espEconomy: strategy and practiceEconomy: strategy and practice1997-99672663-550XИнститут экономики10.51176/1997-9967-2025-2-104-121esp-1602Research ArticleФИНАНСОВАЯ ЭКОНОМИКАFINANCIAL ECONOMYОценка уровня финансовой инклюзии женщин в Казахстане: эмпирический анализ структурных факторовAssessment of the Level of Financial Inclusion of Women in Kazakhstan: An Empirical Analysis of Structural Factorshttps://orcid.org/0000-0003-3412-3706КирееваА. А.KireyevaA. A.

к.э.н., ведущий научный сотрудник

 

Cand Sc. (Econ.), Leading Researcher

28 Shevchenko str., Almaty

anel.kireyeva@ieconom.kzhttps://orcid.org/0000-0002-4357-0287КурмашеваМ. Т.KurmashevaM. T.

PhD докторант

PhD candidate

8a Abay ave., Almaty

makpaltalgatkyzy@gmail.comИнститут экономики КН МНВО РККазахстанInstitute of Economics CS MSHE RKKazakhstanУниверситет международного бизнеса им. Кенжегали СагадиеваКазахстанKenzhegali Sagadiyev University of International BusinessKazakhstan202514072025202104121Copyright © Киреева А.А., Курмашева М.Т., 20252025Киреева А.А., Курмашева М.Т.Kireyeva A.A., Kurmasheva M.T.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://esp.ieconom.kz/jour/article/view/1602

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In conditions of gender imbalance and territorial asymmetry, women’s access to financial resources remains limited. The study aims to assess the level of financial inclusion of women in Kazakhstan based on an analysis of structural factors and their relationship with the transformation of the employment structure. The empirical base of the study is based on official statistics from the Bureau of National Statistics, World Bank reports, as well as industry reviews and specialized databases on the dynamics of small business lending. Structural modelling using the partial least squares method (PLS-SEM) and the Random Forest algorithm is used as a methodological basis. The results show that the GRP variables and the share of wages in GDP have the greatest impact on the parameters of women’s entrepreneurial lending in Kazakhstan. According to the partial least squares model, the coefficients of determination were R2 = 0.935 for  volume of loans and R2 = 0.822 for their number, which confirms the high explanatory power of the model. The regional analysis confirms the presence of spatial heterogeneity: the greatest synchronicity in lending dynamics is observed in Zhambyl, Turkestan, and East Kazakhstan regions; the lowest - in Mangystau and Atyrau. The results justify the need for financial support tools that consider regional specificities and are consistent with employment and professional adaptation programs to eliminate institutional barriers and improve financial inclusion effectiveness. Future research could focus on assessing financial support mechanisms and analyzing the interaction between employment and digitalization programs for women’s entrepreneurship.

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The authors declare that there are no conflicts of interest present.