Abstract: Lower tariffs typically raise productivity, production, and trade, increasing the benefits from building infrastructure. Infrastructure spending by governments should therefore increase after countries open up to trade. I test this hypothesis empirically using a trade reform in India and find that a 1 percentage point reduction in tariffs increased states’ infrastructure spending by 0.5% between 1991 and 2001. To understand the mechanisms behind my empirical findings, I develop and calibrate a multi-region model of international trade, private capital accumulation, and infrastructure spending, in which each government chooses such spending to maximize their state’s welfare. I find if governments choose infrastructure following the reform optimally, infrastructure would have increased by 60% on average. The actual increase, based on my empirical findings, was about 29%. Counterfactual exercises show that raising aggregate infrastructure towards its optimal following the trade reform will result in state GDP to increase by 7% points on average.

Abstract: In this paper, we estimate the general equilibrium effects of the China Shock on U.S. local labor markets. To capture general equilibrium effects, we begin by computing a measure of market access using a quantitative spatial model with estimated domestic sectoral trade costs and input-output linkages. Guided by the model, we first regress changes in market access on Chinese import exposure to capture the local effect of the China Shock within each market, ignoring domestic spillovers. Then, we use the model’s spatial structure to capture empirically the spread of the shock across regions and sectors through domestic trade and input-output linkages. This yields a predicted general equilibrium effect of the China Shock on each local labor market. Finally, we estimate the relationship between employment changes and this spatially diffused shock. Our results show that accounting for general equilibrium spillovers reduces the estimated negative impact on manufacturing employment by a factor of 2.5. These findings highlight the importance of incorporating model-based spatial and general equilibrium linkages when evaluating the labor market effects of globalization.

Abstract: For the first time in the literature we estimate the contribution of spatial centrality to determine city size. We do this using archaeological data on cities of the region of Bukhara observed in the 9th CE. The unique feature of this region is that it was homogeneous in all respects (technology, amenities, climate, culture, language, religion, etc.) and has been homogeneous for the twelve centuries before the 9th CE. This homogeneity rules out confounding factors and endogeneity issues. We develop a simple general equilibrium spatial model that we estimate using the method of moments. The estimated model predicts very well the 9th century city size thus showing that spatial centrality is the major determinant of city size. The Silk Road contributes to explaining what centrality cannot. Interestingly, the estimated on data for the same region in the 21st century performs less well, indicating that other factors influence city size in modern economies. In a further comparison with the 21st century, we find little evidence of the persistence of the oasis urban structure. We find instead that the centroid of the region has moved towards the economic core of the Uzbek economy, both in terms of population and location of cities. In a counterfactual exercise we use the model estimated for the 9th century to compute the counterfactual population shares of the U.S. commuting zones. As expected, the model underestimates the population share of large and central zones while overestimates the share of small and peripheral zones. This suggests that agglomeration mechanisms of modern have contributed to make large zones larger and small zones smaller. Lastly, in a comparative counterfactual we estimate that infrastructures explain about eleven percent of populations shares of U.S. commuting zones. 

Abstract: An increasing number of countries use Balanced budget rules (BBRs) to control government debt, but with the potential cost of high volatility of expenditures. We find that U.S. state governments substantially smooth expenditures using savings despite BBRs. Designated “rainy day” funds are small, but government agencies hold substantial savings outside of states’ General Fund, which buffer revenue fluctuations. We estimate a buffer stock model fitted to revenue, savings, and expenditures consolidated over all agencies and find that expenditures are smoothed as if guided by a planner with a discount rate similar to that typically found for consumers.