We propose a new regression method to estimate the impact of explanatory variables on quantiles of the unconditional … (marginal) distribution of an outcome variable. The proposed method consists of running a regression of the (recentered …, as well as policy effects, can be estimated using our regression approach. We propose three different regression …

Standard sufficient conditions for identification in the regression discontinuity design are continuity of the …

regression of Y onto X in a subpopulation homogenous in W = w (formally a conditional linear predictor). Let b₀ (w) be … the coefficient vector on X in this regression. We introduce a semiparametrically efficient estimate of the average β … methods of semiparametric regression (e.g., the partially linear regression model) …

We study nonparametric regression in a setting where N(N-1) dyadic outcomes are observed for N randomly sampled units … sets of results. First, we calculate lower bounds on the minimax risk for estimating the regression function at (i) a point … analog of the familiar Nadaraya-Watson (NW) kernel regression estimator. We show that the NW kernel regression estimator …

This paper is about the nonparametric regression of a choice variable on a nonlinear budget set under utility … budget sets make this regression three dimensional with a more parsimonious specification than previously derived. We show … restrictions of utility maximization on the budget set regression and show how to check these restrictions in applications. We …