Innovative ways of agricultural development in the Republic of Kazakhstan

Document Type : Research Paper

Authors

1 Department of Management, al-Farabi Kazakh National University, 71 al-Farabi Ave., Almaty, 050040, Kazakhstan

2 Kazakh Research Institute of Economics of Agro-Industrial Complex and Rural Development, 30B Satpayev St., Almaty, 050057, Kazakhstan

3 Department of Veterinary Sanitary Examination and Hygiene, Faculty of Veterinary Science, Kazakh National Agrarian Research University, 8 Abay Avenue, Almaty, 050010, Kazakhstan

10.22124/cjes.2026.9915

Abstract

This study determines which classes of agricultural innovation are economically justified under the factor prices, farm structure, and financing conditions prevailing in Kazakhstan and identifies the conditions under which their adoption becomes rational for the individual producer. This study applies partial-budget analysis in the ex-ante scenario tradition established in the economics of agricultural robotics. Cost, price, and policy parameters are drawn from the Kazakhstani market and official sources for 2023–2026; technical performance coefficients for AI-based targeted spraying are transferred from published field trials and treated as scenario bounds. The decision variable is the maximum investment a producer can justify over an eight-year horizon, evaluated at concessional and commercial discount rates across farm sizes from 1000 to 20000 hectares. Spring wheat production in Northern Kazakhstan operates at approximately zero economic profit in an average season, clearing at 4 400 KZT ha-1 at a yield of 12 c ha-1 and a price of 87 000 KZT ton-1. AI-based targeted spraying reduces herbicide expenditure by 8 780 to 15 200 KZT ha-1, a saving equivalent to a yield increase of 1.0 to 1.75 c ha-1 and amounting to two to three times the average gross margin. The binding constraint on adoption is the cost of capital rather than technical performance: concessional finance raises justifiable investment by 52%, an effect exceeding the entire range of technical performance uncertainty. The break-even sown area lies between approximately 1 400 and 4 200 hectares depending on system price and financing terms. This study replaces the technological recommendations that dominate the regional literature with an economic decision rule specifying technology class, farm size, financing terms, and investment sequence. It further establishes that robotization and fleet renewal are complements in sequence rather than competing alternatives, and that service provision rather than purchase subsidy is the viable diffusion pathway for producers below the scale threshold.

Keywords

References

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Caspian Journal of Environmental Sciences
Volume 24, Issue 4
October 2026
Pages 997-1011

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