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

Marlon Fritz (), Thomas Gries and Yuanhua Feng
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Marlon Fritz: Paderborn University

No 96, Working Papers CIE from Paderborn University, CIE Center for International Economics

Abstract: We study the dynamic pattern of business cycles using US GDP data between 1790 and 2010. To address difficulties in the 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 Rate Trends (MGT) with a time length of 24 years. Afterwards, nonlinear SETAR models are fitted parametrically. Additionally, we test the trend in a recent developed test and the estimated SETAR models against their linear alternatives. The results indicate asymmetric characteristics during booms and busts.

Keywords: Business Cycles; Trend and Cycle Decomposition; Semiparametric Estimation; SETAR model (search for similar items in EconPapers)
JEL-codes: C14 C22 C51 E32 (search for similar items in EconPapers)
Pages: 28 pages
Date: 2016-09
New Economics Papers: this item is included in nep-mac
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http://groups.uni-paderborn.de/wp-wiwi/RePEc/pdf/ciepap/WP96.pdf (application/pdf)

Related works:
Journal Article: Growth Trends and Systematic Patterns of Booms and Busts‐Testing 200 Years of Business Cycle Dynamics (2019)
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Persistent link: https://EconPapers.repec.org/RePEc:pdn:ciepap:96

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