This paper develops methods for evaluating marginal policy changes. We characterize how the effects of marginal policy changes depend on the direction of the policy change, and show that marginal policy effects are fundamentally easier to identify and to estimate than conventional treatment...

This paper considers the identification and estimation of an extension of Roy's model (1951) of occupational choice, which includes a non-pecuniary component in the decision equation and allows for uncertainty on the potential outcomes. This framework is well suited to various economic contexts,...

Using data from the China Health and Nutrition Survey (CHNS), this study analyzes peer effects on obesity in a sample of 3- to 18-year-old children and adolescents in China. Even after a rich set of covariates and unobserved individual heterogeneity are controlled for, it is evident that such...

We analyze the impact of profit sharing on the share of workers receiving training. An effect is plausible because: 1) profit sharing is a credible commitment by firms to reward firm-specific skills acquired by formal or informal training, 2) profit sharing may reduce turnover and increase the...

We exploit the variation in the admissions cutoffs across colleges of a leading Indian university in a regression discontinuity framework to estimate the causal effects of enrolling in a selective college on: cognitive attainment, behavioral preferences, and Big Five personality. We find that...

We investigate the impact of the presence of university dropouts on the academic success of first-time students. Our identification strategy relies on quasi-random variation in the proportion of returning dropouts. The estimated average zero effect of dropouts on first- time students' success...

In cases of non-compliance with a prescribed treatment, estimates of causal effects typically rely on instrumental variables. However, when participation is also misreported, this approach can be severely biased. We provide an instrumental variable method that researchers can use to identify the...

This paper assesses the effectiveness of unconfoundedness-based estimators of mean effects for multiple or multivalued treatments in eliminating biases arising from nonrandom treatment assignment. We evaluate these multiple treatment estimators by simultaneously equalizing average outcomes among...

The linear IV estimator, in which the dependent variable is a linear function of a potentially endogenous regressor, is a major workhorse in empirical economics. When this regressor takes on multiple values, the linear specification restricts the marginal effects to be constant across all...

There is a large theoretical literature on methods for estimating causal effects under unconfoundedness, exogeneity, or selection-on-observables type assumptions using matching or propensity score methods. Much of this literature is highly technical and has not made inroads into empirical...