REGRESSION MODEL FOR SUBSTANTIATION OF SUSTAINABLE STATE POLICY IN A DIGITAL ECONOMY
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Date
2020
Authors
Lozynska, T. M.
Dorofyeyev, O. V.
Ponochovnyi, Y. L.
Лозинська, Тамара Миколаївна
Дорофєєв, Олександр Вікторович
Поночовний, Юрій Леонідович
Власенко, Тетяна Анатоліївна
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Abstract
Description
The article discusses the use of digital
mathematical models in justifying public policy for sustainable
economic development. The wider expediency uses of statistical
analysis methods to substantiate public administration decisions
in the digital economy is explained. The technique of forming
and preparation of experimental data for the construction of a
mathematical regression model is described. The hypothesis of
normal distribution of the input data was tested according to the
statistical criteria of Kolmogorov-Smirnov and Lilliefors and
Shapiro-Wilk. Box-Cox transformation was used to normalize
the data. The linear multiple regression coefficients are
determined by the least squares method. The quality of the
resulting model was evaluated using the Student's and Fisher's
criteria. The results of the forecast of financial stability of
agricultural enterprises for 2020-2022 and the factor indicators
indicate the negative dynamics of the effective indicator of their
financial condition. The proposed model can be used to
continuously monitor the financial condition of agricultural
enterprises by linking it to the State Statistics Service of
Ukraine
Keywords
digital economy, state policy of sustainable development, financial sustainability, agricultural enterprise, mathematical simulation, linear multiple regression, normal distribution