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Filter-design and model-based analysis of trends and cycles in the presence of outliers and structural breaks

Author

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  • Rainer Metz

    (GESIS – Leibniz Institute for the Social Sciences, Liliencronstr. 6, 50931 Cologne, Germany.)

Abstract
A large proportion of today’s econometric literature addresses the question of whether long run GDP follows a random walk or a log linear trend with one or more structural breaks. Much less attention is paid to the modelling of the long run trend and cycle component. In most studies, the trend is simply eliminated by taking first differences of the log of the series without considering the implications of this kind of trend removal for growth and cycles. Filter design and model-based approaches are used here to assess the long run trend and the cyclical component of Chile’s per capita GDP from 1820 to 2007. Careful attention is paid to outliers and trend breaks and how they influence the appraisal of the components. We show that filter and model-based approaches give comparable results if the filter and model parameters are not chosen mechanically but tailor-made for the time series to be investigated.

Suggested Citation

  • Rainer Metz, 2010. "Filter-design and model-based analysis of trends and cycles in the presence of outliers and structural breaks," Cliometrica, Journal of Historical Economics and Econometric History, Association Française de Cliométrie (AFC), vol. 4(1), pages 51-73, January.
    • Handle: RePEc:afc:cliome:v:4:y:2010:i:1:p:51-73
    DOI: 10.1007/s11698-009-0036-1
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    Citations

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    Cited by:

    1. José Luis Cendejas & Félix-Fernando Muñoz & Nadia Fernández-de-Pinedo, 2017. "A contribution to the analysis of historical economic fluctuations (1870–2010): filtering, spurious cycles, and unobserved component modeling," Cliometrica, Springer;Cliometric Society (Association Francaise de Cliométrie), vol. 11(1), pages 93-125, January.
    2. Konstantakis, Konstantinos N. & Michaelides, Panayotis G., 2017. "Does technology cause business cycles in the USA? A Schumpeter-inspired approach," Structural Change and Economic Dynamics, Elsevier, vol. 43(C), pages 15-26, December.
    3. Rainer Metz, 2011. "Do Kondratieff waves exist? How time series techniques can help to solve the problem," Cliometrica, Journal of Historical Economics and Econometric History, Association Française de Cliométrie (AFC), vol. 5(3), pages 205-238, October.
    4. Kufenko, Vadim, 2016. "Spurious periodicities in cliometric series: Simultaneous testing," Violette Reihe: Schriftenreihe des Promotionsschwerpunkts "Globalisierung und Beschäftigung" 48/2016, University of Hohenheim, Carl von Ossietzky University Oldenburg, Evangelisches Studienwerk.
    5. Olivier Darné & Amélie Charles, 2011. "Large shocks in U.S. macroeconomic time series: 1860-1988," Cliometrica, Journal of Historical Economics and Econometric History, Association Française de Cliométrie (AFC), vol. 5(1), pages 79-100, January.
    6. Claude Diebolt & Karine Pellier, 2022. "Patents in the Long Run : Theory, History and Statistics," Working Papers hal-02929514, HAL.
    7. Claude DIEBOLT & Karine PELLIER, 2018. "Patents in the Long Run: Theory, History and Statistics," Working Papers of BETA 2018-20, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    8. Vadim Kufenko, 2020. "Hide-and-Seek with time-series filters: a model-based Monte Carlo study," Empirical Economics, Springer, vol. 59(5), pages 2335-2361, November.

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