Abstract
The study aims to analyse the key factors affecting grain production in Kazakhstan to develop recommendations for improving the efficiency and sustainability of the agricultural sector. Statistical methods and econometric modelling techniques were used, including the least squares method with heteroscedasticity and autocorrelation robust errors and autoregression with external factors for time series analysis. These methods were used to estimate the impact of various internal and external factors on the gross grain harvest. The analysis demonstrated that grain yields depend on a variety of factors, such as innovations in agricultural technology, climatic conditions and economic policy. The identified factors were grouped with measurable indicators for each, which became the basis for building models. The study determined that the autoregressive model is more suitable for describing the impact on the dependent variable – grain harvest. The most influential indicators are yields and research and development costs. The results of the study can be used to adjust agricultural policy and strategies for agricultural development in Kazakhstan. Proposals for optimising land use and integrating modern agricultural technologies will increase productivity and reduce the impact of negative factors.