IMPROVING THE PROVISION OF AGRICULTURAL MACHINERY THROUGH LEASING, CREDIT AND OWN FUNDS (THE CASE OF COTTON FARMING)

Abstract

The paper analyses the relationship between the number of modern agricultural machines used in cotton farming and the machinery acquired through credit, leasing and producers’ own funds, as well as cotton yield, using 2019–2023 data. Pairwise correlation and regression analysis, Student’s t and Fisher’s F tests and linear trend functions are applied. Because of the small sample (n = 5) and strong multicollinearity among the financing sources (r = 0.93–0.99), pairwise models were estimated instead of a multiple regression. The number of high-performance resource-saving tractors increased by 40.1% in 2019–2023; a statistically significant relationship with cotton yield (R² = 0.945; p = 0.006) was found, while the effect of financing sources was only significant at the 10% level. Based on the trend model (R² = 0.994), the number of tractors is expected to be in the range of 8.3–9.4 thousand by 2028 (point forecast: 8,867).