Please use this identifier to cite or link to this item: http://elar.urfu.ru/handle/10995/131779
Title: Regressional modeling and forecasting of economic growth for Arkhangelsk region
Authors: Goridko, N. P.
Nizhegorodtsev, R. M.
Issue Date: 2012
Publisher: Institute of Economics, Ural Branch of the Russian Academy of Sciences
Институт экономики Уральского отделения РАН
Citation: Goridko N. P. Regressional modeling and forecasting of economic growth for Arkhangelsk region / N. P. Goridko, R. M. Nizhegorodtsev // Economy of Region. — 2012. — Iss. 4. — P. 122-130.
Abstract: 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.
Keywords: AUTOREGRESSION
CONFIDENCE INTERVAL OF THE FORECAST
ECONOMIC GROWTH FACTORS
REGRESSION MODEL
TREND VALUE
URI: http://elar.urfu.ru/handle/10995/131779
Access: info:eu-repo/semantics/openAccess
SCOPUS ID: 84991434552
ISSN: 2411-1406
2072-6414
DOI: 10.17059/2012-4-12
Origin: Экономика региона. 2012. Выпуск 4
Appears in Collections:Economy of Regions

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