  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.
