Risk Perception and Agricultural Insurance Acceptance: Evidence from in , China

Jinxiu Ding Department of Public Finance, School of Economics University [email protected]

Chin-Hsien Yu Institute of Development Studies Southwestern University of Finance & Economics [email protected]

Douglass Shaw Department of Agricultural Economics Texas A&M University [email protected] Selected Poster prepared for presentation at the 2018 Agricultural & Applied Economics Association Annual Meeting, Washington D.C., August 5-August 7

Copyright 2018 by Jinxiu Ding, Chin-Hsien Yu, and Douglass Shaw. All rights reserved. Readers may make verbatim copies of this document for non-commercial purposes by any means, provided this copyright notice appears on all such copies. Risk Perception and Agricultural Insurance Acceptance: Evidence from Typhoon Meranti in Fujian, China Jinxiu Ding1, Chin-Hsien Yu2, Douglass Shaw3 1 Department of Public Finance, Xiamen University 2 Institute of Development Studies, Southwestern University of Finance and Economics 3 Department of Agricultural Economics, Texas A&M University

Background Survey Design Results  The central government of China continues to increase  The survey was conducted 7 months after Typhoon Meranti. subsidies on agricultural insurance, there still exists  Three pre-tests of the questionnaire were set between April insufficient demand for agricultural insurance. and May, 2017.  The existing research on the analysis of the factors  The questionnaires are designed as six versions through two affecting the demand for agricultural insurance in information treatment and one sequence control of advantage China mainly focused on objective conditions, with few and disadvantage of agricultural insurance. focusing on subjective conditions, especially on the role of risk perception.  One formal survey was conducted on May, 2017, and the other was on July, 2017. A total of 336 questionnaires were  Risk perception is an important factor of insurance issued and 325 effective ones had been collected. consumption decision (Athavale and Avila, 2011; Botzen and van den Bergh, 2012; Sherrick et al., 2004). Descriptive Statistics Objectives  Will farmers’ risk perceptions affect their attitude toward the agricultural insurance?  Will farmers’ agricultural insurance acceptance be changed when typhoon information / agricultural insurance information is provided?

Study Area  Coastal province Fujian is suffered by average 4 typhoons per year. Binary Logistic Model  On September, 2016, severe Typhoon Meranti made To investigate the impact of risk perception on farmers’ attitudes landfall over Xiamen, Fujian and caused economic towards agricultural insurance, we apply the binary logistic model Conclusions losses more than US$2.6 billion. Hence Fujian is specified as follows: chosen as the representative area to do the survey.  Farmers who perceived higher worry on typhoon damage or p n perceived higher risks of their residence place are more likely l n ( ) i      XZ  Three representative cities were selected: Longyan City ikki k1 (1) 1 pi to purchase agricultural insurance. (less affected area), City (hard-hit area) and  Farmers who express greater disaster assistance from the City (hard-hit area).  pPr( Y 1 X , Z , , Z ) denotes the probability of i i i1 i ni central government are more likely to hold agricultural conditional on the series of independent variables.  Totally 28 villages in 15 towns were chosen based on insurance. stratified sampling method  Y  1 if farmer chooses to purchase agricultural insurance in i  The probability of purchasing agricultural insurance is not near future. significantly increased when typhoon information is provided.  Control variables include risk preference, disaster assistance References from government, typhoon experience, knowledge of  Athavale, M., and S.M. Avila. 2011. An Analysis of the Demand for insurance, information treatment, agricultural production, Earthquake Insurance. Risk Management and Insurance Review 14 (2): social demographics, and city dummies. 233-246.  Botzen, W.J.W., and J.C.J.M. van den Bergh. 2012. Monetary Valuation of Insurance against Flood Risk under Climate Change. International Economic Review 53 (3): 1005-1025.  Sherrick, B.J., P.J. Barry, P.N. Ellinger, and G.D. Schnitkey. 2004. Factors Influencing Farmers’ Crop Insurance Decisions. American Journal of Agricultural Economics 86 (1): 103-114.