A contribution to the analysis of historical economic fluctuations (1870–2010): filtering, spurious cycles, and unobserved component modeling

José Luis Cendejas Bueno, Félix-Fernando Muñoz () and Nadia Fernández- de-Pinedo
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Nadia Fernández- de-Pinedo: Universidad Autónoma de Madrid
Authors registered in the RePEc Author Service: Nadia Fernandez de Pinedo

Cliometrica, 2017, vol. 11, issue 1, No 4, 93-125

Abstract: Abstract Time series filtering methods such as the Hodrick–Prescott (HP) filter, with a consensual choice of the smoothing parameter, eliminate the possibility of identifying long swing cycles (e.g., Kondratieff type) or, alternatively, may distort periodicities that are in fact present in the data, giving rise, for example, to spurious Kuznets-type cycles. In this paper, we propose filtering Maddison’s time series for the period 1870–2010 for a selection of developed countries using a less restrictive filtering technique that does not impose but instead estimates the cutoff frequency. In particular, we use unobserved component models that optimally estimate the smoothing parameter. Using this methodology, we identify cycles of periods, primarily in the range of 4–7 years (Juglar-type cycles), and a number of patterns of cyclical convergence. We analyze the historical processes underlying this last empirical finding: Peacetime periods, monetary arrangements, trade and investment flows, and industrial boosts are confluent forces driving the economic dynamism. After 1950, we observe a common business cycle factor that groups all economies, which is consistent with the consolidation of the so-called second globalization.

Keywords: Historical business cycles; Spectral analysis; Unobserved component models; Maddison’s time series (search for similar items in EconPapers)
JEL-codes: C32 E32 N1 (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (2)

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Working Paper: A contribution to the analysis of historical economic fluctuations (1870-2010): filtering, spurious cycles and unobserved component modelling (2015)
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DOI: 10.1007/s11698-015-0135-0

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