An Empirical Comparison of Methods for Temporal Distribution and Interpolation at the National Accounts
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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- Robert B. Litterman, 1983. "A random walk, Markov model for the distribution of time series," Staff Report 84, Federal Reserve Bank of Minneapolis.
- David Aadland, 2000. "Distribution and interpolation using transformed data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 27(2), pages 141-156. Full references (including those not matched with items on IDEAS)
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