I develop a novel view of the trade frictions between rich and poor countries by arguing that to reconcile bilateral trade volumes and price data within a standard gravity model, the trade frictions between rich and poor countries must be systematically asymmetric, with poor countries facing higher costs to export relative to rich countries. I provide a method to model these asymmetries and demonstrate the merits of my approach relative to alternatives in the trade literature. I then argue that these trade frictions are quantitatively important to understanding the large differences in standards of living and total factor productivity across countries.

Cross-country labor productivity differences are larger in agriculture than in non-agriculture. We propose a new explanation for these patterns in which the self-selection of heterogeneous workers determines sector productivity. We formalize our theory in a general-equilibrium Roy model in which preferences feature a subsistence food requirement. In the model, subsistence requirements induce workers that are relatively unproductive at agricultural work to nonetheless select into the agriculture sector in poor countries. When parameterized, the model predicts that productivity differences are roughly twice as large in agriculture as non-agriculture even when countries differ by an economy-wide efficiency term that affects both sectors uniformly.

We study how opening to trade affects economic growth in a model where heterogeneous firms can adopt new technologies already in use by other firms in their home country. We characterize the growth rate using a summary statistic of the profit distribution: the mean-min ratio. Opening to trade increases the profit spread through increased export opportunities and foreign competition, induces more rapid technology adoption, and generates faster growth. Quantitatively, these forces produce large welfare gains from trade by increasing an inefficiently low rate of technology adoption and economic growth.

According to national accounts data, value added per worker is much higher in the nonagricultural sector than in agriculture in the typical country, particularly in developing countries. Taken at face value, this “agricultural productivity gap” suggests that labor is greatly misallocated across sectors. In this article, we draw on new micro evidence to ask to what extent the gap is still present when better measures of sector labor inputs and value added are taken into consideration. We find that even after considering sector differences in hours worked and human capital per worker, as well as alternative measures of sector output constructed from household survey data, a puzzlingly large gap remains.

This paper studies the welfare effects of encouraging rural–urban migration in the developing world. To do so, we build and analyze a dynamic general‐equilibrium model of migration that features a rich set of migration motives. We estimate the model to replicate the results of a field experiment that subsidized seasonal migration in rural Bangladesh, leading to significant increases in migration and consumption. We show that the welfare gains from migration subsidies come from providing better insurance for vulnerable rural households rather than from correcting spatial misallocation by relaxing credit constraints for those with high productivity in urban areas that are stuck in rural areas.

Recent studies argue that cross-country labor productivity differences are much larger in agriculture than in the aggregate. We reexamine the agricultural productivity data underlying this conclusion using new evidence from disaggregate sources. We find that for the world's staple grains-maize, rice, and wheat-cross-country differences in the quantity of grain produced per worker are enormous according to both micro- and macrosources. Our findings validate the idea that understanding agricultural productivity is at the heart of understanding world income inequality.