Universities' Efficiency and Regional Economic Short-run Growth: Empirical Evidence from Russia
This paper studies structural transformation and its implications for productivity growth in the BRIC countries (Brazil, Russia, India, and China) from the 1980s onwards. Based on a critical assessment of the reliability and consistency of various primary data sources, we bring together a new database that provides trends in value added and employment at a detailed 35-sector level. Structural decomposition analysis suggests that for China, India and Russia reallocation of labour across sectors is contributing to aggregate productivity growth, whereas in Brazil it is not. This confirms and strengthens the findings of McMillan and Rodrik [NBER working paper 17143, 2011]. However, this result is overturned when a distinction is made between formal and informal activities within sectors. Increasing formalization of the Brazilian economy since 2000 appears to be growth-enhancing, while in India the increase in informality after the reforms is growth-reducing.
We expect economic growth to remain strong in Poland and Latvia in 2016. Despite this robust growth, the new Polish government is likely to soften monetary and fiscal policies to further stimulate the economy, in our view. In 2015, the Latvian economy demonstrated strong resilience to external shocks.
The balance of the world economy is shifting away from the established economies of Europe, Japan, and the USA, towards the emerging economies of Asia, especially India and China. With contributions from some of the world's leading growth theorists, this book analyses the long-term process of structural change and productivity growth across the world from a unique comparative perspective. Ongoing research from the World KLEMS Initiative is used to comparatively study new sources of growth - including the role of investment in intangible assets, human capital, technology catch-up, and trade in global value chains. This book provides comparisons of industries and economies that are key to analysing the impacts of international trade and investment. This makes it an ideal read for academics and students interested in understanding current patterns of economic growth. It will also be of value to professionals with an interest in the drivers of economic growth and crisis.
The world, of late, has seen a productivity slowdown. Many countries continue to recover from various shocks in the macro business environment, along with structural changes and inward looking policies. In contemporary times of growth slumps, various exits and protectionist regimes, this book engages with the study of productivity dynamics in the emerging and industrialized economies. The essays address the crucial aspects, such as the roles of human capital, investment accounting and datasets, that help understanding of productivity performance of global economy and its several regions.
The purpose of the work is to model disproportions in development of regional economy of Russia and to determine perspectives and recommendations for overcoming them and achieving the balance of the economy. The applied methods are based on Popkova's methodology of calculation of “underdevelopment whirlpools,” which allows conducting dynamic modeling of disproportions in development of regional economy. The research is performed in three consecutive stages. At the first stage, the dynamic model of development of the Russia's regional economy is compiled with the help of the methodology of “underdevelopment whirlpools” in federal districts of the Russian Federation based on GDP per capita. At the second stage, the key factors of emergence of disproportions in development of the Russia's regional economy are determined and models of multiple regression of development of the Russia's regional economy are compiled. At the third stage, target parameters of the determined factors are set for reducing the “underdevelopment whirlpools” in the Russia's regional economy by automatized solution of the optimization task with application of the simplex method and recommendations for overcoming the disproportions in development of the Russia's regional economy are compiled. As a result, it is concluded that regional economy of Russia is not well-balanced, as it has deep structural disproportions. These disproportions are caused by insufficient attention to peculiarities of regional economic systems during development and implementation of regional strategies of state management of economy. For more precise accounting of the influence of the key factors of appearance of disproportions and highly-effective management of them for overcoming the “underdevelopment whirlpools,” the algorithm of overcoming the disproportions in development of the Russia's regional economy is developed by the authors, which envisages various managerial measures depending on peculiarities of each Russian region.
The fundamental idea underpinning spatial econometric models of economic growth is as follows: regional growth is determined not only by social, economic, geographic traits of a region but also by spillovers from other regions, most importantly adjacent ones. If one region starts booming, it can left neighbors unaffected (neutral mechanism), spur their growth (cooperation mechanism) or slow their growth by pulling resources over (competition mechanism). What mechanism and to which extent occurs in practice matters for designing balanced economic policy and evaluating efficiency of regional policy investment. Classic spatial econometric models make strong although simplifying assumption that the same mechanism matters for all regions in the same manner, and there is no variation in spillovers intensity across regions. This assumption seems plausible for relatively small and homogenous regions of European countries, but it looks excessively strong for large and diverse Russian regions. In this paper we attempt to relax this assumption and propose a new model, fitting better in Russian conditions and bringing only slight sophistication from the estimation point of view. We introduce sensitivity parameter governing regional exposure to externalities. We assume this parameter to be a linear function of region-level observables, like area, population density or urbanization rate. These hypotheses have been confirmed at least partially. We found that dense and urbanized regions were more sensitive to spillovers. In other words, a region surrounded by the fast-growing areas, will grow the more intense, the more its population density and the higher the level of urbanization.