Regressional modeling and forecasting of economic growth for Arkhangelsk region

• Published in: Economy of Region
• Main Authors: Goridko, N. P., Nizhegorodtsev, R. M.
• Format: Article in Journal/Newspaper
• Language: Russian
• Published: Institute of Economics, Ural Branch of the Russian Academy of Sciences 2012
• Subjects: AUTOREGRESSION; CONFIDENCE INTERVAL OF THE FORECAST; ECONOMIC GROWTH FACTORS; REGRESSION MODEL; TREND VALUE; Arkhangelsk
• Online Access: http://elar.urfu.ru/handle/10995/131779; https://doi.org/10.17059/2012-4-12

The regression models of GRP, considering the impact of three main factors: investment in fixed assets, wages amount, and, importantly, the innovation factor –the expenditures for research and development, are constructed in this paper on the empirical data for Arkhangelsk region. That approach permits to evaluate explicitly the contribution of innovation to economic growth. Regression analysis is the main research instrument, all calculations are performed in the Microsoft Excel. There were made meaningful conclusions regarding the potential of the region's GRP growth by various factors, including impacts of positive and negative time lags. Adequate and relevant models are the base for estimation and forecasting values of the dependent variable (GRP) and evaluating their confidence intervals. The invented method of research can be used in factor assessment and prediction of regional economic growth, including growth by expectations.