Essays in Spatial Economics, Trade, and Climate Change

Abstract

In this thesis, I study topics on climate change, trade, and agglomeration. I utilize modern quantitative spatial modelling tools and structural estimation techniques to investigate how space and spatial frictions affect economic outcomes, with a particular focus on climate change. In Chapter 1, I quantify the relative importance of three fundamental sources of agglomeration benefits for the spatial distribution of the US economy: the access to ideas, labor, and goods. I develop a quantitative spatial model to structurally recover industry-location productivities and estimate agglomeration spillover parameters for 26 tradable industries. I decompose the observed spatial distribution of employment into the separate contributions of the different forces and simulate counterfactual economies in which they are absent. Knowledge spillovers have the most sizable effect on aggregate economic activity, whose elimination generates a 26 percent reduction in an index of spatial concentration. This is followed by access to goods, with a 20 percent reduction, and then access to labor with 6 percent. The relative importance of each force depends crucially on the type of industry and spatial range considered. In joint work with John Spray and Filiz Unsal, chapter 2 develops a quantitative spatial general equilibrium model with heterogeneous households and locations to study households’ vulnerability to food insecurity from climate shocks. In the model, households endogenously respond to negative climate shocks by increasing off-farm labor, importing additional food and temporarily migrating to earn additional income to ensure sufficient calories. Because these coping strategies are most effective when trade and migration costs are low, remote households are more vulnerable to climate shocks. Poorer households are also more vulnerable because more of their income and consumption is derived from the agricultural sector. We calibrate the model to 77 districts in Nepal and estimate the impact of historical climate shocks in 2011-2022 on food consumption and welfare. We estimate that, on an annual basis, floods, landslides, and storms combined generated GDP losses of 2 percent, welfare losses of 1.5 percent for the average household and increased the rate of undernourishment by almost 7 percent. In counterfactual simulations, we show the role of better access to migration and trade in building resilience to climate shocks. Chapter 3 quantifies the welfare impact of climate variability and assesses the role of trade integration as a climate adaptation strategy. Climate change involves not only changes in mean climatic conditions, but also in the degree of climate variability, i.e. how much weather fluctuates year-to-year around the mean. In this chapter, I measure the effect of weather fluctuations on agricultural yields by combining weather data from a 0.5ºx0.5º grid with agricultural production series for 23 different crops in 1961-2022. I then use climate projections from general circulation models to assess the change in climate variability in the future under an RCP8.5 emissions scenario. I calibrate a quantitative trade model with multiple sectors for all 54 African countries and quantify the impact of productivity shocks from weather fluctuations on household consumption. According to the results, climate variability is expected to generate annual consumption-equivalent losses of 1.31 percent in 2015-2100 for the average African household and of 6.7 percent among the top five most affected countries. If all African countries were assigned trade costs equivalent to the 90th percentile of trade openness, the welfare impact of future climate variability would be reduced by 27 percent, on average. However, differences in comparative advantage in agriculture affects countries' exposure to climate variability, leading to heterogeneous welfare effects across space. For instance, households among the top five countries that benefit the most from trade integration see decreases of more than 75 percent in welfare losses, while those among the bottom five experience a 50 percent average increase in them.