County-level yield data are used in applied research and crop insurance policy in place of farmlevel yield data, which are likely sparse, not broadly representative, and subject to selection bias. We exploit the fact that county-level yields are the aggregate of farm-level yields to derive...

Mechanistic crop growth models are becoming increasingly important in agricultural research and are extensively used in climate change impact assessments. In such studies, statistics of crop yields are usually evaluated without the explicit consideration of sample size requirements. The purpose...

The literature on climate change and crop yields recognizes the need to allow for highly non-linear marginal effects. This study combines these two areas of the literature by using Flexible Fourier Transforms (FFT’s) to ensure flexibility for both the time trend and the weather effects. This...

This study develops a multi-crop insurance model which is employed to evaluate crop insurance decisions when several crops are produced jointly. The results suggest that the diversification effects derived from producing multiple crops can substantially alter the risk reduction impacts of crop...

Normal, gamma and beta distributions are applied to 609 crop yield histories of Ontario farmers to determine which, if any, best describe crop yields. In addition, a distribution free non-parametric kernel estimator was applied to the same data to determine its efficiency in premium estimation...