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Modelling Multiple Regimes in the Business Cycle

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Author Info
Van Dijk, D.
Franses, P.H.

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Abstract

The Interest in business cycle asymmetry has been steadily increasing over the last fifteen years. Most research has focused on the different behaviour of macro-economic variables during expansions and contractions, which by now is well documented. Recent evidence suggests that such a two-phase characterization of the business cycle might be too restrictive. In particular, it might be worthwhile to decompose the recovery phase in a high-growth phase (immediately following the trough of a cycle) and a subsequent moderate-growth phase. In this paper, the issue of multiple regimes is addressed using Smooth Transition Autoregressive [STAR] models. A possible limitation of STAR models as they are currently used is that essentially they deal with only two regimes. We propose a generalization of the STAR model such that more than two regimes can be accommodated. It is demonstrated that the class of Multiple Regime STAR [MRSTAR] models can be obtained from the two-regime model in an elegant way. Then main properties of the MRSTAR model and several issues which might be relevant for empirical specification are discussed in detail. In particular, a lagrange Multiplier-type test is derived which can be used to determine the appropriate number of regimes. Application o f the new model class to US real GNP and US unemployment rate provides evidence in favour of the existence of multiple business cycle phases.

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Publisher Info
Paper provided by Erasmus University of Rotterdam - Econometric Institute in its series Papers with number 9734/a.

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Length: 36 pages
Date of creation: 1997
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Handle: RePEc:fth:erroem:9734/a

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Related research
Keywords: BUSINESS CYCLES ; REGRESSION ANALYSIS ; TESTS;

Other versions of this item:

Find related papers by JEL classification:
E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Hypothesis Testing

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  11. P.H.B.F. Franses & P. de Bruin & D.J.C. van Dijk, 2000. "Seasonal smooth transition autoregression," Econometric Institute Report 185, Erasmus University Rotterdam, Econometric Institute. [Downloadable!]
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  13. Valentina Corradi & Norman R. Swanson, 2003. "The Effect of Data Transformation on Common Cycle, Cointegration and Unit Root Tests: Monte Carlo Results and a Simple Test," Departmental Working Papers 200322, Rutgers University, Department of Economics. [Downloadable!]
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  14. Balagtas, Joseph V. & Holt, Matthew T., 2006. "Unit Roots, TV-STARs, and the Commodity Terms of Trade: A Further Assessment of the Prebisch-Singer Hypothesis," 2006 Annual meeting, July 23-26, Long Beach, CA 21405, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association). [Downloadable!]
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