Power Law Distributions and the Behaviour of Venture Capital Investors: A Methodology for Using Heavy-Tailed Distribution Estimates to Describe Differences in European and American Entrepreneurial Ecosystems

The increasing coverage in the recent literature of comparison studies between the European and American entrepreneurial ecosystems indicates an ever-increasing need for tools that facilitate the understanding of entrepreneurial phenomena to facilitate the necessary economic and political changes in support of innovation. Other interesting recent literature supports a shift in probability distributions assumed in entrepreneurship research from the Gaussian distributions to heavy-tailed ones. This thesis tries to develop a method that combines the two research trends above. Firstly, it tries to inquire about the distributions of three of the most common variables of interest in entrepreneurship used to describe the financial story of a startup: total funding, exit value and multiple on invested capital (MOIC). The distributions are calculated from different samples that control for the geographic origins of the investor that funded the startups composing the samples. Secondly, by looking at the estimated distribution parameters, it tries to make a comparison between the investing behaviour of American and European investors. If the variables under scrutiny are plausibly distributed according to a power law, then the α parameter of the power law can be used to draw the desired comparisons across samples with different startup headquarters and different compositions of investors’ geographic origins. The data used in this work and the results obtained by the analyses suggest that it is not always possible to describe the variables of interest using a power law. However, from the cases in which this is possible, it seems that the American investors tend to have a higher α, which suggests a potentially higher likelihood of having larger values. Therefore, it appears that American investors have a higher propensity to, in case the observed variable was the total funding, invest really high amounts of money in single startups.