Azimkhan A. Satybaldin, Mikhail V. Tamarovskij, Viktor N. Sivolap, Ivan A. Shinkarev
Abstract
The aim of the research was to find optimal solutions for the use of investments in creating herds of beef cattle by the method of expanded reproduction and maintaining a high genetic status of animals. Processing of scientific and statistical material was carried out by the method of comparative analysis using benchmarking elements. For calculation of planning variables normative, calculation-analytical and optimization methods were used. The article presents the results of existing programs for the development of beef cattle breeding. The calculated indicators for the formation of a herd of beef cattle with expanded reproduction and a schedule for paying off credit debt are given by taking into account possible volumes of livestock sales. It has been established that with the existing loan repayment periods enterprises are forced to sell most of the young stock received. This limits the possibilities for reproduction of the herd. Introduction into the herd of a large number of repair heifers leads to a decrease in the genetic status of livestock. Ttaking into account the volume and timing of sales, the vacation on the payment of the main debt and interest on the loan should be increased to 6-7 years. All design parameters can be adapted to enterprises with different beef cattle. To increase the effectiveness of programs for the development of beef cattle breeding the need for the formation of credit resources with a long maturity is indicated. This will reduce the need for credit resources and generates an incentive for business entities to expand the reproduction of beef cattle herds.
Key words: investments, loan repayment periods, beef cattle, expanded reproduction, “long money”.
Cite
А.А. Сатыбалдин, М.В. Тамаровский, В.Н. Сиволап, И.А. Шинкарев Оптимизация инвестиционных параметров при формировании стад мясного скота методом расширенного воспроизводства // Экономика: стратегия и практика. — 2019 — № 4 (14) — С. 9-21.
