This paper provides conditions for identification and estimation of the conditional or unconditional average effect of a binary treatment or policy on a scalar outcome in models where treatment may be misclassified. Misclassification probabilities and the true probability of treatment are also...

When selection bias can purely be attributed to observables, several estimators have been discussed in the literature to estimate the average effect of a binary treatment or policy on a scalar outcome. Identification typically exploits the unconfoundedness of the treatment, which is verified if...

One of the lessons of the treatment effects literature is the lack of consensus about the ability of statistical and econometric methods to replicate experimental estimates. In this paper, we provide new evidence using an unusual unemployment insurance experiment that allows the identification...

We study participation and relative earnings in the formal, informal, and self-employed sectors in Bolivia. We estimate quantile earnings equations corrected for self-selectivity to address potential biases in the estimates of relative earnings gaps due to the endogeneity of sector...

Quantile regression (QR) methods fit a linear model for conditional quantiles, just as ordinary least squares (OLS) regression estimates a linear model for conditional means. An attractive feature of the OLS estimator is that it gives a minimum mean square error approximation to the conditional...

Finite-sample inference methods are developed for quantile regression models. The methods are conservative in that (i) they apply to arbitrary sample sizes without the liberal assumption that sample sizes approach infinity, (ii) they apply when the quantiles are partially or set identified,...

There is conflicting evidence regarding the recent evolution of unemployment duration in the U.S. In this study we rely on censored quantile regression methods to analyze the changes in the US unemployment duration distribution. We employed the decomposition method proposed by Machado and Mata...

This paper investigates how conditional quantiles of a given distribution relate to each other. Given two conditional quantiles estimated nonparametrically, we investigate their relation by linking them through a parametric transformation. Asymptotic normality of the associated parameter vector...

In this paper, we present methods for deriving testable implication from models with multiple equilibria. Our framework includes many economic models with a one-dimensional endogenous variable---examples are macroeconomic growth models (Solow, 1956), partial equilibrium models, and games of...

This lecture explores conditions under which there is identification of the impact on an outcome of exogenous variation in a variable which is endogenous when data are gathered. The starting point is the Cowles Commission linear simultaneous equations model. The parametric and additive error...