Analysis of the dynamics and factors of the growth of cities of Russia in the post-Soviet period.

Relevance of the study was that in the period of globalization in cities is concentrated the greatest potential for economic growth and welfare. Cities as economic units within itself create synergies that allow you to save costs of economic actors, thereby increasing the standard of living. Capital, intellectual and other resources are important for growth of life’s quality. However, at the present time there is no comprehensive understanding of the reasons why some cities are growing faster than others. Object of study were cities of the Russian Federation with a population of over 100,000 people. The subject of the study were the socio-economic characteristics of cities, its dynamics and interactions. The purpose of the research was to determine the factors based on economic growth of cities and influenced on its dynamics. For achievement the objectives of the study the following tasks have been solved: 1.Existing scientific directions, articles and empirical research by topics operation were considered; 2.The factors that can have influence on economic growth of the city were selected. 3.Database for analysis economic urban growth with selected factors was built. 4.Economic growth of the cities and selected factors was analyzed. 5.Regression model economic urban growth was built. 6.Factors that have influence on economic urban growth was analyzed. 7.The results at regression Model and analysis of factors were summarized. The first chapter of the study depict the main research directors related to the economy of cities, both theoretical and empirical studies of foreign and domestic authors on the subject. According to the results of the review that was made selection of factors that can influence on the rate of economic growth of the city. The research proposes a method for measurement at convergence of cities by paces of growth of economic indicators, which permit to assess the degree of convergence / divergence by indexes of dynamics. According to this method it can analyzed the dynamics of changes of economic indicators. In the sample examined there is the convergence by pace of growth, wages and investment, and the divergence by growth rates of employment and economic growth of the city. Considering the method of construction the index of economic growth of the city it can be concluded that the divergence by the rate of employment growth considered period is more important than the convergence of the growth rate of wages. The third chapter is based on a linear regression model by averaged parameters over the period 1999-2011, where the dependent variable appears as the average annual economic growth of the city for a 13 year period. The most appropriate of the two models of economic growth model has the following form: Y = 0,0375 + 0,0005 * X2 + 0,0422 * X3 + 0,0838 * X4 + 0.0020 * X5 + 0.0817 * X6 - 0,00281 * X12 + 0,0095 * X13, where •Y - average annual rate economic growth of the city; •X2 - volume investment on unit Population (thousand. rubles. in 1999 prices); •X3 - average share budget investment; •X4 - average rate growth capital- labor; •X5 - average annual clean migratory increase (ppm); •X6 - deviation by module share employment in Industry in de Goro from the average for the sample (30%); •X12 - distance to Moscow (thousand. Km.) •X13 - accessory City to Regional center. The coefficient of determination for this model is 0.29. Ending paragraph of the third chapter analyzes the factors that are relevant for the linear regression model. For the average share of budget investment and average annual net migration were constructed a linear regression model with factors by status of the city center and the regional share of employment in the industry for the first indicator, the distance to Moscow and the share of employment in the industry for the second indicator. By the results of a linear regression model for urban growth, as well as analysis of relevant factors it has been built flowchart indicating the regression coefficients, the reasons for its influence based on theoretical studies, discussed in Chapter 1.