This Article Full Text (PDF) References Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Alert me to new issues of the journal Add to Saved Citations Download to citation manager Request Permissions Request Reprints Add to My Marked Citations Citing Articles Citing Articles via Google Scholar Citing Articles via Scopus Google Scholar Articles by RAFFALOVICH, L. E. Search for Related Content Social Bookmarking                         What's this?

Detrending Time Series

A Cautionary Note

State University of New York at Albany

Trends in time series may produce spurious covariation among variables. Although it is clearly necessary to model such sources of covariation, it is equally necessary to model those processes correctly. This article considers two types of processes that produce trends in time series. Trend stationary processes produce a constant rate of change in the level of a variable. Difference stationary processes produce a random rate of change in the level of a variable. Methods to detrend time series presuppose one or the other of these two basic processes. Tests to distinguish trend stationary from difference stationary processes are described and illustrated. It is shown that choice of method makes a difference and that the consequences of incorrectly detrending time series may be severe.

Sociological Methods & Research, Vol. 22, No. 4, 492-519 (1994)
DOI: 10.1177/0049124194022004003


CiteULike    Complore    Connotea    Del.icio.us    Digg    Reddit    Technorati    Twitter    What's this?