Конкурентоспособность экономики в эпоху глобализации: российский и международный опыт: материалы Международной научно-практической конференции (Белгород, 9-10 октября 2012 г.)
This paper examines how export and export destination stimulates innovation by Russian manufacturing firms. The discussion is guided by the theoretical models for heterogeneous firms engaged in international trade which predict that, because more productive firms generate higher profit gains, they are able to afford high entry costs, and trade liberalization encourages the use of more progressive technologies and brings higher returns from R&D investments. We will test the theory using a panel of Russian manufacturing firms surveyed in 2004 and 2009, and use export entry and export destinations to identify the causal effects on various direct measures of technologies, skill and management innovations. We find evidence on exporters’ higher R&D financing, better management and technological upgrades. Exporters, most noticeably long-time and continuous exporters, are more active in monitoring their competitors, both domestically and internationally, and more frequently employ highly qualified managers. Exporters are more active in IT implementation. When it comes to export destination, we find that non-CIS exporters are more prone to learning. However, we cannot identify that government or foreign ownership shows any impact on learning-by-exporting effects.
This article assesses the level of openness of Russian economy. It is shown that the open-ness indicators used in the Concept of Long-term Social and Economic Development of the Russian Federation differ from those employed by international organisations. The present research analyses both the intensity of Russian trade in terms of its gross domestic product and the relative strength of import penetration in Russia. Methodological differences determine the differences in the analysis results.
In this paper we study convergence among Russian regions. We find that while there was no convergence in 1990s, the situation changed dramatically in 2000s. While interregional GDP per capita gaps still persist, the differentials in incomes and wages decreased substantially. We show that fiscal redistribution did not play a major role in convergence. We therefore try to understand the phenomenon of recent convergence using panel data on the interregional reallocation of capital and labor. We find that capital market in Russian regions is integrated in a sense that local investment does not depend on local savings. We also show that economic growth and financial development has substantially decreased the barriers to labor mobility. We find that in 1990s many poor Russian regions were in a poverty trap: potential workers wanted to leave those regions but could not afford to finance the move. In 2000s (especially in late 2000s), these barriers were no longer binding. Overall economic development allowed even poorest Russian regions to grow out of the poverty traps. This resulted in convergence in Russian labor market; the interregional gaps in incomes, wages and unemployment rates are now below those in Europe. The results imply that economic growth and development of financial and real estate markets eventually result in interregional convergence.
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.