{
  "title": "Limited Information Bayesian Model Averaging for Dynamic Panels with An Application to a Trade Gravity Model",
  "publication": "IMF Working Papers, October 1, 2011",
  "sourceUrl": "https://www.imf.org/en/publications/wp/issues/2016/12/31/limited-information-bayesian-model-averaging-for-dynamic-panels-with-an-application-to-a-25270",
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  "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.",
  "sections": [
    {
      "heading": "Overview and contribution",
      "content": "- Extends the Bayesian Model Averaging framework to panel data models where the lagged dependent variable as well as endogenous variables appear as regressors.\n- Proposes a Limited Information Bayesian Model Averaging (LIBMA) methodology.\n- Illustrates LIBMA with an application to the estimation of a dynamic gravity model for bilateral trade."
    },
    {
      "heading": "Methodology",
      "content": "- Limited Information Bayesian Model Averaging (LIBMA) designed for short dynamic panel data models with endogenous regressors and model uncertainty.\n- Tests LIBMA using simulated data."
    },
    {
      "heading": "Key findings from simulations",
      "content": "- Simulation results suggest that asymptotically the methodology performs well both in Bayesian model averaging and selection.\n- LIBMA recovers the data generating process well.\n- LIBMA yields high posterior inclusion probabilities for all the relevant regressors.\n- Parameter estimates from LIBMA are very close to their true values.\n- Findings indicate LIBMA is well suited for inference in short dynamic panel data models with endogenous regressors in the context of model uncertainty."
    },
    {
      "heading": "Application",
      "content": "- Application to a dynamic gravity model for bilateral trade is used to illustrate the methodology (details of the application are presented in the paper)."
    },
    {
      "heading": "Publication and metadata",
      "content": "- Authors: Huigang Chen, Alin T Mirestean, Charalambos G Tsangarides\n- Date: October 1, 2011\n- Series: Working Paper No. 2011/230\n- Issue: 230\n- Volume: 2011\n- Pages: 45\n- DOI: https://doi.org/10.5089/9781463921309.001\n- Stock No: WPIEA2011230\n- ISBN: 9781463921309\n- ISSN: 1018-5941\n- Subject: Bayesian models, Estimation techniques, Exchange rate arrangements, Gravity models\n- Keywords: WP\n\nIMF Working Papers — Limited Information Bayesian Model Averaging for Dynamic Panels with An Application to a Trade Gravity Model (Huigang Chen, Alin T Mirestean, Charalambos G Tsangarides), October 1, 2011.\n\n---\n\n Content in this bundle\n\n- wp11230\n  - wp11230 (Markdown version){rel=\"alternate\" type=\"text/markdown\"}\n  - wp11230 (PDF){rel=\"external\" type=\"application/pdf\"}\n\n---\n\nSource: https://www.imf.org/en/publications/wp/issues/2016/12/31/limited-information-bayesian-model-averaging-for-dynamic-panels-with-an-application-to-a-25270"
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    "Authors: Huigang Chen, Alin T Mirestean, Charalambos G Tsangarides",
    "Published: October 1, 2011",
    "Series: IMF Working Papers",
    "DOI: https://doi.org/10.5089/9781463921309.001",
    "Extends the Bayesian Model Averaging framework to panel data models where the lagged dependent variable as well as endogenous variables appear as regressors.",
    "Proposes a Limited Information Bayesian Model Averaging (LIBMA) methodology.",
    "Illustrates LIBMA with an application to the estimation of a dynamic gravity model for bilateral trade.",
    "Limited Information Bayesian Model Averaging (LIBMA) designed for short dynamic panel data models with endogenous regressors and model uncertainty.",
    "Tests LIBMA using simulated data.",
    "Simulation results suggest that asymptotically the methodology performs well both in Bayesian model averaging and selection.",
    "LIBMA recovers the data generating process well.",
    "LIBMA yields high posterior inclusion probabilities for all the relevant regressors.",
    "Parameter estimates from LIBMA are very close to their true values.",
    "Findings indicate LIBMA is well suited for inference in short dynamic panel data models with endogenous regressors in the context of model uncertainty.",
    "Application to a dynamic gravity model for bilateral trade is used to illustrate the methodology (details of the application are presented in the paper).",
    "Authors: Huigang Chen, Alin T Mirestean, Charalambos G Tsangarides",
    "Date: October 1, 2011",
    "Series: Working Paper No. 2011/230",
    "Issue: 230",
    "Volume: 2011",
    "Pages: 45",
    "DOI: https://doi.org/10.5089/9781463921309.001",
    "Stock No: WPIEA2011230",
    "ISBN: 9781463921309",
    "ISSN: 1018-5941",
    "Subject: Bayesian models, Estimation techniques, Exchange rate arrangements, Gravity models",
    "Keywords: WP",
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