Spatial differentiation of demographic potential and human capital across Kazakhstan’s regions

Nyussupova Gulnara, Gaibnazarova Zumrat Talatovna, Khassanova Gaukhar, Terechshenko Tatyana

Меҳнат иқтисодиёти ва инсон капитали · 2026-yil

Annotatsiya

This study examines the spatial differentiation of demographic potential and human capital across Kazakhstan’s 17 regions and three cities of republican significance during 2023–2025. Using official statistics for 60 region-year observations, two composite indices are constructed: demographic potential (D), based on four demographic indicators, and human capital (H), based on education, digital literacy, and health. Regions are classified into four types using fixed pooled medians, and classification robustness is tested under 22 alternative weighting and threshold scenarios. Between 2023 and 2025, D declined in 19 regions, while H increased in 16. Spearman’s rank correlations remained positive (0.496–0.580), although regional positions did not fully coincide. The high-D, low-H type contracted from six regions to one, whereas the low-D, high-H type expanded from one to six. Twelve regions retained their baseline type throughout the period, ten met the strict robustness criterion, and overall classification agreement reached 94.8%. Almaty region and Ulytau consistently displayed opposite demographic–human capital profiles. The findings show that separate measurement reveals regional differences that may be obscured by a single composite index and provides a basis for differentiated regional monitoring. Given the short observation period, the results are descriptive and do not establish causal relationships or long-term trends.

Maqola ma’lumotlari
MualliflarNyussupova Gulnara, Gaibnazarova Zumrat Talatovna, Khassanova Gaukhar, Terechshenko Tatyana
JurnalМеҳнат иқтисодиёти ва инсон капитали
NashriyotТДИУ
ISSN3030-3117
Nashr sanasi2026-10-29
Son1.
TilIngliz
Ilmiy sohaIqtisodiyot
DOI10.67668/lehc/voliss1-maxsus/513
Indeksga qo‘shilgan2026-10-29

Kalit so‘zlar

inson kapitali, hududiy differensiallashuv, Qozog‘iston, человеческий капитал, региональная дифференциация, Казахстан, human capital, regional differentiation, Kazakhstan

Ilmiy soha

Iqtibos keltirish

APANyussupova Gulnara, Gaibnazarova Zumrat Talatovna, Khassanova Gaukhar, & Terechshenko Tatyana (2026). SPATIAL DIFFERENTIATION OF DEMOGRAPHIC POTENTIAL AND HUMAN CAPITAL ACROSS KAZAKHSTAN’S REGIONS. Меҳнат иқтисодиёти ва инсон капитали, (1.). https://doi.org/10.67668/lehc/voliss1-maxsus/513
GOST (OAK)Nyussupova Gulnara va b. SPATIAL DIFFERENTIATION OF DEMOGRAPHIC POTENTIAL AND HUMAN CAPITAL ACROSS KAZAKHSTAN’S REGIONS // Меҳнат иқтисодиёти ва инсон капитали. – 2026. – № 1.. – DOI: 10.67668/lehc/voliss1-maxsus/513.
MLANyussupova Gulnara, Gaibnazarova Zumrat Talatovna, Khassanova Gaukhar, and Terechshenko Tatyana. “SPATIAL DIFFERENTIATION OF DEMOGRAPHIC POTENTIAL AND HUMAN CAPITAL ACROSS KAZAKHSTAN’S REGIONS.” Меҳнат иқтисодиёти ва инсон капитали, (1.), 2026. https://doi.org/10.67668/lehc/voliss1-maxsus/513
ChicagoNyussupova Gulnara, Gaibnazarova Zumrat Talatovna, Khassanova Gaukhar, and Terechshenko Tatyana. “SPATIAL DIFFERENTIATION OF DEMOGRAPHIC POTENTIAL AND HUMAN CAPITAL ACROSS KAZAKHSTAN’S REGIONS.” Меҳнат иқтисодиёти ва инсон капитали, (1.) (2026). https://doi.org/10.67668/lehc/voliss1-maxsus/513
HarvardNyussupova Gulnara, Gaibnazarova Zumrat Talatovna, Khassanova Gaukhar, and Terechshenko Tatyana (2026) ‘SPATIAL DIFFERENTIATION OF DEMOGRAPHIC POTENTIAL AND HUMAN CAPITAL ACROSS KAZAKHSTAN’S REGIONS’, Меҳнат иқтисодиёти ва инсон капитали, (1.). https://doi.org/10.67668/lehc/voliss1-maxsus/513
BibTeX
@article{nyussupovagulnara2026,
  title = {SPATIAL DIFFERENTIATION OF DEMOGRAPHIC POTENTIAL AND HUMAN CAPITAL ACROSS KAZAKHSTAN’S REGIONS},
  author = {Nyussupova Gulnara and Gaibnazarova Zumrat Talatovna and Khassanova Gaukhar and Terechshenko Tatyana},
  journal = {Меҳнат иқтисодиёти ва инсон капитали},
  year = {2026},
  number = {1.},
  doi = {10.67668/lehc/voliss1-maxsus/513},
  url = {https://doi.org/10.67668/lehc/voliss1-maxsus/513}
}

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