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1-3 Conditional Yield Distribution: An Almost Ideal Approach

  • 发布日期:2017-12-22 08:33:00

题目: Conditional Yield Distribution: An Almost Ideal Approach
主讲人: Ford Ramsey
时间:2018年1月3日下午2:00

地点:主楼418室

主讲人介绍

        Dr. Ford Ramsey is assistant professor in the Department of Agricultural and Applied Economics at Virginia Polytechnic Institute and State University. He received his PhD in Economics in 2017 from North Carolina State University and undergraduate and master’s degrees from the University of North Carolina at Chapel Hill. His research focuses on the utilization of statistical and econometric methods in agricultural economics. Applications include characterizing crop yield distributions, pricing crop insurance contracts, and describing structural change in production systems.

内容介绍: 

        Crop yields are characterized by technological change, the effects of weather and other covariates, spatial correlation, and a paucity of data in any one location. Viewing observed yields are being drawn from a probability distribution, estimation of the conditional yield distribution requires statistical approaches that are able to account for these features. Comprehensive solutions for characterizing the distribution of yields can be considered ideal. Common parametric and nonparametric methods for the estimation of yield densities have rarely dealt with these aspects in unified manner. We propose a Bayesian spatial quantile regression model for the conditional yield distribution that is distribution-free, incorporates weather (covariate) effects, and integrates spatial correlation. Results provide insight into the temporal and spatial evolution of crop yields.

 

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