Dynamic Identification of Dynamic Stochastic General Equilibrium Models

• 成果类型: Article
• 署名作者: Komunjer, Ivana; Ng, Serena
• 署名单位: University of California System; University of California San Diego; Columbia University
• 刊物名称: ECONOMETRICA
• ISSN/ISSBN: 0012-9682
• DOI: 10.3982/ECTA8916
• 发表日期: 2011
• 页码: 1995-2032
• 关键词: vector autoregressions; form; REPRESENTATIONS; systems

摘要

This paper studies dynamic identification of parameters of a dynamic stochastic general equilibrium model from the first and second moments of the data. Classical results for dynamic simultaneous equations do not apply because the state space solution of the model does not constitute a standard reduced form. Full rank of the Jacobian matrix of derivatives of the solution parameters with respect to the parameters of interest is necessary but not sufficient for identification. We use restrictions implied by observational equivalence to obtain two sets of rank and order conditions: one for stochastically singular models and another for nonsingular models. Measurement errors, mean, long-run, and a priori restrictions can be accommodated. An example is considered to illustrate the results.