Measurement‐error detection: international evidence on industrial production

Kosei Fukuda

Applied Stochastic Models in Business and Industry, 2006, vol. 22, issue 4, 313-319

Abstract: The existence or non‐existence of measurement error (ME) in observed time series is examined not by hypothesis testing but by model selection using the values of information criteria of a battery of alternative models with and without ME. Whether the time series contains ME is determined as a result of model selection. This method is compared with recently proposed hypothesis‐testing method. Simulation results suggest that the performances of the proposed method are usually comparable to and sometimes better than those of the hypothesis‐testing method. The proposed method is applied to monthly time series of industrial production for fifteen developed countries. Obtained results indicate that MEs are detected for at least one and at most seven countries. Copyright © 2006 John Wiley & Sons, Ltd.

Date: 2006
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https://doi.org/10.1002/asmb.617

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Persistent link: https://EconPapers.repec.org/RePEc:wly:apsmbi:v:22:y:2006:i:4:p:313-319

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