A simple and robust estimator for linear regression models with strictly exogenous instruments Articles uri icon

publication date

  • February 2018

start page

  • 36

end page

  • 54


  • 1


  • 21

International Standard Serial Number (ISSN)

  • 1368-4221

Electronic International Standard Serial Number (EISSN)

  • 1368-423X


  • In this paper, I investigate the estimation of linear regression models with strictly exogenous instruments under minimal identifying assumptions. I introduce a uniformly (in the data¿generating process) consistent estimator under nearly minimal identifying assumptions. The proposed estimator, called the integrated instrumental variables (IIV) estimator, is a simple weighted least¿squares estimator. It does not require the choice of a bandwidth or tuning parameter, or the selection of a finite set of instruments. Thus, the estimator is extremely simple to implement. Monte Carlo evidence supports the theoretical claims and suggests that the IIV estimator is a robust complement to optimal instrumental variables in finite samples. In an application with quarterly UK data, the IIV estimator estimates a positive and significant elasticity of intertemporal substitution and an equally sensible estimate for its reciprocal, in sharp contrast to instrumental variables methods that fail to identify these parameters.


  • Economics


  • uniform identification; instrumental variables; weak instruments; uniform inference; intertemporal elasticity of substitution