Political Loyalty vs Economic Performance: Evidence from Machine Politics in Russia’s Regions
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 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.
What role does the business play in economic growth? What circumstances are necessary for the stable business development? Recent literature focuses on the factors of business environment promoting or constraining firm growth. Using the country aggregate values of the firm-level World Bank Enterprise Survey (WBES) data on the subjective estimates of the business obstacles 128 countries are classified into six clusters. Due to the fact that firms report many obstacles to growth the contributions of 13 obstacles to business environment are recalculated for understanding the major business constraints. Lastly, cross tables analysis finds that there is a correlation between the prevalence of the business obstacles and national income growth, export growth, high-technology export. The results have important implications for the priority of reforms. Corruption, electricity and tax rates are the main business constraints in the world. Moreover, access to finance and competition in the informal sector of economy are also the major obstacles for business in the part of the countries.
A political scientist examines how regional elites shape the electoral fortunes of Russia’s hegemonic party, United Russia (UR). Using original data on regional legislative elections from 2003 to 2011, we show that UR performs better in those regions where regional governors control strong political machines. Russia’s leadership undercut its own electoral strategy by replacing popular elected governors with colorless bureaucrats who struggled to mobilize votes on behalf of United Russia. This is one of the reasons for United Russia’s poor performance in recent elections.
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.
We address the external effects on public sector efficiency measures acquired using Data Envelopment Analysis. We use the health care system in Russian regions in 2011 to evaluate modern approaches to accounting for external effects. We propose a promising method of correcting DEA efficiency measures. Despite the multiple advantages DEA offers, the usage of this approach carries with it a number of methodological difficulties. Accounting for multiple factors of efficiency calls for more complex methods, among which the most promising are DMU clustering and calculating local production possibility frontiers. Using regression models for estimate correction requires further study due to possible systematic errors during estimation. A mixture of data correction and DMU clustering together with multi-stage DEA seems most promising at the moment. Analyzing several stages of transforming society’s resources into social welfare will allow for picking out the weak points in a state agency’s work.