Signaling and herding in reward-based crowdfunding

This paper investigates how signaling and herding behavior interact in crowdfunding markets to give raise to an information cascade, even when there are no identifiable experts, which is the typical case in reward-based crowdfunding. Using daily funding data for on all the projects launched on Kickstarter during one month, we find that during the initial phase of the campaign, the funding decisions of a reduced number of early backers are based on information and quality signals offered by the creator. However, during the second phase, signaling is substituted by the herding behavior of a large number of late backers, imitating early backers. The results suggest that, even in the absence of identifiable experts, backers self-select into early or late backers depending on their ability to process the information, so that herding after signaling generates an information cascade that ameliorates asymmetric information problems. The findings are relevant for (i) creators, that will obtain better results by targeting their crowdfunding campaigns at better informed potential contributors, and (ii) regulators, that can expect backers' self-selection and herding to work together to protect uninformed backers from fraud and deception even when participation is not restricted. Information Cascades in Funding Markets without Experts: Our paper shows that in funding markets where there are no identifiable experts, such as reward-funding crowdfunding, a phenomenon of information cascades leading to efficient finance decisions may appear. In reward-based crowdfunding most backers are not experts in the products and services they are buying and, even those that may know more, cannot be identified by the rest of the backers. Thus, these funding markets are expected to produce inadequate funding decisions. However, we show that better-informed backers self-select into becoming early backers, while worst-informed backers prefer to be late backers. This results in a positive reinforcing information cascade that improves the quality of funding decisions. This result has implications for entrepreneurs, who should target their campaigns at better informed potential backers, for backers looking for attractive products to fund, and for regulators worried about consumer protection in reward-based platforms.