Jialing Yu

  • PhD Candidate
  • Oregon State University
  • Applied Economics


Junjie Wu

Thesis or Dissertation Citation: 

In progress

Research Abstract: 

The publicly subsidized Federal Crop Insurance Program has expanded rapidly in recent decades in the United States. With the reform in the 2014 Farm Bill, the Federal Crop Insurance Program has become the most important component of U.S. farm policies. The primary goal of the program is to provide risk protections for farmers. However, there is sporadic evidence of welfare costs associated with the program due to moral hazard, adverse selection, deadweight loss from the subsidy transfer and transaction costs. To provide a complete and systematic assessment, it requires a thorough theoretical understandings and credible empirical measurement of the welfare effect of the Federal Crop Insurance Program. We apply the sufficient statistics approach to consolidate various welfare effects of crop insurance and to provide quantitative evidence for the welfare analysis. We analyze a model in a setting where information asymmetry and systemic risk form an adverse environment for private sectors to provide insurance and therefore create a need for government intervention. From the model, we derive the condition for optimal contract and identify key parameters that affect the welfare effects of risk protection, information asymmetry, and premium subsidy. The results not only provide policy implications and but also suggest the key parameters needed for measuring the welfare effect of publically provided crop insurance programs empirically. To measure the welfare effect of the Federal Crop Insurance Program, we need to understand how the program affects the distribution of revenue. To this end, a moment-based approach is used to estimate the reduced-form equations of the first two moments of revenue distributions using farm-level Agricultural Census data from the U.S. Heartland region for 2002, 2007 and 2012. The control function approach is applied to control for the endogeneity problem caused by the self-selection of insurance coverage, under the assumption that selection into different coverage level is based on a set of observed covariates and time-invariant factors. Our results show that increase in coverage level is associated with a lower mean and higher variability of farm revenue per acre. The impacts of insurance coverage on the revenue distribution, as a reduced-form representation of the moral hazard, suggest a welfare loss. Other key parameters affecting marginal welfare effects of the Federal Crop Insurance Program include risk attitude parameters, insurance demand elasticity with respect to price, the impacts of insurance coverage on the production outcomes, marginal welfare cost of deadweight loss, and loading factors. We collect the information on the range of the values of these parameters from existing literature. The Bootstrap method is applied to estimate marginal welfare effects discussed in the conceptual model. The results suggest that under the current policy setting, the net marginal welfare effects of coverage level and subsidy rate are both negative, suggesting that both the coverage level and the subsidy rate are greater than their optimal level. However, from farmers’ perspectives, the current risk protection level is appropriate.

Publications and Presentations: 

Yu, J. Estimating Distributional Impacts of Federal Crop Insurance Program. Agricultural & Applied Economics Association and Western Agricultural Economics Association Meeting, July 26-28, 2015, San Francisco, CA (oral).