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Reply to Discussion of “Bayesian forecasting of multivariate time series: scalability, structure uncertainty and decisions”

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  • Mike West

    (Duke University)

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  • Mike West, 2020. "Reply to Discussion of “Bayesian forecasting of multivariate time series: scalability, structure uncertainty and decisions”," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(1), pages 41-44, February.
    • Handle: RePEc:spr:aistmt:v:72:y:2020:i:1:d:10.1007_s10463-019-00744-0
    DOI: 10.1007/s10463-019-00744-0
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    References listed on IDEAS

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    1. Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2021. "Economic Predictions With Big Data: The Illusion of Sparsity," Econometrica, Econometric Society, vol. 89(5), pages 2409-2437, September.
    2. Bitto, Angela & Frühwirth-Schnatter, Sylvia, 2019. "Achieving shrinkage in a time-varying parameter model framework," Journal of Econometrics, Elsevier, vol. 210(1), pages 75-97.
    3. Christopher A. Sims, 2012. "Statistical Modeling of Monetary Policy and Its Effects," American Economic Review, American Economic Association, vol. 102(4), pages 1187-1205, June.
    4. Kimura Takeshi & Nakajima Jouchi, 2016. "Identifying conventional and unconventional monetary policy shocks: a latent threshold approach," The B.E. Journal of Macroeconomics, De Gruyter, vol. 16(1), pages 277-300, January.
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    Cited by:

    1. Nelson Kyakutwika & Bruce Bartlett, 2023. "Bayesian Forecasting of Stock Returns on the JSE using Simultaneous Graphical Dynamic Linear Models," Papers 2307.08665, arXiv.org.
    2. Fokianos, Konstantinos & Fried, Roland & Kharin, Yuriy & Voloshko, Valeriy, 2022. "Statistical analysis of multivariate discrete-valued time series," Journal of Multivariate Analysis, Elsevier, vol. 188(C).
    3. Adebanji, Atinuke & Rios Insua, David & Ruggeri, Fabrizio, 2022. "Dynamic linear models for policy monitoring. The case of maternal and neonatal mortality in Ghana," Socio-Economic Planning Sciences, Elsevier, vol. 83(C).
    4. Fokianos, Konstantinos, 2024. "Multivariate Count Time Series Modelling," Econometrics and Statistics, Elsevier, vol. 31(C), pages 100-116.
    5. Bruno P. C. Levy & Hedibert F. Lopes, 2021. "Dynamic Ordering Learning in Multivariate Forecasting," Papers 2101.04164, arXiv.org, revised Nov 2021.
    6. Luis Gruber & Gregor Kastner, 2022. "Forecasting macroeconomic data with Bayesian VARs: Sparse or dense? It depends!," Papers 2206.04902, arXiv.org, revised Nov 2024.

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