Estimating VAR's sampled at mixed or irregular spaced frequencies : a Bayesian approach
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.
File(s): File format is application/pdf http://www.kansascityfed.org/publicat/reswkpap/pdf/rwp11-11.pdf
Provider: Federal Reserve Bank of Kansas City
Part of Series: Research Working Paper
Publication Date: 2011
Number: RWP 11-11