Crowdfunding has recently become available for entrepreneurs. Most academic studies analyse data from rewards-based (pre-selling) campaigns. In contrast, in this paper we analyse 636 campaigns, encompassing 17,188 investors and 64,831 investments between 2012 and 2015, from one of the leading European equity crowdfunding platforms. We provide descriptive statistics and carry out cross-campaign regression analysis. The descriptive statistics address its size, growth and geographic distributions in the UK. The regressions analyse which factors are associated with the probability of a successful campaign. We find some similarities and some interesting dissimilarities when comparing the descriptive statistics and regression results to research on rewards-based crowding. The data show that equity crowdfunding will likely pose great challenges to VC and business angel financiers in the near future. We discuss some research challenges and opportunities with these kind of data.

Crowdfunding has recently become available for entrepreneurs. Most academic studies analyse data from rewards-based (pre-selling) campaigns. In contrast, in this paper we analyse 636 campaigns, encompassing 17,188 investors and 64,831 investments between 2012 and 2015, from one of the leading European equity crowdfunding platforms. We provide descriptive statistics and carry out cross-campaign regression analysis. The descriptive statistics address its size, growth and geographic distributions in the UK. The regressions analyse which factors are associated with the probability of a successful campaign. We find some similarities and some interesting dissimilarities when comparing the descriptive statistics and regression results to research on rewards-based crowding. The data show that equity crowdfunding will likely pose great challenges to VC and business angel financiers in the near future. We discuss some research challenges and opportunities with these kind of data.

Do equity crowdfunding investors rationally or irrationally herd? We build a model of rational information aggregation where both informed and uninformed investors arrive sequentially and rationally choose whether and how much to invest. We compare the predictions of the model to several alternative models of irrational herding and no herding, and test those predictions using data on all investments on a leading European equity crowdfunding platform. We show empirically that the size and likelihood of a pledge is causally affected by the size of the most recent pledge, and by the time elapsed since the most recent pledge. These results are consistent with rational information aggregation, and inconsistent with naïve herding, independent investments, and common information shocks. However, there is still room for negative information cascades to occur. Implications for platform design and regulatory actions are discussed.

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