The recent backslash against globalization has resulted in increased trade protectionism in many countries, and most notably in the United States. Although this phenomenon can be related to several factors, the international trade literature has studied at least three reasons for trade protectionism. One of them is the so-called terms-of-trade manipulation, which refers to the idea that an increase in tariffs can benefit a country by allowing it to extract rents from foreign producers by forcing them to reduce prices. A second reason is the influence of special-interest groups on the government’s choice of trade policy. A third one is the idea that trade protectionism brings industries back home. The relocation of industries is probably the most frequent reason for trade protectionism in trade policy negotiations. There are no shortage of historical episodes where governments have explicitly mentioned this argument for trade protectionism, while references to terms-of trade manipulation are usually absent in such pro-protectionism historical episodes. Surprisingly, however, there is very little empirical and quantitative assessments of this idea in the trade literature.
We propose to study empirically and quantitatively the effects of trade policy on industrial and labor location in the U.S. The first part of the project is empirical in which we will look at past episodes of protectionism to determine the elasticity of labor and industrial location to changes in trade policy. The second part of the project consists on developing a dynamic general-equilibrium model with forward-looking decisions of firms on where to locate production, forward-looking decisions of workers on where to supply labor, and capital accumulation. The model also features multiple countries, multiple industries, international trade, and inter-regional trade. We plan to take the model to the data using trade and production data for many locations and industries, as well as using data on firm’s demographics from several data sources. We hope with this project to understand the tradeoffs countries, industries, and workers face when countries unexpectedly change their trade policy. More broadly, we hope to learn about the policy implications of trade policy across industries, regions and workers.
Requisite Skills and Qualifications:
The RA’s would work with large datasets. Familiarity with Stata, R, Matlab, Julia or similar statistical programming languages is a requirement. The applicant should be comfortable working with economic and mathematical models.