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Testing Temporal Disaggregation

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  • Christian Mueller

Abstract

Economists and econometricians very often work with data which has been temporally disaggregated prior to use. Hence, the quality of the disaggregation clearly affects the quality of the analyses. Building on Chow and Lin's (1971) disaggregation model this paper proposes a new estimation approach and a specification test which assesses the quality of the disaggregation model. An advantage of the proposal is that estimation and testing can both be pursued using the aggregated data while the standard method requires a mixture of high and low frequency data. A small simulation study shows that the test indeed provides useful information.

Suggested Citation

  • Christian Mueller, 2006. "Testing Temporal Disaggregation," KOF Working papers 06-134, KOF Swiss Economic Institute, ETH Zurich.
  • Handle: RePEc:kof:wpskof:06-134
    DOI: 10.3929/ethz-a-005187504
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    References listed on IDEAS

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    1. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    2. Litterman, Robert B, 1983. "A Random Walk, Markov Model for the Distribution of Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(2), pages 169-173, April.
    3. Chow, Gregory C & Lin, An-loh, 1971. "Best Linear Unbiased Interpolation, Distribution, and Extrapolation of Time Series by Related Series," The Review of Economics and Statistics, MIT Press, vol. 53(4), pages 372-375, November.
    4. Marcellino, Massimiliano, 1999. "Some Consequences of Temporal Aggregation in Empirical Analysis," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(1), pages 129-136, January.
    5. Hirotugu Akaike, 1969. "Fitting autoregressive models for prediction," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 21(1), pages 243-247, December.
    6. Fernandez, Roque B, 1981. "A Methodological Note on the Estimation of Time Series," The Review of Economics and Statistics, MIT Press, vol. 63(3), pages 471-476, August.
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    More about this item

    Keywords

    Temporal disaggregation; Restricted ARMA;

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