Business cycle dynamics: A bottom-up approach with Markov-chain measurement
Business cycle dynamics can be seen as footprints left by individual decision makers. Tracing those footprints we offer a novel, largely model independent and exogenous measure of the business cycle dynamics. This measure also, allows for distinguishing positive and negative shocks without prior est...
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| Format: | Elektronisch Artikel |
| Sprache: | English |
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Paris
OECD Publishing
2015
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| Online-Zugang: | Volltext |
| Zusammenfassung: | Business cycle dynamics can be seen as footprints left by individual decision makers. Tracing those footprints we offer a novel, largely model independent and exogenous measure of the business cycle dynamics. This measure also, allows for distinguishing positive and negative shocks without prior estimation. Utilizing more than twentythousand observations of firms surveyed quarterly in the periods (1999-2006), we employ a Markov-chain approach combined with conventional time series econometrics for gauging the dynamics of business cycles. Since we start the analysis with firm level data we label our method the "bottom-up approach". |
| Beschreibung: | 1 Online-Ressource (21 p.) 21 x 28cm. |
| DOI: | 10.1787/jbcma-2015-5jrs0lv6xs7b |
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| spelling | Müller, Christian VerfasserIn aut Business cycle dynamics A bottom-up approach with Markov-chain measurement Christian, Müller and Eva, Köberl Paris OECD Publishing 2015 1 Online-Ressource (21 p.) 21 x 28cm. Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Business cycle dynamics can be seen as footprints left by individual decision makers. Tracing those footprints we offer a novel, largely model independent and exogenous measure of the business cycle dynamics. This measure also, allows for distinguishing positive and negative shocks without prior estimation. Utilizing more than twentythousand observations of firms surveyed quarterly in the periods (1999-2006), we employ a Markov-chain approach combined with conventional time series econometrics for gauging the dynamics of business cycles. Since we start the analysis with firm level data we label our method the "bottom-up approach". Economics Köberl, Eva MitwirkendeR ctb Enthalten in OECD Journal: Journal of Business Cycle Measurement and Analysis Vol. 2015, no. 1, p. 41-61 volume:2015 year:2015 number:1 pages:41-61 FWS01 ZDB-13-SOC FWS_PDA_SOC https://doi.org/10.1787/jbcma-2015-5jrs0lv6xs7b Volltext |
| spellingShingle | Müller, Christian Business cycle dynamics A bottom-up approach with Markov-chain measurement Economics |
| title | Business cycle dynamics A bottom-up approach with Markov-chain measurement |
| title_auth | Business cycle dynamics A bottom-up approach with Markov-chain measurement |
| title_exact_search | Business cycle dynamics A bottom-up approach with Markov-chain measurement |
| title_full | Business cycle dynamics A bottom-up approach with Markov-chain measurement Christian, Müller and Eva, Köberl |
| title_fullStr | Business cycle dynamics A bottom-up approach with Markov-chain measurement Christian, Müller and Eva, Köberl |
| title_full_unstemmed | Business cycle dynamics A bottom-up approach with Markov-chain measurement Christian, Müller and Eva, Köberl |
| title_short | Business cycle dynamics |
| title_sort | business cycle dynamics a bottom up approach with markov chain measurement |
| title_sub | A bottom-up approach with Markov-chain measurement |
| topic | Economics |
| topic_facet | Economics |
| url | https://doi.org/10.1787/jbcma-2015-5jrs0lv6xs7b |
| work_keys_str_mv | AT mullerchristian businesscycledynamicsabottomupapproachwithmarkovchainmeasurement AT koberleva businesscycledynamicsabottomupapproachwithmarkovchainmeasurement |