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Seasonal Adjustment By A Bayesian Modeling

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  • Hirotugu Akaike

Abstract

. The basic ideas underlying the construction of a newly introduced seasonal adjustment procedure by a Bayesian modeling are discussed in detail. Particular emphasis is placed on the use of the concept of the likelihood of a Bayesian model for model selection. The performance of the procedure is illustrated by a numerical example.

Suggested Citation

  • Hirotugu Akaike, 1980. "Seasonal Adjustment By A Bayesian Modeling," Journal of Time Series Analysis, Wiley Blackwell, vol. 1(1), pages 1-13, January.
    • Handle: RePEc:bla:jtsera:v:1:y:1980:i:1:p:1-13
    DOI: 10.1111/j.1467-9892.1980.tb00296.x
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    Cited by:

    1. Sergey Seleznev & Natalia Turdyeva & Ramis Khabibullin & Anna Tsvetkova, 2020. "Seasonal adjustment of the Bank of Russia Payment System financial flows data," Bank of Russia Working Paper Series wps65, Bank of Russia.
    2. Hall, Viv B & Thomson, Peter, 2022. "A boosted HP filter for business cycle analysis: evidence from New Zealand’s small open economy," Working Paper Series 9473, Victoria University of Wellington, School of Economics and Finance.
    3. Viv B Hall & Peter Thomson, 2020. "Does Hamilton’s OLS regression provide a “better alternative†to the Hodrick-Prescott filter? A New Zealand business cycle perspective," CAMA Working Papers 2020-71, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    4. Viv B. Hall & Peter Thomson, 2021. "Does Hamilton’s OLS Regression Provide a “better alternative” to the Hodrick-Prescott Filter? A New Zealand Business Cycle Perspective," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(2), pages 151-183, November.
    5. Rolando Gonzales Martínez, 2012. "Baysian seasonal analysis with robust priors," Investigación & Desarrollo, Universidad Privada Boliviana, vol. 1(1), pages 88-93.
    6. Seisho Sato & Naoto Kunitomo, 2021. "Backward Smoothing for Noisy Non-stationary Time Series," CARF F-Series CARF-F-517, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    7. Schlicht, Ekkehart, 1982. "Seasonal Adjustment in a Stochastic Model," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 38058, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    8. Schlicht, Ekkehart, 1984. "Zerlegung ökonomischer Zeitreihen: Ein deterministischer und stochastischer Ansatz," Munich Reprints in Economics 3344, University of Munich, Department of Economics.
    9. Schlicht, Ekkehart & Pauly, Ralf, 1982. "Descriptive Seasonal Adjustment by Minimizing Perturbations," Darmstadt Discussion Papers in Economics 16, Darmstadt University of Technology, Department of Law and Economics.
    10. Fackler, Paul L., 1989. "Modeling Trend and Higher Moment Properties of U.S. Corn Yields," 1989 Quantifying Long Run Agricultural Risks and Evaluating Farmer Responses to Risk Meeting, April 9-12, 1989, Sanibel Island, Florida 271523, Regional Research Projects > S-232: Quantifying Long Run Agricultural Risks and Evaluating Farmer Responses to Risk.
    11. Naoto Kunitomo & Seisho Sato, 2015. "Trend, Seasonality and Economic Time Series:the Nonstationary Errors-in-variables Models," CIRJE F-Series CIRJE-F-977, CIRJE, Faculty of Economics, University of Tokyo.
    12. Simone di Paolo & Danilo Liberati, 2024. "Seasonal adjustment of credit time series in the Bank of Italy," Questioni di Economia e Finanza (Occasional Papers) 835, Bank of Italy, Economic Research and International Relations Area.
    13. Ollech, Daniel, 2018. "Seasonal adjustment of daily time series," Discussion Papers 41/2018, Deutsche Bundesbank.
    14. Viv B. Hall & Peter Thomson, 2022. "A boosted HP filter for business cycle analysis:evidence from New Zealand's small open economy," CAMA Working Papers 2022-45, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    15. Nicolai Meinshausen & Peter Bühlmann, 2010. "Stability selection," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(4), pages 417-473, September.
    16. Mise, Emi & Kim, Tae-Hwan & Newbold, Paul, 2005. "On suboptimality of the Hodrick-Prescott filter at time series endpoints," Journal of Macroeconomics, Elsevier, vol. 27(1), pages 53-67, March.
    17. Tucker McElroy & Anindya Roy, 2022. "A Review of Seasonal Adjustment Diagnostics," International Statistical Review, International Statistical Institute, vol. 90(2), pages 259-284, August.
    18. Kato, Hiroko & Naniwa, Sadao & Ishiguro, Makio, 1996. "A bayesian multivariate nonstationary time series model for estimating mutual relationships among variables," Journal of Econometrics, Elsevier, vol. 75(1), pages 147-161, November.
    19. Marcos Bujosa & Antonio García Ferrer & Peter Young, 2002. "An ARMA Representation of Unobserved Component Models under Generalized Random Walk Specifications: New Algorithms and Examples," Documentos de Trabajo del ICAE 0204, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    20. Daniel Tzabbar & Jeongsik (Jay) Lee & Donghwi (Josh) Seo, 2022. "Collaborative structure and post‐mobility knowledge spillovers: A dyadic approach," Strategic Management Journal, Wiley Blackwell, vol. 43(9), pages 1728-1762, September.

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