Comparative advantage, whether driven by technology or factor endowment, is at the core of neoclassical trade theory. Using tools from the mathematics of complementarity, this paper offers a simple yet unifying perspective on the fundamental forces that shape comparative advantage. The main results characterize sufficient conditions on factor productivity and factor supply to predict patterns of international specialization in a multifactor generalization of the Ricardian model which we refer to as an “elementary neoclassical economy.” These conditions, which hold for an arbitrarily large number of countries, goods, and factors, generalize and extend many results from the previous trade literature. They also offer new insights about the joint effects of technology and factor endowments on international specialization.

Technological change, from the advent of robots to expanded trade opportunities, creates winners and losers. How should government policy respond? We provide a general theory of optimal technology regulation in a second-best world, with rich heterogeneity across households, linear taxes on the subset of firms affected by technological change, and a non-linear tax on labour income. Our first set of results consists of optimal tax formulas, with minimal structural assumptions, involving sufficient statistics that can be implemented using evidence on the distributional impact of new technologies, such as robots and trade. Our final results are comparative static exercises illustrating, among other things, that while distributional concerns create a rationale for non-zero taxes on robots and trade, the magnitude of these taxes may decrease as the process of automation and globalization deepens and inequality increases.

This paper develops a simple model of international trade with intermediation. We consider an economy with two islands and two types of agents, farmers and traders. Farmers can produce two goods, but to sell these goods in centralized (Walrasian) markets, they need to be matched with a trader, and this entails costly search. In the absence of search frictions, our model reduces to a standard Ricardian model of trade. We use this simple model to contrast the implications of changes in the integration of Walrasian markets, which allow traders from different islands to exchange their goods, and changes in the access to these Walrasian markets, which allow farmers to trade with traders from different islands. We find that intermediation always magnifies the gains from trade under the former type of integration, but leads to more nuanced welfare results under the latter, including the possibility of aggregate losses.

When asked to name one proposition in the social sciences that is both true and non-trivial, Paul Samuelson famously replied: ‘Ricardo's theory of comparative advantage’. Truth, however, in Samuelson's reply refers to the fact that Ricardo's theory of comparative advantage is mathematically correct, not that it is empirically valid. In this paper we develop and implement an empirical test of Ricardo's ideas. We use novel agricultural data that describe the productivity in 17 crops of 1.6 million parcels of land in 55 countries around the world. We find that a regression of log observed output on log predicted output has a (precisely estimated) slope of 0.84 and an R-squared of 0.93. In our view, these findings offer considerable support for Ricardo's ideas.

The theory of international trade has paid scant attention to market institutions. Neither neoclassical theory nor new trade models typically specify the process by which supply and demand meet. Yet in the real world, intermediaries play a central role in materializing the gains from exchange outlined by standard trade theories. In Antr’and Costinot (2010), we have developed a stylized but explicit model of intermediation in trade. In this short paper, we present a variant of this model that illustrates the potential role of intermediaries in facilitating the realization of the gains from trade.

This paper develops tools and techniques to analyze the determinants of factor allocation and factor prices in economies with a large number of goods and factors. The main results of our paper characterize sufficient conditions for robust monotone comparative statics predictions in a Roy-like assignment model. These general results are then used to generate new insights about the consequences of globalization.

The primary motivation behind quantitative work in international trade and many other fields is to shed light on the economic consequences of policy changes and other shocks. To help assess and potentially strengthen the credibility of such quantitative predictions, we introduce an IV-based goodness-of-fit measure that provides the basis for testing causal predictions in arbitrary general equilibrium environments as well as for estimating the average misspecification in these predictions. As an illustration of how to use the measure in practice, we revisit the welfare consequences of the U.S.-China trade war predicted by Fajgelbaum et al. (2020).

This paper offers the first empirical analysis of the impact of adaptation on the boundary of multinational firms. To do so, we develop a ranking of sectors in terms of “routineness” by merging two sets of data: ratings of occupations by their intensities in solving problems from the U.S. Department of Labor's Occupational Information Network and U.S. employment shares of occupations by sectors from the Bureau of Labor Statistics Occupational Employment Statistics. Using U.S. Census trade data, we demonstrate that the share of intrafirm trade tends to be higher in less routine sectors.

We develop a methodology to construct nonparametric counterfactual predictions, free of functional form restrictions on preferences and technology, in neoclassical models of international trade. First, we establish the equivalence between such models and reduced exchange models in which countries directly exchange factor services. This equivalence implies that, for an arbitrary change in trade costs, counterfactual changes in the factor content of trade, factor prices, and welfare only depend on the shape of a reduced factor demand system. Second, we provide sufficient conditions under which estimates of this system can be recovered nonparametrically. Together, these results offer a strict generalization of the parametric approach used in so-called gravity models. Finally, we use China's recent integration into the world economy to illustrate the feasibility and potential benefits of our approach.

A large agronomic literature models the implications of climate change for a variety of crops and locations around the world. The goal of the present paper is to quantify the macro-level consequences of these micro-level shocks. Using an extremely rich micro-level data set that contains information about the productivity—both before and after climate change—of each of 10 crops for each of 1.7 million fields covering the surface of the earth, we find that the impact of climate change on these agricultural markets would amount to a 0.26 percent reduction in global GDP when trade and production patterns are allowed to adjust. Since the value of output in our 10 crops is equal to 1.8 percent of world GDP, this corresponds to about one-sixth of total crop value.