Modelling of Economic Systems

A special issue of Systems (ISSN 2079-8954).

Deadline for manuscript submissions: closed (15 May 2018) | Viewed by 43527

Special Issue Editors


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Guest Editor
Faculty of Informatics and Management, University of Hradec Králové, Rokitanského 62, 50003 Hradec Králové, Czech Republic
Interests: system dynamics; systems engineering; modelling; simulation
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Guest Editor
Department of Economics, Faculty of Informatics and Management, University of Hradec Králové, Rokitanského 62, 50003 Hradec Králové, Czech Republic
Interests: macroeconomics; economic growth; economic systems analysis; system dynamics; energy-economy systems

Special Issue Information

Dear Colleagues,

J. W. Forrester, the founder of system dynamics, states, in the foreward of one of his books focusing on modelling of economic systems, that the frontier of better-understanding the behavior of social and economic systems will shape the progress of mankind in this century. Indeed, we need to support movement away from purely mental models, in which economic systems are captured for more insightful and disciplined computer simulation models based on sound formal foundations. The issue of understanding complex system behavior and the challenge of developing easy-to-use models are obvious in the field of economic development.  We need to successfully cope with the collection and organization of data, interdisciplinary model development, transparency of models, and visualization of the results. However, the pay-off is worthy. We can tame complexity and acquire better insights, which is the main assumption of better understanding and meaningful decision making. Models represent essential tools in generating new knowledge. They help us simplify complex phenomena by eliminating everything we believe is extraneous to what we want to study. Computers allow us to expand the scope of our models to include more and more diverse variables, and to ask more “what-if” questions. We can experiment using computer models; in this way, models help us to uncover unintended consequences, emergent attributes, synergic effects, or dominant feedbacks. We look for patterns within the details without losing sight of the big picture. Then, predictions of the short- and long-term outcomes of proposed actions are more precise and helpful. Innovations in software engineering and availability of powerful and affordable hardware have enabled development and application of various approaches to modelling of economic systems together with related tools and techniques. Kindly consult the keywords included in this call. Needless to say, the list is obviously incomplete. In the train of this progress computer models are no longer confined to the computer laboratory. They have moved into every classroom and business information systems. Moreover, combination of approaches or methods brings new added value. By building on the strengths of each we acquire models that exceeds the knowledge derived from choosing one method over the other. Experimenting with computer models will open a new world in our understanding of economic systems. This Special issue focuses on broad range of methodological and application issues associated with economic models within their whole life cycle. Papers should show interest in three main uses of models: Understanding, assessing, and optimising. Accepted papers are intended to provide novel approaches to modelling of economic systems, explanation or solution of specific modelling difficulties, description of original models dealing with specific problems, answers to research questions from economics based on alternative approaches, etc. We will accept papers for peer review in the following areas of interest:

  • Multi-agent modelling and simulation of economic systems
  • Dynamic nature of economy captured in system dynamics models
  • Modelling based on large datasets
  • Analysis of closed loops in economy based on simulations
  • Simulation-based support of policy making in energy-economy systems
  • Energy-economy-environment systems and analysis of various scenarios
  • Macroeconomic models
  • Microeconomic models
  • Universality vs. user-friendliness of development of computer models
  • Computer simulations of specific economic systems
  • Transformation of main theories in economics into computer models
  • Application of economic indicators and indices in computer simulations
  • Extension of already existing well-known economic models 
  • Models focused on historic data replication
Dr. Vladimír Bureš
Dr. Lukáš Režný
Guest Editors

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Keywords

  • Simulation
  • System dynamics
  • Agent-based modelling
  • Economic theory
  • Indicator
  • Policy making
  • Energy
  • Environment
  • Model attributes
  • Feedbacks
  • Data-based modelling

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Published Papers (5 papers)

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Research

15 pages, 344 KiB  
Article
Nonlinear Phenomena in Cournot Duopoly Model
by Pavel Pražák and Jaroslav Kovárník
Systems 2018, 6(3), 30; https://doi.org/10.3390/systems6030030 - 13 Jul 2018
Cited by 3 | Viewed by 7671
Abstract
The economic world is very dynamic, and most phenomena appearing in this world are mutually interconnected. These connections may result in the emergence of nonlinear relationships among economic agents. Research discussions about different markets’ structures cannot be considered as finished yet. Even such [...] Read more.
The economic world is very dynamic, and most phenomena appearing in this world are mutually interconnected. These connections may result in the emergence of nonlinear relationships among economic agents. Research discussions about different markets’ structures cannot be considered as finished yet. Even such a well-known concept as oligopoly can be described with different models applying diverse assumptions and using various values of parameters; for example, the Cournot duopoly game, Bertrand duopoly game or Stackelberg duopoly game can be and are used. These models usually assume linear functions and make analyses of the behavior of the two companies. The aim of this paper is to consider a nonlinear inverse demand function in the Cournot duopoly model. Supposing there is a sufficiently large proportion among the costs of the two companies, we can possibly detect nonlinear phenomena such as bifurcation of limit values of production or deterministic chaos. To prove a sensitive dependence on the initial condition, which accompanies deterministic chaos, the concept of Lyapunov exponents is used. We also point out the fact that even though some particular values of parameters are irrelevant for the above-mentioned nonlinear phenomena, it is worth being aware of their existence. Full article
(This article belongs to the Special Issue Modelling of Economic Systems)
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13 pages, 346 KiB  
Article
Monetary and Fiscal Policy Interactions in the Czech Republic
by Pavel Rezabek and Petr Doucek
Systems 2018, 6(2), 25; https://doi.org/10.3390/systems6020025 - 17 Jun 2018
Cited by 1 | Viewed by 8077
Abstract
The paper provides empirical analysis of interactions between monetary and fiscal policy in the Czech Republic and document changes in policy conduct across the time. To this end, we build and estimate a six-variable Bayesian VAR and propose some refinements to the modelling [...] Read more.
The paper provides empirical analysis of interactions between monetary and fiscal policy in the Czech Republic and document changes in policy conduct across the time. To this end, we build and estimate a six-variable Bayesian VAR and propose some refinements to the modelling framework. These improvements make it possible to better capture the main features of the economic system populated by both macroeconomic policy authorities. The results point to the lack of complementarity between policy actions adopted by the authorities and suggest that there is still enough room for enhancing the effectiveness of economic policies. Full article
(This article belongs to the Special Issue Modelling of Economic Systems)
18 pages, 2938 KiB  
Article
How to Express and to Measure Whether an Economic System Develops Intensively
by Petr Wawrosz, Jiří Mihola and Jana Kotěšovcová
Systems 2018, 6(2), 24; https://doi.org/10.3390/systems6020024 - 14 Jun 2018
Cited by 2 | Viewed by 6649
Abstract
This article presents comprehensive typology of all possible relationships among inputs of an economic system, their productivity, and output. Each situation is given an exact name explaining how intensive and extensive factors contributes to the system development. The exact contributions of the factors [...] Read more.
This article presents comprehensive typology of all possible relationships among inputs of an economic system, their productivity, and output. Each situation is given an exact name explaining how intensive and extensive factors contributes to the system development. The exact contributions of the factors can be counted by so-called dynamic intensity and extensity parameters. The article describes logic of the parameters, discusses their advantages and problems and assigns their values to the presented nomenclature of the developments. The parameters are further compared with growth accounting methods and their use is demonstrated on the development of macroeconomic system on the national economy level when it is counted how intensive and extensive parameters contribute to the Czech and German GDP development in the period 1991–2017. The analysis confirms that the parameters can be used as an alternative methods to growth accounting and that managers of any economic system should pay attention whether a system achieves positive value of the dynamic intensive parameters in long run. Full article
(This article belongs to the Special Issue Modelling of Economic Systems)
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18 pages, 17453 KiB  
Article
Efficient and Equitable Climate Change Policies
by Socrates Kypreos, James Glynn, Evangelos Panos, George Giannakidis and Brian Ó Gallachóir
Systems 2018, 6(2), 10; https://doi.org/10.3390/systems6020010 - 13 Apr 2018
Cited by 2 | Viewed by 9065
Abstract
This report describes the Integrated Assessment Model TIAM-MACRO, which is a Ramsey-type macroeconomic growth model linked with a technology-rich engineering model of the energy-system and with a stylized sub-model of climate change. TIAM-MACRO contributes to coherent and consistent policy analyses at both the [...] Read more.
This report describes the Integrated Assessment Model TIAM-MACRO, which is a Ramsey-type macroeconomic growth model linked with a technology-rich engineering model of the energy-system and with a stylized sub-model of climate change. TIAM-MACRO contributes to coherent and consistent policy analyses at both the world and regional level and correlates demand for energy services to macro-economic developments across regions and time until the end of the 21st century. With the help of this model, two contrasting scenarios are defined related to the reference development (BASE) case and the 2 °C (2DS) case that follow long-term policies on climatic change mitigation in the spirit of the Paris agreement. Finally, we define ex-post market and non-market damages together with the damages related to Local Atmospheric Pollutants (LAP). The stringency of the 2DS case requires the complete restructuring of the energy and transport systems to be relying on carbon-free technologies and fuels together with technologies of negative emissions, at high costs. The study concludes that carbon policies not only consist of an insurance against the risk of climate change but also improve the ambient air quality, as they have secondary benefits that compensate for part of the cost of carbon control. However, the stringency of the 2DS case is so demanding that the cost of climate policies is above benefits. Full article
(This article belongs to the Special Issue Modelling of Economic Systems)
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23 pages, 30865 KiB  
Article
Adding Feedbacks and Non-Linearity to the Neoclassical Growth Model: A New Realm for System Dynamics Applications
by Lukáš Režný and Vladimír Bureš
Systems 2018, 6(2), 8; https://doi.org/10.3390/systems6020008 - 29 Mar 2018
Cited by 6 | Viewed by 9387
Abstract
Modelling of economic systems is traditionally associated with a mathematical formalism that has its drawbacks and limitations. This study applies system dynamics as a specific modelling technique that enables us to modify and elaborate existing economic models and improve them both from a [...] Read more.
Modelling of economic systems is traditionally associated with a mathematical formalism that has its drawbacks and limitations. This study applies system dynamics as a specific modelling technique that enables us to modify and elaborate existing economic models and improve them both from a theoretical perspective and for practical applications. More specifically, the Solow-Swan growth model is enriched by feedback and non-linearity based on its extension by the energy sector. The influence and role of renewable resources are considered in this enhancement. The developed model is tested in two different scenarios and utilizes sensitivity analysis as the primary tool. Acquired outcomes offer a new perspective on the economy–energy nexus based on real data and demonstrate that system dynamics can be successfully used as a modelling tool even in the theoretical economics as a traditional discipline. Full article
(This article belongs to the Special Issue Modelling of Economic Systems)
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