Nonlinear Panel Data Methods for Dynamic Heterogeneous Agent Models

Posted: 14 Aug 2017

Date Written: August 2017

Abstract

Recent developments in nonlinear panel data analysis allow the identification and estimation of general dynamic systems. We review some results and techniques for nonparametric identification and flexible estimation in the presence of time-invariant and time-varying latent variables. This opens up the possibility of estimating nonlinear reduced forms in a large class of structural dynamic models with heterogeneous agents. We show how such reduced forms may be used to document policy-relevant derivative effects and to improve the understanding and implementation of structural models.

Suggested Citation

Arellano, Manuel and Bonhomme, Stéphane, Nonlinear Panel Data Methods for Dynamic Heterogeneous Agent Models (August 2017). Annual Review of Economics, Vol. 9, pp. 471-496, 2017. Available at SSRN: https://ssrn.com/abstract=3017738 or http://dx.doi.org/10.1146/annurev-economics-063016-104346

Manuel Arellano (Contact Author)

CEMFI ( email )

Casado del Alisal 5
28014 Madrid
Spain
+34 91 429 0551 (Phone)
+34 91 429 1056 (Fax)

Stéphane Bonhomme

University of Chicago

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