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The study applies the flexible nonlinear inference approach of James D. Hamilton (2001) to investigate the relationship between cyclical components of unemployment and output in the Turkish economy where the unemployment rate remains at double digits despite the relatively stable economic environment over the last decade. The paper shows that economic expansion and contraction terms have an asymmetric effect on cyclical unemployment in Turkey. Moreover, the study identifies a specific range for the output gap level at which jobless growth pattern occurs in the Turkish economy. According to our findings, contrary to standard literature, cyclical component of unemployment does not decrease even though cyclical component of output is positive and increases in the middle stages of the upswing phase of the economy. This result may also indicate that the employers are reluctant to extend employment and alter into informalization for reasons such as over-valued domestic currency, surplus labour force and/or any rigid regulatory frameworks in the middle stages of the expansion phase of the economy. However, they become eager to expand employment and renounce informalization only after a certain rate of economic growth is achieved.

Investors should be aware of the information flow across the markets to develop investment policies. The volatility spillover relationships between spot and futures markets includes significant knowledge for the composition of optimal portfolios. In the present study, the relationship between spot and futures markets in Turkey was investigated based on BIST 30 index end-of-day price data for the period between February 2, 2006, and April 30, 2020. The volatility spillover effects and the time-varying dynamic conditional relationships between the markets were investigated with the DCC-GARCH model. The findings reveal the existence of a two-way volatility spillover between markets and a strong dependency between markets' return volatilities. In addition, the effect of negative and positive shocks on market volatility was analyzed with the GJR-GARCH model and the results demonstrated that both markets responded strongly to negative shocks when compared to positive shocks.