Competing on Information in Selection Markets: Evidence from Auto Insurance
Prof. Yi Xin
Assistant Professor of Economics
California Institute of Technology
This paper develops a novel method to empirically analyze competitive equilibrium in selection markets when firms offer differentiated products while having different cost structures and information precision. We apply the method to study a represen- tative sample of Italian auto insurance contracts and associated claims from 2013 to 2021. We find substantial differences in the precision of risk rating across insurers, and companies with less accurate risk rating algorithms tend to have more efficient cost structures. If all insurers were to counterfactually adopt the least advanced in- formation technology (under more stringent privacy regulation), average consumer surplus would increase by 4.5%, and the gain primarily comes from high risk drivers. Allowing all firms to share the best risk rating technology improves the efficiency of the insurer-insuree match: the cost to insure consumers decreases by 4 euros per con- tract, and high-risk consumers are more likely to be covered by insurers with lower claim processing costs.