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

Ching-Wai (Jeremy) Chiu, Bjorn Eraker, Andrew Foerster, Tae Bong Kim and Hernan D. Seoane

No RWP 11-11, Research Working Paper from Federal Reserve Bank of Kansas City

Abstract: 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.

Date: 2011
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-mst
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (31)

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Journal Article: Bayesian Mixed Frequency VARs (2015) Downloads
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