How successful is PPP, and its extension in the monetary model, as a measure of the equilibrium exchange rate? What are the determinants and dynamics of equilibrium real exchange rates? How can misalignments be measured, and what are their causes? What are the effects of specific policies upon the equilibrium exchange rate? The answers to these questions are important to academic theorists, policymakers, international bankers and investment fund managers. This volume encompasses all of the competing views of equilibrium exchange rate determination, from PPP, through other reduced form models, to the macroeconomic balance approach. This volume is essentially empirical: what do we know about exchange rates? The different econometric and theoretical approaches taken by the various authors in this volume lead to mutually consistent conclusions. This consistency gives us confidence that significant progress has been made in understanding what are the fundamental determinants of exchange rates and what are the forces operating to bring them back in line with the fundamentals.

Studies in Consumer Demand - Econometric Methods Applied to Market Data contains eight previously unpublished studies of consumer demand. Each study stands on its own as a complete econometric analysis of demand for a well-defined consumer product. The econometric methods range from simple regression techniques applied in the first four chapters, to the use of logit and multinomial logit models used in chapters 5 and 6, to the use of nested logit models in chapters 6 and 7, and finally to the discrete/continuous modeling methods used in chapter 8. Emphasis is on applications rather than econometric theory. In each case, enough detail is provided for the reader to understand the purpose of the analysis, the availability and suitability of data, and the econometric approach to measuring demand.

Nonlinear Time Series Analysis of Economic and Financial Data provides an examination of the flourishing interest that has developed in this area over the past decade. The constant theme throughout this work is that standard linear time series tools leave unexamined and unexploited economically significant features in frequently used data sets. The book comprises original contributions written by specialists in the field, and offers a combination of both applied and methodological papers. It will be useful to both seasoned veterans of nonlinear time series analysis and those searching for an informative panoramic look at front-line developments in the area.

Cost Structure and the Measurement of Economic Performance is designed to provide a comprehensive guide for students, researchers or consultants who wish to model, construct, interpret, and use economic performance measures. The topical emphasis is on productivity growth and its dependence on the cost structure. The methodological focus is on application of the tools of economic analysis - the `thinking structure' provided by microeconomic theory - to measure technological or cost structure, and link it with market and regulatory structure. This provides a rich basis for evaluation of economic performance and its determinants. The format of the book stresses topics or questions of interest rather than the theoretical tools for analysis. Traditional productivity growth modeling and measurement practices that result in a productivity residual often called the `measure of our ignorance' are initially overviewed, and then the different aspects of technological, market and regulatory structure that might underlie this residual are explored. The ultimate goal is to decompose or explain the residual, by modeling and measuring a multitude of impacts that determine the economic performance of firms, sectors, and economies. The chapters are organized with three broad goals in mind. The first is to introduce the overall ideas involved in economic performance measurement and traditional productivity growth analysis. Issues associated with different types of (short and long run, internal and external) cost economies, market and regulatory impacts, and other general cost efficiencies that might impact these measures are then explored. Finally, some of the theoretical, data construction and econometric tools necessary to justify and implement these models are emphasized.

The twelve papers in this collection grew out of the workshop on "Eco nomic Evolution, Learning, and Complexity" held at the University of Augsburg, Augsburg, Germany on May 23-25, 1997. The Augsburg workshop was the second of two events in the Euroconference Series on Evolutionary Economics, the first of which was held in Athens, Greece in September 1993. A special issue of the Journal of Evolutionary Econo mics (1993(4)) edited by Yannis Katsoulacos on "Evolutionary and Neo classical Perspectives on Market Structure and Economic Growth" con tains selected papers from the Athens conference. The Athens conference explored neoclassical and evolutionary perspectives on technological competition and increasing returns. It helped to identify the dis tinguishing features of evolutionary scholarship. The Augsburg workshop was more oriented toward exploring methodological issues in evolutiona of the papers employed new me ry and related scholarship. A number thods, such as genetic programming and experimental analysis, some developed new econometric techniques or raised new empirical issues in evolutionary economics, and some relied on simulation techniques. Twelve papers covering a range of areas were selected for this collection. The papers address central issues in evolutionary and Schumpeterian accounts of industrial competition, learning, and innovation."

Stochastic Volatility in Financial Markets presents advanced topics in financial econometrics and theoretical finance, and is divided into three main parts. The first part aims at documenting an empirical regularity of financial price changes: the occurrence of sudden and persistent changes of financial markets volatility. This phenomenon, technically termed stochastic volatility', or conditional heteroskedasticity', has been well known for at least 20 years; in this part, further, useful theoretical properties of conditionally heteroskedastic models are uncovered. The second part goes beyond the statistical aspects of stochastic volatility models: it constructs and uses new fully articulated, theoretically-sounded financial asset pricing models that allow for the presence of conditional heteroskedasticity. The third part shows how the inclusion of the statistical aspects of stochastic volatility in a rigorous economic scheme can be faced from an empirical standpoint.

Models, Methods, Concepts and Applications of the Analytic Hierarchy Process is a volume dedicated to selected applications of the Analytic Hierarchy Process (AHP) focused on three themes: economics, the social sciences, and the linking of measurement with human values. (1) The AHP offers economists a substantially different approach to dealing with economic problems through ratio scales. The main mathematical models on which economics has based its quantitative thinking up to now are utility theory, which uses interval scales, and linear programming. We hope that the variety of examples included here can perhaps stimulate researchers in economics to try applying this new approach. (2) The second theme is concerned with the social sciences. The AHP offers psychologists and political scientists the methodology to quantify and derive measurements for intangibles. We hope that the examples included in this book will encourage them to examine the methods of AHP in terms of the problems they seek to solve. (3) The third theme is concerned with providing people in the physical and engineering sciences with a quantitative method to link hard measurement to human values. In such a process one needs to interpret what the measurements mean. A number is useless until someone understands what it means. It can have different meanings in different problems. Ten dollars are plenty to satisfy one's hunger but are useless by themselves in buying a new car. Such measurements are only indicators of the state of a system, but do not relate to the values of the human observers of that system. AHP methods can help resolve the conflicts between hard measurement data and human values.

These three volumes contain an account of Professor Henri Theil's distinguished career as a leader, advisor, administrator, teacher, and researcher in economics and econometrics. The books also contain a selection of his contributions in many areas, such as econometrics, demand analysis, information theory, forecasting, statistics, economic policy analysis and management science. To date he has contributed over 250 articles in refereed journals and chapters in books, and 15 books, three of which became citation classics. His books and articles have appeared in (and have been translated into) many languages, such as Polish, Russian, Dutch, English, French, German, Hungarian, Italian and Japanese. This collection provides excellent reference material to researchers and graduate students working in a variety of disciplines, such as econometrics, economics, management science, operations research, and statistics. Moreover, Professor Theil's career serves as a role model for younger generations of scholars, both in terms of his approach to research and his commitment to his profession. Professor Theil's distinguished career as an academic began in 1953 when he was appointed Professor of Econometrics at the Netherlands School of Economics in Rotterdam (now Erasmus University). Three years later he founded the Econometric Institute in Rotterdam and served as its first director until 1966, when he accepted a joint appointment at the Graduate School of Business and Department of Economics, University of Chicago, U.S.A. In 1981, Theil was appointed to the McKethan-Matherly Eminent Chair at the Graduate School of Business Administration of the University of Florida in Gainesville. Theil has received many international honours including four honorary degrees.

Aspects of Robust Statistics are important in many areas. Based on the International Conference on Robust Statistics 2001 (ICORS 2001) in Vorau, Austria, this volume discusses future directions of the discipline, bringing together leading scientists, experienced researchers and practitioners, as well as younger researchers. The papers cover a multitude of different aspects of Robust Statistics. For instance, the fundamental problem of data summary (weights of evidence) is considered and its robustness properties are studied. Further theoretical subjects include e.g.: robust methods for skewness, time series, longitudinal data, multivariate methods, and tests. Some papers deal with computational aspects and algorithms. Finally, the aspects of application and programming tools complete the volume.

Hospital Cost Analysis provides an overview of theoretical developments in the economic analysis of production and costs in the multiproduct firm, and discusses these developments. Following a lucid explanation of the concepts of jointness, input/output separability and returns to scale, a detailed discussion of the concept measurement and classification of hospital output is provided. A fundamental dilemma confronting economists interested in estimating hospital cost functions is highlighted, viz. the trade-off between flexibility in functional form and homogeneity within hospital output categories. Empirical results on the effects of case mix, scale and utilisation, public/private ownership, and the centralised administration of hospital systems on hospital costs are presented. The implications of hospital cost analysis for public policy with respect to hospital payment schemes, including schemes based on Diagnosis Related Groups (DRGs), are also considered. This book brings together the literature on hospital cost analysis with theoretical developments in the analysis of the multiproduct cost functions. It will be of considerable interest to teachers and students of health economics and health policy advisers interested in the determinants of hospital costs and the design of hospital payment schemes.

Supply chain management (SCM) strives for creating competitive advantage and value for customers by integrating business processes from end users through original suppliers. However, the question of how SCM influences the value of a firm is not fully answered. Various conceptual frameworks that explain the coherence of SCM and company value, comprehended as value-based SCM, are well accepted in scientific research, but quantitative approaches to value-based SCM are found rather seldom. The book contributes to this research gap by proposing quantitative models that allow for assessing influences of SCM on the value of a firm. Opposed to existing models that limit the observation to chosen facets of SCM or selected value drivers, this holistic approach is adequate to * reflect configurational and operational aspects of SCM, * cover all phases of the product life cycle, * financially compare value impacts of profitability-related and asset-related value drivers, and * assess influences of dynamics and uncertainties on company value.

Quantitative Methods for Portfolio Analysis provides practical models and methods for the quantitative analysis of financial asset prices, construction of various portfolios, and computer-assisted trading systems. In particular, this book is required reading for: (1) `Quants' (quantitatively-inclined analysts) in financial industries; (2) financial engineers in investment banks, securities companies, derivative-trading companies, software houses, etc., who are developing portfolio trading systems; (3) graduate students and specialists in the areas of finance, business, economics, statistics, financial engineering; and (4) investors who are interested in Japanese financial markets. Throughout the book the emphasis is placed on the originality and usefulness of models and methods for the construction of portfolios and investment decision making, and examples are provided to demonstrate, with practical analysis, models for Japanese financial markets.

New Directions in Computational Economics brings together for the first time a diverse selection of papers, sharing the underlying theme of application of computing technology as a tool for achieving solutions to realistic problems in computational economics and related areas in the environmental, ecological and energy fields. Part I of the volume addresses experimental and computational issues in auction mechanisms, including a survey of recent results for sealed bid auctions. The second contribution uses neural networks as the basis for estimating bid functions for first price sealed bid auctions. Also presented is the `smart market' computational mechanism which better matches bids and offers for natural gas. Part II consists of papers that formulate and solve models of economics systems. Amman and Kendrick's paper deals with control models and the computational difficulties that result from nonconvexities. Using goal programming, Nagurney, Thore and Pan formulate spatial resource allocation models to analyze various policy issues. Thompson and Thrall next present a rigorous mathematical analysis of the relationship between efficiency and profitability. The problem of matching uncertain streams of assets and liabilities is solved using stochastic optimization techniques in the following paper in this section. Finally, Part III applies economic concepts to issues in computer science in addition to using computational techniques to solve economic models.

Since 1993 a major research programme, "Stochastic Decision Analysis in Forest Management" has been running at Department of Economics and Natural Resources, The Royal Veterinary and Agricultural University (KVL), Copenhagen, in collaboration with Institute of Mathematical Statistics, University of Copenhagen (KU). The research is funded by the two Universities; The Danish Agricultural and Veterinary Research Council; The Danish Research Academy; The National Forest and Nature Agency; and Danish Informatics Network in the Agricultural Sciepces (DINA). A first international workshop in the research programme was held 5 - 8 August, 1996 at Eldrupgaard, Denmark, within the frameworkofacollaborationagreementbetween University of California at Berkeley (UCB) and the Danish Universities, and funded by The Danish Research Academy and the L0venholm Foundation. Having participated in the workshop, Professor Peter Berck (UCB) suggested that the papers be published along with selected papers in the same scientific field, i.e. mainly cointegration analysis of time series in forestry. The editors express their sincere appreciations to the many persons who have contributed to the realisation of the present book: participants in the research programme and the workshop, in particular Professors S0ren Johansen (KU) and Peter Berck (UCB); authors outside the programme/workshop; reviewers of the papers not previously published, in particuler Associate Professors Niels Haldrup (Aarhus University) and Henrik Hansen (KVL); and finally Mrs Mette Riis and Lizzie Rohde who did the tedious work of giving the papers a uniform style. Copenhagen, October 1998.

Experiences with Financial Liberalization provides a broad spectrum of policy experiences relating to financial liberalization around the globe since the 1960s. There is a sizable body of theoretical and aggregative empirical literature in this area, but there is little work documenting and analyzing the experiences of individual countries and/or sets of countries. This book is divided into four parts by geographical region - Africa, Asia and Latin America, Central and Eastern Europe, and the Middle East. Aggregative econometric studies cannot substitute for country-wide studies in allowing the researcher to draw lessons for the future, and this volume adds to this relatively small body of literature.

Coordination is extremely important in economic, political, and social life. The concept of economic equilibrium is based on the coordination of producers and consumers in buying and selling. This book reviews the topic of coordination from an economic, theoretical standpoint. The aim of this volume is twofold: first, the book contributes to the ongoing research on the economics of coordination; and second, it disseminates results and encourages interest in the topic. The volume contains original research on coordination including general game-theoretic questions, particular coordination issues within specific fields of economics (i.e. industrial organization, international trade, and macroeconomics), and experimental research.

This conference brought together an international group of fisheries economists from academia, business, government, and inter-governmentalagencies, to consider a coordinated project to build an econometric model of the world trade in groundfish. A number of the conference participants had just spent up to six weeks at Memorial University of Newfoundland working and preparing papers on the project. This volume presents the papers that these scholars produced, plus additional papers prepared by other conference participants. In addition, various lectures and discussionswhich were transcribed from tapes made of the proceedings are included. The introductory essay explains the genesis of the conference, describes the approach taken to modelling the groundfish trade, very briefly summarizes the technical papers, and describes future plans. The project is continuing as planned, and a second conference was held in St. John's in August 1990. The conference was a NATO Advanced Research Workshop and we wish to thank the ScientificAffairs Division ofNATO for their financial support. Additional financial support was received from the Canadian Centre for Fisheries Innovation in St. John's, the Department of Fisheries and Oceans of the Government of Canada, the Department of Fisheries of the Government of Newfoundland and Labrador, Memorial University of Newfoundland and Air Nova; we acknowledge with appreciation their help.

4 UNIVERSITY RESEARCH AND THE SPATIAL DISTRIBUTION OF HIGH TECHNOLOGY INNOVATIONS AND PRIVATE RESEARCH . . . . . . . . 45 4. 1. INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 4. 2. THE INNOVATION, PRIVATE RESEARCH AND UNIVERSITY RESEARCH DATA . . . . 46 4. 3. THE SPATIAL DISTRIBUTION OF HIGH TECHNOLOGY INNOVATIONS . . . . . . . . . . . . . . . . 50 4. 4. THE SPATIAL DISTRIBUTION OF HIGH TECHNOLOGY R&D ACTIVITIES . . . . . . . . . . . 55 4. 5. THE SPATIAL DISTRIBUTION OF HIGH TECHNOLOGY UNIVERSITY RESEARCH AND ITS RELATION TO INNOVATIONS AND INDUSTRIAL RESEARCH . . . . . . . . . . . . . . . . . . . . . . . . 58 4. 6. SUMMARy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 5 LOCAL KNOWLEDGE TRANSFERS: STATE LEVEL ANALYSIS . . . . . . . . . 67 5. 1. INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 5. 2. STATE ANALYSIS AND LOCAL KNOWLEDGE TRANSFERS: SUMMARY OF EARLIER FINDINGS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 5. 3. ALTERNATIVE INDICATORS OF LOCAL UNIVERSITY KNOWLEDGE TRANSFERS 72 EMPIRICAL RESULT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 5. 4. 5. 5. SUMMARy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 6 THE SPATIAL EXTENT OF UNIVERSITY EFFECTS: MSA LEVEL ANALySIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 6. 1. INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 6. 2. THE MODEL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82 6. 2. ESTIMATION ISSUES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 6. 3. EMPIRICAL RESULTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90 6. 4. SUMMARy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 7 FACTORS GOVERNING UNIVERSITY EFFECTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 7. 1. INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 7. 2. THE EMPIRICAL MODEL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102 7. 3. REGRESSION RESULTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 7. 4. SPATIAL VARIATION IN THE INTENSITY OF UNIVERSITY KNOWLEDGE TRANSFERS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 7. 5. THE "CRITICAL MASS" OF AGGLOMERATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112 7. 6. SUMMARy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119 8 SUMMARY AND CONCLUSIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121 APPENDIX A: DEFINING HIGH TECHNOLOGY FOR THE EMPIRICAL STUDY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127 APPENDIX B: VARIABLE DEFINITIONS AND SOURCES . . . . . . . . . . . . . . . . . . . . . . . 131 REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135 INDEX . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149 List of Tables Table 2. 1.

In this book, we synthesize a rich and vast literature on econometric challenges associated with accounting choices and their causal effects. Identi?cation and es- mation of endogenous causal effects is particularly challenging as observable data are rarely directly linked to the causal effect of interest. A common strategy is to employ logically consistent probability assessment via Bayes' theorem to connect observable data to the causal effect of interest. For example, the implications of earnings management as equilibrium reporting behavior is a centerpiece of our explorations. Rather than offering recipes or algorithms, the book surveys our - periences with accounting and econometrics. That is, we focus on why rather than how. The book can be utilized in a variety of venues. On the surface it is geared - ward graduate studies and surely this is where its roots lie. If we're serious about our studies, that is, if we tackle interesting and challenging problems, then there is a natural progression. Our research addresses problems that are not well - derstood then incorporates them throughout our curricula as our understanding improves and to improve our understanding (in other words, learning and c- riculum development are endogenous). For accounting to be a vibrant academic discipline, we believe it is essential these issues be confronted in the undergr- uate classroom as well as graduate studies. We hope we've made some progress with examples which will encourage these developments.

These three volumes contain an account of Professor Henri Theil's distinguished career as a leader, advisor, administrator, teacher, and researcher in economics and econometrics. The books also contain a selection of his contributions in many areas, such as econometrics, demand analysis, information theory, forecasting, statistics, economic policy analysis and management science. To date he has contributed over 250 articles in refereed journals and chapters in books, and 15 books, three of which became citation classics. His books and articles have appeared in (and have been translated into) many languages, such as Polish, Russian, Dutch, English, French, German, Hungarian, Italian and Japanese. This collection provides excellent reference material to researchers and graduate students working in a variety of disciplines, such as econometrics, economics, management science, operations research, and statistics. Moreover, Professor Theil's career serves as a role model for younger generations of scholars, both in terms of his approach to research and his commitment to his profession. Professor Theil's distinguished career as an academic began in 1953 when he was appointed Professor of Econometrics at the Netherlands School of Economics in Rotterdam (now Erasmus University). Three years later he founded the Econometric Institute in Rotterdam and served as its first director until 1966, when he accepted a joint appointment at the Graduate School of Business and Department of Economics, University of Chicago, U.S.A. In 1981, Theil was appointed to the McKethan-Matherly Eminent Chair at the Graduate School of Business Administration of the University of Florida in Gainesville. Theil has received many international honours including four honorary degrees.

Mathematical economics uses mathematical tools and reasoning to describe and explain economic reality. At the core of mathematical economics is general equilibrium theory. Static and Dynamic Aspects of General Disequilibrium Theory describes and analyses various general equilibrium models, treating theory from an axiomatic point of view, which may lead to a deeper understanding of problems, may help to avoid incorrect reasoning, and may improve communication within the economic science. This volume consists of four parts, each of which is self-contained. Part I deals with the mathematical and economic preliminaries. Part II considers the static aspects of disequilibrium theory. Part III determines price rigidities endogenously. Finally, Part IV deals with dynamic aspects of disequilibrium theory.

The three decades which have followed the publication of Heinz Neudecker's seminal paper Some Theorems on Matrix Differentiation with Special Reference to Kronecker Products' in the Journal of the American Statistical Association (1969) have witnessed the growing influence of matrix analysis in many scientific disciplines. Amongst these are the disciplines to which Neudecker has contributed directly - namely econometrics, economics, psychometrics and multivariate analysis. This book aims to illustrate how powerful the tools of matrix analysis have become as weapons in the statistician's armoury. The majority of its chapters are concerned primarily with theoretical innovations, but all of them have applications in view, and some of them contain extensive illustrations of the applied techniques. This book will provide research workers and graduate students with a cross-section of innovative work in the fields of matrix methods and multivariate statistical analysis. It should be of interest to students and practitioners in a wide range of subjects which rely upon modern methods of statistical analysis. The contributors to the book are themselves practitioners of a wide range of subjects including econometrics, psychometrics, educational statistics, computation methods and electrical engineering, but they find a common ground in the methods which are represented in the book. It is envisaged that the book will serve as an important work of reference and as a source of inspiration for some years to come.

Econometric Business Cycle Research deals with econometric business cycle research (EBCR), a term introduced by the Nobel-laureate Jan Tinbergen for his econometric method of testing (economic) business cycle theories. EBCR combines economic theory and measurement in the study of business cycles, i.e., ups and downs in overall economic activity. We assess four methods of EBCR: business cycle indicators, simultaneous equations models, vector autoregressive systems and real business indicators. After a sketch of the history of the methods, we investigate whether the methods meet the goals of EBCR: the three traditional ones, description, forecasting and policy evaluation, and the one Tinbergen introduced, the implementation|testing of business cycles. The first three EBCR methods are illustrated for the Netherlands, a typical example of a small, open economy. The main conclusion of the book is that simultaneous equation models are the best vehicle for EBCR, if all its goals are to be attained simultaneously. This conclusion is based on a fairly detailed assessment of the methods and is not over-turned in the empirical illustrations. The main conclusion does not imply the end of other EBCR methods. Not all goals have to be met with a single vehicle, other methods might serve the purpose equally well - or even better. For example, if one is interested in business cycle forecasts, one might prefer a business cycle indicator or vector autoregressive system. A second conclusion is that many ideas/concepts that play an important role in current discussions about econometric methodology in general and EBCR in particular, were put forward in the 1930s and 1940s. A third conclusion is that it is difficult, if not impossible, to compare the outcomes of RBC models to outcomes of the other three methods, because RBC modellers are not interested in modelling business cycles on an observation-per-observation basis. A more general conclusion in this respect is that methods should adopt the same concept of business cycles to make them comparable.

This book provides a framework for analyzing and forecasting a variety of mineral and energy markets and related industries. Such modeling activity has been at the forefront of the economic and engineering professions for some time, having received a major stimulus fC?llowing the first oil price shock in 1973. Since that time, other shocks have affected these markets and industries, causing disequilibrium economic adjustments which are difficult to analyze and to predict. Moreover, geopolitics remains an important factor which can destabilize crude oil markets and associated refining industries. Mineral and energy modeling, consequently, has become a major interest of energy-related corporations, mining and drilling companies, metal manufacturers, public utilities, investment banks,. national government agencies and international organizations. This book hopes to advance mineral and energy modeling as follows: (1) The modeling process is presented sequentially by leading the model builder from model specification, estimation, simulation, and validation to practical model applications, including explaining history, analyzing policy, and market and price forecasting; (2) New developments in modeling approaches are presented which encompass econometric market and industry models, spatial equilibrium and programming models, optimal resource depletion models, input-output models, economic sector models, and macro oriented energy interaction models (including computable general equilibrium); (3) The verification and application of the models is considered not only individually but also in relation to the performance of alternative modeling approaches; and (4) The modeling framework includes a perspective on new directions, so that the present model building advice will extend into the future.

All former Soviet Union countries experience their past as a heavy burden. It led to the centralisation of scientific personnel, the separation of research from teaching at universities, and a concentration of certain branches of technology in different parts of the Union. This has given rise to a one-sided technology and science potential which frequently cannot be sufficiently supported due to a lack of adequate finance. Cooperation between the Baltic States themselves is often hampered by an exaggerated sense of national identity, and international cooperation can be made difficult by linguistic problems. A critical issue is finance. The Baltic States themselves are experiencing budgetary constraints, and the West is cutting back on funding. The analytical issues dealt with here include specific questions, such as in the sectors of energy policy, electrical equipment and electronics, and environmental considerations. The transfer of technology is also discussed, as is security: there is the possibility that science and scientific results can be obtained from the former Soviet Union at low cost by the criminal community.