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Business Cycle Asymmetry: Deepness and Steepness in Turkey

Author

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  • Banu Tanrıöver
  • Rahmi Yamak

Abstract

The purpose of this study is to examine “steepness†and “deepness†asymmetry in The Turkish business cycle. The study explains the concept and the kind of business cycle asymmetry and examines the kind of the asymmetry by using quarterly real GDP, industrial production, and manufacturing production in Turkey for the period of 1987:I-2014:I. The presence of seasonal component was determined by Kruskal-Wallis test and decomposed with X12-ARIMA method. Then skewness test that consists of steepness and deepness tests of Sichel (1993) was applied to cycle components. The significance level of the skewness statistics was investigated by using Newey-West (1987) method. According to Newey-West results, the presence of deepness asymmetry was accepted for real GDP, industrial production and manufacturing production in all the kernels options. The presence of steepness asymmetry was also accepted for all the variables.

Suggested Citation

  • Banu Tanrıöver & Rahmi Yamak, 2015. "Business Cycle Asymmetry: Deepness and Steepness in Turkey," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 18(58), pages 81-96, December.
    • Handle: RePEc:rej:journl:v:18:y:2015:i:58:p:81-96
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Business Cycle Asymmetry; Steepness and Deepness Asymmetry; Skewness Test; Kruskal-Wallis Test; Newey-West Standard Error;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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