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Reconciliation of seasonally adjusted data with applications to the Swedish quarterly national accounts

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  • Suad Elezović
  • Yingfu Xie

Abstract

Because of the nonlinearity of the seasonal adjustment procedure, the equality between an aggregate series and the sum of its components usually breaks down after seasonally adjusting the series separately. However, some users of official statistics still request consistency between the seasonally adjusted aggregate series and the sum of the corresponding subseries. To achieve the aggregation consistency, a general Denton‐type reconciliation procedure is proposed here. The additivity constraint is imposed on seasonally adjusted components balancing between magnitude and volatility of each series. Some evaluation criteria, based on a set of chosen minimization functions, are further discussed. The implementation and choice of approaches are discussed through a real example by reconciliation of time series in constant prices from the Swedish quarterly national accounts. Finally, some limitations of the method are outlined and possible future works are proposed.

Suggested Citation

  • Suad Elezović & Yingfu Xie, 2018. "Reconciliation of seasonally adjusted data with applications to the Swedish quarterly national accounts," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 72(4), pages 590-602, November.
    • Handle: RePEc:bla:stanee:v:72:y:2018:i:4:p:590-602
    DOI: 10.1111/stan.12155
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    References listed on IDEAS

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    1. Findley, David F, et al, 1998. "New Capabilities and Methods of the X-12-ARIMA Seasonal-Adjustment Program," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 127-152, April.
    2. Tommaso Di Fonzo & Marco Marini, 2011. "Simultaneous and two‐step reconciliation of systems of time series: methodological and practical issues," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 60(2), pages 143-164, March.
    3. Findley, David F, et al, 1998. "New Capabilities and Methods of the X-12-ARIMA Seasonal-Adjustment Program: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 169-177, April.
    4. Di Fonzo, Tommaso, 1990. "The Estimation of M Disaggregate Time Series When Contemporaneous and Temporal Aggregates Are Known," The Review of Economics and Statistics, MIT Press, vol. 72(1), pages 178-182, February.
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