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Autoregressive‐asymmetric moving average models for business cycle data
Author(s) -
Brånnås Kurt,
De Gooijer Jan G.
Publication year - 1994
Publication title -
journal of forecasting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.543
H-Index - 59
eISSN - 1099-131X
pISSN - 0277-6693
DOI - 10.1002/for.3980130605
Subject(s) - autoregressive model , business cycle , asymmetry , econometrics , statistic , wald test , economics , nonlinear system , mathematics , statistical hypothesis testing , statistics , keynesian economics , physics , quantum mechanics
Much business cycle research is based on an assumption of symmetric cycles, though it is frequently argued that the downturns are steeper and more short‐lived than the upturns; implying cyclical asymmetries. A new class of nonlinear autoregressive‐asymmetric moving average models is introduced. These models are able to deal with symmetric as well as asymmetric phenomena. A likelihood estimation procedure and a Wald test statistic for symmetry are presented. Evidence of asymmetry is found in US real GNP growth rates.