Limited Information Bayesian Model Averaging for Dynamic Panels with an Application to a Trade Gravity Model.

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Bibliographic Details
Author / Creator:Chen, Huigang.
Imprint:Washington : International Monetary Fund, 2011.
Description:1 online resource (62 pages)
Language:English
Series:IMF Working Papers
IMF Working Papers.
Subject:
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/12502393
Hidden Bibliographic Details
Other authors / contributors:Mirestean, Alin.
Tsangarides, Charalambos G.
ISBN:9781463990121
146399012X
1463921896
9781463921897
1463967160
9781463967161
Notes:Includes bibliographical references.
English.
Print version record.
Summary:This paper extends the Bayesian Model Averaging framework to panel data models where the lagged dependent variable as well as endogenous variables appear as regressors. We propose a Limited Information Bayesian Model Averaging (LIBMA) methodology and then test it using simulated data. Simulation results suggest that asymptotically our methodology performs well both in Bayesian model averaging and selection. In particular, LIBMA recovers the data generating process well, with high posterior inclusion probabilities for all the relevant regressors, and parameter estimates very close to their true.
Other form:Print version: Chen, Huigang. Limited Information Bayesian Model Averaging for Dynamic Panels with an Application to a Trade Gravity Model. Washington : International Monetary Fund, ©2011 9781463921309