Global cost of living patterns: machine learning insights and structural economic interpretation


Çelik S., ÇİMEN G., Yavan S.

Quality and Quantity, 2026 (Scopus) identifier

  • Yayın Türü: Makale / Tam Makale
  • Basım Tarihi: 2026
  • Doi Numarası: 10.1007/s11135-026-02752-8
  • Dergi Adı: Quality and Quantity
  • Derginin Tarandığı İndeksler: Scopus, IBZ Online, ABI/INFORM, Index Islamicus, Political Science Complete, Psycinfo
  • Anahtar Kelimeler: Cost of living, Global economic comparison, K-means clustering, Local purchasing power, Machine learning, Rent index, SHAP
  • Sivas Cumhuriyet Üniversitesi Adresli: Evet

Özet

The cost of living refers to the economic indicator for the value of goods and services consumed by the population, which varies greatly from country to country due to factors such as price, income, housing, and consumption. The study undertook the analysis based on the data-driven approach for the exploration of the pattern of the cost of living in 143 countries of the world using factors such as price and income. In the study, the supervised machine learning method was implemented for the validation purpose, along with the analysis using the SHAP method for the importance of the cost of living. The study reveals the significant differences in the cost of living around the world. The study reveals the importance of housing, food, and restaurant expenses, which form the major factors affecting the cost of living. The study also reveals the higher purchasing power in high-cost economies, which acts as the factor for the compensation of the high cost of housing, while the low-cost economies suffer from the constraints due to the low income level. The fiscal policy was not considered in the study, but it provides the framework for the indirect discussion on the policy.