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An Empirical Comparison of Methods for Temporal Distribution and Interpolation at the National Accounts

Listed author(s):
  • Baoline Chen

    (Bureau of Economic Analysis)

This study evaluates five mathematical and five statistical methods for temporal disaggregation in an attempt to select the most suitable method(s) for routine compilation of sub-annual estimates through temporal distribution and interpolation in the national accounts at BEA. The evaluation is conducted using 60 series of annual data from the National Economic Accounts, and the final sub-annual estimates are evaluated according to specific criteria to ensure high quality final estimates that are in compliance with operational policy at the national accounts. The study covers the cases of temporal disaggregation when 1) both annual and sub-annual information is available; 2) only annual data are available; 3) sub-annual estimates have both temporal and contemporaneous constraints; and 4) annual data contain negative values. The estimation results show that the modified Denton proportional first difference method outperforms the other methods, though the Casey-Trager growth preservation model is a close competitor in certain cases. Lagrange polynomial interpolation procedure is inferior to all other methods.

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Paper provided by Bureau of Economic Analysis in its series BEA Papers with number 0077.

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Date of creation: Aug 2007
Handle: RePEc:bea:papers:0077
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  1. 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.
  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. David Aadland, 2000. "Distribution and interpolation using transformed data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 27(2), pages 141-156.
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