Paper #1640

Title:

Confidence intervals for bias and size distortion in IV and local projections–IV models

Authors:

Gergely Ganics, Atsushi Inoue and Barbara Rossi

Date:

September 2018

Abstract:

In this paper we propose methods to construct confidence intervals for the bias of the two-stage least squares estimator, and the size distortion of the associated Wald test in instrumental variable models. Importantly our framework covers the local projections – instrumental variable model as well. Unlike tests for weak instruments, whose distributions are non-standard and depend on nuisance parameters that cannot be estimated consistently, the confidence intervals for the strength of identification are straightforward and computationally easy to calculate, as they are obtained from inverting a chi-squared distribution. Furthermore, they provide more information to researchers on instrument strength than the binary decision offered by tests. Monte Carlo simulations show that the confidence intervals have good small sample coverage. We illustrate the usefulness of the proposed methods to measure the strength of identification in two empirical situations: the estimation of the intertemporal elasticity of substitution in a linearized Euler equation, and government spending multipliers.

Keywords:

Instrumental variables, weak instruments, weak identification, concentration parameter, local projections.

JEL codes:

C22, C52, C53

Area of Research:

Macroeconomics and International Economics / Statistics, Econometrics and Quantitative Methods

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