Convergence Properties of the Likelihood of Computed Dynamic Models
Abstract
This paper studies the econometrics of computed dynamic models. Since these models generally lack a closed-form solution, their policy functions are approximated by numerical methods. Hence, the researcher can only evaluate an approximated likelihood associated with the approximated policy function rather than the exact likelihood implied by the exact policy function. What are the consequences for inference of the use of approximated likelihoods? First, we find conditions under which, as the approximated policy function converges to the exact policy, the approximated likelihood also converges to the exact likelihood. Second, we show that second order approximation errors in the policy function, which almost always are ignored by researchers, have first order effects on the likelihood function. Third, we discuss convergence of Bayesian and classical estimates. Finally, we propose to use a likelihood ratio test as a diagnostic device for problems derived from the use of approximated likelihoods. Copyright The Econometric Society 2006.Download Info
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Article provided by Econometric Society in its journal Econometrica.
Volume (Year): 74 (2006)
Issue (Month): 1 (01)
Pages: 93-119
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- Jesús Fernández-Villaverde & Juan F. Rubio-Ramirez & Manuel Santos, 2005. "Convergence Properties of the Likelihood of Computed Dynamic Models," Levine's Bibliography 122247000000000822, UCLA Department of Economics.
- Jesus Fernandez-Villaverde & Juan Rubio & Manuel Santos, 2005. "Convergence Properties of the Likelihood of Computed Dynamic Models," NBER Technical Working Papers 0315, National Bureau of Economic Research, Inc.
- Jesús Fernández-Villaverde & Juan Francisco Rubio-Ramírez & Manuel Santos, 2004. "Convergence properties of the likelihood of computed dynamic models," Working Paper 2004-27, Federal Reserve Bank of Atlanta.
- Jesus Fernandez-Villaverde & Juan F. Rubio-Ramirez & Manuel Santos, 2004. "Convergence Properties of the Likelihood of Computed Dynamic Models," PIER Working Paper Archive 04-034, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
- C5 - Mathematical and Quantitative Methods - - Econometric Modeling
- E1 - Macroeconomics and Monetary Economics - - General Aggregative Models
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