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This study examines the impact of agricultural investment on the economic growth of different sectors using a first- and fifth-order multivariate Markov chain model. Four interrelated industry series 1995–2018 were considered. The studied data were structured from the Organization for Economic Co-operation and Development (OECD) sources. Specifically, the relationship between agriculture, hunting, forestry, food products, beverages and tobacco, chemical and chemical products, wholesale and retail trade, and the rest of the economy was studied. The first- and fifth-order multivariable model of the Markov chain was proposed to predict the impact of investments allocated to agriculture on the above-mentioned industries according to the economic situation in Kazakhstan over the 1995–2018 years. The accuracy of the model was tested and analyzed. In particular, we obtain the prediction probability decreases from 0.99 to 0.58, and the accuracy of both models is 99%. Indeed, these research is a short-term probabilistic forecasting model that policymakers can use to evaluate and implement initiatives to improve the situation in a country. And the results show a significant impact of agricultural investment on sectoral economic growth, with significant variation across sectors.

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Using Markov Chain Model to Forecasting of the Agricultural Industry Development

  • 会议论文

  • 发表日期：

    2025年

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  • Seyit Kerimkhulle,
  • Gulnara Turtkarayeva,
  • Rashid Mussaibekov,
  • Nazgul Ospanova,
  • Shakharzat Kuttykozhayeva,
  • Alibek Adalbek

摘要

This study examines the impact of agricultural investment on the economic growth of different sectors using a first- and fifth-order multivariate Markov chain model. Four interrelated industry series 1995–2018 were considered. The studied data were structured from the Organization for Economic Co-operation and Development (OECD) sources. Specifically, the relationship between agriculture, hunting, forestry, food products, beverages and tobacco, chemical and chemical products, wholesale and retail trade, and the rest of the economy was studied. The first- and fifth-order multivariable model of the Markov chain was proposed to predict the impact of investments allocated to agriculture on the above-mentioned industries according to the economic situation in Kazakhstan over the 1995–2018 years. The accuracy of the model was tested and analyzed. In particular, we obtain the prediction probability decreases from 0.99 to 0.58, and the accuracy of both models is 99%. Indeed, these research is a short-term probabilistic forecasting model that policymakers can use to evaluate and implement initiatives to improve the situation in a country. And the results show a significant impact of agricultural investment on sectoral economic growth, with significant variation across sectors.