Growth Trends and Systematic Patterns of Booms and Busts‐Testing 200 Years of Business Cycle Dynamics

17 Pages Posted: 11 Jan 2019

See all articles by Marlon Fritz

Marlon Fritz

University of Paderborn

Thomas Gries

University of Paderborn

Yuanhua Feng

University of Paderborn

Date Written: February 2019

Abstract

We study the dynamic pattern of business cycles using US GDP data between 1790 and 2015. To address difficulties in trend and cycle decomposition, we introduce a semiparametric estimation approach with an iterative plug‐in (IPI) algorithm for endogenous bandwidth selection. This algorithm identifies continuously moving growth trends with trend‐supporting growth periods. A simulation study demonstrates the value‐added of our trend identification. Afterwards, nonlinear SETAR models are fitted parametrically. Further, we test the trend using a recently developed test and the estimated SETAR models against their linear alternatives. The results indicate asymmetric characteristics during booms and busts.

Suggested Citation

Fritz, Marlon and Gries, Thomas and Feng, Yuanhua, Growth Trends and Systematic Patterns of Booms and Busts‐Testing 200 Years of Business Cycle Dynamics (February 2019). Oxford Bulletin of Economics and Statistics, Vol. 81, Issue 1, pp. 62-78, 2019, Available at SSRN: https://ssrn.com/abstract=3313682 or http://dx.doi.org/10.1111/obes.12267

Marlon Fritz (Contact Author)

University of Paderborn ( email )

Warburger Str. 100
Paderborn, D-33098
Germany

Thomas Gries

University of Paderborn ( email )

Warburger St. 100
Paderborn, D-33098
Germany

Yuanhua Feng

University of Paderborn ( email )

Warburger Str. 100
Paderborn, D-33098
Germany

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