Abstract
Our study quantifies the impact of climate change on the income of corn farms in Ontario, at the 2068 horizon, under several warming scenarios. It is articulated around a discrete-time dynamic model of corn farm income with an annual time-step, corresponding to one agricultural cycle from planting to harvest. At each period, we compute the income of a farm given the corn yield, which is highly dependent on weather variables: temperature and rainfall. We also provide a reproducible forecast of the yearly distribution of corn yield for the regions around ten cities in Ontario, located where most of the corn growing activity takes place in the province. The price of corn futures at harvest time is taken into account and we fit our model by using 49 years of county-level historical climate and corn yield data. We then conduct out-of-sample Monte-Carlo simulations in order to obtain the farm income forecasts under a given climate change scenario, from 0^circC to + 4^circC.
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