This paper presents a bio-economic crop yield response (BECYR) model that estimates the effects of weather, prices, land quality, groundwater level, time trend and local CO2 on field crop yields for the province of Ontario, Canada. We incorporate growing season variables and a proxy variable for CO2 in our model to differentiate the hypothesized growing season length effect and CO2 fertilization effect from technological advances modeled as a time trend. We find that including these variables changes the estimated rate of technological change for both corn and soybeans. The estimated effect of increasing local CO2 is beneficial for corn and soybean yields. Both linear and nonlinear functional forms for CO2 are used. The estimated linear effect of CO2 is consistent with the literature, but the long-term nonlinear effect of CO2 is inconsistent with the literature. Our data on local CO2 levels, however, are far from ideal. More research will be required to characterize the effects of atmospheric carbon dioxide on crop yields at the field level. Finally, our results indicate that historical trends in temperature and precipitation have not yet resulted in appreciable threats to crop production in the region.

 

Qin (Chin) Xu is an agricultural economist. She is doing her post-doc in the Department of Food, Agricultural and Resource Economics at the University of Guelph. She obtained her PhD degree there in 2018. She has a Master Degree in economics and a Bachelor Degree in environmental science with a minor in agricultural economics from the Dalhousie University. Qin is studying the crop yield models for Ontario, the demand for irrigation water, the simulation of Ontario crop production under alternative climate change scenarios, and the feasibility of using irrigation andtile drainage as the adaptation strategies for Ontario crop production. Today, the seminar will mainly focus on the econometric crop yield models.