UC Berkeley

Some new technologies or financial products have the potential to dramatically improve economic development and household welfare, but adoption is often sub-optimally slow. In this dissertation, I explore the barriers to the diffusion of innovations, identify and assess potential ways to overcome these constraints, and evaluate the impact of innovation adoption on household behavior, using both experimental and non-experimental methods.

Using data from a two-year randomized experiment in rural China, the first chapter studies the influence of social networks on the decision to adopt a new weather insurance product and the mechanisms through which social networks operate. In the first year, I provided financial education to a random subset of farmers and found a large social network effect on insurance take-up: for untreated farmers, having an additional friend receiving financial education raises take-up by almost half as much as obtaining financial education directly, a spillover effect equivalent to offering a 12% reduction in the average insurance premium. By varying the information available to subjects about their peers' take-up decisions and using randomized default options, I show that the positive social network effect is not driven by scale effects, imitation, or informal risk-sharing, but instead by the diffusion of insurance knowledge. One year later, social networks continue to affect insurance demand: observing an above-median share of friends receiving payouts increases insurance take-up at a rate equivalent to about 50% of the impact of receiving payouts directly. I also find that social network effects are larger in villages where households are more strongly connected, and when the people who receive financial education first are more central in the social network.

The second chapter is based on a coauthored paper with Changcheng Song, "Insurance Take-up in Rural China: Learning from Hypothetical Experience". This chapter 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.

In the third chapter, I take advantage of a natural experiment and a rich household-level panel dataset to test the impact of an agricultural insurance program on household level production, borrowing, and saving. The empirical strategy includes both difference-in-difference and triple difference estimations. I find that first, introducing insurance increases the production area of insured crops by around 20%, and it decreases production diversification; second, provision of insurance raises the credit demand by 25%; third, it decreases the household saving by more than 30%; fourth, the effect of insurance policy on borrowing persists in the long-run, while that on saving is significant only in the medium-run; fifth, the impact of insurance is bigger on larger farmers, and households with lower migration remittance.