Local bias and performance of venture capital institutions: evidence from the Chinese venture capital market

Abstract

Purpose The purpose of this paper is twofold to examine the factors that contribute to local bias of venture capital in China and to explore the relationship between local bias and performance of venture capital institutions. Design/methodology/approach Local bias was measured in line with the model developed by Cumming and Dai (2010). Regression techniques were performed for our long-term cross-sectional data to analyse the potential determinants of local bias. This is followed by the Probit model to test the relationship between local preference and successful exit. Findings The overall finding indicated that local bias in China increased over time. The stiff competition among venture capital institutions reduced local bias, but the enhanced innovation capabilities of a particular geographical area amplified local bias because of the knowledge spillover effect. Finally, the results suggested that venture capital institutions with less local bias enjoy a greater likelihood of making successful exits. Research limitations/implications This study used successful venture capital exit as a proxy for venture capital institution’s performance because of the unavailability of information such as internal rate of return. Future research should try to adopt other way of measuring venture capital institution’s performance. Practical implications This study sheds light on the various possible causes of local bias that the policymakers need to be aware of. Despite the rapid rise of China’s venture capital market in recent years, venture capital institutions have yet to make inroads into the local high-tech industry. This study implies to the policymakers that to reverse this trend, they should formulate policies that foster the long-term performance of venture capital institutions, mitigate the severity of local bias and raise the competitiveness of the Chinese venture capital market. Originality/value Because of data limitations, there is currently lack of prior empirical research on local bias of Chinese venture capital institutions based on large-scale data. This study intends to fill the gap.