Effectiveness of Agricultural subsidies in Zhambyl region: an empirical analysis

2026

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DOI 10.46914/1562-2959-2026-1-2-365-377
Data confidence 85 high
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Abstract

This study empirically examines the effectiveness of agricultural subsidies in enhancing farm productivity in the Zhambyl region of Kazakhstan over the 2010–2025 period. Despite substantial public expenditure and the widespread use of subsidies as a core instrument of agricultural policy, their actual contribution to productivity growth remains contested. Using a quantitative research design, this study analyzes panel data from 34 farms (510 observations) obtained from the Ministry of Agriculture of the Republic of Kazakhstan. A two-way fixed effects regression model, validated through the Hausman test, is employed to estimate the relationship between subsidy amounts and farm productivity, controlling for land area and fixed assets. Diagnostic tests confirm the model’s compliance with key classical regression assumptions. The results reveal that agricultural subsidies have no statistically significant effect on farm productivity (β = 0.228, p > 0.05). This finding remains robust across sub-period analyses (2010–2015 and 2016–2025), indicating that increased subsidy volumes have not translated into measurable productivity gains. The study identifies structural inefficiencies in subsidy design, including disproportionate allocation to large farms, weak conditionality, and a focus on cost compensation rather than performance stimulation. These findings contribute to the growing body of evidence questioning the efficacy of untargeted financial support and underscore the urgent need for policy reform. The paper advocates for a transition toward “smart,” region-specific, and results-based subsidy mechanisms linked to technology adoption, sustainable practices, and robust monitoring frameworks. The study provides actionable recommendations for policymakers seeking to enhance the efficiency and sustainability of public spending in Kazakhstan’s agricultural sector.