COMPARISON OF TIME AND CROSS‐SECTIONAL AGGREGATION UNDER A TIME SERIES RANDOM COMPONENT MODEL

John L. Eltinge

Journal of Time Series Analysis, 1994, vol. 15, issue 2, 167-181

Abstract: Abstract. Small‐area estimation under a stationary time series random component model is considered. Cross‐sectional aggregation and varying degrees of time aggregation are treated as competing prediction methods. An estimated mean‐squared prediction error criterion is used to compare these methods. Some exact and asymptotic properties of this criterion are developed, a consistent estimator of the associated asymptotic variance is presented and simultaneous approximate confidence intervals for the mean‐squared prediction errors are discussed. Time aggregation of a single series is considered as a special case. In addition, an extension to the assessment of mean‐squared prediction errors of synthetic small‐area predictors is outlined.

Date: 1994
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https://doi.org/10.1111/j.1467-9892.1994.tb00183.x

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Persistent link: https://EconPapers.repec.org/RePEc:bla:jtsera:v:15:y:1994:i:2:p:167-181

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