Written by a world leader in the field and aimed at researchers in applied and engineering sciences, this brilliant text has as its main goal imparting an understanding of the methods so that practitioners can make immediate use of existing algorithms and software, and so that researchers can extend the state of the art and find new applications. It includes algorithms on seeking feasibility and analyzing infeasibility, as well as describing new and surprising applications.

This book provides a synthesis of some recent issues and an up-to-date treatment of some of the major important issues in distributional analysis that I have covered in my previous book Ethical Social Index Numbers, which was widely accepted by students, teachers, researchers and practitioners in the area. Wide coverage of on-going and advanced topics and their analytical, articulate and authoritative p- sentation make the book theoretically and methodologically quite contemporary and inclusive, and highly responsive to the practical problems of recent concern. Since many countries of the world are still characterized by high levels of income inequality, Chap. 1 analyzes the problems of income inequality measurement in detail. Poverty alleviation is an overriding goal of development and social policy. To formulate antipoverty policies, research on poverty has mostly focused on inco- based indices. In view of this, a substantive analysis of income-based poverty has been presented in Chap. 2. The subject of Chap. 3 is people's perception about income inequality in terms of deprivation. Since polarization is of current concern to analysts and social decisi- makers, a discussion on polarization is presented in Chap. 4.

Income Elasticity and Economic Development Methods and Applications is mainly concerned with methods of estimating income elasticity. This field is connected with economic development that can be achieved by reducing income inequality. This is highly relevant in today's world, where the gap between rich and poor is widening with the growth of economic development. Income Elasticity and Economic Development Methods and Applications provides a good example in showing how to calculate income elasticity, using a number of methods from widely available grouped data. Some of the techniques presented here can be used in a wide range of policy areas in all developed, developing and under-developed countries. Policy analysts, economists, business analysts and market researchers will find this book very useful.

The econometric consequences of nonstationary data have wide ranging im plications for empirical research in economics. Specifically, these issues have implications for the study of empirical relations such as a money demand func tion that links macroeconomic aggregates: real money balances, real income and a nominal interest rate. Traditional monetary theory predicts that these nonsta tionary series form a cointegrating relation and accordingly, that the dynamics of a vector process comprised of these variables generates distinct patterns. Re cent econometric developments designed to cope with nonstationarities have changed the course of empirical research in the area, but many fundamental challenges, for example the issue of identification, remain. This book represents the efforts undertaken by the authors in recent years in an effort to determine the consequences that nonstationarity has for the study of aggregate money demand relations. We have brought together an empirical methodology that we find useful in conducting empirical research. Some of the work was undertaken during the authors' sabbatical periods and we wish to acknowledge the generous support of Arizona State University and Michigan State University respectively. Professor Hoffman wishes to acknowledge the support of the Fulbright-Hays Foundation that supported sabbattical research in Europe and separate support of the Council of 100 Summer Research Program at Arizona State University."

Lawrence Klein, University of Pennsylvania Jaime Marquez, Federal Reserve BoarrI* All examination of the economics literature over the last twenty years reveals a marked tendency towards polarisation. On the one hand, there has been a propensity to develop theoretical models which have little connection with either empirical verification or problems requiring immediate attention. On the other iland, empirical analyses are generally typified by testing for its own sake, with limited examination of the implications of the results. As a result, the number of papers confronting theory with facts towards the solution of economic problems has been on the decline for years. To fill this growing gap in the literature, we have invited a number of authors to write papers using both theoretical and empirical techniques to address current issues of interest to the profession at large: the US trade deficit and the global implications of policies that attempt to reduce it, the international ramifications of the debt crisis, the international oil market and its implications for the US oil industry, and the development of new econometric techniques. In addressing these issues, each author has approached the subject matter from an eclectic standpoint - that is, avoiding strict adherence to a given doctrine.

Markov chains have increasingly become useful way of capturing stochastic nature of many economic and financial variables. Although the hidden Markov processes have been widely employed for some time in many engineering applications e.g. speech recognition, its effectiveness has now been recognized in areas of social science research as well. The main aim of Hidden Markov Models: Applications to Financial Economics is to make such techniques available to more researchers in financial economics. As such we only cover the necessary theoretical aspects in each chapter while focusing on real life applications using contemporary data mainly from OECD group of countries. The underlying assumption here is that the researchers in financial economics would be familiar with such application although empirical techniques would be more traditional econometrics. Keeping the application level in a more familiar level, we focus on the methodology based on hidden Markov processes. This will, we believe, help the reader to develop more in-depth understanding of the modeling issues thereby benefiting their future research.

In a relatively short period of time, data envelopment analysis (DEA) has grown into a powerful analytical tool for measuring and evaluating performance. DEA is computational at its core and this book is one of several Springer aim to publish on the subject. This work deals with the micro aspects of handling and modeling data issues in DEA problems. It is a handbook treatment dealing with specific data problems, including imprecise data and undesirable outputs.

This book is the result of my doctoral dissertation research at the Department of Econometrics of the University of Geneva, Switzerland. This research was also partially financed by the Swiss National Science Foundation (grants 12- 31072.91 and 12-40300.94). First and foremost, I wish to express my deepest gratitude to Professor Manfred Gilli, my thesis supervisor, for his constant support and help. I would also like to thank the president of my jury, Professor Fabrizio Carlevaro, as well as the other members of the jury, Professor Andrew Hughes Hallett, Professor Jean-Philippe Vial and Professor Gerhard Wanner. I am grateful to my colleagues and friends of the Departement of Econometrics, especially David Miceli who provided constant help and kind understanding during all the stages of my research. I would also like to thank Pascale Mignon for proofreading my text and im proving my English. Finally, I am greatly indebted to my parents for their kindness and encourage ments without which I could never have achieved my goals. Giorgio Pauletto Department of Econometrics, University of Geneva, Geneva, Switzerland Chapter 1 Introduction The purpose of this book is to present the available methodologies for the solution of large-scale macroeconometric models. This work reviews classical solution methods and introduces more recent techniques, such as parallel com puting and nonstationary iterative algorithms."

Patrick Artus and Yves Barroux The Applied Econometric Association organised an international conference on "Monetary and Financial Models" in Geneva in January 1987. The purpose of this book is to make available to the public a choice of the papers that were presented at the conference. The selected papers all deal with the setting of monetary targets and the effects of monetary policy on the economy as well as with the analysis of the financial behaviours of economic agents. Other papers presented at the same conference but dealing with the external aspects of monetary policy (exchange rate policy, international coordination of economic policies, international transmission of business cycles, . . . ) are the matter of a distinct publication. The papers put together to make up this book either are theoretical research contributions or consist of applied statistical or econometric work. It seemed to be more logical to start with the more theoretical papers. The topics tackled in the first two parts of the book have in common the fact that they appeared just recently in the field of economic research and deal with the analysis of the behaviour of Central Banks. They analyse this behaviour so as to be able to exhibit its major determinants as well as revealed preferences of Central Banks: this topic comes under the caption "optimal monetary policy and reaction function of the monetary authorities."

Simulation methods are revolutionizing the practice of applied economic analysis. This volume collects eighteen chapters written by leading researchers from prestigious research institutions the world over. The common denominator of the papers is their relevance for applied research in environmental and resource economics.

The topics range from discrete choice modeling with heterogeneity of preferences, to Bayesian estimation, to Monte Carlo experiments, to structural estimation of Kuhn-Tucker demand systems, to evaluation of simulation noise in maximum simulated likelihood estimates, to dynamic natural resource modeling. Empirical cases are used to show the practical use and the results brought forth by the different methods.

A non-technical introduction to the question of modeling with time-varying parameters, using the beta coefficient from Financial Economics as the main example. After a brief introduction to this coefficient for those not versed in finance, the book presents a number of rather well known tests for constant coefficients and then performs these tests on data from the Stockholm Exchange. The Kalman filter is then introduced and a simple example is used to demonstrate the power of the filter. The filter is then used to estimate the market model with time-varying betas. The book concludes with further examples of how the Kalman filter may be used in estimation models used in analyzing other aspects of finance. Since both the programs and the data used in the book are available for downloading, the book is especially valuable for students and other researchers interested in learning the art of modeling with time varying coefficients.

Non-Parametric Statistical Diagnosis

Productivity growth is a keyword for sustainable economic growth in a knowledge-based society. There has been significant methodological development in the literature on productivity and efficiency analysis, e.g. SFA (Stochastic Frontier Analysis) and DEA (Data Envelopment Analysis). All these methodological developments should be matched with applications in order to provide practical implications for private and public decision-makers. This volume provides a collection of up-to-date and new applications of productivity and efficiency analysis. In particular, the case studies cover various economic issues in the Asia-Pacific region. The authors analyze the performance of manufacturing firms, banks, venture capital, broadcasting firms, as well as the issues of efficiency in the education sector, regional development, and defense industry. These case studies will shed light on the potential contribution of productivity and efficiency analysis to the enhancement of economic performance.

World-renowned experts in spatial statistics and spatial econometrics present the latest advances in specification and estimation of spatial econometric models. This includes information on the development of tools and software, and various applications. The text introduces new tests and estimators for spatial regression models, including discrete choice and simultaneous equation models. The performance of techniques is demonstrated through simulation results and a wide array of applications related to economic growth, international trade, knowledge externalities, population-employment dynamics, urban crime, land use, and environmental issues. An exciting new text for academics with a theoretical interest in spatial statistics and econometrics, and for practitioners looking for modern and up-to-date techniques.

This book examines non-Gaussian distributions. It addresses the causes and consequences of non-normality and time dependency in both asset returns and option prices. The book is written for non-mathematicians who want to model financial market prices so the emphasis throughout is on practice. There are abundant empirical illustrations of the models and techniques described, many of which could be equally applied to other financial time series.

This second edition sees the light three years after the first one: too short a time to feel seriously concerned to redesign the entire book, but sufficient to be challenged by the prospect of sharpening our investigation on the working of econometric dynamic models and to be inclined to change the title of the new edition by dropping the "Topics in" of the former edition. After considerable soul searching we agreed to include several results related to topics already covered, as well as additional sections devoted to new and sophisticated techniques, which hinge mostly on the latest research work on linear matrix polynomials by the second author. This explains the growth of chapter one and the deeper insight into representation theorems in the last chapter of the book. The role of the second chapter is that of providing a bridge between the mathematical techniques in the backstage and the econometric profiles in the forefront of dynamic modelling. For this purpose, we decided to add a new section where the reader can find the stochastic rationale of vector autoregressive specifications in econometrics. The third (and last) chapter improves on that of the first edition by re- ing the fruits of the thorough analytic equipment previously drawn up."

Astranger in academia cannot but be impressed by the apparent uniformity and precision of the methodology currently applied to the measurement of economic relationships. In scores of journal articles and other studies, a theoretical argument is typically presented to justify the position that a certain variable is related to certain other, possibly causal, variables. Regression or a related method is applied to a set of observations on these variables, and the conclusion often emerges that the causa,l variables are indeed "significant" at a certain "level," thereby lending support to the theoretical argument-an argument presumably formulated independently of the observations. A variable may be declared significant (and few doubt that this does not mean important) at, say, the 0. 05 level, but not the 0. 01. The effects of the variables are calculated to many significant digits, and are often accompanied by intervals and forecasts of not quite obvious meaning but certainly of reassuring "confidence. " The uniformity is also evident in the many mathematically advanced text books of statistics and econometrics, and in their less rigorous introductory versions for students in economics or business. It is reflected in the tools of the profession: computer programs, from the generaiones addressed to the incidental researcher to the dedicated and sophisticated programs used by the experts, display the same terms and implement the same methodology. In short, there appears no visible alternative to the established methodol ogy and no sign of reservat ions concerning its validity.

In this book, different quantitative approaches to the study of electoral systems have been developed: game-theoretic, decision-theoretic, statistical, probabilistic, combinatorial, geometric, and optimization ones. All the authors are prominent scholars from these disciplines. Quantitative approaches offer a powerful tool to detect inconsistencies or poor performance in actual systems. Applications to concrete settings such as EU, American Congress, regional, and committee voting are discussed.

This text provides a new approach to the subject, including a comprehensive survey of novel theoretical approaches, methods, and models used in macroeconomics and macroeconometrics. The book gives extensive insight into economic policy, incorporates a strong international perspective, and offers a broad historical perspective.

Over the past 25 years, applied econometrics has undergone tremen dous changes, with active developments in fields of research such as time series, labor econometrics, financial econometrics and simulation based methods. Time series analysis has been an active field of research since the seminal work by Box and Jenkins (1976), who introduced a gen eral framework in which time series can be analyzed. In the world of financial econometrics and the application of time series techniques, the ARCH model of Engle (1982) has shifted the focus from the modelling of the process in itself to the modelling of the volatility of the process. In less than 15 years, it has become one of the most successful fields of 1 applied econometric research with hundreds of published papers. As an alternative to the ARCH modelling of the volatility, Taylor (1986) intro duced the stochastic volatility model, whose features are quite similar to the ARCH specification but which involves an unobserved or latent component for the volatility. While being more difficult to estimate than usual GARCH models, stochastic volatility models have found numerous applications in the modelling of volatility and more particularly in the econometric part of option pricing formulas. Although modelling volatil ity is one of the best known examples of applied financial econometrics, other topics (factor models, present value relationships, term structure 2 models) were also successfully tackled.

The determinants of yield curve dynamics have been thoroughly discussed in finance models. However, little can be said about the macroeconomic factors behind the movements of short- and long-term interest rates as well as the risk compensation demanded by financial investors. By taking on a macro-finance perspective, the book's approach explicitly acknowledges the close feedback between monetary policy, the macroeconomy and financial conditions. Both theoretical and empirical models are applied in order to get a profound understanding of the interlinkages between economic activity, the conduct of monetary policy and the underlying macroeconomic factors of bond price movements. Moreover, the book identifies a broad risk-taking channel of monetary transmission which allows a reassessment of the role of financial constraints; it enables policy makers to develop new guidelines for monetary policy and for financial supervision of how to cope with evolving financial imbalances.

On May 27-31, 1985, a series of symposia was held at The University of Western Ontario, London, Canada, to celebrate the 70th birthday of Pro fessor V. M. Joshi. These symposia were chosen to reflect Professor Joshi's research interests as well as areas of expertise in statistical science among faculty in the Departments of Statistical and Actuarial Sciences, Economics, Epidemiology and Biostatistics, and Philosophy. From these symposia, the six volumes which comprise the "Joshi Festschrift" have arisen. The 117 articles in this work reflect the broad interests and high quality of research of those who attended our conference. We would like to thank all of the contributors for their superb cooperation in helping us to complete this project. Our deepest gratitude must go to the three people who have spent so much of their time in the past year typing these volumes: Jackie Bell, Lise Constant, and Sandy Tarnowski. This work has been printed from "camera ready" copy produced by our Vax 785 computer and QMS Lasergraphix printers, using the text processing software TEX. At the initiation of this project, we were neophytes in the use of this system. Thank you, Jackie, Lise, and Sandy, for having the persistence and dedication needed to complete this undertaking."

Economists, psychologists, and marketers are interested in determining the monetary value people place on non-market goods for a variety of reasons: to carry out cost-benefit analysis, to determine the welfare effects of technological innovation or public policy, to forecast new product success, and to understand individual and consumer behavior. Unfortunately, many currently available techniques for eliciting individuals' values suffer from a serious problem in that they involve asking individuals hypothetical questions about intended behavior. Experimental auctions circumvent this problem because they involve individuals exchanging real money for real goods in an active market. This represents a promising means for eliciting non-market values. Lusk and Shogren provide a comprehensive guide to the theory and practice of experimental auctions. It will be a valuable resource to graduate students, practitioners and researchers concerned with the design and utilization of experimental auctions in applied economic and marketing research.

Economists, psychologists, and marketers are interested in determining the monetary value people place on non-market goods for a variety of reasons: to carry out cost-benefit analysis, to determine the welfare effects of technological innovation or public policy, to forecast new product success, and to understand individual and consumer behavior. Unfortunately, many currently available techniques for eliciting individuals' values suffer from a serious problem in that they involve asking individuals hypothetical questions about intended behavior. Experimental auctions circumvent this problem because they involve individuals exchanging real money for real goods in an active market. This represents a promising means for eliciting non-market values. Lusk and Shogren provide a comprehensive guide to the theory and practice of experimental auctions. It will be a valuable resource to graduate students, practitioners and researchers concerned with the design and utilization of experimental auctions in applied economic and marketing research.

This book presents the state of the art in multilevel analysis, with an emphasis on more advanced topics. These topics are discussed conceptually, analyzed mathematically, and illustrated by empirical examples. Multilevel analysis is the statistical analysis of hierarchically and non-hierarchically nested data. The simplest example is clustered data, such as a sample of students clustered within schools. Multilevel data are especially prevalent in the social and behavioral sciences and in the biomedical sciences. The chapter authors are all leading experts in the field. Given the omnipresence of multilevel data in the social, behavioral, and biomedical sciences, this book is essential for empirical researchers in these fields.