This paper considers tests in an instrumental variables (IVs) regression model with IVs that may be weak. Tests that have near-optimal asymptotic power properties with Gaussian errors for weak and strong IVs have been determined in Andrews, Moreira, and Stock (2006a). In this paper, we seek...

We show that the Anderson-Rubin (AR) statistic is the sum of two independent piv-otal statistics. One statistic is a score statistic that tests location and the other statistictests misspecification. The chi-squared distribution of the location statistic has a degreesof freedom parameter that is...

We study the finite-sample properties of tests for overidentifying restrictions in linear regression models with a single endogenous regressor and weak instruments. Under the assumption of Gaussian disturbances, we derive expressions for a variety of test statistics as functions of eight...

The paper is a keynote lecture from the Tilburg-Madrid Conference on Hypothesis Tests: Foundations and Applications at the Universidad Nacional de Educación a Distancia (UNED) Madrid, Spain, 15-16 December 2011. It addresses the role of tests of statistical hypotheses (specification tests) in...

The problem of multicollinearity in the assessments of coefficients is well established. However, it is rarely researched in the estimations of macroeconomic variables and economic performance of developing countries. Predicatively, it has impacts on the estimations of coefficients that should...

This paper reviews the literature on applications of state-space modelling to macroeconomic questions, with four examples related to modelling unobserved trends, transition across different steady states, expectations formation and forecasting/data revision issues. Due to the flexibility of the...

We give a set of identifying conditions for simultaneous equation systems (SES) with heteroskedasticity in the framework of the Gaussian quasi maximum likelihood (QML) approach. Our conditions rely on the presence of heteroskedasticity rather than exclusion restrictions. The QML estimators are...

We give a set of identifying conditions for simultaneous equation systems (SES) with heteroskedasticity in the framework of the Gaussian quasi maximum likelihood (QML) approach. Our conditions rely on the presence of heteroskedasticity rather than exclusion restrictions. The QML estimators are...

This paper investigates the use of regularization priors in the context of treatment effect estimation using observational data where the number of control variables is large relative to the number of observations. First, the phenomenon of “regularization-induced confounding” is introduced,...

This paper describes a randomization-based inference procedure for the distribution or quantiles of potential outcomes for a binary treatment and instrument. The method imposes no parametric model for the treatment effect, and remains valid for small n, a weak instrument, or inference on tail...