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Extracting Economic Cycles using Modified Autoregressions
Author(s) -
Morton Alex S.,
Wilson Granville Tunnicliffe
Publication year - 2001
Publication title -
the manchester school
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.361
H-Index - 42
eISSN - 1467-9957
pISSN - 1463-6786
DOI - 10.1111/1467-9957.00270
Subject(s) - akaike information criterion , autoregressive model , series (stratigraphy) , econometrics , multivariate statistics , star model , unemployment , economics , extension (predicate logic) , mathematics , time series , autoregressive integrated moving average , computer science , statistics , macroeconomics , paleontology , biology , programming language
We review a family of modified autoregressive models in both discrete‐ and continuous‐time formulations. We present the case for these models by showing first how a standard discrete‐time autoregressive model with orders selected by criteria such as the Akaike information criterion can fail to identify the correct periods of cyclical variations in a simulated example. We then show how the modified models can overcome this failure, and further illustrate this success with a real example of an unemployment series. A new extension of the continuous‐time modified model to multivariate series is described. This is applied to a pair of series with mixed monthly, quarterly and annual sampling intervals. Common cyclical components of the two series are then extracted.

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