СТАТИСТИЧЕСКОЕ ИССЛЕДОВАНИЕ ПРОСТРАНСТВЕННО-ВРЕМЕННОГО РАЗВИТИЯ СЕЛЬСКОГО ХОЗЯЙСТВА НА МЕЗОУРОВНЕ

Abstract

Significant transformations in the Russian economy in 1990-2000 negatively affected the development of agriculture. The number of workers in the industry has declined, and the production of some types of products has dropped to catastrophic levels. In this regard, we consider it timely and necessary to conduct a statistical study of the state of the industry at the meso-level and the factors that influence it. The aim of the research is to study the development of agriculture at the meso-level in the historical aspect based on statistical methods for assessing the current and forecasting future states. The object of research is Orenburg region and its municipalities, which is due to a number of reasons: the region occupies a stable leading position in the agriculture of Volga Federal District; the industry’s contribution to GRP is about 8%; municipalities of the region are in unequal conditions that affect the development of agriculture in the region. The development of crop production in Orenburg region in 1991-2019 characterized by an increase in sunflower production and a lateral trend in gross grain harvest, while the production of silage, annual and perennial grasses significantly decreased. The lack of a forage base against the background of low early maturity led to a significant reduction in the number of cattle - this negatively affected milk production in the region. Meat production managed to keep from falling only due to the growth of poultry population. The construction of regression models based on panel data covering 35 municipalities (period 2000-2019 and 5 variables) showed that three factors influence the volume of agricultural production - the availability of acreage, investment in fixed assets and the number of cattle. The constructed statistically significant regression model with fixed effects indicates a stable structure of producers and the presence of hidden factors. This determines the direction of further research, which consists in identifying latent variables that have a significant impact on the development of the region’s industry