Abstract: I study the collaboration between high-tech companies and academics using a theoretical two-sided matching model with moral hazard. I take the pharma-academic alliances as one particular example. The academic's effort determines the future probability of success. This outcome is not contractual. In an interim stage, the company receives a signal on the prospects of the output. This signal allows the company to decide whether to abandon the project and is used to motivate the academic. The equilibrium consists of a menu of incentive contracts and matching between firms and academics. Considering different evaluation technologies, I show that the equilibrium matching is unique and can be positive assortative (PAM) or negative assortative (NAM) depending on the firms' evaluation technology. Moreover, when considering the matching market, a better academic's payment could be lower because she is matched with a lower-paid company, and motivating her to exert sufficient effort does not require a higher payoff. I also discuss the results in different setups.
Abstract: We analyse if and how the characteristics of grant research panels affect the applicants’ likelihood of obtaining funding and, especially, if particular types of panels favour particular types of applicants. We use the UK’s Engineering and Physical Sciences Research Council (EPSRC) award decisions. Our main results indicate that panel members tend to favour more (or penalise less) applicants with similar characteristics to them, as the similar-to-me hypothesis suggests. We show, for instance, that the quality of the applicants is more critical for panels of high quality than for panels of relatively lower quality, that basic-oriented panels tend to penalise applied-oriented applicants, and that panels with fewer female members tend to penalise teams with more female applicants.