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Momentum, Bayesian Learning, and Forgetting: Theoretical and Empirical Analyses on Automobile Insurance Policyholders

Office of Alumni and External Relations    2021-11-03

Subject: Momentum, Bayesian Learning, and Forgetting: Theoretical and Empirical Analyses on Automobile Insurance Policyholders

Guest: Chao Ma,  Assistant Professor, Xiamen University

Host: Li Zhao, Associate ProfessorAntai

Time: Wednesday, Nov 3, 2021, 14:30-16:00

Venue: Tencent Meeting


Abstract:

Analyzing data from a Chinese automobile insurance company, we find that policyholders’ past accident experience reduces their accident probabilities in the current period. Our explanation is that accidents make policyholders update their beliefs about their risk types upward and hence exert more caution. The Chinese “bonus-malus” scheme helps to rule out the possibility that the negative dependence of accidents is completely driven by changes in financial incentives caused by accidents. Additionally, we find that the magnitude of the negative effect of a past accident is smaller if the accident occurred longer ago, suggesting a forgetting effect in the learning process.

Bio:

Chao Ma is assistant professor at WISE and Department of finance at Xiamen University. He obtained PhD in economics from Ohio State University. His research areas include empirical industrial organization, household finance, real estate finance, corporate finance, and applied microeconomics. His research has been published in International Economic Review,Journal of Economics & Management Strategy,International Journal of Industrial Organization,Journal of Housing Economics,Journal of Real Estate Finance and Economics.

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