Assistant Professor Imke Reimer’s paper “The Impacts of Telematics on Competition and Consumer Behavior in Insurance” with Benjamin R. Shiller (Assistant Professor of Economics, Brandeis University) has been accepted for publication at the Journal of Law and Economics.
In this paper, Reimers and Shiller investigate the impact on recent technological innovations of Pay How Your Drive (PHYD) programs such as Progressive’s Snapshot on both driver behavior and firm competition. Such insurance programs use telematics devices to monitor driving behaviors like hard braking, late night driving, and mileage. They then offer personalized discounts to drivers predicted to have low accident risk based on these observed driving behaviors.
In their empirical analyses, the authors find these programs cause a large and significant reduction in fatal car accidents: enrolled drivers reduce their risk of being in a fatal accident by about 50%. On the competition side, they find that while innovating firms experience initial profit increases, the profits are eroded when competing firms enter. This suggests the innovations do not cause prices and profits to rise on average in the long run, and thus novel antitrust concerns do not materialize.
Recent technological innovations allow insurance providers to closely monitor and collect detailed data on their customer’s behaviors. Such innovations offer potential benefits by mitigating moral hazard problems, but may provide the incumbent with a lasting first-mover advantage, which may harm consumers. We investigate these outcomes in the context of Pay How You Drive (PHYD) auto insurance, which offers tailored discounts to drivers monitored by telematics devices. We exploit the staggered entry of PHYD insurance across states and insurers in a difference-in-differences framework. While innovating firms experience initial profit increases, these profits are eroded by entry, suggesting that this innovation does not raise novel antitrust concerns. Furthermore, we find a meaningful impact of PHYD programs on fatal car accidents. Our findings are consistent with impacts implied by canonical theoretical models.