Stress Scenario Development: Global Challenges for the Russian Agricultural Sector
Automated identification of new technology trends (trend monitoring, trend hunting, trend watch) is among the hot topics in technology management. Despite many beneficial results in this field, almost no solutions allow users to escape from getting too general or garbage results which make it impossible to identify trends at the stage of weak signals. Lack of attention is paid to automated labeling and merging (for the ‘same’ trends).
Our approach aimed at overcoming such drawbacks is based on the ‘BlackBox’ principle. The concept of a technology trend (TT) is characterized by a complex nature, low formalization level, blurred boundaries, and high degree of domain dependency leading to the need for expert knowledge. For all that, ‘Big Data’ in IT and ‘Genome Editing’ in Healthcare should have some similar features which actually allow us to name both phenomena ‘a TT’. This leads us to an idea of hunting for domain independent ‘external signs’ (trend indicators) while letting a TT itself stay a black box for an observer.
We employ Gartner’s Hype Cycle in our methodology. We build an elaborate ontology of a TT and a system of indicators of TTs ‘presence’ in documents of various genres. The indicators are interrelated with the ontology through linguistic and extra linguistic markers. Both markers and text genres are mapped onto the phases of a technology life cycle. The ontology-driven information extraction (IE) is carried out.
Future-oriented technology analysis methods can play a significant role in enabling early warning signal detection and pro-active policy action which will help to better prepare policy- and decision-makers in today’s complex and inter-dependent environments. This paper analyses the use of different horizon scanning approaches and methods as applied in the Scanning for Emerging Science and Technology Issues project. A comparative analysis is provided as well as a brief evaluation the needs of policy-makers if they are to identify areas in which policy needs to be formulated. This paper suggests that the selection of the best scanning approaches and methods is subject to contextual and content issues. At the same time, there are certain issues which characterise horizon scanning processes, methods and results that should be kept in mind by both practitioners and policy-makers.
This article looks at the evolution of state agricultural policy in the context of a change in the general political line from the radical liberalism of the 1990s to state patronage and active support of the agricultural sector today. The privatization of land and the creation of private farms, the National Priority Project Development of the Agro-Industrial Complex, the adoption of Russia’s Food Security Doctrine, Russia’s accession to the WTO, and import substitution in response to Western sanctions are considered as stages of this policy. The author draws the conclusion that agricultural policy is inconsistent because of its excessive dependence on the political context, as determined by foreign policy collisions and the transformation of Russia’s internal development model.
Having reviewed existing global energy forecasts made by reputable multilateral and national government agencies, major energy corporations and specialized consulting firms, the authors noticed that most of them are by and large based on extrapolation of conventional long-term trends depicting gradual growth of fossil fuels demand and catching-up supply. Unlike this approach the paper focuses on the possible cases when conventional trends are broken, supply-demand imbalances become huge and the situation in the global energy markets is rapidly and dramatically changing with severe consequences for Russian economy, seriously dependent on fossil fuels exports. Revealing these stress scenarios and major drivers leading to their realization are in the focus of the research. Basing on STEEPV approach the authors start from analyzing various combinations of factors capable to launch stress scenarios for Russian economy. Formulating concrete stress scenarios and assessing their negative impact on Russian economy constitute the next step of the analysis. In conclusion the paper underlines the urgency to integrate stress analysis related to global energy trends into the Russian national systems of technology foresight and strategic planning, which are now in the early stages of development.
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.