Hostages and the Rise of US Venture Capital

Jennifer Kuan

September, 2009

Abstract:

The vast majority of venture capital investments in the US today are made within thriving and dynamic networks of venture capitalists. These networks reduce venture capital’s risk—and thus expand total investment—by allowing investors to diversify their portfolios. But how did these networks arise? This question is economically important—20% of publicly traded firms was once funded by venture capital—and at the same time, relatively understudied, for the existing literature analyzes the inner workings of established networks, but the mechanisms needed for starting a network are known to be substantially different from those used to maintain one. This paper uses data from the 1970s, a time of explosive network growth in the US, to explore the role of hostage exchange, a self-enforcing mechanism proposed by theory. We find that hostage exchange, especially multi-lateral exchange, helped venture capitalists overcome extreme agency problems to establish fledgling networks.

Contact Information: Stanford Institute for Economic Policy Research, Stanford University, Stanford, CA 94306-6015; jwkuan@stanford.edu

1

Over the past forty years, many of the world’s most innovative new firms were financed

by venture capital, with 20% of publicly traded firms in 2000 having been VC-funded

(Gompers and Lerner, 2001). By financing firms in information technology, venture

capital has brought to market dozens of household names in computers, software and

communications—and changed the way Americans live and do business (Von Burg and

Kenney, 2000). But as a way of financing innovation, venture capital as it is practiced

today is relatively new. Less than a century before venture capital’s arrival, chemical

firms were financed by an entrepreneur’s own personal or family fortune because of the

unavailability of outside finance (Da Rin, 1998). Financiers were reluctant to invest in

that high-tech industry, with its market uncertainty and their own lack of scientific or

technological knowledge.

All of this makes the very existence of venture capital financing surprising, and its rapid

rise, from its beginnings in the late 1950s to its explosive growth in the 1980s, an

interesting puzzle. The vast majority of research on venture capital examines various

features of venture investing today, with relatively few studies looking at the early period

before 1980. One important feature of venture capital investing is the cooperation among

individual firms that co-invest in start-ups. The “trust” necessary to co-invest has been

much studied, however, the mechanisms holding together an existing network can differ

from the mechanisms used to start up a network (Bercovitz et al, 2006; Hallen, 2007). For

example, reputations and the expectation of future interactions are both mechanisms that

could prevent opportunistic behavior in a co-investing partner, but both of these take time

to establish. How, from the first steps, did shared norms and expectations form?

2

The 1960s were a period of experimentation that eventually led to the “limited

partnership” venture capital firm that prevails today (Kenney and Florida, 2000). During

this time, venture capitalists co-invested with one another, creating the foundation for

future cooperation (Kogut et al, 2007; Cohen and Fields, 2000). In this paper, I examine

the role that one mechanism might have played in starting up venture capital networks:

hostage exchange. According to the theory proposed by Williamson (1996), hostage

exchange involves a buyer and a seller. The buyer has reason to suspect that the seller

will fail to deliver a good as promised, so the seller offers something of value to be

forfeited to the buyer in such an event. But this makes the seller vulnerable to the buyer,

who could make a false claim in order to keep the hostage. To guard against this, the

buyer also offers a hostage. One difficulty of hostage exchange is the hostage itself. An

obvious hostage is money; but if both sides post funds, the net effect is zero. Thus the

practicality of hostage exchange may be impeded by the inability to find a suitable

hostage. (One exception is the use of equity investments among Japanese firms

(Ahmadjian and Oxley (2006)).

In venture capital co-investing, however, hostages are possible. By taking turns serving

as “lead investor”, venture capitalists who co-invest together can in effect post hostages. I

describe the details below. To test whether hostages laid the groundwork for today’s

network, I examine data from 1970-1975, a period of apparent calm. During this period,

total investment was relatively stable and the number of venture capitalists grew slowly.

However, connections between venture capitalists grew explosively (figures 1 and 2), as

3

the network experienced a period of phase transition, according to Kogut et al (2007).

Using both a discrete time and continuous time model, I show that venture capitalists

who exchanged hostages were more likely to cooperate again.

This study examines the role of hostages, a rarely-seen self-enforcing mechanism, in the

context of venture capital. By helping safeguard cooperative transactions during a period

without shared norms or expectations, hostages laid the foundation for the rapid growth

in venture capital and firms in the 1980s. Moreover, the use of hostages in the early

period of network formation suggests further research in other segments of the capital

market.

Background

In the modern practice of venture capital investing, venture capitalists raise funds from

“limited partners” who pay venture capitalists a management fee to invest in risky new

firms (“start-ups”). Each fund exists for a fixed, pre-announced period of time, typically

ten years, and invests in ten to twenty entrepreneurial start-ups. Ljungquist et al, (2005)

estimate that VCs write off 75.3% of their investments, on average, while Kenney and

Florida (2000) cite a common rule of thumb: “for every ten investments, three are

complete losses; another three or four neither succeed nor fail; another two or three return

three or more times the initial investment; and one or perhaps two investments return

more than ten times the initial investment.” The high-return outcomes for a start-up are

usually a buy-out by another firm or an initial public offering, but until these exits occur,

4

it can be very hard to predict which start-up will succeed and which will not. At the end

of the fund’s term, limited partners share any returns with the venture capitalists who

have a “carried interest” (usually 20%).

Another important feature of modern venture capital investing is hands-on management.

Venture capitalists occupy board seats, provide advice and business contacts, and

function as active managers. Sahlman (1990) estimates that VCs spend half their time

monitoring their start-ups, suggesting that managerial time is a key scarce resource in

venture capital investing. This heavy managerial involvement sets venture capital

investing apart from other types of private equity investing and accounts for the success

of many start-ups. However, active management by venture capitalists also complicates

the venture fund’s portfolio problem. On the one hand, the fund would like to invest in

many start-ups in order to minimize its portfolio risk; on the other hand, each start-up

requires active management, which limits the number of start-ups a fund can invest in.

Syndicates

Co-investing with another venture capitalist helps solve the portfolio problem. If a

venture capitalist invests funds in a start-up being actively managed by a different

venture capitalist, he can invest in more start-ups than he can manage himself. Thus co-

investing among venture capitalists takes the form of a “lead investor” who actively

manages the start-up and “participants”1. While the literature describes many other

1 Gorman & Sahlman (1989) find that a VC spends ten times more time managing a start-up when he serves as the lead VC than when he is only a participant.

5

reasons for such syndicates (including risk sharing (Wilson, 1968), liquidity constraints

(Brandner, Amit, Antweiler, 2002) and expertise (Stuart and Sorenson, 2001)), reducing

portfolio risk alone (Diamond, 1984) would result in improved survival of venture capital

firms and increased total investment in venture capital.

That said, syndicates present venture capitalists with an additional set of agency

problems, in addition to the more-studied problems between venture capitalist and

entrepreneur2 and between venture capitalist and limited partner3. Venture capitalists

within a syndicate face an information asymmetry between the lead investor and the

participants. Examples of how a firm’s managers can cheat investors come mostly from

parts of the capital market that are regulated, so that fraud comes to light as a violation of

securities laws. At Enron, insiders overstated profits to boost share prices; Bernard

Madoff misstated investment returns to attract investors whose funds he embezzled, and

Sibir Energy “lent” its CEO hundreds of millions of dollars before folding. A lead

investor is in a similar position to cheat fellow investors with the added benefit of a lack

of regulation and a shared understanding that a start-up’s failure does not imply fraud,

2 Contractual arrangements also include staged financing (issuing funds in stages as the start-up grows, reserving the right to abandon the start-up) (Gompers, 1995), and use convertible securities to prevent entrepreneurs from misrepresenting the start-up’s prospects (Cornelli and Yosha, 2003). Kaplan and Stromberg (2003), in their study of venture capital contracts, find various combinations of these and other contract provisions, including anti-dilution protection, conditions under which venture capitalists relinquish control (automatic conversion of preferred shares to common shares), vesting and non-compete clauses for entrepreneurs. Also, contracts in their sample seem to respond to information, so repeat entrepreneurs, about whom venture capitalists have some information about quality, face weaker restrictions than first-timers, for example.3 Gompers and Lerner (1996) discuss some solutions to the limited partner (LP) problem, including covenants, or contractual limitations on how the general partners of a venture capital firm should be compensated, what types of start-ups the fund can invest in, and what outside activities general partners can engage in (e.g. to avoid conflicts of interest). But these covenants are expensive to monitor and appear inconsistently among limited partner contracts. Lerner, Schoar, and Wongsunwai (2007) find large differences in the performance of LPs, attributing some of this to differences in sophistication and objectives. In general, the LP problem has prevented unsophisticated public participation in venture capital investing (Hsu and Kenney, 2004, described the failure of ARD in the 1950s and McGee, 2000, describes the more recent failure of meVC).

6

since start-ups commonly fail even in the best of circumstances. Because fraud is so hard

to detect in a venture capital setting makes it more attractive, especially as the funds

available for expropriation can far exceed a lead investor’s 20% carried interest.

Given the opportunity and temptation to cheat participants, syndication should be very

difficult to accomplish, let alone become the prevailing mode of investing. The literature

explores mechanisms that are used in existing networks, such as the norm of reciprocity

between high-status incumbents (Piskorski, 2002) and low-status entrants (Ferrary,

2001). However, shared norms, including the expectation of future interaction, must be

established. Cohen and Field (2000) note that venture capital networks were built not just

among strangers but among “immigrants” to a region. Thus the civic engagement of

individual venture capitalists could not have provided the social capital for cooperation.4

Even such notions as high- and low-status and reputation are features of an existing

network. Given the ten-year lifetime of a fund, other mechanisms would have been

necessary to promote cooperation before reputations could be firmly established.

Hostages

While hostage exchange is a difficult mechanism to implement, when it is possible, it is

both powerful and simple. The trouble, of course, is in finding a suitable hostage, since

the ideal hostage is worth more to the party offering the hostage than to the potential

4 By contrast, long-distance trade, as studied by Greif (1990), exhibits the same informational problems as venture capital syndicates, and probably did exploit social interconnectedness to reduce incentives to cheat. With the long-distance traders, one member of the Maghribi ethnic group would sell a distant member’s goods, and vice versa. However, because the goods are sold far away, a member must rely on his partner’s report of revenues; hence the information asymmetry. Cheating a fellow member would result in social sanctions.

7

recipient. In the case of venture capital syndicates, the hostage is the participant

investment. When a participant invests in a start-up managed by a lead investor, his

investment is vulnerable to expropriation by the lead. To guarantee against expropriation,

the lead investor invests as a participant in another start-up, this time managed by the

previous deal’s participant. Now the investors take turns serving as participant and lead,

leaving each vulnerable to the other, but where both are better off if neither cheats.

Suppose two venture capitalists operate in an initial condition without shared beliefs.

Venture capitalist B expects venture capitalist A to cheat if left unsupervised as lead

investor and therefore does not co-invest as a participant. However, both would gain if

they could participate in each other’s start-ups because doing so solves their portfolio

problem. To persuade venture capitalist B of his honesty, venture capitalist A offers to

invest as a participant in a start-up that B leads. If B then invest in A’s start-up, B can

keep A’s investment if he is cheated. A’s investment in B’s start-up gives an honest A the

incentive to disclose information about the start-up he manages, so that in the likely event

the start-up fails, B will believe failure was not due to fraud. The exchange of hostages

thus differentiates the lead investors from fraudulent corporate insiders who attempt to

hide information from investors and regulators.

In this example, two venture capitalists exchange hostages, but such an arrangement

could extend to several parties, so long as each venture capitalist could be sanctioned.5 In

5 One example of a multilateral arrangement is a three-way kidney exchange, in which each patient has a willing but incompatible donor who matches a different patient (Kohn, 2003). It is easy to see that each patient must supply a donor, and that should any donor change his mind, all three patients are halted. That is, with a closed chain, any patient can “punish” any other patient.

8

practice, posting hostages within a small group greatly increases the impact of a single

hostage by opening up transactions to multiple co-investors. Table 6 illustrates a

multilateral hostage exchange involving five investors (A, B, C, D, and E) and five start-

ups (1, 2, 3, 4, and 5). Investor A leads the syndicate for Start-up 1, with Investors B and

E investing as participants. If this deal were considered in isolation, then A would be in a

position to cheat participants B and E. However, Start-up 5, in which E leads and A

participates, makes A punishable by E should A cheat E in Start-up 1. Add to this Start-

ups 2, 3, and 4: B leads Start-up 2 and C participates; C leads Start-up 3 and D

participates; and D leads Start-up 4, and E participates. Now, if A cheats B, B can

withhold C’s return, who can withhold D’s return, who can withhold E’s return, who can

withhold A’s return. That is, B can induce punishment of A. In the end, all five investors

have the power to punish all other investors.6

The hostage mechanism is clearly one that threatens punishment and as such differs

notably from the withholding of future cooperation or loss of reputation. While this

distinction may be merely one of degree, with one punishment being worse than others,

experimental evidence suggests that a “stick”, added to the “carrot” of future interactions

may be particularly helpful in sustaining cooperation among equals (Molm, 1997).

Data

6 Sociologists measure the “closure” of a network as the number of ties that two players have in common divided by the sum of the ties of those two players. Greater closure is thought to correlate with “stronger” networks. The case of a highly structured closed loop extends this general concept of closure, though it is not known whether larger loops are more difficult to maintain.

9

Given the plausibility of a hostage mechanism in early venture capital syndicates, the

empirical question now arises, Was hostage exchange used? This paper uses data from

1970-1975, the earliest period for which data are available and a time of explosive

network formation, to explore the role of hostage exchange. For example, in 1970, a

quarter of venture capital investments involved syndicates; by 1980, over half did (Figure

3).7 Figures 1 and 2 show how quickly the network of venture capitalists grew, showing

co-investors who did at least two deals together in the period 1970-1972 and 1970-1975,

respectively. Did venture capitalists exchange hostages, and if so, did this facilitate the

growth of network ties?

To answer this question, we use data from Venture Xpert (one of two privately compiled

databases of venture capital investments) like a number of other studies in the literature.

However, most studies discard the data from the 1970s for being relatively incomplete.8

Also, because other studies focus on venture capital firms, they discard data on banks and

insurance companies making venture capital investments. But the data show that in this

early period, financial firms comprised a relatively large share of venture investors: only

42% are venture capital firms, the rest are banks, insurance companies and large firms

(Table 2). Kenney and Florida (2000) note that limited partnerships eventually displace

these financial institutions as well as federally subsidized SBICs (Small Business

Investment Companies).

7 The figures are similar for dollars amounts invested.8 Because VCs are not required to make regulatory filings, no public data are available on venture capital investment activity. Rather, the data are compiled from surveys. The design of this study requires only that VCs in the database be surveyed each year, which is clearly the case with this data set.

10

In the first three years of the decade, 1970-2, 150 VCs made at least one investment. This

cohort is examined over the 6-year period 1970-1975.9 Most firms seem open to trying

syndication: 123 invest as part of a syndicate, but 57 do so only once and another 24 just

twice (Table 3). This means that many of the syndicates involved a small number of

repeat-syndicators: 42 investors participated in more than two syndicates, and ten took

part in ten or more, including Sprout, Charles River, TA Associates and Mayfield Fund;

investment banks Hambrecht&Quist, and Rothschild; and venture arms of commercial

banks BankAmerica, Citicorp, First Chicago and BancBoston.

About half of the investors were based in New York or New England while only 10%, or

16 firms, were based in Northern California (see Table 1). But West Coast venture

capitalists achieve a higher level of cooperation than East Coast venture capitalists. This

fits with a broader literature on differences between innovative regions (e.g., Saxenian,

1996) and suggests future research into why venture capital networks are less active

elsewhere in the world, especially if building them involves hostage exchange, a self-

enforcing mechanism.

Model and Analysis

How did the tentative experimentation in syndication during the 1970s eventually

become the dominant mode of venture capital investing? Using an approach similar to

9 Note that the period studied, the first half of the 1970s, experienced the oil price rise of 1974. This may depress venture capital investment, however in interviews, VCs claim that a market downturn is the best time to invest in start-ups as inputs tend to be lower-priced. Indeed, the data show that a majority of VCs (79) invested more or less constantly throughout the period.

11

Sorenson and Stuart (2001), each syndicate is modeled as consisting of one-on-one

relationships among syndicate members (as in Powell et al, 2004, for instance), which in

turn comprise a network of relationships. For example, suppose a venture capitalist

invests with two other venture capitalists in a syndicate. This three-party syndicate is

made up of three pair-wise relationships or “dyads”. The many interconnected

relationships among pairs of venture capitalists in various syndicates ultimately form a

network.

If hostage exchange facilitates co-investment, then dyads that exchange hostages should

co-invest more frequently than those that do not. However, other factors may explain

frequent co-investing. For example, high quality venture capitalists might prefer to co-

invest with each other (Sorensen, 200X). In this period, reputation—as might be formed

by a successful fund—are less of a factor because funds take ten years to mature so very

few venture capitalists had a reputation for success in 1970.

Table 5 reports the results of a logit regression exploring several variables that might

represent co-investor attractiveness, where the dependent variable is dyad formation

between two venture capitalists10. The measure of “network centrality” used here is

simply the number of different co-investors a venture capitalist has. Notice that size

variables are not significant, but quality variables are, suggest that higher quality venture

capitalists do form more dyads. A tendency to join syndicates was also significant; the

percentage of deals that were syndicated made a dyad more likely to form, though the

10 Count models produce similar results.

12

number of syndicated deals had a slight negative effect. Proximity was also significant, as

investors worked more with others in the same region.

A. Discrete time analysis

The first model for testing whether hostages aided network formation is the most

intuitive, a discrete time logit model that analyzes whether hostage exchange in period 1

makes two venture capitalists more likely to cooperate again in period 2. Dividing the

whole period, 1970-1975, into two three-year periods, we find that in period 1, 123 of

150 venture capitalists participated in at least one syndicate creating 386 different dyads.

Most of these dyads engage just once in period 1 and do not re-engage in period 2. Of the

small minority that do multiple deals in period 1, over half go on to re-engage in period 2

(see Table 4).

In addition to the control variables identified above, other explanatory variables must be

considered, especially repeated interaction. The “shadow of the future” prevents a

venture capitalist who values future deals with his partner from behaving

opportunistically. The number of deals two investors do together in period 1 might be one

indication of how valuable future deals are for both partners. Also, the more deals two

partners do in period 1, the more compatible they are and thus the more likely they are to

do deals in period 2.

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Finally, to test the hypothesis, hostage exchange must be identified in the data. Following

the literature, the lead investor invests the most capital in the first round of funding.11 In

the bilateral case, a hostage exchange would require a pair of investors to invest in at

least two deals with each taking a turn as lead. Support for the hypothesis would take the

form of a dyad investing in this reciprocal pattern in period 1 producing a greater

likelihood of re-engaging in period 2. Descriptively, seven dyads swapped leadership

roles in period 1, of which only two paired again in period 2. Expanding the definition of

hostage exchange to include partners who invested as equals at least twice (since with

equal partners, either might serve as the leader) adds another 34 dyads. Of these, only

30% paired again in period 2, less than the average dyad that does multiple deals in

period. Taking into consideration multilateral hostage arrangements adds another 30

period 1 pairings, of which 21 or 70% paired again in period 2 (see Table 4).

Table 7 reports the results of the logit regression in which dyad formation in period 2 is

the dependent variable and hostage exchange and repeated interaction are explanatory

variables. Hostage exchange (the “stick”) helped facilitate syndication but repeat

interaction (the “carrot”) was also important. Geography was also significant as VCs in

the same state were more likely to partner. This last finding fits with the findings of other

studies that show how proximity helps with information gathering (Lerner, 1995).

B. Continuous time analysis

11 “Staged financing” is one of many mechanisms VCs use to overcome agency problems with entrepreneurs (Gompers, 1995). Start-ups typically raise funds in “stages” or “rounds”; early stages involve greater risk and smaller amounts of funding.

14

Another approach to analyzing the effect of hostages is to measure the time between

deals for each dyad. Using a hazard model, we measure the effects of hostage exchange

on the rate of dyad formation, controlling for other factors identified above. Table 8

shows that hostages are indeed an important factor in facilitating dyad formation. Venture

capitalist quality as measured by centrality is also significant, as is the tendency of

venture capitalists to form syndicates. Geographical proximity is positive but not

significant.

Discussion and Conclusion

For students of the modern practice of venture capital investing, it is hard to imagine

funding start-ups without syndicates; once venture capital funds began forming, co-

investing quickly became standard. One reason for the widespread use of syndicates is

the venture capital fund’s portfolio problem: co-investing allows funds to invest in more

start-ups than it can actively manage. While it is possible to increase the size of the

venture capital firms to increase managerial capacity—and today’s limited partnerships

typically have more general partners than the solo operations of the 1970s—even for

larger firms with greater management capacity, investing in syndicates is a Pareto

improvement because it allows firms more flexibility and diversity in its investments.

In the 1970s, venture capital firms performed their first tentative experiments with

syndication, as dozens of venture capitalists co-invested with one another, often only

15

once. But in a few short years, a sparse network filled out to become a large, densely

connected network of co-investors, laying the groundwork for the explosion in the

number of venture capitalists and invested capital that would come at the end of the

decade. During a period of seemingly flat growth, when the number of venture capitalists

grew slowly, total investments remained stable, and the 1974 oil price rise created a

pervasive sense of pessimism, venture capitalists began to establish a clever means of

survival through cooperation. So when the ERISA (Employee Retirement Income

Security Act) decision allowing pension funds to invest in venture capital funds was

made in 1978, the influx of new capital was readily absorbed by highly functioning

venture capital funds.

The ability of venture capitalists to deploy large amounts of capital to innovative start-

ups faced tremendous problems. Syndicates involve an information asymmetry among

investors so severe that similar cooperation has been stymied throughout history. This

study has argued that hostages are a mechanism that helped overcome the agency

problem facing co-investors and facilitated the establishment of the thriving venture

network that serves as an engine of growth today.

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Figure 1: Network of VCs with repeated interaction (1970-1972)

20

Figure 2: Network of VCs with repeated interaction (1973-1975)

QuickTime™ and aTIFF (LZW) decompressor

are needed to see this picture.

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Figure 3: Venture Capital Deals, 1970-1980

Figure 4: Frequency of Investors Participating in Syndicates

22

0

10

20

30

40

50

60

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

Number of Syndicatees

0

100

200

300

400

500

600

1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980

Year

Number of Deals

0

10

20

30

40

50

60

% Syndicated

Number of Deals% Syndicated

Figure 5: Frequency of Firms’ Time to Next Transaction After 1970-2

Figure 6: A Multilateral Hostage Arrangement, 1970—1972

Leader Participant

23

0

10

20

30

40

50

60

70

80

90

1 2 3 4 5 6 7 8 8+

Years

Frequency

Citicorp

First Chicago

Heizer

Sprout

Rothschild

Patricof

Texas

BA

BancBoston

Becker

Figure 7: The California Network, 1970-1972

Table 1: Frequency of Geographical Region among Venture Capital Firms, 1970-2

Region

FrequencyGreater New York 51New England 21N. California 16Southeast 14Great Lakes 13Great Plains 7S. California 5Mid-Atlantic 4Ohio Valley 4South 4Non-US 3Canada 1Rocky Mountains 1Unknown 6

24

BA Arthur Rock

Union Venture

Sutter Hill

Norwest Venture

Idanta Partners

Stanford University

Bryan & Edwards

LightspeedContinental Capital

Mayfield Fund

H&Q (Chase)

Table 2: Frequency of Firm Type among Venture Capital Investors, 1970-2

Type of Investor FrequencyPrivate Firm Investing Own Capital 64Non-Financial Corp. Affiliate or Subsidiary 18Investment/Merchant Bank Subsid/Affil 16SBIC Not elsewhere classified 15Affiliate/Subsidary of Oth. Financial. Instit. 11Insurance Firm Affiliate or Subsidiary 6Commercial Bank Affiliate or Subsidiary 5Investment Management/Finance Consulting 4Endowment 3MESBIC not elsewhere classified 3Individuals 3Private Equity Advisor or Fund of Fund Mgr 1Pension Fund-Public 1

Table 3: Descriptive Statistics for 1970-1972:

Number of Investors 150

Exited 26

Participated in a Syndicate (1970-2) 123

Total Dollar Amount Invested ($000) $710,316

Total Rounds of Financing 1480

Number of New Start-ups 349

Amount Invested in New Start-ups ($000) $239,426

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Table 4: Frequency of Period 1 and Period 2 Pairings

All Venture Capitalists “California Network”

Period 1 Pairing Arrangement

Pairs in Period 1

% “Re-pairings”in Period 2

Pairs in Period 1

% “Re-pairings”in Period 2

One Pairing Only 340 19% 7 29%

2+ Pairings 46 54% 10 70%

Swapped or Joint Leadership

41 30% 2 100%

Multilateral Hostage Posting

30 70% N/A N/A

Table 5: Logit regression of firm characteristics on pairing between investors

Independent Variable: Dyad Formation (1970-1972)

Range Coefficient

Centrality 0 - 27 0.018***(0.001)

Leader (y=1) 0.305***(0.115)

Number of deals 1 - 36 0.001(0.002)

Total $ invested (000) $10 - $30,970 0.000(0.000)

$ invested in syndicates (000) $0 - $15,435 0.000(0.000)

Number of syndicated deals 0 - 18 -0.016***(0.005)

% Deals that were Syndicated 0 – 1,mean = 0.6

1.131***(0.251)

Same Region (y=1) 0.587***(0.156)

Pseudo R-Squared 0.276Number of observations 7340

* indicates that the estimated coefficient is significantly different from zero at the 10 percent level, ** indicates that is significant at the 5 percent level, and *** indicates significance at the 1 percent level.

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Table 6: Multilateral Hostage Situation

Start-up Investors

Heizer (A) Sprout (B) Rothschild (C ) First Chicago (D) Citicorp (E)

(1) Paradyne L P P

(2) Archon L P

(3) Detwiler L P

(4) Entrex L P

(5) Data 100 P LP = Participant L = Leader

Table 7: Logit Regression of Period 2 Dyad Formation

Independent Variable: Period 2 Dyad FormationN=7340Number of Deals Done by a Pair in Period 1 0.66***

(0.14)Hostage Posting (y=1) 0.91*

(0.49)Centrality 0.01***

(0.001)Leader (y=1) 0.61***

(0.11)Number of Syndicated Deals -0.003

(0.004)% Deals that were Syndicated 0.33

(0.21)Same State (y=1) 0.53***

(0.16)Pseudo R-Squared 0.20

* indicates that the estimated coefficient is significantly different from zero at the 10 percent level, ** indicates that is significant at the 5 percent level, and *** indicates significance at the 1 percent level.

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Table 8: Hazard model of time between deals for a dyad

Time elapsed between dealsN = 7966

Hazard ratio

Hostage Posting (y=1) 2.925***(0.449)

Centrality 1.001***(0.0004)

Leader (y=1) 0.979(0.018)

Number of Syndicated Deals 1.003***(0.001)

% Deals that were Syndicated 0.990(0.034)

Same Region (y=1) 1.034(0.031)

* indicates that the estimated coefficient is significantly different from zero at the 10 percent level, ** indicates that is significant at the 5 percent level, and *** indicates significance at the 1 percent level.

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