Limited Information Bayesian Model Averaging for Dynamic Panels with An Application to a Trade Gravity Model /

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 res...

पूर्ण विवरण

ग्रंथसूची विवरण
मुख्य लेखक: Chen, Huigang
अन्य लेखक: Mirestean, Alin, Tsangarides, Charalambos
स्वरूप: पत्रिका
भाषा:English
प्रकाशित: Washington, D.C. : International Monetary Fund, 2011.
श्रृंखला:IMF Working Papers; Working Paper ; No. 2011/230
विषय:
WP
ऑनलाइन पहुंच:Full text available on IMF
विवरण
सारांश: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.
वस्तु वर्णन:<strong>Off-Campus Access:</strong> No User ID or Password Required
<strong>On-Campus Access:</strong> No User ID or Password Required
भौतिक वर्णन:1 online resource (45 pages)
स्वरूप:Mode of access: Internet
आईएसएसएन:1018-5941
अभिगमन:Electronic access restricted to authorized BRAC University faculty, staff and students