Макроэкономическое моделирование в условиях инновационности и неопределенности
Today, macroeconomic processes are determined by factors of political turbulence, rapid development of innovations and other economic shocks. In this regard, the problem of choosing methods and models that adequately meet modern needs and allows achieving reliable results of macroeconomic forecasting becomes more relevant. The article proves the relevance of DSGE modeling methodology to existing challenges. It is shown that this concept serves as a tool for forecasting and foresight as a purposeful activity for the formation of a desirable future. It also helps to identify the value of innovations in the economic system. Conclusions of the study can be used to improve the state economic policy.
The collection of materials of the International Conference
This book develops foresight techniques to turn future societal challenges into opportunities. The authors present foresight approaches for innovation policy and management. Future developments in fields such as education, energy, new materials, nanotechnologies are highlighted for different countries. Readers will discover tools and instruments to capture the potentials of the grand societal challenges as defined by the United Nations. This book is a valuable resource for researchers and scholars with an interest in foresight methods and gives practical hints for policy makers and managers to take account of the grand opportunities in their business and policy strategies.
When doubt arises in a decision-making situation, a polyphony of inner voices may emerge, each voice motivating the person towards a specific choice option, often even suggesting reasons in favour of this option. The paper presents two steps of a proposed method that facilitates finding an authentic position. During the first step, inner voices are verbalised, and specific nuances of their intonation are paid attention to. At the second step, the person is asked to feel and estimate how close each of these voices is to his or her own deeper Self. Examples of application of the method within counseling practice are presented.
Decision-makers at all levels are being confronted with novel complexities and uncertainties and face long-term challenges which require foresight about long-term future prospects, assumptions, and strategies. This book explores how foresight studies can be systematically undertaken and used in this context. It explicates why and how methods like horizon scanning, scenario planning, and roadmapping should be applied when dealing with high levels of uncertainty. The scope of the book moves beyond “narrow” technology foresight, towards addressing systemic interrelations between social, technological, economic, environmental, and political systems. Applications of foresight tools to such fields as energy, cities, health, transportation, education, and sustainability are considered as well as enabling technologies including nano-, bio-, and information technologies and cognitive sciences. The approaches will be illustrated with specific actual cases.
Technology mining (TM) helps to acquire intelligence about the evolution of research and development (R&D), technologies, products, and markets for various STI areas and what is likely to emerge in the future by identifying trends. The present chapter introduces a methodology for the identification of trends through a combination of “thematic clustering” based on the co-occurrence of terms, and “dynamic term clustering” based on the correlation of their dynamics across time. In this way, it is possible to identify and distinguish four patterns in the evolution of terms, which eventually lead to (i) weak signals of future trends, as well as (ii) emerging, (iii) maturing, and (iv) declining trends. Key trends identified are then further analyzed by looking at the semantic connections between terms identified through TM. This helps to understand the context and further features of the trend. The proposed approach is demonstrated in the field photonics as an emerging technology with a number of potential application areas.
Foresight has gained much attention as a tool for developing and informing science, technology and innovation policy and company strategies. It is frequently used for detecting not only potential development paths of technologies but also possible economic and societal changes; and for identifying challenges that nations, societies and companies might face in the future. Raising awareness within the respective communities of trends and challenges is critically important—and the biggest challenge is how we can develop measures to meet these anticipated challenges. Paradoxically, perhaps, it may be more helpful for creating and implementing successful measures if these are elaborated by thinking about grasping opportunities, rather than framing them in terms of threats that have to be responded to. Accordingly there is a need to change the mindsets in science, technology and innovation policy making—and to engender solution and opportunity orientation among scientists and engineers.
In this paper we propose a method for predicting significant multivariate nonstationary time series, ie series, in which changes in the structure, variables, or model coefficients of the variables. Due to the time-dependent processes that give rise to economic indicators, most economic time series falls into the category under consideration. The need to predict rate of capital flight as the subject of investigation, the volume of Russian investment abroad of non-banking corporations, as its major component.
Technology foresight has been increasingly undertaken by developing countries to identify technologies whose adoption might serve as a platform for future economic growth. However, foresight activities have not, by and large, resulted in well-developed policy initiatives. Three factors are relevant for improvement. First, foresight activities would benefit from being more informed by the convergence literature and global convergence experience over the past several decades, and should therefore incorporate organically the concepts of absorptive capacity and technology gap into foresight exercises. Second, certain preconditions – in particular the existence of a functional national innovation system – enhance the likelihood that foresight exercises will be successful. Third, in order to achieve wide buy-in and promote the sustainability of initiatives generated by the foresight activity, developing countries are advised to consult widely in the foresight process. Policies emanating from foresight activities should additionally address two core challenges: a) a clear definition of those technologies that should be developed internally vs. those that should be sourced from abroad and b) identification of the internal capabilities to be developed in conjunction with those technologies targeted for acquisition from abroad.
Science, technology and innovation (STI) involves numerous policy fields which are championed by different government ministries or agencies. A consistent and coherent anticipatory policy mix is understood to be one that ensures a timely development and implementation of various forward-looking policy instruments. Such timely implementation is crucial for the eventual impact of the policy measures. This also requires that foresight for STI policies looks beyond the potential development paths and challenges but includes the time dimension and the outline of necessary policy responses including a relevant implementation framework. In addition the institutions which are part of the National Innovation Systems (NIS) should to be considered thoroughly for a well-balanced and comprehensive policy mix. Not only national but also regional and local actors need to be involved—and they need to be involved not only in the implementation of policy but at much earlier stages in the foresight and subsequent design procedures of the policy mix. One practical approach for convincing and engaging NIS actors at different levels is to stress opportunities which offer advantages to each of them, instead of just focusing on challenges and problems.
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.