Insurance Take-up in Rural China: Learning from Hypothetical Experience
1080 South University
Ann Arbor, Michigan 48109-1106
This paper uses a novel experimental design to test for the role of experience and information in insurance take-up in rural China, where weather insurance was a new and highly subsidized product. We randomly select a group of poor households to play insurance games and find that it improves the actual insurance take-up by 48%. In order to determine the mechanism behind this effect, we test whether it is due to: (1) changes in risk attitudes, (2) changes in the perceived probability of future disasters, (3) learning the objective benefits of insurance, or (4) hypothetical experience of disaster. We show that the effect cannot be explained by mechanisms (1) to (3), and that the experience acquired in playing the insurance game matters. We develop a simple model in which agents give less weight to disasters and benefits which they experienced infrequently. Our estimation also suggests that compared with experience with real disasters in the previous year, experience gained in the insurance game played recently has a stronger effect on the actual insurance take-up, implying that learning from experience displays a strong recency effect.
Jing Cai is currently an assistant professor in the Department of Economics at the University of Michigan. She received her Ph.D. from the University of California at Berkeley in 2012. Her current research focuses on the role of social networks in information diffusion, adoption and impacts of new financial products in developing countries, impacts of tax incentives on firm behavior, and the effect of political connections on firm performance.