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Economic Analysis: Theory and Practice
 

Econometric analysis of gross domestic product of Russia and its relations to investment in fixed assets, volume of employment in the economy, and oil and gas production

Vol. 15, Iss. 2, FEBRUARY 2016

PDF  Article PDF Version

Received: 28 December 2015

Accepted: 11 January 2016

Available online: 4 March 2016

Subject Heading: MATHEMATICAL METHODS AND MODELS

JEL Classification: C22, C51, E22, O11

Pages: 183-196

Kozinova A.T. Lobachevsky State University of Nizhny Novgorod – National Research University, Nizhny Novgorod, Russian Federation
antonina.kozinova@gmail.com

Subject The article presents the econometric analysis of macroeconomic indicators of Russia, i.e. gross domestic product, investment in fixed assets, volume of employment in the economy, and oil and gas production.
Objectives The aim is to develop effective models to analyze the gross domestic product of Russia and its relations to macroeconomic indicators.
Methods The study employs correlation and regression analysis of statistical data from Quarter 4, 2003 to Quarter 3, 2014.
Results During the period under consideration, there is a strong direct correlation of GDP trend with trends in the investment in fixed assets and the number of employed in the economy. At the same time, there is a moderate correlation of the GDP trend with trends in oil and gas production. There is a strong direct correlation of seasonal fluctuations of GDP with seasonally adjusted investment in fixed capital and oil production. Meanwhile, there is moderate correlation of seasonally adjusted GDP and the volume of employment in the economy. The correlation of seasonally adjusted GDP and gas production was weak. Based on the correlation analysis results, I offer various models and analyze their quality.
Conclusions Parameters of statistically significant models with factor indicator can be used for quantitative assessment of their impact on GDP. Parameters of models with dummy variables in the crisis component can be used for quantitative assessment of changes in GDP during crises.

Keywords: correlation, regression, dummy variable, trend, seasonal fluctuation, model

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