We present an expository, general analysis of valid post-selection or post-regularization
inference about a low-dimensional target parameter in the presence of a very high-dimensional …

This chapter reviews the theory of extremal quantile regression. It shows that each of the
sequences produces different asymptotic approximation to the distribution of the quantile …

We revisit the classic semi‐parametric problem of inference on a low‐dimensional parameter
θ 0 in the presence of high‐dimensional nuisance parameters η 0 . We depart from the …

The ability of quantile regression models to characterize the heterogeneous impact of variables
on different points of an outcome distribution makes them appealing in many economic …

Counterfactual distributions are important ingredients for policy analysis and decomposition
analysis in empirical economics. In this article, we develop modeling and inference tools for …

This paper proposes a method to address the longstanding problem of lack of monotonicity
in estimation of conditional and structural quantile functions, also known as the quantile …

This paper develops a framework for performing estimation and inference in econometric
models with partial identification, focusing particularly on models characterized by moment …

This article considers the problem of testing many moment inequalities where the number of
moment inequalities, denoted by $p$ , is possibly much larger than the sample size $n$ . …

Nonseparable panel models are important in a variety of economic settings, including discrete
choice. This paper gives identification and estimation results for nonseparable models …

In this paper, we develop robust inference procedures for an instrumental variables model
defined by Y=D ′ α(U) where D ′ α(U) is strictly increasing in U and U is a uniform variable …