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Brank, J. et al. (2011). Feature Selection. In C. Sammat, & G. I. Webb (Eds.), Encyclopedia of Machine Learning (pp. 402-406). Springer.
https://doi.org/10.1007/978-0-387-30164-8_306

has been cited by the following article:

• TITLE: No Country for Old Men (or Women): The Impact of Migration on Pension Funding Adequacy and Sustainability

  AUTHORS: Thomas Poufinas, James Ming Chen, Charalampos Agiropoulos, George Galanos

  KEYWORDS: Pensions, Pension Adequacy, Migration, Machine Learning, EU Countries

  JOURNAL NAME: Theoretical Economics Letters, Vol.14 No.3, June 28, 2024

  ABSTRACT: This study explores factors influencing pension fund adequacy and sustainability across 21 EU countries from 2007-2018, with a specific focus on the role of migration. Results from Bayesian and regularized linear models reveal no significant evidence that migration bolsters pension funding. Public debt and fertility negatively affect funding in new EU countries, while private debt has a positive effect. The greatest factor is a country’s socialist history. Policymakers are advised to consider strategies to integrate migrants across the EU for better pension contributions and recognize the disparities between former socialist and wealthier EU nations.