The Nexus of Government Risk Management Subsidies, Rates of Technological Change, Yield Resiliency, and On-Farm Climate Change Adaptation

Sente, Livia
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University of Guelph

The extent to which production agriculture adopts technologies that mitigate the impacts of climate change on crop yields will impact our ability to feed nine billion people by the year 2050. For many risk-averse farmers in developed countries, government business risk management programs help manage yield risks under a changing climate. I use a neural network to predict average county corn yields for Ontario and Iowa over the years 2022-2084 under various climate change scenarios. I also estimate rates of technological change, yield resiliency, and crop insurance premium rates in these predicted yield distributions using a normal mixture model. In both Ontario and Iowa, predicted yield distributions shift rightward and exhibit component divergence over time across climate scenarios. Strictly positive rates of technological change and variable Ontario county AgriInsurance premium rates suggest that funding AgriInsurance into the future may require a larger share of taxpayer dollars.

Climate change, Crop yields, Crop insurance, Technological change in agriculture, Agricultural business risk management, Crop yield resiliency, Artificial neural network, Normal mixture model, Ontario production agriculture, Iowa production agriculture