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Using models, developed in one branch of science, to describe similar behaviors encountered in a different one, is the essence of a synergetic approach. A wide range of topics has been developed including Agent-based models, econophysics, socio-economic networks, information, bounded rationality and learning in economics, markets as complex adaptive systems evolutionary economics, multiscale analysis and modeling, nonlinear dynamics and econometrics, physics of risk, statistical and probabilistic methods in economics and finance. Complexity. This publication concentrates on process behavior of economic systems and building models that stem from Haken's, Prigogine's, Taylor's work as well as from nuclear physics models.
These Proceedings report the scientific results of the Summer Study on Plural Rationality and Interactive Decision Processes orga nized jointly by the System and Decision Sciences Program of the Inter national Institute for Applied Systems Analysis (located in Laxenburg, Austria) and the Hungarian Committee for Applied Systems Analysis. The Study, which was held in Sopron over the period 16-26 Augus·t 1984, had a very special character. Sixty-eight researchers from sixteen coun tr~es participated, most of them contributing papers or experiments. In addition many members of IIASA's Young Scientists Summer Program were present. All of these participants were heavily involved in dis cussions; discussions that were not limited to the allotted time but extended well into the evenings and nights. By design, the Study gathered specialists from many disciplines, from philosophy and cultur al anthropology, through decision theory, game theory and economics, to engineering and applied mathematics. A further element of diversity was the representation of several varieties of culture, from typically Western countries, through Middle and Eastern Europe, to the Far East.
In the literature of decision analysis it is traditional to rely on the tools provided by probability theory to deal with problems in which uncertainty plays a substantive role. In recent years, however, it has become increasingly clear that uncertainty is a mul tifaceted concept in which some of the important facets do not lend themselves to analysis by probability-based methods. One such facet is that of fuzzy imprecision, which is associated with the use of fuzzy predicates exemplified by small, large, fast, near, likely, etc. To be more specific, consider a proposition such as "It is very unlikely that the price of oil will decline sharply in the near future," in which the italicized words play the role of fuzzy predicates. The question is: How can one express the mean ing of this proposition through the use of probability-based methods? If this cannot be done effectively in a probabilistic framework, then how can one employ the information provided by the proposition in question to bear on a decision relating to an investment in a company engaged in exploration and marketing of oil? As another example, consider a collection of rules of the form "If X is Ai then Y is B,," j = 1, . . . , n, in which X and Yare real-valued variables and Ai and Bi are fuzzy numbers exemplified by small, large, not very small, close to 5, etc.
McrM has been an active research area for over 20 years and the previous conferences clearly showed a tremendous growth of interest. A variety of successful applications and recent developments of interactive computer software to support decision making confinn a sustained progress. We therefore decided to make our theme "Inlproving Decision Making in Organisations". '!he aim was to take stock of the impact of multicriteria concepts in organisations and to involve management practitioners from a wide range of backgrounds. To this end the conference was organised round five broad themes and papers were solicited on the following topics:- Psychology - how do individuals in practice use and relate to the methodologies. Organisation - how do our models fit into the decision making framework of real organisations. Application - how have the models been used in practice and what is the users view. Methodology - what are the new areas in model development. Related Areas - is there complementary work eg. Expert Systems which may be attempting to solve very similar problems. '!he call for papers produced an overwhelming response of over 100 papers. '!hey were from a variety of disciplines and applications, and we decided to devote approximately one day to each of the five areas. We are very impressed by the results which can be seen in this edited proceedings.
This monograph is intended for an advanced undergraduate or graduate course of engineering and management science. as well as for persons in business. industry. military or in any field. who want an introductory and a capsule look into the methods of group decision making under multiple criteria. This is a sequel to our previous works entitled "Multiple Objective Decision Making--Methods and Applications (No. 164 of the Lecture Notes). and "Multiple Attribute Decision Making--Methods and Applications (No. 186 of the Lecture Notes). Moving from a single decision maker (the consideration of Lecture Notes 164 and 186) to a multiple decision maker setting introduces a great deal of complexity into the analysis. The problem is no longer the selection of the most preferred alternative among the nondominated solutions according to one individual's (single decision maker's) preference structure. The analysis is extended to account for the conflicts among different interest groups who have different objectives. goals. and so forth. Group decision making under multiple criteria includes such diverse and interconnected fields as preference analysis. utility theory. social choice theory. committee decision theory. theory of voting. game theory. expert evaluation analysis. aggregation of qualitative factors. economic equilibrium theory. etc; these are simplified and systematically classified for beginners. This work is to provide readers with a capsule look into the existing methods. their characteristics. and applicability in the complexity of group decision making.
This study is concerned with forecasting time series variables and the impact of the level of aggregation on the efficiency of the forecasts. Since temporally and contemporaneously disaggregated data at various levels have become available for many countries, regions, and variables during the last decades the question which data and procedures to use for prediction has become increasingly important in recent years. This study aims at pointing out some of the problems involved and at pro viding some suggestions how to proceed in particular situations. Many of the results have been circulated as working papers, some have been published as journal articles, and some have been presented at conferences and in seminars. I express my gratitude to all those who have commented on parts of this study. They are too numerous to be listed here and many of them are anonymous referees and are therefore unknown to me. Some early results related to the present study are contained in my monograph "Prognose aggregierter Zeitreihen" (Lutkepohl (1986a)) which was essentially completed in 1983. The present study contains major extensions of that research and also summarizes the earlier results to the extent they are of interest in the context of this study.
A new procedure for the maximum-likelihood estimation of dynamic econometric models with errors in both endogenous and exogenous variables is presented in this monograph. A complete analytical development of the expressions used in problems of estimation and verification of models in state-space form is presented. The results are useful in relation not only to the problem of errors in variables but also to any other possible econometric application of state-space formulations.
This monograph grew out of a project which was sponsored by the Swiss National Foundation ("Schweizerischer Nationalfonds") under grant no. 4. 636-0. 83. 09. Yithin this project, prediction-oriented estimation methods for the canonical econometric disequilibrium model were developed. The present monograph deals with the application of these estimation techniques to three aggregative markets of the Swiss economy. Parts of the monograph have been presented at various places: the estimation techniques described in chapter 3 at the European Meeting of the Econometric Society, Madrid 1984; the application to residential investment described in chapter 4 at a symposium on housing policy at the University of Mannheim, 1984; the empirical study on the money stock described in chapter 5 at the Symposium on Money, Banking and Insurance held at the University of Karlsruhe, 1984, as well as at a joint seminar of the University of Basle and the Bank for International Settlements (BIS), 1985; and, finally, the empirical study on the aggregate labor market described in chapter 6 at a seminar of the University of ZUrich, 1985. Comments from toe seminar participants, in particular from Palle S. Andersen (BIS) who served as a discussant, Pascal Bridel (Swiss National Bank, SNB), Franz Ettlin (SNB), and Kurt Schiltknecht (Nordfinanz-Bank, Zurich) are gratefully acknowledged, without implying any responsibility on their part. The methodological part described in chapters 2 and 3 is contributed by G. Frei and B.
This volume consists of six essays that develop and/or apply "rational expectations equilibrium inventory models" to study the time series behavior of production, sales, prices, and inventories at the industry level. By "rational expectations equilibrium inventory model" I mean the extension of the inventory model of Holt, Modigliani, Muth, and Simon (1960) to account for: (i) discounting, (ii) infinite horizon planning, (iii) observed and unobserved by the "econometrician" stochastic shocks in the production, factor adjustment, storage, and backorders management processes of firms, as well as in the demand they face for their products; and (iv) rational expectations. As is well known according to the Holt et al. model firms hold inventories in order to: (a) smooth production, (b) smooth production changes, and (c) avoid stockouts. Following the work of Zabel (1972), Maccini (1976), Reagan (1982), and Reagan and Weitzman (1982), Blinder (1982) laid the foundations of the rational expectations equilibrium inventory model. To the three reasons for holding inventories in the model of Holt et al. was added (d) optimal pricing. Moreover, the popular "accelerator" or "partial adjustment" inventory behavior equation of Lovell (1961) received its microfoundations and thus overcame the "Lucas critique of econometric modelling.