An alternative Approach to the Dating of Business Cycle: Nonparametric Kernel Estimation

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43110%2F10%3A00157886" target="_blank" >RIV/62156489:43110/10:00157886 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

An alternative Approach to the Dating of Business Cycle: Nonparametric Kernel Estimation

Original language description

The paper provides the methodological background for the Czech Republic business cycle dating process using an alternative approach. This approach is based on the mathematical principle of identification of extremes using estimates of derivations of timetrend of the analysed time series, for which the nonparametric Gasser-Müller estimate is used. The presented methodological approach is applied on the real gross domestic product data sets, the total industry (excluding construction), the gross capitalformation and the final consumption expenditure. The selected variables are sourced from the national accounts system. The obtained results are compared to the widely used naive technique of business cycle dating written by Canova (1998, 1999) or Bonenkamp (2001). The presented new method specifies the identification of turning points in the business cycle dating process.

Czech name

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Czech description

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Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

BB - Applied statistics, operational research

OECD FORD branch

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Project

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Continuities

Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year

2010

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Prague Economic Papers

ISSN

1210-0455

e-ISSN

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Volume of the periodical

3

Issue of the periodical within the volume

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Country of publishing house

CZ - CZECH REPUBLIC

Number of pages

22

Pages from-to

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UT code for WoS article

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EID of the result in the Scopus database

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