Event Details

Accounting and Finance, Finance seminar to be presented by Eric Renault, University of Warwick. Paper title: Coordinated Testing for Identification Failure and Correct Model Specification.

Eric Renault (warwick.ac.uk)

Abstract

In the context of GMM or Minimum Distance (MD) inference, we develop a specifica-

tion test that is: (i) robust to weak identification; (ii) easy to implement and broadly

applicable; and (iii) powerful. We first show that it is still possible to rely on the

J-test of overidentification, but only after adjusting its critical values and only when

considering its continuously-updated form. Second, to address the lack of power of

such a specification test, we resort to a conditional inference approach, where we

use information about the existence of a number of strongly identified directions in

the parameter space to define data-dependent critical values. The implementation of

our suggested coordinated testing approach is based on developing a powerful test of

weak identification that is compatible with mixed identification strengths - that is,

subvector and/or directions in the parameters space that display different strength of

identification (e.g. weak and non-weak).

We illustrate the performance of our different testing strategies through three

applications: Discrete Choice models with simultaneity and the New Keynesian Philips

curve (in a GMM framework), as well as Asset Pricing models with stochastic volatility

and leverage (in a MD framework).

Keywords: GMM; weak IV; misspecification; subvector.

JEL codes: C32; C12; C13; C51.