Modelling and Forecasting Financial Data brings together a coherent and accessible set of chapters on recent research results on this topic. To make such methods readily useful in practice, the contributors to this volume have agreed to make available to readers upon request all computer programs used to implement the methods discussed in their respective chapters. Modelling and Forecasting Financial Data is a valuable resource for researchers and graduate students studying complex systems in finance, biology, and physics, as well as those applying such methods to nonlinear time series analysis and signal processing.

The modern system-wide approach to applied demand analysis emphasizes a unity between theory and applications. Its firm foundations in economic theory make it one of the most successful areas of applied econometrics. A System-Wide Analysis of International Consumption Patterns presents a large number of applications of recent innovations in the area and uses consumption data for 18 OECD countries to provide convincing evidence, one way or the other, about the validity of consumption theory. The empirical results presented in the book have a number of uses. Reliable estimates of income and price elasticities of demand are provided for 10 commodity groups in 18 countries. A feature of these results is that a number of major empirical regularities are identified that seem to hold across different periods and different countries. A System-Wide Analysis of International Consumption Patterns also presents an extensive application of recently developed Monte Carlo testing procedures - to test demand theory and the structure of preferences. The results so obtained are in stark contrast to most previous findings based on the conventional asymptotic tests. Other results presented in the book include: (i) Differences in economic variables (prices and and incomes in particular) account for observed differences in consumption patterns internationally, while differences in tastes seem to play a much smaller role. (ii) Own-price elasticities are approximately proportional to the corresponding income elasticities, a result coinciding with Pigou's law. (iii) The income elasticity of the marginal utility of income does not seem to depend on income, which contradicts the famous Frisch's conjecture.

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.

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.

Unlike uncertain dynamical systems in physical sciences where models for prediction are somewhat given to us by physical laws, uncertain dynamical systems in economics need statistical models. In this context, modeling and optimization surface as basic ingredients for fruitful applications. This volume concentrates on the current methodology of copulas and maximum entropy optimization. This volume contains main research presentations at the Sixth International Conference of the Thailand Econometrics Society held at the Faculty of Economics, Chiang Mai University, Thailand, during January 10-11, 2013. It consists of keynote addresses, theoretical and applied contributions. These contributions to Econometrics are somewhat centered around the theme of Copulas and Maximum Entropy Econometrics. The method of copulas is applied to a variety of economic problems where multivariate model building and correlation analysis are needed. As for the art of choosing copulas in practical problems, the principle of maximum entropy surfaces as a potential way to do so. The state-of-the-art of Maximum Entropy Econometrics is presented in the first keynote address, while the second keynote address focusses on testing stationarity in economic time series data.

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.

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.

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.

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.

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.

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.

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.

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.

PREFACE TO THE COLLECTION PREAMBLE The editors are pleased to present a selection of Henri Theil's contributions to economics and econometrics in three volumes. In Volume I we have provided an overview of Theil's contributions, a brief biography, an annotated bibliography of his research, and a selection of published and unpublished articles and chapters in books dealing with topics in econometrics. Volume II contains Theil's contributions to demand analysis and information theory. Volume III includes Theil's contributions in economic policy and forecasting, and management science. The selection of articles is intended to provide examples of Theil's many seminal and pathbreaking contributions to economics in such areas as econometrics, statistics, demand analysis, information theory, economic policy analysis, aggregation theory, forecasting, index numbers, management science, sociology, operations research, higher education and much more. The collection is also intended to serve as a tribute to him on the occasion of his 68th birthday: These three volumes also highlight some of Theil's contributions and service to the profession as a leader, advisor, administrator, teacher, and researcher. Theil's contributions, which encompass many disciplines, have been extensively cited both in scientific and professional journals. These citations often place Theil among 10 researchers (ranked according to number of times cited) in the world in various the top disciplines.

Agent-Based Computer Simulation of Dichotomous Economic Growth reports a project in agent-based computer stimulation of processes of economic growth in a population of boundedly rational learning agents. The study is an exercise in comparative simulation. That is, the same family of growth models will be simulated under different assumptions about the nature of the learning process and details of the production and growth processes. The purpose of this procedure is to establish a relationship between the assumptions and the simulation results. The study brings together a number of theoretical and technical developments, only some of which may be familiar to any particular reader. In this first chapter, some issues in economic growth are reviewed and the objectives of the study are outlined. In the second chapter, the simulation techniques are introduced and illustrated with baseline simulations of boundedly rational learning processes that do not involve the complications of dealing with long-run economic growth. The third chapter sketches the consensus modern theory of economic growth which is the starting point for further study. In the fourth chapter, a family of steady growth models are simulated, bringing the simulation, growth and learning aspects of the study together. In subsequent chapters, variants on the growth model are explored in a similar way. The ninth chapter introduces trade, with a spacial trading model that is combined with the growth model in the tenth chapter. The book returns again and again to the key question: to what extent can the simulations `explain' the puzzles of economic growth, and particularly the key puzzle of dichotomization, by constructing growth and learning processes that produce the puzzling results? And just what assumptions of the simulations are most predictable associated with the puzzling results?

Econophysics is an emerging interdisciplinary field that takes advantage of the concepts and methods of statistical physics to analyse economic phenomena. This book expands the explanatory scope of econophysics to the real economy by using methods from statistical physics to analyse the success and failure of companies. Using large data sets of companies and income-earners in Japan and Europe, a distinguished team of researchers show how these methods allow us to analyse companies, from huge corporations to small firms, as heterogeneous agents interacting at multiple layers of complex networks. They then show how successful this approach is in explaining a wide range of recent findings relating to the dynamics of companies. With mathematics kept to a minimum, the book is not only a lively introduction to the field of econophysics but also provides fresh insights into company behaviour.

The field of Computational Economics is a fast growing area. Due to the limitations in analytical modeling, more and more researchers apply numerical methods as a means of problem solving. In tum these quantitative results can be used to make qualitative statements. This volume of the Advanced Series in Theoretical and Applied and Econometrics comprises a selected number of papers in the field of computational economics presented at the Annual Meeting of the Society Economic Dynamics and Control held in Minneapolis, June 1990. The volume covers ten papers dealing with computational issues in Econo metrics, Economics and Optimization. The first five papers in these proceedings are dedicated to numerical issues in econometric estimation. The following three papers are concerned with computational issues in model solving and optimization. The last two papers highlight some numerical techniques for solving micro models. We are sure that Computational Economics will become an important new trend in Economics in the coming decade. Hopefully this volume can be one of the first contributions highlighting this new trend. The Editors H.M. Amman et a1. (eds), Computational Economics and Econometrics, vii. (c) 1992 Kluwer Academic Publishers. PART ONE ECONOMETRICS LIKELIHOOD EVALUATION FOR DYNAMIC LATENT VARIABLES 1 MODELS DAVID F. HENDRY Nuffield College, Oxford, U.K. and JEAN-FRANc;mS RICHARD ISDS, Pittsburgh University, Pittsburgh, PA, U.S.A."

Economics has been basically a study of the interactions between organizations, with some organizations being so small we only have one person in them. The internal organization of the largest hierarchies has indeed been looked at, but a good reason for working less on these organizations is that the internal reactions are much harder to understand. It is sensible to solve the problems we can solve and put the others off until later. The author's basic purpose here is to look at these larger hierarchical organizations, and develop a scientific account of them. In Economic Hierarchies, Organization and the Structure of Production Gordon Tullock examines the internal functioning and organization of the corporation. In the author's personal tradition, the book relies on narrative analysis rather than mathematical complexity to convey insights into the functioning of the corporation.

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.

The present work is an extension of my doctoral thesis done at Stanford in the early 1970s. In one clear sense it responds to the call for consilience by Edward O. Wilson. I agree with Wilson that there is a pressing need in the sciences today for the unification of the social with the natural sciences. I consider the present work to proceed from the perspective of behavioral ecology, specifically a subfield which I choose to call interpersonal behavioral ecology th Ecology, as a general field, has emerged in the last quarter of the 20 century as a major theme of concern as we have become increasingly aware that we must preserve the planet whose limited resources we share with all other earthly creatures. Interpersonal behavioral ecology, however, focuses not on the physical environment, but upon our social environment. It concerns our interpersonal behavioral interactions at all levels, from simple dyadic one-to-one personal interactions to our larger, even global, social, economic, and political interactions. Interpersonal behavioral ecology, as I see it, then, is concerned with our behavior toward each other, from the most obvious behaviors of war between nations, to excessive competition, exploitation, crime, abuse, and even to the ways in which we interact with each other as individuals in the family, in our social lives, in the workplace, and in the marketplace.

Technology Commercialization: DEA and Related Analytical Methods for Evaluating The Use and Implementation of Technical Innovation examines both general Research & Development commercialization and targeted new product innovation. New product development is a major occupation of the technical sector of the global economy and is viewed in many ways as a means of economic stability for a business, an industry, and a country. The heart of the book is a detailing of the analytical methods-with special, but not exclusive emphasis on DEA methods-for evaluating and ranking the most promising R & D and technical innovation being developed. The sponsors of the research and development may involve universities, countries, industries, and corporations-all of these sources are covered in the book. In addition, the trade-off of environmental problems vis-a-vis new product development is discussed in a section of the book. Sten Thore (editor and author) has woven together the chapter contributions by a strong group of international researchers into a book that has characteristics of both a monograph and a unified edited volume of well-written papers in DEA, technology evaluation, R&D, and environmental economics. Finally, the use of DEA as an evaluation method for product innovation is an important new development in the field of R&D commercialization.

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.

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.

Every advance in computer architecture and software tempts statisticians to tackle numerically harder problems. To do so intelligently requires a good working knowledge of numerical analysis. This book equips students to craft their own software and to understand the advantages and disadvantages of different numerical methods. Issues of numerical stability, accurate approximation, computational complexity, and mathematical modeling share the limelight in a broad yet rigorous overview of those parts of numerical analysis most relevant to statisticians. In this second edition, the material on optimization has been completely rewritten. There is now an entire chapter on the MM algorithm in addition to more comprehensive treatments of constrained optimization, penalty and barrier methods, and model selection via the lasso. There is also new material on the Cholesky decomposition, Gram-Schmidt orthogonalization, the QR decomposition, the singular value decomposition, and reproducing kernel Hilbert spaces. The discussions of the bootstrap, permutation testing, independent Monte Carlo, and hidden Markov chains are updated, and a new chapter on advanced MCMC topics introduces students to Markov random fields, reversible jump MCMC, and convergence analysis in Gibbs sampling. Numerical Analysis for Statisticians can serve as a graduate text for a course surveying computational statistics. With a careful selection of topics and appropriate supplementation, it can be used at the undergraduate level. It contains enough material for a graduate course on optimization theory. Because many chapters are nearly self-contained, professional statisticians will also find the book useful as a reference.

Control theory methods in economics have historically developed over three phases. The first involved basically the feedback control rules in a deterministic framework which were applied in macrodynamic models for analyzing stabilization policies. The second phase raised the issues of various types of inconsistencies in deterministic optimal control models due to changing information and other aspects of stochasticity. Rational expectations models have been extensively used in this plan to resolve some of the inconsistency problems. The third phase has recently focused on the various aspects of adaptive control. where stochasticity and information adaptivity are introduced in diverse ways e.g . risk adjustment and risk sensitivity of optimal control, recursive updating rules via Kalman filtering and weighted recursive least squares and variable structure control methods in nonlinear framework. Problems of efficient econometric estimation of optimal control models have now acquired significant importance. This monograph provides an integrated view of control theory methods, synthesizing the three phases from feedback control to stochastic control and from stochastic control to adaptive control. Aspects of econometric estimation are strongly emphasized here, since these are very important in empirical applications in economics."