Nonlinear Panel Data Methods for Dynamic Heterogeneous Agent Models

• Manuel Arellano ^[2] ; Stéphane Bonhomme ^[1]
  1. [1] University of Chicago

     University of Chicago

     City of Chicago, Estados Unidos

     
  2. [2] CEMFI
• Localización: Documentos de Trabajo ( CEMFI ), Nº. 3 (CEMFI Working Paper No. 1703, January 2017), 2017
• Idioma: inglés
• Enlaces
  • Texto completo (pdf)
• Resumen

  • Recent developments in nonlinear panel data analysis allow identifying and estimating general dynamic systems. In this review we describe some results and techniques for nonparametric identification and flexible estimation in the presence of time-invariant and time-varying latent variables. This opens the possibility to estimate 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 facilitate the implementation of structural models.