ESTIMATION AND FORECAST OF REGIONAL COMPETITIVENESS LEVEL
Galina Gagarina (),
Nikita Moiseev (),
Alla Ryzhakova and
Gleb Ryzhakov
Additional contact information
Galina Gagarina: Plekhanov Russian University of Economics
Nikita Moiseev: Plekhanov Russian University of Economics
Alla Ryzhakova: Plekhanov Russian University of Economics
Gleb Ryzhakov: Plekhanov Russian University of Economics
Economy of region, 2016, vol. 1, issue 4, 1040 - 1049
Abstract:
The paper is devoted to the development of methods for point and interval forecasting of the integral index of regional competitiveness. We stick to one of the most commonly used approaches to assessing the level of competitiveness based on its advantages over the others. As a result of this approach, the integral competitiveness index appears to be bounded, i.e. has a lower and upper limit. Due to this particular feature, it is proposed to carry out the forecasting of competitiveness index using multivariate logistic regression. The parameters of such model are determined using OLS through an inverse logarithmic transformation of the dependent variable. To calculate interval forecasts for the model, we proposed a new probability distribution for the errors of the nonlinear regression equation in the class of logistic curves. According to the proposed method, we calculated and forecasted the regional competitiveness level for the Russian Federation until 2020. The analysis of the data revealed some features of the regions distribution in terms of competitiveness level and indicated regional development trends. The paper has been prepared within the research project â„–1675: "Methodological and analytical tools for solving problems of spatial development of Russian economy under conditions of modern reforms" in terms of the basic part of the state order in the field of scientific activity of Russian Ministry of Education.
Keywords: integral index of competitiveness; time series forecasting; prediction of bounded variables; logistic regression; OLS; multifactor linear regression (search for similar items in EconPapers)
JEL-codes: C52 C53 (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (1)
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Persistent link: https://EconPapers.repec.org/RePEc:ura:ecregj:v:1:y:2016:i:4:p:1040-1049
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