Publication in refereed journal
香港中文大学研究人员 ( 现职)
| 庄太量教授 (经济学系) |
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Scopushttp://aims.cuhk.edu.hk/converis/portal/Publication/0Scopus source URL
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摘要Most of the existing autoregressive models presume that the observations are perfectly measured. In empirical studies, the variable of interest is unavoidably measured with various kinds of errors. Thus, misleading conclusions may be yielded due to the inconsistency of the parameter estimates caused by the measurement errors. Thus far, no theoretical result on the direction of bias of the lag order estimate is available in the literature. In this note, we will discuss the estimation an AR model in the presence of measurement errors. It is shown that the inclusion of measurement errors will drastically increase the complexity of the problem. We show that the lag lengths selected by the AIC and BIC are increasing with the sample size at a logarithmic rate.
着者Chong T.T.-L., Zhang Y., Wong C.-L., Liew V.K.-S.
期刊名称Economics Bulletin
出版年份2http://aims.cuhk.edu.hk/converis/portal/Publication/0http://aims.cuhk.edu.hk/converis/portal/Publication/06
月份12
日期1
卷号3
期次1
出版社Economics Bulletin
出版地United States
国际标準期刊号1545-2921
语言英式英语
关键词Akaike information criterion, Autoregressive process, Bayesian information criterion, Measurement error
