Despite significant progress in average yields, the sensitivity of corn and soybean yields to extreme heat has remained relatively constant over time. We combine county-level corn and soybeans yields in the United States from 1989-2013 with the fraction of the planting area that is insured under the federal crop insurance program, which expanded greatly over this time period as premium subsidies increased from 20 percent to 60 percent. Insured corn and soybeans are significantly more sensitive to extreme heat that uninsured crops. Insured farmers do not have the incentive to engage in costly adaptation as insurance compensates them for potential losses.

We compare prices of financial derivatives whose payouts are based on future weather outcomes to CMIP5 climate model predictions as well as observed weather station data across eight cities in the US from 2001 through 2020. Derivative prices respond both to short-term weather forecasts for the next two weeks and longer-term warming trends. We show that the long-term trends in derivative prices are comparable to station-level data and climate model output. The one exception is February in the northeastern US, where financial markets price in a polar vortex-induced cooling effect, a recent scientific finding that was not present in the older CMIP5 climate output. When looking at the spatial and temporal heterogeneity in trends, futures prices are more aligned with climate model output than observed weather station trends, suggesting that market participants closely align their expectations with scientific projections rather than recent observations.

We present a new framework to identify supply elasticities of storable commodities where past shocks are used as exogenous price shifters. In the agricultural context, past yield shocks change inventory levels and futures prices of agricultural commodities. We use our estimated elasticities to evaluate the impact of the 2009 Renewable Fuel Standard on commodity prices, quantities, and food consumers' surplus for the four basic staples: corn, rice, soybeans, and wheat. Prices increase 20 percent if one-third of commodities used to produce ethanol are recycled as feedstock, with a positively skewed 95 percent confidence interval that ranges from 14 to 35 percent.

We link farmland values to climatic, soil, and socioeconomic variables for U.S. counties east of the 100th meridian, the historical boundary of agriculture not primarily dependent on irrigation. Degree days, a nonlinear transformation of the climatic variables suggested by agronomic experiments as more relevant to crop yield, gives an improved fit and increased robustness. Estimated coefficients are consistent with the experimental results. The model is employed to estimate the potential impacts on farmland values for a range of recent warming scenarios. The predictions are very robust, and more than 75% of the counties in our sample show a statistically significant effect, ranging from moderate gains to large losses, with losses in the aggregate that can become quite large under scenarios involving sustained heavy use of fossil fuels.

In a series of studies employing a variety of approaches, we have found that the potential impact of climate change on US agriculture is likely negative. Deschênes and Greenstone (2007) report dramatically different results based on regressions of agricultural profits and yields on weather variables. The divergence is explained by (1) missing and incorrect weather and climate data in their study; (2) their use of older climate change projections rather than the more recent and less optimistic projections from the Fourth Assessment Report; and (3) difficulties in their profit measure due to the confounding effects of storage.