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Overcoming Distances via Syndication with Local Friends:
The Case of Venture Capital
Tereza Tykvová
(joint work with Andrea Schertler)
EFM Symposium Montreal
April 16, 2010
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“Venture capital is not about the people you know but rather where
you are: FIBRE networks cross the world. Data bits move at light
speed. The globe has been flattened, and national boundaries
obliterated. Yet…physical distance is very much on the minds of the
investors who provide venture capital.”
“ … if a start-up company seeking venture capital is not within a 20-
minute drive of the venture firm’s offices, it will not be funded. ”
Source: Stross, Randall, “It’s not the people you know. It’s where you are.” The New York Times, 22 October 2006.
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BUT:
“VCs who once bragged about never driving more than half an hour to
visit a portfolio company are jetting to Australia for optical engineers,
Israel for security whizzes, India and Kazakhstan for brute software
coding, South Korea for online gaming, and Japan for graphics chips.
For growth across the board, China is the place to go.”
“VCs in Silicon Valley used to pride themselves on being local… That
was well and good when the U.S. was the mecca for technology.”
Source: The Global Startup, Forbes Global, 29 November 2004.
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Research questions (I)
1) Does geographical and institutional distance matter in VC
internationalization?
2) Do experienced VCs cross borders while inexperienced VCs stay at
home?
3) Do foreign VCs overcome distances by teaming up with local VCs?
BUT: Information asymmetries among syndicate members (Casamatta and
Haritchabalet JFI 2007, Cestone, Lerner and White 2009 WP)
Questions and literature
SummaryTransaction data
Participation model
Lead model
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Research questions (II)
4) Do repeated relationships help overcome distances? Repeated
relationships are supposed to reduce information asymmetries (Pichler and
Wilhelm JF 2001, Hochberg, Ljungqvist and Lu JF 2007)
5) Are repeated relationships more helpful when information
asymmetries are particularly pronounced?
6) Does the lead VC’s experience help overcome distances?
Questions and literature
SummaryTransaction data
Participation model
Lead model
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Related literature on VC internationalization
- Recent interest in this topic
Where?
VCs (worldwide) invest into geographically and institutionally proximate countries (Aizenman/Kendall NBER 2008).
Who?
VCs (from US) with a larger international experience (Guler/Guillén JIBS 2010) and with stronger home-country networks (Guler/Guillén AMJ 2010) expand faster into new foreign countries.
How?
PEs (from UK) with int. experience (and experience in host countries) are less likely to team up with a local PE in cont. Europe (Meuleman/Wright JBV 2010).
Our analysis combines the where, who and how in a single framework.
Our analysis uses an extensive dataset of worldwide deals.
Questions and literature
SummaryTransaction data
Participation model
Lead model
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Worldwide venture capital transaction data 2000-2008 (Zephyr)
Portfolio firms
- Name, industry and location (city and ZIP code).
- Transaction size.
- Age (Amadeus, Orbis).
Venture capitalists
- Name and location (city and ZIP code).
- Business description of all VCs in each transaction.
Questions and literature
SummaryTransaction data
Participation model
Lead model
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Worldwide venture capital links
Total links (2000-2008), Source: Zephyr
Questions and literature
SummaryTransaction data
Participation model
Lead model
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Model set-up
Combination of all cb transactions with all potential cb VCs
Dependent variable (binary):
One if the potential VC participates in the transaction, zero otherwise.
Estimation method: Conditional logit model with transaction FE.
Selected RHS variables (t … time varying; past three years): – Potential VC – firm: Geographical distance – Firm: Fixed effects, presence of a domestic VC (dummy interacted
with distance); age and volume in extensions– Potential VC: Experience (t), location (country dummies) – Potential VC – firm country: Joint border (dummy), same law
tradition (dummy), newcomer (dummy, t)– Potential VC – participating domestic VCs: Repeated relationship
(dummy, t)
Questions and literature
SummaryTransaction data
Participation model
Lead model
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Does distance matter? Does a local VC help?
Geographical and institutional distances matter.
Marginal effects of geographical and institutional distances as well as
joint border are smaller if a local VC participates. Teaming up with local VCs helps.
Cross-border transactions
All DD=0 DD=1
Distance+distanceDD -0.003*** -0.004*** -0.002***Same law 0.005*** 0.008*** 0.003***Joint border 0.001* 0.002* 0.001**Repeated rel. to dom VC 0.033***
Newcomer -0.052***
Experience 0.005***
Pseudo R2 0.2562
Marginal effects; 4,457,121 observations; model includes transaction-FE, and VC-country dummies, *** (**) significant at 1% (5%).
Questions and literature
SummaryTransaction data
Participation model
Lead model
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Do repeated relationship matter? Does experience matter?
Repeated relationships help.
Experience and country experience help.
Marginal effect of foreign VC’s experience is higher if no local VC
participates.
Cross-border transactions
All DD=0 DD=1
Distance+distanceDD -0.003***
Same law 0.005***
Joint border 0.001*
Repeated rel. to dom VC 0.033***
Newcomer -0.052***
Experience 0.005*** 0.008*** 0.003***Pseudo R2 0.2562
Marginal effects; 4,457,121 observations; model includes transaction-FE, and VC-country dummies, *** (**) significant at 1% (5%).
Questions and literature
SummaryTransaction data
Participation model
Lead model
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Are repeated relationships more important if information asymmetries
are more pronounced?
Repeated relationships to domestic VCs are more important if the
portfolio company is young.
Questions and literature
SummaryTransaction data
Participation model
Lead model
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Model set-up
Combination of dom and cb syndicated transactions with all potent. VCs
Model for potential synd. partners (exclude lead VC)
Dependent variable:
Dummy equals one if the potential VC participates in the given
transaction, zero otherwise.
Estimation method: Conditional logit model with transaction FE.
Selected RHS variables: – Potential VC – firm: Geographical distance– Potential VC – lead VCs: Repeated relationship (dummy, t) – Lead VC: Experience (t); interacted with the distance between the
potential VC and the firm.– Potential VC – firm country: Newcomer vs. old hand (dummy, t)
Questions and literature
SummaryTransaction data
Participation model
Lead model
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Does the lead VC’s experience help overcome distances?
Marginal effect of distance is negative only if the lead VC is
inexperienced. Lead VC experience helps.
Syndicated transactions
All Inexp lead Exp lead
Old hands
Distance+distanceLeadExp
-0.005*** -0.015*** -0.001
Same law 0.065***
Newcomer -0.389***
Old hand -0.068***
Experience 0.068***
Repeated rel. to lead VC 0.5094***
Pseudo R2 0.2762 Marginal effects; 9,536,664 observations; model includes transaction-FE and VC-country dummies, *** (**) significant at 1% (5%).
Questions and literature
SummaryTransaction data
Participation model
Lead model
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- Geographical and institutional distances matter
- VCs overcome distances by:
- Accumulating experience (resp. country experience)
- Syndication
- with local VCs
- with experienced lead VCs
- Repeated relationships make such syndication easier
- more helpful when information asymmetries are high
Questions and literature
SummaryTransaction data
Participation model
Lead model
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Thank you for your attention!
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