Individual Returns to Training in a Russian Firm
Estimating mincer-type wage equations on the micro-data of Occupational Wages Survey, 2007 we first receive estimates for returns to higher education for all regions-subjects of Russian Federation. Our results show that interregional differentces in returns are very large in Russia. Returns to higher education received from the estimation of basic mincerian equation lie in the range from 32 to 140% (from the average wage of workers with secondary education), and the country level of return equals to 65%. Variation in estimates based on an augmented wage equation (which additionally includes industries and ownership) is much lower, but it still remains quite substantial: estimates differ from about 60 to 150%, and the country level of return equals to 90%. In this regard, the standard approach producing one estimate of return to education for the whole country seems to be a serious simplification, and an answer to the question what is the level of return to education in Russia is no more trivial.
отдача от образования, РЕГИОНЫ, РОССИЯ, Return to Education, Regions, Russia
This paper is devoted to the rational behavior in the sense of the educational level choice. The theoretical model is based on the discounted flow of personal’s utility function covered the period of the education and future work. Maximizing the flow under the budget constraint we received differential equation included the rate of income grow after the acquisition of education. The solution is the Mincerian type equation. The main result of the model is that the persons with rapid growth of their earnings profile should have the smaller slope coefficients of schooling in the earnings equation. The empirical part of the research is based on the Russian Longitudinal Monitoring Survey (RLMS) data set. The theoretical results have been confirmed by the regression analysis. Splitting the RLMS sample according to the respondents’ wage profiles we received that highly educated agents unlike the unskilled workers have higher income but slighter slope earnings profiles. It means that the workers expected the high growth of their incomes after the schooling are less inclined to receive higher level of education. Otherwise the persons who expected high income on the job start justify their hopes, but come across the low growth of the incomes.
Editors Neal Chalofsky, Tonette Rocco, and Michael Lane Morris have compiled a collection of chapters sponsored by the Academy of Human Resource Development that provide revolutionary insight into the concepts, theories, research initiatives, and practical applications essential to HRD. Topics range from HRD foundations, workforce development, and management to more specific topics such as implementing and managing HRD initiatives in the organization. The chapters are written by professionals who offer a wide range of experience and who represent the industry from varying international and demographic perspectives. The questions addressed include:
• Nationally and internationally, how does HRD stand with regard to academic study and research?
• What is its place in the professional world?
• What are the philosophies, values, and critical perspectives driving HRD forward?
• What theories, research initiatives, and other ideas are required to understand HRD and function successfully within this field?
• As the industry grows, what are the challenges and important issues that professionals expect to face? What hot topics are occupying these professionals now?
The concept and aim of evidence-based entrepreneurship (EBE) is discussed as a strategy to overcome the divide between knowledge developed in the field of entrepreneurship and its use in practice. We argue that meta-analyses can and should be used in entrepreneurship research (and that it should also be used for qualitative work).
In this work the demand for the incoming tourism in the Russian Federation is modeling. The panel data for 16 countries - the basic sources of tourist streams - and the period with 2000 for 2009 are used. Modeling is spent separately for each of 10 tourist zones of Russia. In quality a determinant of demand there are considered a total national product in a country of origin, the exchange rate, transport charges, cost of residing, lag of the demand variable and the fictitious variables reflecting influence of shocks in quality a determinants of demand. The received estimations of dynamic models of demand correspond to expectations, are statistically significant and can be useful in practice of planning of development of entrance tourism in various municipal formations and regions of Russia.