Disaggregation of annual time‐series data to quarterly figures: A comparative study

Wai‐Sum Chan

48 citations0/0 files storedJournal of Forecasting

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Forecasting Techniques and Applications Time Series Analysis and Forecasting Statistical and numerical algorithms

Abstract

Abstract In this paper we consider some of the prominent methods that are available in the literature for the problem of disaggregating annual time‐series data to quarterly figures. The procedures are briefly described and illustrated through a real data set. The performances of the methods are compared in a Monte Carlo study. The results indicate that the complicated model‐based procedure is usually superior to other non‐model‐based alternatives in the large sample situations. Based on the simulation results, we make some recommendations regarding the use of these methods.

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References

1993Introduction to Multiple Time Series Analysis 1971Best Linear Unbiased Interpolation, Distribution, and Extrapolation of Time Series by Related Series 1981A Methodological Note on the Estimation of Time Series 1983A Random Walk, Markov Model for the Distribution of Time Series 1967Further Methods of Derivation of Quarterly Figures from Annual Data 2017The Craft of Economic Modeling

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