Bubble. Number of VC Deals is the natural log of the number of deals (investments) in the VC industry at time t. Market return is the annual return of the S&P 500 index. Bubble is an indicator variable which is a one if time t is the year 1998, 1999, or 2000. Robust standard errors (clustered around PC) are given in brackets. *, **, *** indicate significance levels of 10, 5, and 1 percent respectively. Panel A: Litigation Before

VC Quality VC Scrutiny VC Funding

Expertise # Previous

IPOs Capital under

Mgmt # of Rounds VC Invests

# of VCs invested in PC

Fund Amount Invested in PC

1 2 3 4 5 6 Litigation Before VC -0.702*** -3.105*** -1.390*** 5.949*** 0.544** 1.221 [0.120] [0.430] [0.332] [1.400] [0.260] [3.963] # of Wins 0.015 -0.242 0.764*** 0.621 0.618* 0.481 [0.074] [0.170] [0.273] [0.798] [0.371] [1.509] # of Losses -0.054 0.009 0.304 1.801 -0.446 1.527 [0.109] [0.270] [0.319] [2.399] [0.364] [3.991] # of Settlements 0.040** -0.120*** 0.174** -0.365** -0.057 2.047*** [0.020] [0.034] [0.071] [0.176] [0.050] [0.735] # of Injunctions -0.225* 0.929*** -1.402*** -0.425 -0.917** -5.534** [0.118] [0.305] [0.427] [0.994] [0.356] [2.782] Industry FE? Yes Yes Yes Yes Yes Yes Observations 182,222 131,838 120,931 139,726 182,222 72,877 R-squared 0.018 0.624 0.029 0.320 0.341 0.027

Panel B: Litigation During

VC Quality VC Scrutiny VC Funding

Expertise # Previous

IPOs

Capital Under

Management

# of Rounds for VC

investment

Number of VCs invested

in PC

Fund Amnt Invested in

PC Stop

Funding 1 2 3 4 5 6 7 Litigation During 0.151** -0.667*** 0.605*** 0.604 0.527*** 3.466*** -0.488*** [0.066] [0.129] [0.193] [0.718] [0.180] [1.221] [0.018] # of Wins 0.001 -0.17 0.713** 0.56 0.564 -0.174 -0.041*** [0.077] [0.163] [0.295] [0.783] [0.368] [1.434] [0.005] # of Losses -0.129 -0.039 0.1 1.957 -0.53 0.695 -0.095*** [0.107] [0.252] [0.318] [2.477] [0.381] [3.893] [0.012] # of Settlements 0.006 -0.069* 0.07 -0.355* -0.121** 1.536** -0.019*** [0.021] [0.036] [0.089] [0.182] [0.054] [0.714] [0.005] # of Injunctions -0.113 0.711** -1.032** -0.423 -0.683** -3.922 -0.046*** [0.112] [0.281] [0.466] [0.979] [0.339] [2.606] [0.009] Industry FE? Yes Yes Yes Yes Yes Yes YesObservations 182,222 131,838 120,931 139,726 182,222 72,877 182,222 R-squared 0.018 0.623 0.029 0.319 0.341 0.027 Pseudo R-squared 0.116

39

Table VII. Effect of type and outcome of litigation on current status of firms following venture capital

The following multinomial logit model is specified: Pr(Current Statusj) = Ψ(ά + γ0 Lawsuitj + γ1 INVi,j + γ2 VCi + γ3 Yt + γ4 Indi + ε). Current Status is either Defunct, Private, Exit via M&A or Exit via IPO. Litigation Before (During) is an indicator variable that takes on a value of one if PC litigation occurs before (during) VC funding and zero otherwise. Investment Characteristics include PC Age, Yrs Since Last Investment and Mtk/Book Ratio. PC Age is the natural log of the number of years VCi has been in business. Years Since Last Inv is 2006 minus the year that the VC made its last investment in the PC. Mkt/Book Ratio is the market-to-book ratio of the industry to which PCj belongs. VC Characteristics include Prefer to Originate, Corporate VC and Risk. Prefer to Originate describes the VCs preferred role in a syndication. Corporate VC is a dummy variable that takes on a value of one if the VC is corporate and zero otherwise. Risk is an index from zero to two which sums IT Dummy and Early Stage Dummy, indicators of whether VCi invests in the IT and/or Early Stage PCs, respectively. Market Characteristics include Number of VC Deals, Market Return and Bubble. Number of VC Deals is the natural log of the number of deals (investments) in the VC industry at time t. Market return is the annual return of the S&P 500 index. Bubble is an indicator variable which is a one if time t is the year 1998, 1999, or 2000. Marginal effects are reported. Robust standard errors (clustered around PC) are given in brackets. *, **, *** indicate significance levels of 10, 5, and 1 percent respectively.

Panel A: Litigation Before

Pr(Defunct) Pr(Private) Pr(Exit via M&A) Pr(Exit via IPO)

1 2 3 4 5 6 7 8

Litigation Before 0.000 0.000 -0.096*** -0.080*** -0.007 -0.002 0.103*** 0.082***

[0.005] [0.005] [0.015] [0.015] [0.009] [0.010] [0.011] [0.011]

Case Type:

# Shareholder 0.005 -0.090*** -0.030 0.116***

[0.011] [0.032] [0.024] [0.016]

# Contract -0.009*** -0.013*** -0.007** 0.030***

[0.002] [0.004] [0.003] [0.002]

# ProdLiability -0.013** 0.055*** -0.008 -0.034***

[0.005] [0.014] [0.010] [0.009]

# Antitrust -0.122*** 0.166*** -0.033 -0.012

[0.037] [0.036] [0.023] [0.018]

# Employment 0.015* 0.066** -0.043 -0.038*

[0.008] [0.032] [0.027] [0.021]

# IPR -0.013*** -0.026*** -0.012*** 0.051***

[0.002] [0.004] [0.003] [0.002]

Case Outcome:

# Wins -0.001 0.015 -0.013* -0.002

[0.004] [0.009] [0.007] [0.005]

# Losses -0.018*** 0.056*** -0.041*** 0.003

[0.006] [0.013] [0.010] [0.007]

# Injunctions -0.028*** 0.012 0.023* -0.008

[0.009] [0.017] [0.013] [0.009]

# Settles -0.011*** -0.009*** -0.009*** 0.028***

[0.001] [0.002] [0.002] [0.001]

Observations 182,222 182,222 182,222 182,222 182,222 182,222 182,222 182,222

Pseudo R-squared 0.198 0.198 0.198 0.198 0.198 0.198 0.198 0.198

40

Panel B: Litigation During

1 2 3 4 5 6 7 8

Litigation During -0.001 -0.004 -0.119*** -0.113*** -0.005 -0.007 0.126*** 0.123***

[0.003] [0.003] [0.007] [0.007] [0.005] [0.005] [0.005] [0.006]

Case Type:

# Shareholder 0.004 -0.047 -0.033 0.076***

[0.011] [0.031] [0.024] [0.015]

# Contract -0.008*** 0.007 -0.005 0.006**

[0.002] [0.005] [0.004] [0.002]

# ProdLiability -0.012** 0.072*** -0.007 -0.053***

[0.005] [0.014] [0.010] [0.010]

# Antitrust -0.119*** 0.168*** -0.033 -0.016

[0.037] [0.036] [0.023] [0.017]

# Employment 0.015* 0.079** -0.045* -0.049**

[0.008] [0.031] [0.026] [0.020]

# IPR -0.012*** 0.000 -0.013*** 0.025***

[0.002] [0.004] [0.003] [0.002]

Case Outcome:

# Wins 0.000 0.017* -0.013* -0.004

[0.004] [0.009] [0.007] [0.004]

# Losses -0.017*** 0.068*** -0.042*** -0.009

[0.006] [0.013] [0.010] [0.006]

# Injunctions -0.027*** -0.001 0.025** 0.003

[0.009] [0.016] [0.012] [0.008]

# Settles -0.010*** 0.007*** -0.009*** 0.012***

[0.001] [0.002] [0.002] [0.001]

Observations 182,222 182,222 182,222 182,222 182,222 182,222 182,222 182,222

Pseudo R-squared 0.199 0.199 0.199 0.199 0.199 0.199 0.199 0.199

41

Table VIII. Two-Stage Treatment Model

The following two-stage treatment model is specified: VCTermsij = α + β0 Lawsuit’j + β1 INVi,j + β3 VCi + β4 Yt + β5 Indt + ε where Lawsuit’i is the result of the following model: Lawsuitij= α + β1 Y’t + β2 Indt + ε. VCTerms is either Expertise, # Previous IPOs, Capital Under Mgmt, No Rounds VC invests, # of VCs invested in PC, or Fund Amnt Invested in PC. Expertise is the number of funds the venture capitalist has raised before time t. # Previous IPOs is the number of IPOs for which VCi has been responsible. Capital under Management is the total capital ($Mil) the fund manages. # Rounds VC Invests refers to the number of rounds of financing in the VC investment. # of VCs Invested in PC is the number of VCs in the funding syndicate. Fund Amnt Invested in PC is the amount the fund has invested in the PC ($Mil). Litigation During is an indicator variable that takes on a value of one if PC litigation occurs during VC funding and zero otherwise. Investment Characteristics include PC Age, Yrs since Last Investment and Mtk/Book Ratio. PC Age is the natural log of the number of years VCi has been in business. Years Since Last Inv is 2006 minus the year that the VC made its last investment in the PC. Mkt/Book Ratio is the market-to-book ratio of the industry to which PCj belongs. VC Characteristics include Prefer to Originate, Corporate VC and Risk. Prefer to Originate describes the VCs preferred role in a syndication. Corporate VC is a dummy variable that takes on a value of one if the VC is corporate and zero otherwise. Risk is an index from zero to two which sums IT Dummy and Early Stage Dummy, indicators of whether VCi invests in the IT and/or Early Stage PCs, respectively. Market Characteristics include Number of VC Deals, Market Return and Bubble. Number of VC Deals is the natural log of the number of deals (investments) in the VC industry at time t. Market return is the annual return of the S&P 500 index. Bubble is an indicator variable which is a one if time t is the year 1998, 1999, or 2000. Robust standard errors (clustered around PC) are given in brackets. *, **, *** indicate significance levels of 10, 5, and 1 percent respectively. Panel A: Litigation Before

VC Quality VC Scrutiny VC Funding

Expertise # Previous IPOs Capital under

Mgmt # of Rounds VC Invests

# of VCs invested in PC

Fund Amount Invested in PC

1 2 3 4 5 6 Expected Sign: - - - + +/I +/I Second Stage: Litigation Before -1.319*** -18.024*** -1.523*** 22.121*** 6.121*** 8.243***

[0.191] [0.764] [0.411] [3.118] [0.642] [0.250] First Stage: Number of VC Deals 0.192*** 0.258*** 0.176*** 0.173*** 0.142*** 0.126***

[0.018] [0.029] [0.020] [0.031] [0.023] [0.020] Market Return 0.103* 0.508*** 0.060 0.106 0.164** 0.134**

[0.060] [0.087] [0.068] [0.085] [0.064] [0.060] Bubble 0.197*** 0.339*** 0.159*** 0.219*** 0.192*** 0.120**

[0.045] [0.056] [0.053] [0.057] [0.048] [0.047] Number of type 0.017*** 0.028*** 0.011* 0.016*** 0.013*** 0.011***

[0.005] [0.004] [0.006] [0.005] [0.004] [0.004] Observations 182,221 131,838 120,931 139,725 182,221 72,877 Model Χ2 2,533*** 10,447*** 4,062*** 3,928*** 5,820*** 2,566***

Panel B: Litigation During

VC Quality VC Scrutiny VC Funding

Expertise # Previous

IPOs

Capital under Mgmt

# of Rounds VC Invests

# of VCs invested in

PC

Fund Amount

Invested in PC

Stop Funding

1 2 3 4 5 6 7 Expected Sign: + - + +/I + + - Second Stage: Litigation During 7.945*** -12.086*** 12.691*** 23.610*** 7.067*** 7.524*** -0.008***

[0.189] [0.609] [0.201] [1.060] [0.320] [0.192] [0.002] First Stage: Number of VC Deals 0.010 -0.030* 0.007 -0.052** -0.037** 0.030* 0.000***

[0.011] [0.016] [0.009] [0.021] [0.016] [0.017] [0.00] Market Return 0.022 0.045 -0.079** -0.049 -0.084 0.178** -0.007***

[0.046] [0.064] [0.037] [0.069] [0.057] [0.079] [0.002] Bubble 0.150*** 0.303*** 0.186*** 0.210*** 0.236*** 0.132*** 0.029***

[0.025] [0.033] [0.028] [0.040] [0.038] [0.044] [0.001] Number of type 0.016*** 0.028*** 0.019*** 0.022*** 0.021*** 0.020*** 0.000***

[0.002] [0.003] [0.002] [0.004] [0.004] [0.003] [0.000] Observations 182,222 131,838 120,931 139,726 182,222 72,877 182,222 Model Χ2 9,968*** 22,047*** 6,069*** 3,369*** 5,776*** 5,350*** 3,401***

42

Table IX. Matched Sample Approach with Propensity Score Matching

The following two-stage treatment model is specified: VCTermsij = α + β0 Lawsuitj + β1 INVi,j + β3 VCi + β4 Yt + β5 Indt + ε. Firms are matched based on nearest neighbor. VCTerms is either Expertise, # Previous IPOs, Capital Under Mgmt, No Rounds VC invests, # of VCs invested in PC, or Fund Amnt Invested in PC. Expertise is the number of funds the venture capitalist has raised before time t. # Previous IPOs is the number of IPOs for which VCi has been responsible. Capital under Management is the total capital ($Mil) the fund manages. # Rounds VC Invests refers to the number of rounds of financing in the VC investment. # of VCs Invested in PC is the number of VCs in the funding syndicate. Fund Amnt Invested in PC is the amount the fund has invested in the PC ($Mil). Litigation During is an indicator variable that takes on a value of one if PC litigation occurs during VC funding and zero otherwise. Investment Characteristics include PC Age, Yrs since Last Investment and Mtk/Book Ratio. PC Age is the natural log of the number of years VCi has been in business. Years Since Last Inv is 2006 minus the year that the VC made its last investment in the PC. Mkt/Book Ratio is the market-to-book ratio of the industry to which PCj belongs. VC Characteristics include Prefer to Originate, Corporate VC and Risk. Prefer to Originate describes the VCs preferred role in a syndication. Corporate VC is a dummy variable that takes on a value of one if the VC is corporate and zero otherwise. Risk is an index from zero to two which sums IT Dummy and Early Stage Dummy, indicators of whether VCi invests in the IT and/or Early Stage PCs, respectively. Market Characteristics include Number of VC Deals, Market Return and Bubble. Number of VC Deals is the natural log of the number of deals (investments) in the VC industry at time t. Market return is the annual return of the S&P 500 index. Bubble is an indicator variable which is a one if time t is the year 1998, 1999, or 2000. Robust standard errors (clustered around PC) are given in brackets. *, **, *** indicate significance levels of 10, 5, and 1 percent respectively. Panel A: Litigation Before

Outcome Expected Treated Controls Difference Std. Errors T-stat Sign 1 2 3 4 5 Expertise - 3.360 3.147 0.213*** 0.084 2.52 # Previous IPOs - 4.263 5.437 -1.174*** 0.206 -5.7 Capital Under Mgmt - 4.243 3.673 0.570*** 0.199 2.87 # Rounds VC Invests + 18.533 14.594 3.939*** 0.340 11.6 # VCs Invested in PC I 7.958 6.225 1.733*** 0.091 18.99 Fund Amnt Invested in PC I 11.040 5.391 5.649*** 1.144 4.94

Panel B: Litigation During

Outcome Expected Treated Controls Difference Std. Errors T-stat Sign 1 2 3 4 5 Expertise + 3.360 3.147 0.213*** 0.084 2.52 # Previous IPOs - 4.263 5.437 -1.174*** 0.206 -5.7 Capital Under Mgmt + 4.243 3.673 0.570*** 0.199 2.87 # Rounds VC Invests I 18.533 14.594 3.939*** 0.340 11.6 # VCs Invested in PC + 7.958 6.225 1.733*** 0.091 18.99 Fund Amnt Invested in PC + 11.040 5.391 5.649*** 1.144 4.94 Stop Funding - 0.148 0.613 -0.464*** 0.008 -56.4