UC Davis

Agricultural production around the world has undergone tremendous changes over the past century. However, two features remain salient in modern agricultural production. One is that global crop production depends heavily on a few major crop-producing regions, and the other is that climatic conditions still play a vital role in determining crop production in these regions. Not surprisingly, anthropogenic global warming has been considered one of the greatest threats to feeding the world’s growing populations. This dissertation studies the impacts of climatic events on agriculture in three aspects: farmers’ decisions in the first chapter, farm profits in the second chapter, and agricultural production in the third chapter.

In the first chapter, I ask the following question: can we find statistical evidence that farmers in the US Corn Belt show recency effects associated with local yield shocks? As climate change is projected to increase extreme heat events in frequency and severity, farmers are expected to see an increase in crop yield variability. Using field-level crop choice data in the major US Corn Belt states (Iowa, Illinois, and Indiana), this chapter uncovers statistical evidence that crop choice decisions in the region feature recency effects associated with local yield shocks largely driven by plausibly random weather. In the region, short-run acreage adjustment occurs mainly along the intensive margin (transition between corn and soybeans). I show that farmers are less likely to plant corn---which is more susceptible to heat/water stress than soybeans---after a hotter or drier than average year, irrespective of the within-season timing of the heat. This means that low yields of corn or soybeans in one year predict less corn being planted in the subsequent year. Interestingly, relative yield does not predict the probability of growing corn next year. Based on the insights from my conceptual model, these empirical results suggest that farmers respond sensitively to total exposure to extreme heat during the previous growing season but do not respond to when it was concentrated (e.g., 1st half or 2nd half of the growing season) or which crop it affected most.

In the second chapter, I ask the following question: what are the economic costs of large-scale droughts to crop producers? Extreme weather events, such as heatwaves and droughts, in a major crop-producing area decrease crop yields but tend to increase crop prices. Such a negative correlation makes it difficult to quantify net crop revenue impacts. This paper proposes a panel approach to estimating the impacts of extreme weather events in major crop-producing regions on crop revenues accounting for the correlation between crop price and yield in the context of US crop production. I first show that, under some conditions, weather-induced changes in crop revenues are identical to those of crop profits, for which data are scant. To estimate weather-induced crop revenue effects, I use a national-level yield shock as an explanatory variable in addition to local weather variables. This variable bears two appealing features. First, it can account for heterogeneous crop yield responses to weather across regions. Second, it permits coefficients that can be interpreted as the conditional price flexibilities of demand. I show that, when estimating crop revenue impacts of weather, it is important to additionally account for spatially varying degrees of the correlation between local and aggregate yield shocks, temporally varying price flexibilities of demand, and spatially heterogeneous yield responses to weather. I apply this approach to the 1988 and 2012 US Midwest droughts to quantify the impacts of the droughts on crop revenues across US counties. I estimate that crop revenue was impacted by (-)11% for corn and (+)1% for soybeans in 1988, and (+)11% for corn and 0% in 2012. I also document that, in the two years, regional inequality of crop revenues substantially deteriorated.

In the third chapter, I work with John Abatzoglou to answer the following question: how does planting-season weather affect agricultural production? Record-high prevented planting of staple crops such as corn and soybeans in the US Corn Belt due to heavy rainfall in recent years has spurred the concern over food security, as growing evidence suggests winter and spring precipitation extremes will occur more frequently in the upper US Corn Belt in the coming decades. We examine within-season time-varying effects of planting-season water balance---precipitation minus reference evapotranspiration---on prevented planting of corn and soybeans in the US Corn Belt. Our results show significant impacts of excess moisture on preventing planting and suggest a 58-176% increase in prevented planting during the months of April-June per standard deviation increase in water balance. This framework is additionally used alongside downscaled climate change projections to estimate future changes in county-level prevented planting during the mid-century (2036--2065) under the moderate emission scenario (RCP 4.5). We find that prevented planting will increase in parts of Iowa, Minnesota, and Wisconsin by 0-30% and generally decrease in the other parts of the US Corn Belt. This work highlights the value of incorporating water balance data in assessing prevented-planting impacts and is the first known study to examine changing risk of prevented planting under future climate scenarios that may help inform adaptation efforts to avoid losses.