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Моделирование Доходов Социально-Экономических Систем На Основе Производственной Функции // Modeling Of Income Of Socio-Economic Systems On The Basis Of The Production Function

Author

Listed:
  • A. Kamaletdinov Sh.

    (Financial University)

  • A. Ksenofontov A.

    (Financial University)

  • А. Камалетдинов Ш.

    (Финансовый университет)

  • А. Ксенофонтов А.

    (Финансовый университет)

Abstract

Topic. The article examines the problems associated with forecasting of the development prospects of the economy.Purpose. The creation of a model used to predict the replenishment of budgets of all levels. Analysis of the state of the Russian economy in general and its 85 re gions.Methodology. The research was conducted on the basis of economic and statistical techniques, system analysis, and scientific methods of comparison and mapping. The work applied the proposed the authors the term “macroeconomic production function” — an analog of the production function, which expresses the dependence of production results of the enterprise and factors of production. We used data on tax revenues for all kinds of taxes, employment and gross regional product contained in consolidated informationanalytical system of regional tax revenues “Taxes of Russia”. Data analysis and estimation of parameters was performed using the programs of statistical data processing — IBM SPSS Statistics 20. In the multiple regression procedure of SPSS it was used methods of inclusion, allowing step-by-step selection in a regression equation only the significant independent variables.Results. Based on the proposed model, we conducted the comparison of actual and estimated values of tax revenues for all the subjects of the Russian Federation in 2011 and 2014. We obtained the values of point estimates of the model parameters of macroeconomic production functions. Further, we provided simulation of the values of tax revenues for all the subjects of the Russian Federation for 2014 year. Next, we compared the actual and calculated (from the model) values of tax revenues. Finally, we present the results of comparing the actual and estimated (from the model) values of tax revenues for all the subjects of the Russian Federation for 2014 year. Conclusions. The dependence of tax revenues from the factor of labor productivity is constant for every year. With the growth of capital, the amount of tax incomes of subjects of the Russian Federation was threefold higher than increase in productivity of labor. It can be used for planning of economic development of regions. Предмет. В статье исследуются проблемы, связанные с прогнозированием перспектив развития экономики страны.Цель. Создание модели, позволяющей прогнозировать пополнение бюджетов всех уровней. Анализ состояния экономики Российской Федерации в целом и ее 85 субъектов.Методология. Исследования проводились на основе экономико-статистических методов, системного анализа, а также общенаучных методов сравнений и сопоставлений. В работе применен предложенный авторами статьи термин «макроэкономическая производственная функция» — аналог производственной функции, которая выражает зависимость результатов производства предприятия от факторов производства. Используются данные о налоговых доходах по всем видам налогов, численности занятого населения и валовому региональному продукту, консолидированные в информационно-аналитической системе региональных налоговых поступлений «Налоги РФ». Анализ данных и оценка параметров проводились с помощью программы статистической обработки информации — IBM SPSS Statistics 20. В процедуре множественной регрессии SPSS использовались методы включения, позволяющие производить пошаговый отбор в регрессионное уравнение только значимых независимых переменных.Результаты. На основе предложенной модели проводится сравнение фактических и расчетных значений налоговых поступлений для всех субъектов РФ по данным за 2011 и 2014 гг. Получены значения точечных оценок параметров модели макроэкономической производственной функции. Проведено моделирование значений налоговых поступлений для всех субъектов РФ по данным 2014 г. Произведено сравнение фактических и расчетных (по представленной модели) значений налоговых поступлений. Представлены результаты сравнения фактических и расчетных (по представленной модели) значений налоговых поступлений для всех субъектов РФ по данным 2014 г. Выводы. Зависимость налоговых доходов от фактора производительности труда постоянна ежегодно. Объем налоговых доходов субъектов РФ с ростом капитала троекратно выше, чем от увеличения производительности труда. Это может быть использовано для планирования экономического развития регионов.

Suggested Citation

  • A. Kamaletdinov Sh. & A. Ksenofontov A. & А. Камалетдинов Ш. & А. Ксенофонтов А., 2018. "Моделирование Доходов Социально-Экономических Систем На Основе Производственной Функции // Modeling Of Income Of Socio-Economic Systems On The Basis Of The Production Function," Финансы: теория и практика/Finance: Theory and Practice // Finance: Theory and Practice, ФГОБУВО Финансовый университет при Правительстве Российской Федерации // Financial University under The Government of Russian Federation, vol. 22(1), pages 118-127.
  • Handle: RePEc:scn:financ:y:2018:i:1:p:118-127
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    References listed on IDEAS

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    1. Christian Dreger, 2017. "Long-term growth perspectives in Japan and the Euro area," Asia Europe Journal, Springer, vol. 15(4), pages 363-375, December.
    2. Gerald Daniels & Venoo Kakar, 2017. "Economic Growth and the CES Production Function with Human Capital," Economics Bulletin, AccessEcon, vol. 37(2), pages 930-951.
    3. Serena Brianzoni & Cristiana Mammana & Elisabetta Michetti, 2012. "Local and Global Dynamics in a Discrete Time Growth Model with Nonconcave Production Function," Working Papers 70-2012, Macerata University, Department of Finance and Economic Sciences, revised Sep 2015.
    4. Kang-Wook Lee & Wooyong Jung & Seung Heon Han, 2017. "Country Selection Model for Sustainable Construction Businesses Using Hybrid of Objective and Subjective Information," Sustainability, MDPI, vol. 9(5), pages 1-18, May.
    5. Mallick, Debdulal, 2012. "The role of the elasticity of substitution in economic growth: A cross-country investigation," Labour Economics, Elsevier, vol. 19(5), pages 682-694.
    6. Rainer Klump & Peter McAdam & Alpo Willman, 2012. "The Normalized Ces Production Function: Theory And Empirics," Journal of Economic Surveys, Wiley Blackwell, vol. 26(5), pages 769-799, December.
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