HKUST Library Institutional Repository Banner

HKUST Institutional Repository >
Economics >
ECON Journal/Magazine Articles >

Please use this identifier to cite or link to this item: http://hdl.handle.net/1783.1/2917
Title: Simulation estimation of dynamic switching regression and dynamic disequilibrium models : some Monte Carlo results
Authors: Lee, Lung-Fei
Keywords: Simulated likelihood
Regime classification
Dynamic switching model
Markov switching model
Disequilibrium model
Issue Date: 1997
Citation: Journal of econometrics, v. 78, 1997, p. 179-204
Abstract: This article considers the estimation of dynamic exogenous switching regression models and dynamic endogenous switching models. With autocorrelation in disturbances or latent lagged dependent variables, likelihood functions of such models involve high dimensional integrals and a huge number of summations over unobserved regime paths. Simulated likelihood methods and simulated methods of moments are available. These approaches simulate both continuous and discrete latent dependent variables. By Monte Carlo experiments, it is found that the performances of various approaches depend crucially on how discrete state variables are simulated. The valuable approach is to simulate regime paths with regime probabilities based on the current and past sample information.
Rights: '[Journal of econometrics] © copyright (1997) Elsevier. The Journal's web site is located at http://www.sciencedirect.com/'
URI: http://hdl.handle.net/1783.1/2917
Appears in Collections:ECON Journal/Magazine Articles

Files in This Item:

File Description SizeFormat
Simul.pdfpre-published version2238KbAdobe PDFView/Open

Find published version via OpenURL Link Resolver

All items in this Repository are protected by copyright, with all rights reserved.