What determines the distribution of establishments in terms of size and life-cycle growth? How are those determinants related to aggregate productivity? We provide novel answers by developing a framework that uses price and quantity information on establishments' outputs and inputs to jointly estimate the demand and production parameters, and subsequently establishments' quality-adjusted productivity, deriving both micro-level and aggregate implications. We find that the dominant source of variation in establishment size is variation in quality/product appeal but that variation in technical efficiency plays an important supporting role. Multiple factors dampen dispersion in establishment size including dispersion in input (quality-adjusted) prices, markups, and residual wedges. Relatively moderate dampening factors induce large aggregate allocative efficiency losses relative to their absence. We show that joint estimation of the parameters of the demand and production function crucially affects inferences on the determinants of the size distribution of firms and their implications for aggregate productivity.
The relationship between businesses and inequality has been a focus of recent attention globally.
This chapter summarizes basic facts about this relationship in Latin America. Unlike advanced economies where superstar firm growth has prompted concerns over disproportionate income growth at the top, the facts we summarize illustrate that the main concern for Latin America is the extreme prevalence of tiny businesses whose workers and owners tend to populate the bottom income segments. The empirical likelihood that these businesses improve their productivity and grow to hire more workers and pay better wages is also very low. The region displays a deficit of employment generation in small and medium enterprises, by contrast to both micro businesses (including self-employment) and large corporations. While the former tend to remunerate both workers and owners with very low incomes, the latter pay high wages but exhibit low labor shares.
Using official employment surveys for 45 advanced economies and Latin American countries, this paper shows that the positive cross-country correlation between business size and GDP per capita is tighter than previously found using firm-level datasets and finds a close negative business size-Gini relationship. The paper also finds a closer connection between individual income and business size for workers in less developed countries compared with those in advanced economies. Because employment data address the bias against the smallest productive units that characterize firm-level datasets, our approach uniquely assesses and highlights the dominance of the left tail of the business size distribution in less developed countries.
How should gender discrimination and systemic disadvantage be addressed when more discriminatory and less generous students systematically sort into certain fields, courses, and instructors' sections? In this paper, we estimate measures of gender bias and evaluation generosity at the student level by examining the gap between how a student rates male and female instructors, controlling for professor fixed effects. Accounting for measurement error, we find significant variation in gender bias and generosity across students. Furthermore, we uncover that bias varies systematically by gender and field of study and that patterns of sorting are sufficiently large to place female faculty at a substantive disadvantage in some fields and male faculty at a disadvantage in others. Finally, we document that sexist attitudes are predictive of gender-based sorting and propose Empirical Bayes inspired measures of student-level bias to correct for instructor-specific advantages and disadvantages caused by sorting.
Work in Progress
Tariff Pass-Through Along the Supply Chain: Evidence from Tariffs on European Wines. With Aaron Flaaen, Ali Hortaçsu, Felix Tintelnot, and Daniel Yi Xu.
Regional Policy in the Presence of Informality. With Rafael Dix-Carneiro and Sharon Traiberman.
Pre-Doctoral Work
"Talented" Men and "Kind" Women? Gender Bias in Student Evaluations of Teaching (2021). Documento CEDE No. 46. (Master's Thesis) [Working
Paper]. Media coverage: [El Espectador].
This paper studies gender biases in the student
evaluations of teaching at a university in Colombia. I use a linear
regression with student fixed effects that account for grades and
professor skills, measured with a value-added model, to determine that,
on average, full-time female professors receive evaluations lower by
0.07 standard deviations than male professors. Meanwhile, there are no
gender differences among adjunct professors or teacher assistants.
However, there is significant heterogeneity. In courses with 35 to 55
year-old professors, with more than 50 students, or with a smaller share
of female students, female professors are discriminated against the
most. In such cases, biases have a magnitude of about 0.1-0.2 standard
deviations and represent 40\% of all evaluations. Additionally, women
are mostly described with words related to personal characteristics
("kind" or "comprehensive"), and men are associated with course-related
topics or positive adjectives ("topic", "exam", "talented"). Based on
the results found, I propose several possible measures to reduce student
bias and allow analysis on the evaluations to consider the gender
differences.