The efficacy of the retirement pension provision system: Modeling, and assessing of the case of Kazakhstan

Artikel

This research is aimed at developing a methodology for assessing the efficacy of a macroeconomic model of the Kazakhstani pension provision system. A hierarchy of indicators of the pension system efficacy is built using the graph method. The representativeness of these indicators is confirmed by using expert assessment and factor analysis. A multi-factor assessment model is built using an additive convolution of the normalized values of the 2014-2019 resulting indicators with a breakdown by regions, regarding the coefficients of their significance. A regression model is developed to show the dependence of the pension system efficacy on the share of the accumulative system in the structure of retirement scheme financing. The optimal part of the accumulative system amounting to 79.5% of the total system is determined to be the level at which the pension system efficiency is maximized. A neural model for predicting the pension system efficacy under the influence of labor market indicators is built. The size of the minimum required annual payroll deductions from the wages of persons working according to the accumulative system is calculated depending on the length of service; this minimum size ensures a replacement rate of 40% with regard to the optimal ratio of the accumulative and solidarity pension systems. These findings will be useful to state bodies when developing and clarifying directions for reforming the pension system in Kazakhstan.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Journal: Journal of Open Innovation: Technology, Market, and Complexity ; ISSN: 2199-8531 ; Volume: 6 ; Year: 2020 ; Issue: 4 ; Pages: 1-16 ; Basel: MDPI

Classification and Topics

• Classification: Management
• Subject: labor market ; accumulative pension model ; Kazakhstan ; pension fund ; pension system ; pensioners ; social insurance ; solidarity pension model

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Junusbekova, Gulsara Ashirbayevna ; Zhaumitova, Marzhan Dosymovna
• Event: Veröffentlichung
• (who): MDPI
• (where): Basel
• (when): 2020

Further information

• DOI: doi:10.3390/joitmc6040158
• Handle: http://hdl.handle.net/10419/241544
• Last update: 10.03.2025, 11:43 AM CET