OLS and IV estimation of regression models including endogenous interaction terms

We analyze a class of linear regression models including interactions of endogenous regressors and exogenous covariates. We show how to generate instrumental variables using the nonlinear functional form of the structural equation when traditional excluded instruments are unknown. We propose to use...

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Bibliographic Details
Main Authors: Bun, M.J.G (Author), Harrison, T.D (Author)
Format: Article
Language:English
Published: Taylor and Francis Inc. 2019
Subjects:
OLS
Online Access:View Fulltext in Publisher
Description
Summary:We analyze a class of linear regression models including interactions of endogenous regressors and exogenous covariates. We show how to generate instrumental variables using the nonlinear functional form of the structural equation when traditional excluded instruments are unknown. We propose to use these instruments with identification robust IV inference. We furthermore show that, whenever functional form identification is not valid, the ordinary least squares (OLS) estimator of the coefficient of the interaction term is consistent and standard OLS inference applies. Using our alternative empirical methods we confirm recent empirical findings on the nonlinear causal relation between financial development and economic growth. © 2018, Published with license by Taylor & Francis Group, LLC. © 2018, © 2018 Maurice J. G. Bun and Teresa D. Harrison.
ISBN:07474938 (ISSN)
DOI:10.1080/07474938.2018.1427486