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The Impact on Forecasts and Impulse Responses of Restricting Drift in a Vector Autoregression

Author

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  • John Landon-Lane

    (Rutgers University)

Abstract

Inference on the long-run properties of a Vector Autoregression (VAR) consisting wholly of I(1) variables are made using Bayesian methods. In particular, the implications on the forecast and impulse response function distributions of directly estimating and restricting the drift parameters of variables in a VAR are studied. It is found that the forecast and impulse response distributions are sensitive to the prior distribution placed over the drift parameters.

Suggested Citation

  • John Landon-Lane, 2001. "The Impact on Forecasts and Impulse Responses of Restricting Drift in a Vector Autoregression," Departmental Working Papers 200114, Rutgers University, Department of Economics.
    • Handle: RePEc:rut:rutres:200114
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    File URL: http://www.sas.rutgers.edu/virtual/snde/wp/2001-14.pdf
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    More about this item

    Keywords

    Forecasts; Impulse Response Function; Markov chain Monte Carlo; Vector Autoregression;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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