The experimental phenomenon known as`probability matching' is often offered as evidence in support of adaptive learning models and against the idea that people maximise their expected utility. Recent interest in dynamic-based equilibrium theories means the term re-appears in Economics. However, there seems to be conflicting views on what is actually meant by the term and about the validity of the data.The purpose of this paper is therefore threefold: First, to introduce today's readers to what is meant by probability matching, and in particular to clarify which aspects of this phenomenon challenge the utility-maximisation hypothesis. Second, to familiarise the reader with the different theoretical approaches to behaviour in such circumstances, and to focus on the differences in predictions between these theories in light of recent advances. Third, to provide a comprehensive survey of repeated, binary choice experiments.
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.
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