Work

A New Projection-type Split-sample Score Test in Linear Instrumental Variables Regression

Year: 2010

Type: article

Abstract: In this paper we introduce a new method of projection-type inference and describe it in the context of two stage least squares–based split-sample inference on subsets of structural coefficients in a linear instrumental variables regression model. The use of the new method not only guards against the uncontrolled overrejection of the true value of the parameters of interest but also reduces the conservativeness of the usual method of projection proposed by Dufour and his coauthors (Dufour, 1997,Econometrica65, 1365–1388; Dufour and Jasiak, 2001,International Economic Review41, 815–843; Dufour and Taamouti, 2005, discussion paper; Dufour and Taamouti, 2005,Econometrica73, 1351–1365; Dufour and Taamouti, 2007,Journal of Econometrics139, 133–153).

Source: Econometric Theory

DOI: 10.1017/s0266466609990806

Authors: Saraswata Chaudhuri, Thomas Richardson, James Robins, Eric Zivot

Institutions: University of North Carolina at Chapel Hill, University of Washington, Harvard University

Language: English

Topic: Advanced Causal Inference Techniques

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

Open Access status: green

Funders: National Science Foundation, University of Washington, National Institutes of Health, National Institute of Allergy and Infectious Diseases

Awards: Collaborative Research: Graphical and Algebraic Models for Multivariate Categorical Data, Analytic Methods for HIV Treatment and Co-factor Effects, G9000055107