Циклы, кризисы, ловушки современной Мир-Системы. Исследование кондратьевских, жюгляровских и вековых циклов, глобальных кризисов, мальтузианских и постмальтузианских ловушек
The paper represents the review of contemporary approaches to the analysis of financial market imperfections and financial crises and their impact on fluctuations of the key macroeconomic variables during the business cycle as well as the transmission mechanism of financial shocks on the real economy in the framework of New Keynesian dynamic stochastic general equilibrium models. These models are widely used for the evaluation of monetary policy effects on macroeconomy and constitute the theoretical base for elaboration the optimal monetary policy not only during the crisis but for the further perspective. The construction of such models types for different economies including the Russian economy requires considering the institutional features and specific development and functioning characteristics of the of the national financial sector and economy as a whole.
Analyzing the reasons of financial crises in the book «The Black Swan» N.N. Taleb concludes that modern economic models badly describe reality for they are not able to forecast such crises in advance. We tried to present processes on stock exchange as two random processes one of which happens rather often (regular regime) and the other one - rather rare. Our answer is that if regular processes are correctly recognized with the probability a bit higher than 1/2, this allows to get positive average gain. We believe that this very phenomenon lies in the basis of unwillingness of people to expect crises permanently and to try recognizing them.
ФИНАНСОВЫЕ КРИЗИСЫ, биржа, пуассоновский процесс, financial crises, Stock exchange, Poisson processes
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.