مدل پویا ماکرو اطلاعات ابتدایی از یک سیستم اقتصادی در بازار
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|8610||2006||35 صفحه PDF||سفارش دهید||محاسبه نشده|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Information Sciences, Volume 176, Issue 23, 4 December 2006, Pages 3556–3590
Information represents a common and universal substance, actively participating in a diversity of physical or virtual interactions, including various forms of economic interaction. The information regularities of economical dynamics and the mathematical evaluation of the economical system’s processes are studied by building the information systemic models, based on Informational Macrodynamics. Study focuses on an elementary production–organization, the production’s interaction and management, and different market dynamics, with modeling an organization by the hierarchical structure of information, cooperative, dynamic space-distributed network. The system’s cooperative dynamics coordinate and mutually connect the micro- and macroeconomical processes, which include both the dynamics within each basic economic element and the cooperative integration between the system’s elements. The models use a common mathematical formalism and the information as a universal equivalent of money and a common models’ language. The found formalized information mechanisms govern market’s cooperative dynamics and the information restrictions on these processes. The considered systemic mechanisms of self-control, adaptation, and evolution, represent a general attribute of an economical system.
In the modern economy, the main exchanges occur through the transfer of information between customers, producers, banks, investors, and across the market, utilizing many different signals, physical signs, coded communications, etc. Even a business with a diversity of goods can be represented by an exchange of corresponding information structures and values, expressed particularly by their code substitutes. In such a virtual and/or real information business, all participants produce, transmit, exchange, or consume information. Information appears as a universal equivalent of money, directly exchangeable with different commodities, including human labor. Because exchanges exist in a social system, the quantitative and qualitative values of information also represent a measure of social relations. Since modern economics become an information system, it is imperative to apply the information science’s systems theory for understanding the systemic regularities of the information economy. This includes a joint consideration of the economic system’s components to expose their inter relations, which are necessary not only for the component’s coordinated dynamic cooperation, but also to detect the inner components’ regularities as a part of the systemic relations for the whole system. The first problem in this direction is developing the information models for each particular economic object, such as a local business production and organization, markets, banks, etc., to describe both inner information dynamics and the information relations between them. The second is modeling the specific cooperative dynamics and phenomena, essential for the economic object. The third is unifying the models into the information system using a common information language and modeling methodology, applied to a variety of the object’s interactions and communications. The goal is to reveal the main information regularities of a market economic system, based on a mathematical formalism of cooperative dynamics, a model of the system’s information structure, and an analysis of the information exchange flows and communications throughout the whole system. Since the production and transformation of information are the basics of any information object, we focus on the dynamic regularities of their economic analogies: an elementary production system and market, with the conditions of free competition and open, unrestricted supply–demand processes. The developed methodology is intended not only to identify the current object’s model with all its specific phenomena but also to improve the object’s functioning through optimal control and management, stemming from the system’s modeling. We believe that the information science approach and the results of information system theory will bring a new understanding of economics, business relations, and communications, and create a breakthrough in the solution of important economic problems. Analysis of the References shows that a system’s information model of economics has not been developed yet. Evidently, the first information models of economics were considered by Theil . These included static models and aggregation analysis, applied to local economic problems with the entropy measure of employment, markets, incomes, USA industrial concentrations, and occupational diversity in cities; all of which can be linked to the growth and decline of social systems  and . Marschak  and  applied Shannon’s information theory to economics with the “teams” approach and decentralized organizations. Aoki  developed a stochastic approach to macroecomic modeling based on stochastic dynamics and stochastic random combinatorial analysis. The approach uses Markov processes with probability distributions, determined by the Chapman–Kolmogorov equation. The author’s goal is to unveil stochastic regularities of multi-agent interactive models, including power-laws in share or stock markets. Even excluding information theory, Aoki emphasizes  the key role of uncertainty in standard economic analysis and economic policy. Hirshleifer considers  uncertainty, arising in a market irreversible process of the “liquid” commodities, which unfolds the events over time. Actually, none of the known models directly minimize the uncertainty, providing the control actions and outcomes in terms of quantifiable and marketable production factors and products, or their prices. Hirshleifer  reviews a potential broad use of information theory for a wide description of multiple micro- and macroeconomic processes, including market and trading relations, technological productions, organizations, banking, money flows, price, human behavior, etc. Unfortunately, none of the existing models covers such a broad approach. Let us analyze the informational economic tools, consisting of both analytical models and applied software packages that accomplish the solutions of the economic tasks. Among a huge number of publications, we have chosen the paper’s related Refs. , , , , , , , ,  and  and a limited software, available on the Internet in its relation to this paper. Each of the existing classical microeconomic models (and accompanying software), such as Supply and Demand models, Two Goods—Two Prices curves, Perfect Competition, Monopoly and Monopolistic Competition, are basic elements in specific areas (free markets resources, the theory of the consumer, and theory of the firm) but do not establish a cooperative connection to these areas. The known macroeconomic models (and their software), including Keynesian’s Simple and IS/LM Models and Mundell–Fleming’s Model, are simplified archetypes of the economy, focusing on equilibrium, long-term and short-term interest rates, adjusting Supply/Aggregate Demand and Balance of Payments curves to the IS/LM Model, and income. The Real Business Cycles model shifts attention from the nominal interest rates back to the real factors of production that dominated the original Classical Model. The various elements of these micro- and macroeconomic models are implemented by the MathCAD Programs, including also Profit Maximization under Perfect Competition, Generating Market Demand and Supply, and others. Many specialized programs have been developed by Microsoft, Oracle, and others, such as Price Correlaton/Variance analyses, Auction Simulation, ModelOracle/People Soft, Microsoft Power tools US (for the analysis and evaluation of specific economic projects), and the NRCS software package for Economic assistance and Planning. These and other specific programs, published on the Internet, have been developed by over 200 professional companies. The book  provides information tools for the assessments and evaluation of information productivity for major corporations in view of “business in an information economy.” The publications  and  focus on using computers and the Internet for creating a digital marketplace and “the information network economy”. The examination of these and other information tools shows that none of them, though useful for their particular tasks, can be applied to the entire economy as a cooperative system. We intend to develop the information dynamic model of macroeconomics that takes into account the interaction of the material, social-labor, and biological processes on the basis of the information mathematical formalism, representing a never before investigated problem. Considering a joint information description of different interacting elements that together compose an economic system, we intend to find common information mechanisms and their mathematical expressions, governing the economic processes and their regularities. Starting with the primary system’s components, such as a cooperative behavioral production system and different forms of the market, we will not take into account the government limitations, public and military policies, monopolies, and other specific restrictions and requirements imposed on a free market economy. Even with such limitations and simplifications, our approach sounds productive and promising in revealing the unknown information regularities of an economic system. An aim of Information Systems Modeling (ISM) (as a part of Information System Theory) is to build bridges between the mathematical modeling and systemic formalism and the world of information and information technologies to reveal the common information regularities of a variety of modeling objects with the final goal of exposing the specific information code for each object. ISM uses the unified information systemic approach, based on the Informational Macrodynamics (IMD) , , , , ,  and  formalism with a common information language and information modeling methodology, which is directly implemented in the forms of algorithms and programs for objects of different natures (in areas such as technology, intelligent processes, communications, biology, economics, management, and other physical and non-physical systems with their mutual interactions, informational superimposition, and the information transferred during interactions). We search for the problem’s solution using the IMD as a mathematical theory of revealing information regularities, generated by multiple random interactions, independent of physical or virtual specifics. Regularities of the random interactions characterize a macroprocess with a set of macrotrajectories, determined by the class corresponding to the random microprocess. IMD studies the macroprocess’ dynamics by building the information dynamic models, which describe the information structure and regularities of the microprocesses. The IMD mathematical formalism allows the development of a general systemic macromodel, whose regularities include the cooperative structure of the time-space hierarchical information network, and the functional mechanisms of adaptation, self-organization, and evolution. The designed information models are essential for developing computer algorithms and programs with successful computer applications to a diversity of physical and non-physical systems. Section 2 provides a conceptual review and analysis of the IMD mathematical model as a fundamental basis for building the systemic information model of an economic system. The mathematical proof of the results and the details can be found in  and .
نتیجه گیری انگلیسی
We conclude with the paper economic motivation and a connection between the motivation and formal presentation. This paper intends to provide a systemic information model of cooperative dynamics for mutually connected micro- and macroeconomical processes, focusing on maximal process’ coordination for both the dynamics within each basic economic element, and the cooperative integration between the system’s elements, using a common mathematical formalism (as the analytic tools) and the information as a general economic substance, a universal equivalent of money, and a common model’s language. The paper’s motivations are fulfilled and performed by the IMD information systems model, built on the basis of the information form of the variation principle, applied to an observed stochastic process at microlevel, which is used for current identification of dynamic processes at macrolevel; the identified process approximate the observed process with maximal probability, and concurrently adjusts (adopts) its information by communicating with the microlevel. The formalism describes not only each current modeling process with maximal probability but also portrays such specific economic peculiarities as a local discreteness and global continuousness, chaotic phenomena, robustness, competitiveness, stability (or instability), adaptivity, complexity, and evolution with the organization and compression of the model’s information into the information hierarchical network and the final representation by the information code, enables the mode’s communications. An execution of the model’s peculiarities leads to the minimization of the system’s uncertainty, making the economy more predictable and controllable. None of the existing models is able to combine, into a single formalism, all of the capabilities reflecting the phenomena of a real economy. This paper also applies the formalism’s software as the computation tools for the current model’s identification (arranged for each real economic process), optimization by a chosen criterion (of effectiveness), and practical calculation of the process’s dynamic characteristics, including building the information network and the evaluation of the above phenomena for each particular process. The real economic examples in Section 8, among others, implement these tools. The considered unity of the paper’s information mathematical formalism, information language, and the built information systems models directly link the results to Information Sciences.