02118cas a2200277 a 4500 AALejournalIMF011317 230101c9999 xx r poo 0 0eng d 5.00 USD 9781463921309 1018-5941 BD-DhAAL BD-DhAAL Chen, Huigang. Limited Information Bayesian Model Averaging for Dynamic Panels with An Application to a Trade Gravity Model / Huigang Chen, Alin Mirestean, Charalambos Tsangarides. Washington, D.C. : International Monetary Fund, 2011. 1 online resource (45 pages) IMF Working Papers <strong>Off-Campus Access:</strong> No User ID or Password Required <strong>On-Campus Access:</strong> No User ID or Password Required Electronic access restricted to authorized BRAC University faculty, staff and students 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 values. These findings suggest that our methodology is well suited for inference in short dynamic panel data models with endogenous regressors in the context of model uncertainty. We illustrate the use of LIBMA in an application to the estimation of a dynamic gravity model for bilateral trade. Mode of access: Internet WP imf Mirestean, Alin. Tsangarides, Charalambos. IMF Working Papers; Working Paper ; No. 2011/230 Full text available on IMF http://elibrary.imf.org/view/journals/001/2011/230/001.2011.issue-230-en.xml IMF e-Library