2017
DOI: 10.1016/j.jedc.2016.12.004
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Reconciling output gaps: Unobserved components model and Hodrick–Prescott filter

Abstract: This paper reconciles two widely used trend-cycle decompositions of GDP that give markedly different estimates: the correlated unobserved components model yields output gaps that are small in amplitude, whereas the Hodrick-Prescott (HP) filter generates large and persistent cycles. By embedding the HP filter in an unobserved components model, we show that this difference arises due to differences in the way the stochastic trend is modeled. Moreover, the HP filter implies that the cyclical components are serial… Show more

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Cited by 50 publications
(36 citation statements)
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“…The general evolution of the trend output growth is similar to those obtained previously in the literature (e.g. Berger, Everaert, and Vierke, 2016;Grant and Chan, 2017) using unobserved components models. Moreover, the timing of the apparent slowdown in trend output is consistent with the breakdates identified in Perron and Wada (2009) and Morley and Panovska (2019).…”
Section: Full Sample Resultssupporting
confidence: 85%
“…The general evolution of the trend output growth is similar to those obtained previously in the literature (e.g. Berger, Everaert, and Vierke, 2016;Grant and Chan, 2017) using unobserved components models. Moreover, the timing of the apparent slowdown in trend output is consistent with the breakdates identified in Perron and Wada (2009) and Morley and Panovska (2019).…”
Section: Full Sample Resultssupporting
confidence: 85%
“…It is easy to see that if all the indicators are one, then the trend output y * t has a stochastic trend with a time-varying growth rate a 0 + a t . If δ a = 1 and δ y * = 0, then y * t is the same trend specification implicitly assumed by the Hodrick-Prescott filter (see, e.g, Grant and Chan, 2016b). If δ a = 0 and δ y * = 1, then y * t follows a random walk with drift δ a 0 a 0 .…”
Section: Trend Output Specification Searchmentioning
confidence: 95%
“…For instance, it is well known that the correlated unobserved components model of Morley, Nelson, and Zivot (2003) yields output gap estimates that are small in amplitude, whereas the Hodrick-Prescott (HP) filter generates large and persistent cycles. Grant and Chan (2016b) show that this difference arises entirely due to the different ways the trend output is modeled. In particular, the correlated unobserved components model assumes a random walk trend with a constant drift (or a small number of breaks in the drift), whereas the HP filter implicitly models the output trend as a particular random walk with a stochastic drift (see also Harvey and Jaeger, 1993).…”
Section: Trend Output Specification Searchmentioning
confidence: 98%
See 1 more Smart Citation
“…Following a common practice in econometrics, we decompose the series of insulting epithets into a cyclical component and a trend. The cycle may be viewed as the demand side of the market (Baffigi et al 2013;Grant and Chan 2017), i.e. the extent to which the general population harbours a certain curiosity towards the topics related to homosexuality.…”
Section: Introductionmentioning
confidence: 99%