The Unemployment and Growth Nexus in Türkiye: A Quantile-on Quantile Regression Analysis

Abstract

This study investigates the relationship between economic growth and unemployment in Türkiye over the period 2005: Q1-2024:Q4 using the Quantile-on-Quantile Regression (QQR) approach. The existing literature predominantly relies on linear or mean based models and therefore overlooks potential nonlinear and state-dependent dynamics in the unemployment and growth nexus. By incorporating the full joint distribution of both variables, the QQR method enables a more comprehensive assessment of how different unemployment quantiles interact with various growth quantiles. Preliminary tests confirm non-normality, structural breaks, and nonlinear dependence in the data, validating the suitability of a quantile based framework. The empirical results reveal that the relationship between unemployment and growth is strongly asymmetric. In low growth quantiles particularly when unemployment is high unemployment exerts a pronounced negative effect on output, indicating heightened vulnerability during contractionary phases. In middle growth quantiles, the effect becomes statistically insignificant, suggesting relative resilience under more stable conditions. In high growth quantiles, a positive association emerges when unemployment is low, implying that improvements in labor market conditions support economic expansion. However, at medium and high unemployment quantiles, the effects on growth vary considerably, demonstrating that the interaction is not linear across economic states. Overall, the findings emphasize the importance of adopting distribution sensitive and state-contingent labor market policies. The study contributes to the literature by providing a nuanced understanding of the heterogeneous dynamics underlying Okun’s relationship in an emerging economy context.

Keywords

• Okun's law
• quantile-on-quantile regression
• economic growth
• unemployment
• nonlinear dynamics

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