We develop an exact and distribution-free procedure to test for quantile predictability at several quantile levels jointly, while allowing for an endogenous predictive regressor with any degree of persistence. The approach proceeds by combining together the quantile regression t-statistics from...

We consider inference based on local estimating equations in the presence of nuisance parameters. The framework is useful for a number of applications including those in economic policy evaluation based on discontinuities or kinks and in real-time financial risk management. We focus on the...

Standard tests and confidence sets in the moment inequality literature are not robust to model misspecification in the sense that they exhibit spurious precision when the identified set is empty. This paper introduces tests and confidence sets that provide correct asymptotic inference for a...

Portfolio sorting is ubiquitous in the empirical finance literature, where it has been widely used to identify pricing anomalies. Despite its popularity, little attention has been paid to the statistical properties of the procedure. We develop a general framework for portfolio sorting by casting...

This paper introduces a method which permits valid inference given a finite number of heterogeneous, correlated clusters. Many inference methods assume clusters are asymptotically independent or model dependence across clusters as a function of a distance metric. With panel data, these...

In this paper, we analyze the nonparametric part of a partially linear model when the covariates in parametric and non-parametric parts are subject to measurement errors. Based on a two-stage semi-parametric estimate, we construct a uniform confidence surface of the multivariate function for...

An asymptotic theory for estimation and inference in adaptive learning models with strong mixing regressors and martingale difference innovations is developed. The maintained polynomial gain specification provides a unified framework which permits slow convergence of agents' beliefs and contains...

This article highlights the importance of statistical tests on the trend coefficient in cointegrating regressions when the stochastic regressors contain a deterministic linear trend. In addition to deriving asymptotic theory for t statistics constructed using integrated and modified ordinary...

Models defined by moment inequalities have become a standard modeling framework for empirical economists, spreading over a wide range of fields within economics. From the point of view of an empirical researcher, the literature on inference in moment inequality models is large and complex,...

Conditional heteroskedasticity of the error terms is a common occurrence in financial factor models, such as the CAPM and Fama-French factor models. This feature necessitates the use of heteroskedasticity consistent (HC) standard errors to make valid inference for regression coefficients. In...