Assessing the Causal Impact of Trade Balance, Interest Rates, and Exchange Rates on Unemployment in the Euro Area: A Double Machine Learning Approach
AI Deployment and Adoption in Public Administration and Organizations, Gamze Sart,Funda Hatice Sezgin, Editör, IGI Global yayınevi, Pennsylvania, ss.335-364, 2025
- Yayın Türü: Kitapta Bölüm / Araştırma Kitabı
- Basım Tarihi: 2025
- Yayınevi: IGI Global yayınevi
- Basıldığı Şehir: Pennsylvania
- Sayfa Sayıları: ss.335-364
- Editörler: Gamze Sart,Funda Hatice Sezgin, Editör
- İstanbul Üniversitesi-Cerrahpaşa Adresli: Evet
Özet
This study employs three sophisticated econometric models based on the Dual Machine Learning (DML) methodology to examine the causal effect of pivotal economic variables on unemployment rates within the Eurozone. The models analyse the impact of the trade balance, interest rates and real effective exchange rate on the unemployment rate, while controlling for complex interactions among macroeconomic variables such as exports, imports and exchange rates. A sensitivity analysis of each model demonstrates the varying degree of dependence on the control variables. The results indicate that exchange rate and interest rate variables are pivotal in stabilising treatment effect estimates, emphasising the necessity to consider these factors for the development of reliable unemployment modelling. By employing machine learning-based causal inference, this chapter contributes to the field of labour economics and provides insights for policymakers aiming to achieve balanced economic growth and employment stability in the Euro Area.