Econometric analysis of linearized singular dynamic stochastic general equilibrium models

• Published in: Journal of econometrics Vol. 136; no. 2; pp. 595 - 627
• Main Author: Bierens, Herman J.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.02.2007; Elsevier; Elsevier Sequoia S.A
• Series: Journal of Econometrics
• Subjects: Calibration; Dynamic general equilibrium; Dynamics; Econometrics; Equilibrium models; Estimation; Growth models; Linear models; Singularity; Stochastic models; Studies; Variables; C52; Singularity; C32; C13; Estimation; D90; Dynamic general equilibrium; Calibration
• ISSN: 0304-4076; 1872-6895
• DOI: 10.1016/j.jeconom.2005.11.008

In this paper I propose an alternative to calibration of linearized singular dynamic stochastic general equilibrium models. Given an a-theoretical econometric model as a representative of the data generating process, I will construct an information measure which compares the conditional distribution of the econometric model variables with the corresponding singular conditional distribution of the theoretical model variables. The singularity problem will be solved by using convolutions of both distributions with a non-singular distribution. This information measure will then be maximized to the deep parameters of the theoretical model, which links these parameters to the parameters of the econometric model and provides an alternative to calibration. This approach will be illustrated by an application to a linearized version of the stochastic growth model of King, Plosser and Rebelo.