67,933 research outputs found
Complex networks analysis in socioeconomic models
This chapter aims at reviewing complex networks models and methods that were
either developed for or applied to socioeconomic issues, and pertinent to the
theme of New Economic Geography. After an introduction to the foundations of
the field of complex networks, the present summary adds insights on the
statistical mechanical approach, and on the most relevant computational aspects
for the treatment of these systems. As the most frequently used model for
interacting agent-based systems, a brief description of the statistical
mechanics of the classical Ising model on regular lattices, together with
recent extensions of the same model on small-world Watts-Strogatz and
scale-free Albert-Barabasi complex networks is included. Other sections of the
chapter are devoted to applications of complex networks to economics, finance,
spreading of innovations, and regional trade and developments. The chapter also
reviews results involving applications of complex networks to other relevant
socioeconomic issues, including results for opinion and citation networks.
Finally, some avenues for future research are introduced before summarizing the
main conclusions of the chapter.Comment: 39 pages, 185 references, (not final version of) a chapter prepared
for Complexity and Geographical Economics - Topics and Tools, P.
Commendatore, S.S. Kayam and I. Kubin Eds. (Springer, to be published
Global Income Inequality and Savings: A Data Science Perspective
A society or country with income equally distributed among its people is
truly a fiction! The phenomena of socioeconomic inequalities have been plaguing
mankind from times immemorial. We are interested in gaining an insight about
the co-evolution of the countries in the inequality space, from a data science
perspective. For this purpose, we use the time series data for Gini indices of
different countries, and construct the equal-time cross-correlation matrix. We
then use this to construct a similarity matrix and generate a map with the
countries as different points generated through a multi-dimensional scaling
technique. We also produce a similar map of different countries using the time
series data for Gross Domestic Savings (% of GDP). We also pose a different,
yet significant, question: Can higher savings moderate the income inequality?
In this paper, we have tried to address this question through another data
science technique - linear regression, to seek an empirical linkage between the
income inequality and savings, mainly for relatively small or closed economies.
This question was inspired from an existing theoretical model proposed by
Chakraborti-Chakrabarti (2000), based on the principle of kinetic theory of
gases. We tested our model empirically using Gini index and Gross Domestic
Savings, and observed that the model holds reasonably true for many economies
of the world.Comment: 8 pages, 6 figures. IEEE format. Accepted for publication in 5th IEEE
DSAA 2018 conference at Torino, Ital
Volume of the steady-state space of financial flows in a monetary stock-flow-consistent model
We show that a steady-state stock-flow consistent macro-economic model can be
represented as a Constraint Satisfaction Problem (CSP).The set of solutions is
a polytope, which volume depends on the constraintsapplied and reveals the
potential fragility of the economic circuit,with no need to study the dynamics.
Several methods to compute the volume are compared, inspired by operations
research methods and theanalysis of metabolic networks, both exact and
approximate.We also introduce a random transaction matrix, and study the
particularcase of linear flows with respect to money stocks
Quantitative modelling of the humanâEarth System a new kind of science?
The five grand challenges set out for Earth System Science by the International Council for Science in 2010 require a true fusion of social science, economics and natural scienceâa fusion that has not yet been achieved. In this paper we propose that constructing quantitative models of the dynamics of the humanâEarth system can serve as a catalyst for this fusion. We confront well-known objections to modelling societal dynamics by drawing lessons from the development of natural science over the last four centuries and applying them to social and economic science. First, we pose three questions that require real integration of the three fields of science. They concern the coupling of physical planetary boundaries via social processes; the extension of the concept of planetary boundaries to the humanâEarth System; and the possibly self-defeating nature of the United Nationâs Millennium Development Goals. Second, we ask whether there are regularities or âattractorsâ in the humanâEarth System analogous to those that prompted the search for laws of nature. We nominate some candidates and discuss why we should observe them given that human actors with foresight and intentionality play a fundamental role in the humanâEarth System. We conclude that, at sufficiently large time and space scales, social processes are predictable in some sense. Third, we canvass some essential mathematical techniques that this research fusion must incorporate, and we ask what kind of data would be needed to validate or falsify our models. Finally, we briefly review the state of the art in quantitative modelling of the humanâEarth System today and highlight a gap between so-called integrated assessment models applied at regional and global scale, which could be filled by a new scale of model
Solving dynamic stochastic economic models by mathematical programming decomposition methods.
Discrete-time optimal control problems arise naturally in many economic problems. Despite the rapid growth in computing power and new developments in the literature, many economic problems are still quite challenging to solve. Economists are aware of the limitations of some of these approaches for solving these problems due to memory and computational requirements. However, many of the economic models present some special structure that can be exploited in an efficient manner. This paper introduces a decomposition methodology, based on a mathematical programming framework, to compute the equilibrium path in dynamic models by breaking the problem into a set of smaller independent subproblems. We study the performance of the method solving a set of dynamic stochastic economic models. The numerical results reveal that the proposed methodology is efficient in terms of computing time and accuracyDynamic stochastic economic model; Computation of equilibrium; Mathematical programming; Decomposition techniques;
Application of Supercomputer Technologies for Simulation of Socio-Economic Systems
To date, an extensive experience has been accumulated in investigation of problems related to quality, assessment of management systems, modeling of economic system sustainability. The studies performed have created a basis for formation of a new research area â Economics of Quality. Its tools allow to use opportunities of model simulation for construction of the mathematical models adequately reflecting the role of quality in natural, technical, social regularities of functioning of the complex socioeconomic systems. Extensive application and development of models, and also system modeling with use of supercomputer technologies, on our deep belief, will bring the conducted researches of social and economic systems to essentially new level. Moreover, the current scientific research makes a significant contribution to model simulation of multi-agent social systems and that isnât less important, it belongs to the priority areas in development of science and technology in our country. This article is devoted to the questions of supercomputer technologies application in public sciences, first of all, â regarding technical realization of the large-scale agent-focused models (AFM). The essence of this tool is that owing to increase in power of computers it became possible to describe the behavior of many separate fragments of a difficult system, as social and economic systems represent. The article also deals with the experience of foreign scientists and practicians in launching the AFM on supercomputers, and also the example of AFM developed in CEMI RAS, stages and methods of effective calculating kernel display of multi-agent system on architecture of a modern supercomputer will be analyzed. The experiments on the basis of model simulation on forecasting the population of St. Petersburg according to three scenarios as one of the major factors influencing the development of social and economic system and quality of life of the population are presented in the conclusion
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