Legal, regulatory, and fiscal determinants of venture capital investments

The question whether and how a country’s institutional environment affects unilateral and bilateral venture capital flows in an international context has so far received little attention in the academic literature although it has been the subject of much political debate. Using data on VC investment...

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Bibliographic Details
Main Author: Thiengtham, Dolruedee
Other Authors: Murray, Gordon : Gyoshev, Stanley
Published: University of Exeter 2010
Subjects:
332
Online Access:http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.529344
Description
Summary:The question whether and how a country’s institutional environment affects unilateral and bilateral venture capital flows in an international context has so far received little attention in the academic literature although it has been the subject of much political debate. Using data on VC investments in 55 countries from 1995 to 2008, this dissertation contributes to that debate by examining the effect of a country’s legal, regulatory, and fiscal environment on VC investments. In addition, I explore whether governments can establish a domestic VC industry or attract foreign VC funding via targeted policy reforms. The results of this study suggest that VC investment flows are significantly affected by a country’s institutional environment. In addition, they suggest that the judicial independence of a country’s courts and the adaptability of its laws have a strong influence on the country’s attractiveness for VC investors. Moreover, VC investments are strongly affected by macroeconomic, political, and cultural factors, confirming the results of prior studies in the VC literature. Finally, I show that bankruptcy law reforms, VC-related pension fund regulations, and fiscal reforms are important tools whereby governments can attract and retain domestic and foreign VC investors – a result that should be of much interest to policy makers. A series of sensitivity checks reveals that my results are highly robust to alternative sample compositions, estimation methods, and variable definitions.