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This material is based upon work supported by the National Science Foundation under grant #SES-8410190. Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the authors and do not necessari~y reflect the views of the National Science Foundation. This support was crucial to the completion of this project, and we are grateful for it. As is usually the case when doing academic research, we are also indebted to a number of individuals. Robert Gillingham, John Greenlees, Jack Triplett, and Paul Harte-Chen freely gave of their time to share their ideas concerning income-based cost of living indices. Seminar participants at the BLS, the University of Karlsruhe, and Tilburg University provided insightful comments on preliminary portions of the manuscript. Bill Stober provided encouragement, and Desmond Lo and Albert Tsui read parts of the manuscript. We owe a special thanks to Bert Balk for providing detailed handwritten comments on a preliminary draft. Evelyn Buchanan and Audrey Abel did an excellent job of typing and retyping numerous drafts of the manuscript. Finally, a very warm thanks to our wives, for enduring. CONTENTS Page PREFACE PART I.
1.1 Some characteristics of the floating exchange rate system The flexible exchange rate system has functioned far less satisfactorily than many anticipated in 1973, when the major industrialized countries decided to let their currencies float. The dominant currencies' exchange rates have fluctuated more 1 than expected. These fluctuations concern both short-term movement- intraday fluctuations and movements during a week or a month - and long term changes that last for more than a year. Daily percentage changes of one percent are not unusual for the recent float (see MacDonald, 1988, p.8). However, the release of new information can give rise to much larger changes. For example in August 1987 "the dollar moved down 6 percent in two days based on the July trade figures" (Glynn, 1988, p. 36). For the period 1973-1985 MacDonald (1988, p.10) presents minimum and maximum monthly percentage exchange rate changes. These figures clearly illustrate the magnitude of the volatility and also show that the volatility has not diminished as the experience 2 with floating has increased. In addition to this volatility, exchange rates are also characterized by misalignment: "persistent departure of the exchange rate from its long-run equilibrium" (Williamson, 1983, p.l3). Although the measure of misalignment depends upon the exact definition of the exchange rate's long-run equilibrium, there is a widespread feeling that during the greater part of the 1970s the dollar was undervalued, whereas it was overvalued during the first half of the 1980s.
This book contains a selection of the papers presented at the symposium on "Decision processes in Economics" which was held in Modena (Italy) on 9-10 October 1989. It coincided with the annual meeting of the italian group on Game Theory; the group is formed by economists, mathematicians, engineers and social scientists. One of the targets of the Meeting, and therefore of the book, is to create an opportunity for having together papers by scientists with an "optimal control" education and papers by theorists on refinement of equilibrium, on repeted games and other topics. These two modes of working on Games are quite different but we think that a unitary approch to Games can be given and this book is an attempt in this direction. Another important and updated issue which is emphisized in the book is the discussion of computation and efficiency of numerical methods in Games. Stochastic differential games are treated in the papers by Basar, Haurie -and Deissemberg. Basar considers a stochastic model of a conflict situation between the monetary policy maker (go vernment) and the responding agent (private sector). Because of asymmetry in the (stochastic) information available the Nash and the Stackelberg games become non standard stochastic diffe rential games. After the discussion of the conditions leading to a solution he provides a numerical example for the proposed game. Haurie considers a game where the observed state changes according to a stochastic jump process.
1. 1 Integrating results The empirical study of macroeconomic time series is interesting. It is also difficult and not immediately rewarding. Many statistical and economic issues are involved. The main problems is that these issues are so interrelated that it does not seem sensible to address them one at a time. As soon as one sets about the making of a model of macroeconomic time series one has to choose which problems one will try to tackle oneself and which problems one will leave unresolved or to be solved by others. From a theoretic point of view it can be fruitful to concentrate oneself on only one problem. If one follows this strategy in empirical application one runs a serious risk of making a seemingly interesting model, that is just a corollary of some important mistake in the handling of other problems. Two well known examples of statistical artifacts are the finding of Kuznets "pseudo-waves" of about 20 years in economic activity (Sargent (1979, p. 248)) and the "spurious regression" of macroeconomic time series described in Granger and Newbold (1986, §6. 4). The easiest way to get away with possible mistakes is to admit they may be there in the first place, but that time constraints and unfamiliarity with the solution do not allow the researcher to do something about them. This can be a viable argument.
In this book problems related to the choice of models in such diverse fields as regression, covariance structure, time series analysis and multinomial experiments are discussed. The emphasis is on the statistical implications for model assessment when the assessment is done with the same data that generated the model. This is a problem of long standing, notorious for its difficulty. Some contributors discuss this problem in an illuminating way. Others, and this is a truly novel feature, investigate systematically whether sample re-use methods like the bootstrap can be used to assess the quality of estimators or predictors in a reliable way given the initial model uncertainty. The book should prove to be valuable for advanced practitioners and statistical methodologists alike.
In the last 25 years, the fuzzy set theory has been applied in many disciplines such as operations research, management science, control theory, artificial intelligence/expert system, etc. In this volume, methods and applications of crisp, fuzzy and possibilistic multiple objective decision making are first systematically and thoroughly reviewed and classified. This state-of-the-art survey provides readers with a capsule look into the existing methods, and their characteristics and applicability to analysis of fuzzy and possibilistic programming problems. To realize practical fuzzy modelling, it presents solutions for real-world problems including production/manufacturing, location, logistics, environment management, banking/finance, personnel, marketing, accounting, agriculture economics and data analysis. This book is a guided tour through the literature in the rapidly growing fields of operations research and decision making and includes the most up-to-date bibliographical listing of literature on the topic.
This volume contains selected papers presented at the "International Workshop on Computationally Intensive Methods in Simulation and Op th th timization" held from 23 to 25 August 1990 at the International Institute for Applied Systems Analysis (nASA) in La~enburg, Austria. The purpose of this workshop was to evaluate and to compare recently developed methods dealing with optimization in uncertain environments. It is one of the nASA's activities to study optimal decisions for uncertain systems and to make the result usable in economic, financial, ecological and resource planning. Over 40 participants from 12 different countries contributed to the success of the workshop, 12 papers were selected for this volume. Prof. A. Kurzhanskii Chairman of the Systems and Decision Sciences Program nASA Preface Optimization in an random environment has become an important branch of Applied Mathematics and Operations Research. It deals with optimal de cisions when only incomplete information of t.he future is available. Consider the following example: you have to make the decision about the amount of production although the future demand is unknown. If the size of the de mand can be described by a probability distribution, the problem is called a stochastic optimization problem.
The first attempts to develop a utility theory for choice situations under risk were undertaken by Cramer (1728) and Bernoulli (1738). Considering the famous St. Petersburg Paradox! - a lottery with an infinite expected monetary value -Bernoulli (1738, p. 209) observed that most people would not spend a significant amount of money to engage in that gamble. To account for this observation, Bernoulli (1738, pp. 199-201) proposed that the expected monetary value has to be replaced by the expected utility ("moral expectation") as the relevant criterion for decision making under risk. However, Bernoulli's 2 argument and particularly his choice of a logarithmic utility function seem to be rather arbitrary since they are based entirely on intuitively 3 appealing examples. Not until two centuries later, did von Neumann and Morgenstern (1947) prove that if the preferences of the decision maker satisfy cer tain assumptions they can be represented by the expected value of a real-valued utility function defined on the set of consequences. Despite the identical mathematical form of expected utility, the theory of von Neumann and Morgenstern and Bernoulli's approach have, however, IFor comprehensive discussions of this paradox cf. Menger (1934), Samuelson (1960), (1977), Shapley (1977a), Aumann (1977), Jorland (1987), and Zabell (1987). 2Cramer (1728, p. 212), on the other hand, proposed that the utility of an amount of money is given by the square root of this amount.
In February 1992, I defended my doctoral thesis: Engineering Optimiza tion - selected contributions (IMSOR, The Technical University of Den mark, 1992, p. 92). This dissertation presents retrospectively my central contributions to the theoretical and applied aspects of optimization. When I had finished my thesis I became interested in editing a volume related to a new expanding area of applied optimization. I considered several approaches: simulated annealing, tabu search, genetic algorithms, neural networks, heuristics, expert systems, generalized multipliers, etc. Finally, I decided to edit a volume related to simulated annealing. My main three reasons for this choice were the following: (i) During the last four years my colleagues at IMSOR and I have car ried out several applied projects where simulated annealing was an essential. element in the problem-solving process. Most of the avail able reports and papers have been written in Danish. After a short review I was convinced that most of these works deserved to be pub lished for a wider audience. (ii) After the first reported applications of simulated annealing (1983- 1985), a tremendous amount of theoretical and applied work have been published within many different disciplines. Thus, I believe that simulated annealing is an approach that deserves to be in the curricula of, e.g. Engineering, Physics, Operations Research, Math ematical Programming, Economics, System Sciences, etc. (iii) A contact to an international network of well-known researchers showed that several individuals were willing to contribute to such a volume.