This paper describes the results of a Monte Carlo study of certain aspects of robust regression confidence region …

What are the statistical and computational problems associated with robust nonlinear regression? This paper presents a …

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 …

regression discontinuity (RD) framework to applications where time is the running variable and treatment begins at a particular … threshold in time. In this guide for practitioners, we discuss several features of this "Regression Discontinuity in Time" (RDiT … framework closer to an event study than a regression discontinuity design. Based on these features and motivated by hypothetical …