Nonstationarity and ARIMA(p,d,q) Processes

John D. Levendis
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John D. Levendis: Loyola University New Orleans

Chapter Chapter 5 in Time Series Econometrics, 2023, pp 105-126 from Springer

Abstract: Abstract Many economic and financial time series do not have a constant mean. Rather they show growth or decay. The type of growth–whether deterministic or stochastic–has important implications for policy. In this chpater we examine the different ways to detrend the data. We spend particular attention on the effects of “differencing” (and over-differencing) the data, especially in the context of random walk models with and without drift. We also introduce the ARIMA class of models.

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sptchp:978-3-031-37310-7_5

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DOI: 10.1007/978-3-031-37310-7_5

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