Meta-analysis of determinants of venture capital activity

Objective: The objective of the article is to quantitatively systematise the existing literature on country-level venture capital (VC) activity and find the sources of discrepancy in previous studies. Research Design & Methods: This article collects studies that focus on venture investments across countries. I retrieved 840 estimates reported in 30 studies and analysed them using meta-analysis methods. The average effect sizes were estimated and corrected for publication bias. Then, I controlled for 24 aspects of study design and data in order to find the cause of differences in the primary results. Findings: The findings suggest that the average effect of the studied determinants of VC activity is positive and significant. Technological opportunities, macroeconomic conditions and financial market development show the highest effect which confirms the previous research. The choice of data source influences the results in a systematic way, while model specification does not affect the reported coefficients. The results showed that drivers of VC in developed and developing countries do not differ significantly, the same finding is obtained for various stages of VC. Implications & Recommendations: The analysis of existing literature delineates the research agenda for further enhancing the institutional, technological, and macroeconomic descendants of VC. It revealed that informal institutions have been studied scarcely and deserve more attention in future research. The findings show that VC is not heterogeneous across the stages of investment which is important for venture fund management. By scrutinizing different aspects of model design and data samples I provide methodological recommendations for further research. Contribution & Value Added: To my knowledge, this is the first meta-analysis of VC determinants. The research method allowed to quantitatively summarise previous studies and detect the between-study differences. This article collects all the coefficients of VC drivers that have been reported up to date while previous literature reviews focused on some limited sets of variables. The article contributes to existing theory by answering the questions regarding VC heterogeneity.