Аңдатпа
This study examines regional agricultural credit allocation and intensity in Kazakhstan and their relevance to financial inclusion. Data cover 17 harmonised units in 2014–2023. Two-way fixed-effects models use 153 observations for 2015–2023 (T = 9), after lagging output. Outcomes comprise total real credit, credit per agricultural worker, and credit per hectare. Credit remains concentrated: the 2014–2023 Spearman rank correlation is 0.93, and 13 of 17 units remain in the same quartile. The modest decline in the top-three share is not statistically distinguishable from zero. A 1% increase in lagged agricultural output is associated with 0.63% higher current credit. Subsidies are positively associated with credit, with moderate evidence of a stronger association in initially high-credit regions. The interaction has weaker bootstrap support (p = 0.061; 95% CI [−0.01, 0.30]), so the distributional evidence is suggestive rather than definitive. Separate and joint models support a positive branch-density association; ATM-density estimates are imprecise. Regional differences and the main associations persist in the normalised outcomes. These non-causal associations concern geographic financial access and cannot establish borrower-level exclusion. Aggregate credit growth alone does not establish geographically inclusive agricultural finance.