Drivers of private equity investment activity: are buyout and venture investors really so different?

Abstract

This paper investigates the drivers of private equity activity by undertaking a panel data study for 17 European countries. Activity is affected by both cyclical and structural factors. We control for the cyclical factors and examine structural drivers of investment in private equity. We examine whether these drivers are different for venture capital and buyout investors, and find that indeed there is a strong distinction between the factors influencing investment in these two groups of investors. Based on our results, we consider policy options for governments to attract more investment.

Keywords:

• private equity
• buyout
• venture capital
• panel data
• causality

Notes

1. Note that in this paper, private equity is used as a generic term to cover venture capital and buyout activity.

2. A notable exception being Meyer (2006b).

3. It is important to note at this stage that due to data limitations the study does not include investment decisions made by funds of funds.

4. Note that opportunity-driven entrepreneurship could be considered as innovative entrepreneurship. In addition, while replicative entrepreneurship (which is driven mainly by general growth in the population and the economy) differs from necessity-driven entrepreneurship, the implications for the demand for VC are likely to be similar, on account of the fact that the majority of necessity-driven entrepreneurship is a replicative entrepreneurship, i.e. does not involve a significant element of innovation.

5. In Europe, a ‘stigma of failure’ exists. The European Commission addresses this issue in its Small Business Act for Europe (Brussels, COM(2008)394 final 25.6.2008).

6. No study was undertaken in 2005, and so we interpolate for the missing year: the index changes very gradually for each country so this is not considered to be a limitation.

7. Logs are used to account for the fact that these variables may not change in a linear fashion.

8. Significant at the 1%, 5% and 10% levels means that if the same population is sampled on numerous occasions, the results would support the hypothesis in 99%, 95% and 90% of cases, respectively, and as such we can reject the hypothesis that the outcome arises due to chance.