Venture capital (VC) provides financial and managerial support for new innovative ideas at the initial stages of commercialization. It has helped to find the market for many radical innovations of 20th century, including personal computer, Internet and genetic engineering.
As a part of market economy venture business was not stable from the very beginning. The periods of rapid growth alternated with deep recessions. However each time VC revived anew as the Phoenix due to its very important function in modern knowledge-based economy.
This report presents an analysis of statistical data that prove the existence of several cycles in VC dynamics in the USA and the Great Britain. The main factors of these cycles formation are discussed. The author proposes two possible scenarios of development of VC market for the first 30 years of the new 21st century. A hypothesis is put forward about the relation between VC cycle's amplitude and a phase of Kondratieff's cycle.
This article discusses the theoretical and methodological issues proposed for use in Russia of a new funding mechanism for big ticket investment leasing projects. To achieve this goal are the following: a new version of the classification of leasing with the view in her special place leveraged-leasing; a critical analysis of the model of leveraged leasing, identifying its strengths and weaknesses; developed proposals for the formation of the Russian model leveraged-leasing; analyzed the feasibility of a mechanism of syndicated lending in the leveraged-leasing; is the formation of quantitative and qualitative criteria for big ticket transactions for Russian leasing market, taking into account the foreign and domestic experience; set a price on leasing contracts on interest rates, taking into account the necessary redundancy associated with the assessment of welfare and allowances for losses on defaulted lessors and lessees; using regression analysis, the hypothesis is that, despite the increased risks from the lessor, are associated with increased incidence and duration of contracts, reduce the advances, the relative reduction of prices on realization of investment projects in the leveraged-leasing; developped а methodology for determining leverage leasing projects; prepare recommendations on formation of pricing models leverage-leasing; analyzes the proportions between financial institutions in overseas leasing transactions and in the Russian leasing market; is determined by the relevance and benefits of using this model for Russia.
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.