ASSESSMENT OF INFLUENCE OF NEW TECHNOLOGIES AND THE HUMAN CAPITAL ON FORMATION OF NEW WAYS IN ECONOMY OF RUSSIA
Abstract and keywords
Abstract (English):
Econometric model of the influence of intensity of labor of new fixed assets and human capital, characterized by the level of education of workers, on the contribution of new technological ways in per capita GDP in the modern Russian economy are obtained. Flexibility of the contribution of new orders in the per capita GDP on new technologies, new capital-labor estimated asset is 2.2–2.3. Increasing of intensity of labor of new fixed assets of 1% can increase the contribution of new technological ways in per capita GDP at 2.2–2.3%. The elasticity of the contribution of new orders in the per capita GDP in human capital, evaluating by the level of education of employed workers, measured by the number of years of education in the education system, is 11.7. Increasing of the level of education of employed workers by 1% can increase the contribution of new technological ways in per capita GDP.

Keywords:
new technological way, GDP per capita, new fixed assets, the level of education, econometric models.
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Цель данной работы — исследование влияния новых технологий и человеческого капитала на продуктивность новых — пятого и шестого технологических укладов в экономике современной России. Эмпирические исследования влияния производственных факторов на продуктивность новых технологических укладов в масштабах страны в настоящее время не привлекают должного внимания экономистов. При этом исследования влияния производственных ресурсов на производительность и рост производства нашли отражение во многих  эмпирических исследованиях. Проводятся исследования с использованием данных по странам мира и регионам, проверятся широкий набор факторов. Эмпирические исследования влияния факторов, как правило, основаны на построении линейных регрессионных моделей, которые включают оценки различных видов ресурсов, в том числе инвестиции в физический и человеческий капитал. Для исследования используют перекрестные данные стран, регионов или временные ряды.

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