Sequential Monte Carlo Methods for Estimating Dynamic Microeconomic Models. (16th June 2015)

• Record Type: Journal Article
• Authors: Blevins, Jason R.
• Is Part Of: Journal of applied econometrics. Volume 31:Number 5(2016)
• Page Start: 773
• Page End: 804
• Publication Date: 2015-06-16
• Subjects: Econometrics -- Periodicals; 330.015195
• DOI: 10.1002/jae.2470
• Languages: English
• ISSNs: 0883-7252

Abstract

Summary: This paper develops estimators for dynamic microeconomic models with serially correlated unobserved state variables using sequential Monte Carlo methods to estimate the parameters and the distribution of the unobservables. If persistent unobservables are ignored, the estimates can be subject to a dynamic form of sample selection bias. We focus on single‐agent dynamic discrete‐choice models and dynamic games of incomplete information. We propose a full‐solution maximum likelihood procedure and a two‐step method and use them to estimate an extended version of the capital replacement model of Rust with the original data and in a Monte Carlo study. Copyright © 2015 John Wiley & Sons, Ltd.