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A Methodological Note On The Disaggregation Of Time Series Totals

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  • Daniel O. Stram
  • William W. S. Wei

Abstract

. This paper sheds new light on a generalized least squares approach for disaggregating a series of time series totals to estimate an underlying unaggregated series. By reinterpreting the generalized least squares problem as a time series prediction problem we can produce considerable computational savings relative to standard least squares approaches. Our reinterpretation gives us insight into the nature of the matrices which need to be inverted to compute the disaggregates.

Suggested Citation

  • Daniel O. Stram & William W. S. Wei, 1986. "A Methodological Note On The Disaggregation Of Time Series Totals," Journal of Time Series Analysis, Wiley Blackwell, vol. 7(4), pages 293-302, July.
    • Handle: RePEc:bla:jtsera:v:7:y:1986:i:4:p:293-302
    DOI: 10.1111/j.1467-9892.1986.tb00496.x
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    Cited by:

    1. Kahouli, Sondès, 2011. "Re-examining uranium supply and demand: New insights," Energy Policy, Elsevier, vol. 39(1), pages 358-376, January.
    2. Tommaso Proietti & Alessandro Giovannelli, 2021. "Nowcasting monthly GDP with big data: A model averaging approach," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(2), pages 683-706, April.
    3. Feijoo, Santiago Rodriguez & Caro, Alejandro Rodriguez & Quintana, Delia Davila, 2003. "Methods for quarterly disaggregation without indicators; a comparative study using simulation," Computational Statistics & Data Analysis, Elsevier, vol. 43(1), pages 63-78, May.
    4. Angelini, Elena & Henry, Jerome & Marcellino, Massimiliano, 2006. "Interpolation and backdating with a large information set," Journal of Economic Dynamics and Control, Elsevier, vol. 30(12), pages 2693-2724, December.
    5. Bańbura, Marta & Bobeica, Elena, 2023. "Does the Phillips curve help to forecast euro area inflation?," International Journal of Forecasting, Elsevier, vol. 39(1), pages 364-390.
    6. Alejandro Rodríguez Caro & Santiago Rodríguez Feijoo & Delia Dávila Quintana, 2003. "La trimestralización de variables flujo. Un estudio de simulación de los métodos de desagregación temporal con indicador," Documentos de trabajo conjunto ULL-ULPGC 2003-01, Facultad de Ciencias Económicas de la ULPGC.
    7. Huang, Yu-Lieh, 2012. "Measuring business cycles: A temporal disaggregation model with regime switching," Economic Modelling, Elsevier, vol. 29(2), pages 283-290.
    8. Jérôme TRINH, 2019. "Disaggregating the Chinese annual national accounts to quarterly series," THEMA Working Papers 2019-08, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    9. Chiara Perricone, 2018. "Wavelet analysis for temporal disaggregation," CEIS Research Paper 444, Tor Vergata University, CEIS, revised 29 Oct 2018.
    10. Enrique M. Quilis, 2018. "Temporal disaggregation of economic time series: The view from the trenches," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 72(4), pages 447-470, November.
    11. Xinshuai Dong & Haoyue Dai & Yewen Fan & Songyao Jin & Sathyamoorthy Rajendran & Kun Zhang, 2023. "On the Three Demons in Causality in Finance: Time Resolution, Nonstationarity, and Latent Factors," Papers 2401.05414, arXiv.org, revised Jan 2024.
    12. Mateusz Pipień & Sylwia Roszkowska, 2015. "Szacunki kwartalnego PKB w polskich województwach," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 5, pages 145-169.
    13. Vladim r Hajko, 2015. "Energy-Gross Domestic Product Nexus: Disaggregated Analysis for the Czech Republic in the Post-Transformation Era," International Journal of Energy Economics and Policy, Econjournals, vol. 5(3), pages 869-888.
    14. Mateusz Pipień & Sylwia Roszkowska, 2015. "Quarterly estimates of regional GDP in Poland – application of statistical inference of functions of parameters," NBP Working Papers 219, Narodowy Bank Polski.
    15. Jérôme TRINH, 2019. "Temporal disaggregation of short time series with structural breaks: Estimating quarterly data from yearly emerging economies data," Working Papers 2019-11, Center for Research in Economics and Statistics.
    16. Guerrero, Víctor M. & Peña, Daniel, 1995. "Linear combination of information in time series analysis," DES - Working Papers. Statistics and Econometrics. WS 10340, Universidad Carlos III de Madrid. Departamento de Estadística.
    17. Bu Hyoung Lee, 2022. "Bootstrap Prediction Intervals of Temporal Disaggregation," Stats, MDPI, vol. 5(1), pages 1-13, February.

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