2025 Theses Doctoral

Three Essays in Environmental Economics

Du Puy, Tristan

This dissertation relies on methods from empirical microeconomics and industrial organization to explore key questions relating agricultural land use and the environment: in turn environmental pollution, exposure of food production to climate change, and the relation between local crop diversity and pest diffusion.

Chapter 1: Agricultural subsidies are ubiquitous around the world and represent $749 billion per year in direct transfers. In the European Union (EU), they have accounted for 45\% of the federal budget since 1980. The agricultural industry is also a major source of environmental disruptions, in part because of its use of chemicals, which translate into air, soil, and water pollution. The influence of subsidies on pollution is ambiguous. In this project, I leverage French farm-level administrative data to ask whether these subsidies have substantive environmental effects, and test their relevance compared to the effects of subsidies on economic efficiency. I further study which design most favors joint efficiency and environmental considerations.

A shift-share analysis based on the 1992-1995 MacSharry reform of EU subsidies, the largest reform to date, shows how combined decreases in subsidy levels and changes in their design led to farm exit and reallocations. It also reduced farm-level chemical use and water pollution as measured by remote sensing. In a single agent model of dynamic land use, where producers differ in efficiency and propensity to pollute, I find that more efficient farms pollute on average more. However, policies that focus on reallocating production away from these producers have a small aggregate effect. Recovered elasticities of substitutions across inputs imply that budget-equivalent subsidies that shift the incentives for the use of chemicals have larger effects, and can reproduce part of the gains of chemicals taxation.

Chapter 2: The cost of adapting to a changing climate is one important input into climate mitigation and adaptation policy. But a lack of cost-related data means that such estimates are rare. In this paper, we use uniquely rich data on agriculture in France to provide novel, direct estimates of the marginal cost of adapting to temperature shocks. The dataset is a farm-level panel with measures of outputs, inputs, and prices from 1994-2018. We merge the farm data with measures of realized and forecasted weather. Controlling for realized weather, we use forecasts as information shocks to estimate costs and benefits of ex ante adaptation. In the year that heat shocks arrive, we find that for the average farm in France, the cost of adaptation is low.

In contrast, the benefits of adaptation are large. Dynamically, however, the costs of adapting to that original shock rise over subsequent years, eventually leading the marginal benefits of adaptation to equal marginal costs, a result consistent with a dynamic envelope theorem but inconsistent with a static sufficient statistic approach widely used when estimating climate damages. This pattern of adaptation costs is driven by the behavior that farms engage in when responding to forecasts. In the year of the shock, they use the forecasts to change the timing of key growing decisions as well as their crop mix, rather than to change costly inputs. These decisions create dynamic costs related to soil nutrients and pest control. Finally, we show that forms of adaptation currently implemented by farmers are less likely to remain relevant in a warmer world.

Chapter 3: We provide evidence of the role of local agricultural crop diversity, measured by the number of crops grown locally and the homogeneity of their land allocation, in hampering the diffusion of pests. First, we build consistent county-level diversity measures using a new machine-learning-based method to link the US Census of Agriculture between 1880-2007. Second, we show large declines in local crop diversity over the second half of the 20th century, consistent with previous findings.

Finally, we examine the impact of crop diversity on the spread of two significant pest outbreaks in US agricultural systems—the boll weevil (1890-1930) and the imported fire ant (1940-1997). We address reverse causality concerns by instrumenting local crop diversity with the pre-planting expected standard deviation in crop revenues. To the best of our knowledge, this constitutes the first causal inference study of the role of crop diversity on pest diffusion. We find that lower local crop diversity favored the diffusion of these two pests.