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Vector Autoregression with Mixed Frequency Data

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  • Qian, Hang

Abstract

Three new approaches are proposed to handle mixed frequency Vector Autoregression. The first is an explicit solution to the likelihood and posterior distribution. The second is a parsimonious, time-invariant and invertible state space form. The third is a parallel Gibbs sampler without forward filtering and backward sampling. The three methods are unified since all of them explore the fact that the mixed frequency observations impose linear constraints on the distribution of high frequency latent variables. By a simulation study, different approaches are compared and the parallel Gibbs sampler outperforms others. A financial application on the yield curve forecast is conducted using mixed frequency macro-finance data.

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  • Qian, Hang, 2013. "Vector Autoregression with Mixed Frequency Data," MPRA Paper 47856, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:47856
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    File URL: https://mpra.ub.uni-muenchen.de/47856/1/MPRA_paper_47856.pdf
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    References listed on IDEAS

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    Cited by:

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    3. Kristina Bluwstein & Fabio Canova, 2016. "Beggar-Thy-Neighbor? The International Effects of ECB Unconventional Monetary Policy Measures," International Journal of Central Banking, International Journal of Central Banking, vol. 12(3), pages 69-120, September.
    4. Dilara Berksun & Nukhet Dogan & M. Hakan Berument, 2021. "Electricity Consumption and Economic Growth in Turkey: A Mixed Frequency Var Approach," Energy Economics Letters, Asian Economic and Social Society, vol. 8(1), pages 95-108, June.
    5. Yasutomo Murasawa, 2016. "The Beveridge–Nelson decomposition of mixed-frequency series," Empirical Economics, Springer, vol. 51(4), pages 1415-1441, December.
    6. Chaudhuri, Malika & Calantone, Roger J. & Voorhees, Clay M. & Cockrell, Seth, 2018. "Disentangling the effects of promotion mix on new product sales: An examination of disaggregated drivers and the moderating effect of product class," Journal of Business Research, Elsevier, vol. 90(C), pages 286-294.
    7. Maas, Daniel & Mayer, Eric & Rüth, Sebastian K., 2018. "Current account dynamics and the housing cycle in Spain," Journal of International Money and Finance, Elsevier, vol. 87(C), pages 22-43.
    8. Maas, Daniel & Mayer, Eric & Rüth, Sebastian, 2015. "Current account dynamics and the housing boom and bust cycle in Spain," W.E.P. - Würzburg Economic Papers 94, University of Würzburg, Department of Economics.

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    More about this item

    Keywords

    VAR; Temporal aggregation; State space; Parallel Gibbs sampler;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: 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
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access

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