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

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  • Huigang Chen
  • Alin T Mirestean
  • Charalambos G Tsangarides

Abstract

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.

Suggested Citation

  • Huigang Chen & Alin T Mirestean & Charalambos G Tsangarides, 2011. "Limited Information Bayesian Model Averaging for Dynamic Panels with An Application to a Trade Gravity Model," IMF Working Papers 11/230, International Monetary Fund.
  • Handle: RePEc:imf:imfwpa:11/230
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    Cited by:

    1. Leon-Gonzalez, Roberto & Vinayagathasan, Thanabalasingam, 2015. "Robust determinants of growth in Asian developing economies: A Bayesian panel data model averaging approach," Journal of Asian Economics, Elsevier, vol. 36(C), pages 34-46.
    2. Campbell, Douglas L., 2011. "Estimating the impact of currency unions on trade using a dynamic gravity framework," MPRA Paper 35531, University Library of Munich, Germany.
    3. Jaroslav Bukovina, 2017. "The attention of a society towards corporate brand name and its determinants within the information-rich economy," MENDELU Working Papers in Business and Economics 2017-71, Mendel University in Brno, Faculty of Business and Economics.
    4. León-González, Roberto & Montolio, Daniel, 2015. "Endogeneity and panel data in growth regressions: A Bayesian model averaging approach," Journal of Macroeconomics, Elsevier, vol. 46(C), pages 23-39.

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