From GDP to SDGs: A cross-country efficiency analysis using DEA and the case of Türkiye

This thesis evaluates how efficiently countries convert their economic development into sustainable development outcomes, in alignment with the UN Sustainable Development Goals (SDGs). Using data from 167 countries between 2015 and 2023, it uses Principal Component Analysis (PCA) to reduce the dimensionality of SDG indicators, applies an input-oriented Data Envelopment Analysis (DEA) under a Variable Returns to Scale (BCC) model. This DEA–PCA framework allows for a robust, efficiency-based assessment that overcomes multicollinearity and complexity in high-dimensional development data. The findings reveal substantial disparities in efficiency across regions and income groups. While some countries achieve strong SDG outcomes with modest economic inputs, others underperform despite considerable resources. Türkiye exhibits a decline in efficiency, suggesting a structural disconnect between economic growth and sustainable development progress, pointing to policy misalignment or ineffective use of resources. Empirically, the thesis highlights the need to move beyond traditional economic development measures, such as GDP or GDP per capita, and focus more directly on the SDGs, ensuring that economic development is effectively translated into SDGs.