Research

Abstract: I document a positive correlation between increases in markups and growth of output, value added, and labor productivity at the 3-digit sector level using national accounts data from Mexico. Additionally, I show that those results can be partly accounted for by the positive correlation between increases in markups and total factor productivity growth. Taken together, the findings provide new evidence that a rise of market power can be associated with positive welfare effects and not only with negative outcomes of reduced competition.

Abstract: Slums are a prevalent urban phenomenon in developing countries. They are locations with low-quality dwellings, often built on valuable land, that allow poorer households to access urban markets that otherwise would be unattainable. I build a spatial gen- eral equilibrium framework to analyze the aggregate effects of urban policies in India. The model takes into account individual selection and location differences in returns to education, productivity, and housing rents. I find that demolishing slums in the most productive areas decreases the urban population, with negative effects on welfare and no gains in labor productivity. In contrast, eliminating formal housing distortions increases the urban population while decreasing the presence of slums by a significant amount. It also increases welfare and labor productivity by 6.8 and 1.3 percent, respectively.

Abstract: I argue that the agricultural productivity puzzle is in large part a staple productivity puzzle. Using detailed data from Mexican farms, I show that most farmers grow staple crops, despite the fact that labor productivity in cash crops is substantially higher. To explain this pattern I develop a quantitative general equilibrium framework with multiple regions and crop types, subsistence requirements of staple food, and interregional trade costs. In equilibrium, most farming production is in staple crops because subsistence constraints and high trade costs prevent most farmers from specializing in cash crops. Reducing trade costs in Mexico to the U.S. level would raise the ratio of employment in cash crops to staples by 15 percent and generate a 13 percent increase in agricultural labor productivity.

Abstract: I document new facts on spatial variation in life cycle wage growth within three countries along the development scale: Brazil, Mexico, and the United States. I find that rich states tend to have steeper experience-wage profiles than poor states in each country. Differences in educational attainment and industry mix can account for a large share of the covariance between income per capita and profile steepness in both developing countries, while differences in occupation types are key in every case. Evidence from internal migrants supports the notion of substantial gaps in learning environment across space. Using a general equilibrium model with human capital accumulation and internal migration, I estimate meaningful gains in labor productivity from inducing migration to places with higher lifetime wage growth and find that spatial differences in learning environment account for an important portion of the overall gains.

Abstract: We study whether modeling technology adoption can significantly amplify the importance of human capital differences in accounting for cross-country income gaps. We document that schooling is positively and robustly correlated with measures of technology adoption and usage, and negatively correlated with the prevalence of traditional forms of production, where technology adoption is limited, and productivity is lower. Motivated by this, we build a general equilibrium model with human capital investment, endogenous occupational choices, and technology adoption. Production takes place either in a traditional sector, where technology adoption is absent, or in a modern sector, where managers hire a workforce and optimally choose technology. Economies differ in terms of schooling levels by occupation and in the size of barriers to technology adoption. These differences, working together, result in a factor of 6 between US income and that of the bottom quartile of countries. Schooling differences on their own result in a factor of 3.5, compared to a factor of 2 in a one-sector version of the model where technology choices are absent.