When instruments are weakly correlated with endogenous regressors, conventional
methods for instrumental variables (IV) estimation and inference become unreliable. A large …

This chapter reviews the instrumental variable quantile regression model of Chernozhukov
and Hansen. It discusses the key conditions used for identification of structural quantile …

We propose to smooth the objective function, rather than only the indicator on the check
function, in a linear quantile regression context. Not only does the resulting smoothed …

Many empirical applications of regression discontinuity (RD) models use a running variable
that is rounded and hence discrete, eg age in years, or birth weight in ounces. This paper …

This paper provides identification results for a class of models specified by a triangular
system of two equations with binary endogenous variables. The joint distribution of the latent …

We consider a linear combination of jackknife Anderson-Rubin (AR), jackknife Lagrangian
multiplier (LM), and orthogonalized jackknife LM tests for inference in IV regressions with …

We introduce the class of conditional linear combination tests, which reject null hypotheses
concerning model parameters when a data‐dependent convex combination of two …

This paper introduces a new identification‐and singularity‐robust conditional quasi‐
likelihood ratio (SR‐CQLR) test and a new identification‐and singularity‐robust Anderson …

This paper develops extremum estimation and inference results for nonlinear models with
very general forms of potential identification failure when the source of this identification …

Recently developed econometric methods, that are robust to weak instruments and exploit
information in possible structural changes, are applied to study the Euler equation for …