Focused information criterion for locally misspecified vector autoregressive models

3Citations
Citations of this article
7Readers
Mendeley users who have this article in their library.

Abstract

This paper investigates the focused information criterion and plug-in average for vector autoregressive models with local-to-zero misspecification. These methods have the advantage of focusing on a quantity of interest rather than aiming at overall model fit. Any (sufficiently regular) function of the parameters can be used as a quantity of interest. We determine the asymptotic properties and elaborate on the role of the locally misspecified parameters. In particular, we show that the inability to consistently estimate locally misspecified parameters translates into suboptimal selection and averaging. We apply this framework to impulse response analysis. A Monte Carlo simulation study supports our claims.

Cite

CITATION STYLE

APA

Lohmeyer, J., Palm, F., Reuvers, H., & Urbain, J. P. (2019). Focused information criterion for locally misspecified vector autoregressive models. Econometric Reviews, 38(7), 763–792. https://doi.org/10.1080/07474938.2017.1409410

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free