Benchmarking Time Series with Autocorrelated Survey Errors

descriptionPublicationkeyboard_double_arrow_right Article 01 Dec 1994Publisher:JSTORJournal:International Statistical Review / Revue Internationale de Statistique, volume 62, page 365 (issn: 0306-7734,

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Authors: Cholette, Pierre A.; Dagum, Estela Bee;

doi: 10.2307/1403767

Benchmarking Time Series with Autocorrelated Survey Errors

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Abstract

Summary: The Denton method [\textit{F. T. Denton}, J. Am. Stat. Assoc. 66, 99-102 (1971; Zbl 0216.22801)] is widely used by statistical agencies to benchmark time series (i.e. to adjust them to annual benchmarks). This method does not take into account: (a) the presence of bias, and (b) the presence of autocorrelation and heteroscedasticity in the survey errors. This paper introduces a regression benchmarking method which incorporates (a) and (b) and calculates the relative efficiency with respect to the Denton method, under the assumption of various types of ARMA processes for the survey errors. The results are illustrated with the Canadian Retail Trade series.

Keywords

Time series, auto-correlation, regression, etc. in statistics (GARCH), bias, autocorrelation, regression benchmarking method, relative efficiency, Denton method, ARMA processes, heteroscedasticity, survey errors

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