Национальная система стандартизации Российской Федерации. Принципы, цели, задачи, прогноз развития
Any company in market economy faces with a problem of acceptance of strategic decisions, under conditions of uncertainty concerning the future. Under conditions of economic crisis when level of uncertainty increases, this problem becomes especially actual. One of methods for reduction the influence of the uncertainty factor by the company activity, received a new push to development in second half of twentieth century, is the scenario approach. It gives responsibility to analyze the influence of possible changes of factors and their combinations on company's activity and to make a decision on adequacy of strategy of company's development and possibility of its realization in the given economic situation. Given article offers one of possible techniques of the scenario approach with reference to realization of strategy of the company, based on the algorithm within the limits of model of scenarios research, developed by Bryant&Lempert (2010). Simulation model, on the basis of which scenarios are developed, can consider both internal strategic variables, and a considerable amount of external factors which influence company's activity.
The reality is that uncertainty and different orientation of real estate market trends and a lasting time frame of investment planning are obvious nowadays. Under such conditions, the scenario analysis of risks increases the project loss assessment efficiency. In the long run, this fact might be of paramount importance in order to make efficient managerial decisions in the course of a project realization, moreover— in order to make the final evaluation of a project.
The paper deals with groundbreaking distinctive characteristics of scenario approach, i.e. review and collation of approaches, which are designed to define ‘scenario’ as a notion. The author classifies the approaches and presents methods of identification of scenarios as the most complex step in assessing a risk. The results of the analysis will make it possible to develop a scenario algorithm for assessing risks of a residential real estate project.
The paper examines the structure, governance, and balance sheets of state-controlled banks in Russia, which accounted for over 55 percent of the total assets in the country's banking system in early 2012. The author offers a credible estimate of the size of the country's state banking sector by including banks that are indirectly owned by public organizations. Contrary to some predictions based on the theoretical literature on economic transition, he explains the relatively high profitability and efficiency of Russian state-controlled banks by pointing to their competitive position in such functions as acquisition and disposal of assets on behalf of the government. Also suggested in the paper is a different way of looking at market concentration in Russia (by consolidating the market shares of core state-controlled banks), which produces a picture of a more concentrated market than officially reported. Lastly, one of the author's interesting conclusions is that China provides a better benchmark than the formerly centrally planned economies of Central and Eastern Europe by which to assess the viability of state ownership of banks in Russia and to evaluate the country's banking sector.
The paper examines the principles for the supervision of financial conglomerates proposed by BCBS in the consultative document published in December 2011. Moreover, the article proposes a number of suggestions worked out by the authors within the HSE research team.
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.