Title of article
Modeling The Level Of Investment Attractiveness Of The Agrarian Economy Sector
Author/Authors
Aleskerova, Y Department of Finance, Banking and Insurance - Vinnytsia National Agrarian University, Vinnytsia, Ukraine , Titenko, Zoia National University of Life and Environmental Sciences of Ukraine, Kyiv, Ukraine , Skrypnyk, H National University of Life and Environmental Sciences of Ukraine, Kyiv, Ukraine , Grytsyna, O Department of Finance, Banking and Insurance - Lviv National Agrarian University, Ukraine
Pages
7
From page
647
To page
653
Abstract
The relevance of the research topic is due to the fact that in the current economic conditions attracting
additional investments will ensure the further development of the agricultural sector of the economy.
The purpose of the article is to establish a close link between investment attraction and increased
agricultural output. Positive dynamics were found as a result of the analysis of the dynamics of
investments in fixed assets in the agricultural sector during the analyzed period, but their fluctuations
by years are observed due to the influence of factors of the external and internal environment.
Scientific methods were used in the research process: modeling - to build an investment model for the
development of the agricultural sector of the economy; economic and statistical - to assess the
dynamics of capital investment; analysis and synthesis - to find out the reasons that cause changes in
capital investment.Results of the research. The result of the study is clearly identified trends in
attracting investment in the agricultural sector of Ukraine. The analysis of investment attractiveness
on the basis of neoclassical Cobb-Douglas production function is carried out. The obtained model
made it possible to predict the volume of production based on the expected values of capital and labor.
Keywords
Investment , Investment attractiveness , Agricultural sector , Function of production
Journal title
International Journal of Industrial Engineering and Production Research
Serial Year
2020
Record number
2544232
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