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Estimating VAR's sampled at mixed or irregular spaced frequencies : a Bayesian approach

  • Ching Wai (Jeremy) Chiu
  • Bjørn Eraker
  • Andrew T. Foerster
  • Tae Bong Kim
  • Hernán D. Seoane

Economic data are collected at various frequencies but econometric estimation typically uses the coarsest frequency. This paper develops a Gibbs sampler for estimating VAR models with mixed and irregularly sampled data. The approach allows efficient likelihood inference even with irregular and mixed frequency data. The Gibbs sampler uses simple conjugate posteriors even in high dimensional parameter spaces, avoiding a non-Gaussian likelihood surface even when the Kalman filter applies. Two applications illustrate the methodology and demonstrate efficiency gains from the mixed frequency estimator: one constructs quarterly GDP estimates from monthly data, the second uses weekly financial data to inform monthly output.

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Paper provided by Federal Reserve Bank of Kansas City in its series Research Working Paper with number RWP 11-11.

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Date of creation: 2011
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Handle: RePEc:fip:fedkrw:rwp11-11
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