CCPR Seminar

Social Science in the Age of Genomics

The cost of genetic information has been dropping at a rate faster than that of Moore's law in microcomputing.  As a result, the science of genetic prediction has improved by leaps and bounds in recent years, and with it has emerged a novel field: sociogenomics.  Sociogenomics seeks to integrate genetic and environmental information to obtain a more robust, complete picture of the causes of human behavior.  This talk will highlight some recent examples of sociogenomic research, touching upon issues such as adolescent peer effects, racial discrimination, assortative mating, and fertility patterns.  The talk will conclude by discussing the social and policy implications of genetic prediction.   

Co-sponsored with the Public Policy and Applied Social Science Seminar Series 

Making Sense of Sensitivity: Extending Omitted Variable Bias

We extend the omitted variable bias framework with a suite of tools for sensitivity analysis in regression models that: (i) does not require assumptions about the treatment assignment nor the nature of confounders; (ii) naturally handles multiple confounders, possibly acting non-linearly; (iii) exploits expert knowledge to bound sensitivity parameters; and, (iv) can be easily computed using only standard regression results. In particular, we introduce two novel sensitivity measures suited for routine reporting. The robustness value describes the minimum strength of association unobserved confounding would need to have, both with the treatment and the outcome, to change the research conclusions. The partial R2 of the treatment with the outcome shows how strongly confounders explaining all the residual outcome variation would have to be associated with the treatment to eliminate the estimated effect. Next, we offer graphical tools for elaborating on problematic confounders, examining the sensitivity of point estimates, t-values, as well as “extreme scenarios”. Finally, we describe problems with a common “benchmarking” practice and introduce a novel procedure to instead formally bound the strength of confounders based on comparison to observed covariates. We apply these methods to a running example that estimates the effect of exposure to violence on attitudes toward peace.

Immigration Restrictions as Active Labor Market Policy: Evidence from the Mexican Bracero Exclusion

An important class of active labor market policy has received little impact evaluation: immigration barriers intended to raise wages and employment by shrinking labor supply. Theories of endogenous technical advance raise the possibility of limited or even perverse impact. We study a natural policy experiment: the exclusion of almost half a million Mexican bracero farm workers from the United States to improve farm labor market conditions. With novel labor market data we measure state-level exposure to exclusion and model the absent changes in technology or crop mix. We fail to reject zero labor market impact, inconsistent with this model.

Co-sponsored with the Public Policy and Applied Social Sciences Seminar