Is the Hamilton regression filter really superior to Hodrick-Prescott detrending?
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11230%2F24%3A10490059" target="_blank" >RIV/00216208:11230/24:10490059 - isvavai.cz</a>
Result on the web
<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=aoT7TlhEYj" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=aoT7TlhEYj</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1017/S136510052400018X" target="_blank" >10.1017/S136510052400018X</a>
Alternative languages
Result language
angličtina
Original language name
Is the Hamilton regression filter really superior to Hodrick-Prescott detrending?
Original language description
An article published in 2018 by J.D. Hamilton gained significant attention due to its provocative title, "Why you should never use the Hodrick-Prescott filter." Additionally, an alternative method for detrending, the Hamilton regression filter (HRF), was introduced. His work was frequently interpreted as a proposal to substitute the Hodrick-Prescott (HP) filter with HRF, therefore utilizing and understanding it similarly as HP detrending. This research disputes this perspective, particularly in relation to quarterly business cycle data on aggregate output. Focusing on economic fluctuations in the United States, this study generates a large amount of artificial data that follow a known pattern and include both a trend and cyclical component. The objective is to assess the effectiveness of a certain detrending approach in accurately identifying the real decomposition of the data. In addition to the standard HP smoothing parameter of $lambda = 1600$ , the study also examines values of $lambda <^>{star }$ from earlier research that are seven to twelve times greater. Based on three unique statistical measures of the discrepancy between the estimated and real trends, it is evident that both versions of HP significantly surpass those of HRF. Additionally, HP with $lambda <^>{star }$ consistently outperforms HP-1600.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
50201 - Economic Theory
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Macroeconomic Dynamics
ISSN
1365-1005
e-ISSN
1469-8056
Volume of the periodical
29
Issue of the periodical within the volume
May 2024
Country of publishing house
US - UNITED STATES
Number of pages
14
Pages from-to
1-14
UT code for WoS article
001214586800001
EID of the result in the Scopus database
2-s2.0-85192814681