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This book presents an econometric modeling approach for analysing macroeconomic disequilibria, focusing on the market for goods and labor and the spillovers between these markets transmitted through firms' decisions in the production sphere. The macroeconomic markets are treated as heterogeneous aggregates, consisting of a multitute of micro markets on which demand/supply ratios differ. Disequilibrium models have been under attack because they neglect that inventories enable firms to smooth production over the cycle, but the author argues that buffer stocks (output inventories, unfilled orders) should be accounted for within the disequilibrium framework, giving rise to a dynamic modification rather than a fundamental invalidation of rationing and spillover effects. The model developed in this book combines traditional Keynesian-type analysis with supply-side considerations and at the same time allows for micro-level imbalance. The resulting econometric structure is inherently nonlinear, reflecting that the response of economic activity to demand-side and supply-side factors varies over the cycle, depending on the aggregate mix of regimes. The model is estimated with quarterly data for Switzerland. Various simulation experiments clearly demonstrate the potential of this type of model for empirical business cycle analysis and policy discussions.
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This title was first published in 2000: This text offers a comprehensive collection of selected papers from the 24th Centre for International Research on Economic Tendency Surveys (CIRET) conference. Areas selected include leading indicators and turning points, classifications of business cycles, survey data and policy decisions, attitudes and behaviour of firms, and economic forecasting. The text aims to be of interest to all those concerned with the use of business and consumer surveys in a global context.
This systematic book covers in simple language the physical foundations of evolution equations, stochastic processes and generalized Master equations applied on complex economic systems, helping to understand the large variability of financial markets, trading and communications networks.
A Silverman game is a two-person zero-sum game defined in terms of two sets S I and S II of positive numbers, and two parameters, the threshold T > 1 and the penalty v > 0. Players I and II independently choose numbers from S I and S II, respectively. The higher number wins 1, unless it is at least T times as large as the other, in which case it loses v. Equal numbers tie. Such a game might be used to model various bidding or spending situations in which within some bounds the higher bidder or bigger spender wins, but loses if it is overdone. Such situations may include spending on armaments, advertising spending or sealed bids in an auction. Previous work has dealt mainly with special cases. In this work recent progress for arbitrary discrete sets S I and S II is presented. Under quite general conditions, these games reduce to finite matrix games. A large class of games are completely determined by the diagonal of the matrix, and it is shown how the great majority of these appear to have unique optimal strategies. The work is accessible to all who are familiar with basic noncooperative game theory.
This book explores the econometric implications of a policy-maker's learning. In a simple discrete model the policymaker maximizes the discounted sum of tax revenues subject to a constraint which involves an unknown parameter specifying the occurrence of Bayesian learning. An optimal balance needs to be found between maximizing current payoff and generating information which enhances the efficiency of maximization in subsequent periods. Learning is demonstrated to affect the exogeneity status of policy variables in small samples and to have implications analogous to the phenomenon in the focus of the Lucas critique. Active learning is proven to be a distinct cause of time inconsistency of optimal plane. It is argued that learning cannot be dismissed as a merely transitory source of these phenomena. A simulation exercise supplies quantitative evidence. Finally, the data generated are used to perform empirical exogeneity tests. Results show that the effect of Bayesian learning is empirically detectable. Learning is generally accepted as the driving force towards a rational expectations equilibrium with perfect information. In this context, the result on the loss of exogeneity of policy variables is an out-of-equilibrium econometric implication of the rational expectations hypothesis. This book is the first to explore the effect of an informational feedback on exogeneity.
This special volume contains the Proceedings of a Workshop on "Parallel Algorithms and Transputers for Optimization" which was held at the University of Siegen, on November 9, 1990. The purpose of the Workshop was to bring together those doing research on 2.lgorithms for parallel and distributed optimization and those representatives from industry and business who have an increasing demand for computing power and who may be the potential users of nonsequential approaches. In contrast to many other conferences, especially North-American, on parallel processing and supercomputers the main focus of the contributions and discussion was "problem oriented". This view reflects the following philosophy: How can the existing computing infrastructure (PC's, workstations, local area networks) of an institution or a company be used for parallel and/or distributed problem solution in optimization. This volume of the LECfURE NOTES ON ECONOMICS AND MA THEMA TICAL SYSTEMS contains most of the papers presented at the workshop, plus some additional invited papers covering other important topics related to this workshop. The papers appear here grouped according to four general areas. (1) Solution of optimization problems using massive parallel systems (data parallelism). The authors of these papers are: Lootsma; Gehne. (II) Solution of optimization problems using coarse-grained parallel approaches on multiprocessor systems (control parallelism). The authors of these papers are: Bierwirth, Mattfeld, and Stoppler; Schwartz; Boden, Gehne, and Grauer; and Taudes and Netousek.
The title of this book seems to indicate that the volume is dedicated to a very specialized and narrow area, i. e. , to the relationship between a very special type of optimization and mathematical programming. The contrary is however true. Optimization is certainly a very old and classical area which is of high concern to many disciplines. Engineering as well as management, politics as well as medicine, artificial intelligence as well as operations research, and many other fields are in one way or another concerned with optimization of designs, decisions, structures, procedures, or information processes. It is therefore not surprising that optimization has not grown in a homogeneous way in one discipline either. Traditionally, there was a distinct difference between optimization in engineering, optimization in management, and optimization as it was treated in mathematical sciences. However, for the last decades all these fields have to an increasing degree interacted and contributed to the area of optimization or decision making. In some respects, new disciplines such as artificial intelligence, descriptive decision theory, or modern operations research have facilitated, or even made possible the interaction between the different classical disciplines because they provided bridges and links between areas which had been developing and applied quite independently before. The development of optimiiation over the last decades can best be appreciated when looking at the traditional model of optimization. For a well-structured, Le.
In the last decade highly innovatory developments have taken place in theoretical economics. The new focus of interest seems to be twofold: Firstly, nonlinear models for dynamic processes of the economy are constructed to extend the scope of linear models for tlle stationary euqilibrium state; and secondly a new approach is made to solve the everlasting problem of the relation between micro-and macro-economics. The interdisciplinary field of synergetics is deeply involved in this evolution. The author has made a remarkable contribution to both foci: His application of synergetic concepts to the theory of business cycles combines a partial solution of the micro-macro-problem, namely the modelling of the macro-economic effect of the decisions of investors, producers and consumers, with the natural introduction of nonlinearities. The arising new business cycle theory can on the one side be validated by empirical evidence and on the other hand the typical behavior of nonlinear dynamic systems including the transition to deterministic chaos can be clearly demonstrated. The hope is justified that the model presented in this book is a fw·ther important step in reaching a new level of the quantitative comprehension of dynamic phenomena in the economy. Stuttgart, June 1991 Prof. Dr. Wolfgang Weidlich Foreword It is the author's objective to explain macroeconomic processes on the basis of micro economic decision-making behaviour. In order to achieve this goal, the concept of synergetics is presented as a method of describing dynamic phenomena in multi-com ponent systems with cooperative interactions between their elements.