RECOGNIZING OVERDIFFERENCED TIME SERIES

Ming Chun Chang and David Dickey

Journal of Time Series Analysis, 1994, vol. 15, issue 1, 1-18

Abstract: Abstract. Differencing is often used to render a time series stationary. The decision of how much differencing to do is usually based on plots of data, the autocorrelation function or a statistical test. Hence, it may happen that an analyst mistakenly differences a stationary series. When that happens, the inverse autocorrelation function takes on a specific pattern. We characterize this pattern and discuss the behavior of sample estimates of the inverse autocorrelation function for such overdifferenced series.

Date: 1994
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https://doi.org/10.1111/j.1467-9892.1994.tb00173.x

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