Microeconomics & International Trade Seminars


Thursdays, 1:40 - 3:00 PM in E2-499

Fall 2019

September 26
Daniel Chen, Toulouse School of Economics
"Stereotypes in High Stake Decisions: Evidence from U.S. Circuit Courts"
Host: Dan Friedman
Attitudes towards social groups such as women and racial minorities have been shown to be important determinants of individual’s decisions but are hard to measure for those in policymaking roles. We propose a way to address the challenge in the case of U.S. appellate court judges, for whom we have large corpora of written text (their published opinions). Using the universe of published opinions in U.S. Circuit Courts 1890-2013, we construct a judge-specific measure of gender-stereotyped language (gender slant) by looking at the relative co-occurrence of words identifying gender (male versus female) and words identifying gender stereotypes (career versus family). We find that female and younger judges tend to use less stereotyped language in their opinions. Our measure of gender slant matters for judicial decisions: judges with higher slant vote more conservatively on women rights’ issues. In addition, lexically slanted judges influence workplace outcomes for female judges: more slanted judges are less likely to assign opinions to female judges, cite fewer female-authored opinions and are more likely to reverse lower-court decisions if the district court judge is a woman. Our results expose a possible use of lexical slant to detect decision-makers’ stereotypes that predict behavior and disparate outcomes.

October 10
Frank Wolak, Stanford
"Fast, 'Robust', and Approximately Correct: Estimating Mixed Demand Systems"
Host: Jessie Li
Many econometric models used in applied work integrate over unobserved heterogeneity. We show that a class of these models that includes many random coefficients demand systems can be approximated by a “small-o" expansion that yields a linear two-stage least squares estimator. We study in detail the models of product market shares and prices popular in empirical IO. Our estimator is only approximately correct, but it performs very well in practice. It is extremely fast and easy to implement, and it is “robust" to changes in the higher moments of the distribution of the random coefficients. At the very least, it provides excellent starting values for more commonly used estimators of these models.

October 15 (Note different day)
Aaron Bodoh-Creed, Berkeley Haas
"Pre-College Human Capital Investment and Affirmative Action: A Structural Policy Analysis of U.S. College Admissions"
Host: Natalia Lazzati
We estimate a model of college admissions wherein students endogenously accrue pre-college human capital (HC) as part of a contest for enrollment at high quality colleges. We use methods from the empirical auctions literature to separately identify the roles of school quality, HC, and students’ privately known learning costs on post-college household income. Conditional on graduating, college quality is the most important factor in determining income, while unobserved student characteristics play a nontrivial secondary role. Pre-college HC drives college placement and graduation probability, but not post-college income. We conduct counterfactual experiments comparing the status quo to a color-blind admissions rule and a proportional quota for minority students. Color-blind admissions results in fewer (more) minority students enrolling at the best (worst) schools with a corresponding reduction in household incomes and graduation rates. The signs and magnitudes of changes to HC investment and graduation rate depend on the learning cost of the particular student in question, and accounting for the endogeneity of HC is crucial for predicting the effect of each admissions rule.

November 21
Paul Niehaus, UC San Diego
Host: Alan Spearot

December 5
Jean-Jacques Forneron, Boston University
Host: Jessie Li