A Computational Analysis of Housing Affordability: Robust Bootstrap Regression Modeling of the Safety Premium

This study presents a methodologically rigorous and in-depth analysis of the socio-institutional determinants of housing affordability in nine EU Member States and Georgia over the period 2013-2023. The study transcends conventional macroeconomic models to identify and quantify the impact of non-financial indicators on the Price-to-Income ratio as the dependent variable. The study uses bootstrap regression with 1000 iterations, ensuring the stability of the coefficients and responding to the difficulties of data distribution in both transition and developed economies (unbalanced panel data, sample size of 89). Empirical results demonstrate a high explanatory power of the model (R-squared value of 0.670), where the Safety Index was identified as the main and most important driving factor of value formation (beta coefficient of 0.312, p-value of 0.007). The conclusion that institutional safety functions as a "nonfinancial capital" that exhibits a strong predictive association with the volatility of real estate prices is significant. The research findings also indicate a paradigm shift in real estate valuation, validating the "safety premium" and supporting the Hedonic Pricing Theory. This study argues that institutional stability in the housing ecosystems of transition countries outweighs the importance of traditional financial liquidity as a price determinant.

@article{Terterashvili2026,
  title     = {A Computational Analysis of Housing Affordability: Robust Bootstrap Regression Modeling of the Safety Premium},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {17},
  number    = {6},
  year      = {2026},
  publisher = {The Science and Information Organization},
  author    = {Natia Terterashvili and Shota Shaburishvili},
  doi       = {10.14569/IJACSA.2026.0170630},
  url       = {https://doi.org/10.14569/IJACSA.2026.0170630}
}