Our study aims at quantifying the impact of climate change on corn farming in Ontario under several warming scenarios at the 2068 horizon. 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 given the corn yield, which is highly dependent on weather variables. We also provide a reproducible forecast of the yearly distribution of corn yield for 10 cities in Ontario. The price of corn futures at harvest time is taken into account and we fit our model by using 49 years of historical data. We then conduct out-of-sample Monte-Carlo simulations to obtain the farm income forecasts under a given climate change scenario.
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