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Identifying Turkish business cycle regimes in real time

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  • Barış Soybilgen

Abstract

In this study, we analyse the real-time identification performance of the BBQ method and the Markov switching (MS) model in the case of Turkey by comparing their real-time and ex-post identification results between 1997M01-2017M12. We show that both the BBQ and the MS methodologies identify the nearly same turning point dates for the Turkish economy both ex-post and in real time by using a pseudo real-time data set. We also calculate the real-time identification lag of models and show that the MS model and the BBQ method identify a turning point with a 3–4 months lag and a 6 months lag, respectively. Finally, we show that data revisions do not have a significant impact on the real-time identification performance of the models between 2005M01-2017M12.

Suggested Citation

  • Barış Soybilgen, 2020. "Identifying Turkish business cycle regimes in real time," Applied Economics Letters, Taylor & Francis Journals, vol. 27(1), pages 62-66, January.
    • Handle: RePEc:taf:apeclt:v:27:y:2020:i:1:p:62-66
    DOI: 10.1080/13504851.2019.1607243
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