Upload
daniel-s-hain
View
209
Download
2
Embed Size (px)
Citation preview
Cross Border Venture Capital SyndicationA Network of Emerging Trust
May 18, 2014
Daniel S. Hain 1,2 Sofia A. Johan 3 Daojuan Wang 1
1Department of Business and Management, Aalborg University
2Scancor, Stanford University (Visiting Scholar)
3Schulich School of Business, York University
1
BackgroundPositioning Venture Capital
Venture Capital and its ImpactI Venture capitalists: Financial intermediaries acting as a blend of technological and
financial competences, specialized on providing financial and managerial supportfor knowledge based entrepreneurship.
I Catalyst for commercialization (Samila & Sorenson, 2010), facilitating innovationand entrepreneurship (Kortum & Lerner, 2000), and bringing innovation to marketrapidly (Bygrave, 1992; Cumming & Johan, 2007)
Recent trends in VCI Shift towards globally distributed investment pattern (Aizenmann & Kendall, 2008;
Guler & Gullien, 2010; Baygan & Freudenberg, 2000)I Explanations of cross-border VC flows by macro and financial economists:
I Market capitalization (Black & Gilson, 1998)I Growth rates (Romain & Van Pottelsberghe, 2004)I Institutional environment (Guler & Gullien,2005; 2010)
I Recently, attention of research and VC investment community turns to emergingeconomies (Dai et al., 2012; Bruton et al., 2004)
2
backgroundMotivation
MotivationI Wile promising VC investment opportunities nowadays spring up everywhere
around the globe, we need to understand what enables the formerly more localVC industry to invest in geographically, culturally and institutionally very distanttargets.
I Prosmising candidates suggested by former research (e.g. Tykvova & Scherter,2013): (I) Institutional trust, (II) Teaming up with local VCs
I VC investments in emerging economies steadily increase, yet well lack inempirical evidence regarding the determinants on investment and entry modedecisions in such settings. Furthermore, emerging economies are oftencharacterized by weaker legal institution and property rights.
3
Theory and HypothesesGeographical, Institutional & Cultural Distance
I Interpersonal interaction necessary in pre-deal due diligence and post dealmonitoring and value adding.
I VC investment profit from spatial proximity, hence geographical concentration ofinvestments
I VC might also suffer from higher operating costs in foreign environments with verydifferent institutions, business practices, cultures and ethics
I However, teaming up with a local venture capitalists can be used to bridge highgeographical, cultural and institutional distance
Hypothesis 1HYPOTHESIS 1A - Geographical, cultural and institutional distance negatively affect venture capitalinvestment activity between countries.HYPOTHESIS 1B - The negative effects of geographical, cultural and institutional distance negativelyare less pronounced in cross border investments syndicated with a domestic VC.
4
Theory and Hypothesesrelational & Institutional Trust
I VCs do their best to mitigate agency costs of venture (Fiet, 1995a,b; Shepherdand Zacharakis, 2001) using effective contracts and governance structures toprotect themselves against opportunistic behavior
I Such risks can never be totally eliminated, especially in destination countries withless efficient laws and corporate structures (Cumming and Johan, 2006; La Portaet al., 1998, 2000, 1997)
I Institutional trust in destination country might decrease the investors needs to usemore resources to protect themselves, even in such less efficient regulatoryenvironments
Hypothesis 2HYPOTHESIS 2A - Institutional and relational trust positively affects bilateral venture capitalinvestment activity and diminishes the negative effects of geographical, social and institutionaldistance.HYPOTHESIS 2B - The positive effects of institutional trust appears stronger for investments inemerging vis-á-vis investments in developed economies.HYPOTHESIS 2C - The positive effects of institutional trust appears weaker for cross-borderinvestments syndicated with domestic venture capitalists.HYPOTHESIS 2D - The positive effects of relational trust appears stronger for cross-borderinvestments syndicated with domestic venture capitalists.
5
Empirical StrategyData & Model
Data & Model SetupI Data Source: Zephir M&A Database, extracting only deals including VC
investmentsI Period 2000–2013, ca. 30,650 deals, 78 countriesI Deploying a 2-stage GLS model, correcting for zero-inflation of the many
zero-investment-pairs of country dyads
Dependent VariablesVenture Capital Investment Propensity: Measure of bilareral VC investments relative tothe size of the two economies, and the size of the VC market in the destination country
VCproptj ,i =
VCflow tj ,i/VCinvest t
i
GDP tj /GDP t
i(1)
6
Empirical StrategyIndependent Variables
DistanceI Geographical: ln(km, population density adjusted)I Institutional: same (i.) language (CEPII), (ii.) legal system (La Porta, 1996l)I Cultural: Composed index of cultural difference (Kogut & Singh, 1988)
CDj , i =
5∑
u=1
Iuj − Iuivar(Iu )
2
5(2)
I Technological: Euclidian distance between the sectoral VC investment pattern inSC and DC
dist techti ,j =
√√√√√√√√ 7∑
s=1
(VCt
i ,sVCt
i total−
VCtj ,s
VCtj total
)2
7(3)
7
Empirical StrategyIndependent Variables, cont’d
Relational & Institutional TrustI Institutional Trust (World Value Survey)I Bilateral Trade
tradet−1i→j =
export t−1i→j ∗export t−1
j→i
gdpt−1i ∗gdpt−1
j
(4)
I Share of syndicated VC deals in all VC deals between source and destinationcountry
Destination Country institutionsI Institutional Stability (CEPII)I Corruption Perception Index (Transparency International)
ControlsI ∆ GDP, GDP growth, market capitalization
8
Empirical StrategyDescriptives
Table: Descriptive Statistics – Dyadic Venture Capital Counts
Variable Mean Std. Deviation Minimum Maximum N
DependentVC countti→j 0.568 7.301 0.000 763.000 24,596
VC propti→j 0.019 0.244 0.000 19.947 24,596
Distancedist geoi ,j 8.495 0.990 5.081 9.880 24,596dist culti ,j 0.061 0.023 0.006 0.133 20,280dist techi ,j 0.131 0.169 0.000 1.000 24,596same legali ,j 0.225 0.418 0.000 1.000 24,596same langi ,j 0.119 0.324 0.000 1.000 24,596
Institutions & Relational TrustVC syndt
i→j 0.048 0.198 0.000 1.000 24,596
cpitj * 0.631 0.236 0.170 1.000 23,822
inst stabtj 0.454 0.854 -2.118 1.668 24,596
trustj 0.494 1.199 -1.478 3.459 23,478
tradeti ,j * -0.005 0.003 -0.007 0.131 21,174
Controlsgdpt
j * 4.219 8.82 0.019 59.778 24,596
gdp growthtj 3.119 3.519 -14.072 14.781 24,553
capitalizationtj 80.371 74.504 3.640 606.001 24,037
stockstj 67.387 89.028 -0.800 741.584 24,037
The source country is denoted with subscript i , the destination country with j* indicates the variable is normalized
9
Results & DiscussionAll vs. hosted deals
Figure: GLS model with endogeneous selection - VC propensity between country dyads
all Only foreign-domestic
Variable Model I Model II Model III Model IV Hypotheses
VC propt-1 + * + * + *** + ***
Distance
Dist geo - ** - ** - * - *
Dist cult - ** - ** - * *
Dist tech + + + +
Same legal + * + ** + * + *
Same lang + + + +
Institutional & Relational trust
Trust DC + *** +
Tradet-1 + + Hyp 2a, 2d: -
Institutions
Inst. stabDC - - * - -
CPIDC + + + +
Emerging Economy DC - + - +
Controls
Δ GDPDC - SCt-1 - - - -
Δ GDP growthDC - SCt-1 - * - * - -
Market CapDC - SCt-1 - * - * - ** - **
… … … … …
Year / industry yes yes yes yes
N 20.053 20.053 20.053 20.053
R2 0.13 0.13 0.42 0.42
10
Results & DiscussionDeveloped vs. Emerging Economies
Figure: GLS model with endogeneous selection - VC propensity between country dyads
Dev. Emerg. Dev. Emerg. Dev. Emerg.
Variable I II III IV V VI Hypotheses
VC propt-1 + * + + *** + + *** +
Distance
Dist geo - ** - - * - - ** -
Dist cult - ** - - * - - * -
Dist tech - - - - - -
Same legal + * + + * + + * +
Same lang - - - - - -
Institutional & Relational trust
Trust DC + + ***
VC synd + *** +
Tradet-1 + + - + + + Hyp 2b: -
Institutions
Inst. stabDC - + - + - +
CPIDC - - - - - -
Controls
Δ GDPDC - SCt-1 - - - - - -
Δ GDP growthDC - SCt-1 - *** - - *** - - *** -
Market CapDC - SCt-1 - * - - * - - * -
… … … … … … …
Year / industry yes yes yes yes yes yes
N 11.080 8.973 11.080 8.973 11.080 8.973
R2 0.28 0.04 0.29 0.06 0.28 0.04
11
ConclusionConcluding Remarks
Destination Country institutionsI We provide a nuanced analysis on the effects of geographical, cultural and
institutional distance on cross-border VC dealsI We indeed find these distances to negatively affect VC investment activity
between country dyadsI In case the deal includes at least one local VC from the destination country, these
effects diminishI Institutional trust in the destination country facilitates cross-border deals, but effect
looses significance for deals with local co-investor→ substitution effect ofrelational and institutional trust
I However, that all changes substantially in case the destination country is aemerging economy→ all well established determinants loose their explanatorypower, model yet unable to explain these pattern
Avenues for further researchI Analyzing the micro foundations of cross-border VC dealsI Shed light on investment decisions and investor composition in emerging
economies
12
ConclusionPreview: New Micro Model on Domestic Participation in cross border deals
Figure: Probit - Cross-Border Deal includes at least one Local Investor
all Developed DC Emerging DC
Variable I II III IV V VI Hypotheses
Destination Country
GDPDC + *** + *** + *** + *** + ** + *
GDP growthDC - - - * - * - ** - **
Market CapDC + ** + ** + *** + *** - *** - ***
CPIDC - *** - * - *** - * + +
TrustDC - - - - + *** + ***
Emerging EconomyDC - *** - ***
Dyad
Dist geomean + ** + ** + + + *** + ***
Dist cultmean - ** - - * - - *** - ***
Same legalmax + ** + ** + ** + ** + ** + **
Same langmax
Aquiring foreign VC
Exp sectormax - *** - *** -
Exp countrymax + *** + *** -
Exp targetmax + *** + *** + **
Controls
Year / industry yes yes yes yes yes yes
N 7,251 7,251 6,056 6,056 1,195 1,195
Pseudo R2 0.10 0.13 0.04 0.07 0.11 0.12
Log Likelyhood - 4,375 - 4,257 -3,704 -3,582 -618 -614
13Feedback
Thanks for your attention!I am glad to answer your questions now.