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.

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.

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.

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.

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.

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.

Louis Phlips The stabilisation of primary commodity prices, and the related issue of the stabilisation of export earnings of developing countries, have traditionally been studied without reference to the futures markets (that exist or could exist) for these commodities. These futures markets have in turn been s udied in isolation. The same is true for the new developments on financial markets. Over the last few years, in particular sine the 1985 tin crisis and the October 1987 stock exchange crisis, it has become evident that there are inter actions between commodity, futures, and financial markets and that these inter actions are very important. The more so as trade on futures and financial markets has shown a spectacular increase. This volume brings together a number of recent and unpublished papers on these interactions by leading specialists (and their students). A first set of papers examines how the use of futures markets could help stabilising export earnings of developing countries and how this compares to the rather unsuccessful UNCTAD type interventions via buffer stocks, pegged prices and cartels. A second set of papers faces the fact, largely ignored in the literature, that commodity prices are determined in foreign currencies, with the result that developing countries suffer from the volatility of exchange rates of these currencies (even in cases where commodity prices are relatively stable). Financial markets are thus explicitly linked to futures and commodity markets."

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."

This 2005 volume brings together twelve papers by many of the most prominent applied general equilibrium modelers honoring Herbert Scarf, the father of equilibrium computation in economics. It deals with developments in applied general equilibrium, a field which has broadened greatly since the 1980s. The contributors discuss some traditional as well as some modern topics in the field, including non-convexities in economy-wide models, tax policy, developmental modeling and energy modeling. The book also covers a range of distinct approaches, conceptual issues and computational algorithms, such as calibration and areas of application such as macroeconomics of real business cycles and finance. An introductory chapter written by the editors maps out issues and scenarios for the future evolution of applied general equilibrium.

All humans eventually die, but life expectancies differ over time and among different demographic groups. Teasing out the various causes and correlates of death is a challenge, and it is one we take on in this book. A look at the data on mortality is both interesting and suggestive of some possible relationships. In 1900 life expectancies at birth were 46. 3 and 48. 3 years for men and women respectively, a gender differential of a bit less than 5 percent. Life expectancies for whites then were about 0. 3 years longer than that of the whole population, but life expectancies for blacks were only about 33 years for men and women. At age 65, the remaining life expectancies were about 12 and 11 years for whites and blacks respectively. Fifty years later, life expectancies at birth had grown to 66 and 71 years for males and females respectively. The percentage differential between the sexes was now almost up to 10 percent. The life expectancies of whites were about one year longer than that for the entire population. The big change was for blacks, whose life expectancy had grown to over 60 years with black females living about 5 percent longer than their male counterparts. At age 65 the remaining expected life had increased about two years with much larger percentage gains for blacks.

Macroeconomic Modelling has undergone radical changes in the last few years. There has been considerable innovation in developing robust solution techniques for the new breed of increasingly complex models. Similarly there has been a growing consensus on their long run and dynamic properties, as well as much development on existing themes such as modelling expectations and policy rules. This edited volume focuses on those areas which have undergone the most significant and imaginative developments and brings together the very best of modelling practice. We include specific sections on (I) Solving Large Macroeconomic Models, (II) Rational Expectations and Learning Approaches, (III) Macro Dynamics, and (IV) Long Run and Closures. All of the contributions offer new research whilst putting their developments firmly in context and as such will influence much future research in the area. It will be an invaluable text for those in policy institutions as well as academics and advanced students in the fields of economics, mathematics, business and government. Our contributors include those working in central banks, the IMF, European Commission and established academics.

Testing for a unit root is now an essential part of time series analysis. Indeed no time series study in economics, and other disciplines that use time series observations, can ignore the crucial issue of nonstationarity caused by a unit root. However, the literature on the topic is large and often technical, making it difficult to understand the key practical issues.
This volume provides an accessible introduction and a critical overview of tests for a unit root in time series, with extensive practical examples and illustrations using simulation analysis. It presents the concepts that enable the reader to understand the theoretical background, and importance of random walks and Brownian motion, to the development of unit root tests. The book also examines the latest developments and practical concerns in unit root testing.
This book is indispensable reading for all interested in econometrics, time series econometrics, applied econometrics and applied statistics. It will also be of interest to other disciplines, such as geography, climate change and meteorology, which use time series data.

This important collection brings together leading econometricians to discuss advances in the areas of the econometrics of panel data. The papers in this collection can be grouped into two categories. The first, which includes chapters by Amemiya, Baltagi, Arellano, Bover and Labeaga, primarily deal with different aspects of limited dependent variables and sample selectivity. The second group of papers, including those by Nerlove, Schmidt and Ahn, Kiviet, Davies and Lahiri, consider issues that arise in the estimation of dyanamic (possibly) heterogeneous panel data models. Overall, the contributors focus on the issues of simplifying complex real-world phenomena into easily generalisable inferences from individual outcomes. As the contributions of G. S. Maddala in the fields of limited dependent variables and panel data were particularly influential, it is a fitting tribute that this volume is dedicated to him.

Game Theory has provided an extremely useful tool in enabling economists to venture into unknown areas. Its concepts of conflict and cooperation apply whenever the actions of several agents are interdependent; providing language to formulate as well as to structure, analyze, and understand strategic scenarios. Economic Behavior, Game Theory, and Technology in Emerging Markets explores game theory and its deep impact in developmental economics, specifically the manner in which it provides a way of formalizing institutions. This is particularly important for emerging economies which have not yet received much attention in the academic world. This publication is useful for academics, professors, and researchers in this field, but it has also been compiled to meet the needs of non-specialists as well.

Swaps, futures, options, structured instruments - a wide range of derivative products is traded in today's financial markets. Analyzing, pricing and managing such products often requires fairly sophisticated quantitative tools and methods. This book serves as an introduction to financial mathematics with special emphasis on aspects relevant in practice. In addition to numerous illustrative examples, algorithmic implementations are demonstrated using "Mathematica" and the software package "UnRisk" (available for both students and teachers). The content is organized in 15 chapters that can be treated as independent modules.

In particular, the exposition is tailored for classroom use in a Bachelor or Master program course, as well as for practitioners who wish to further strengthen their quantitative background.

This book reports the results of five empirical studies undertaken in the early seventies by a collaboration headed by Professor Morishima. It deals with applications of the general equilibrium models whose theoretical aspects have been one of Professor Morishima's main interests. Four main econometric models are constructed for the USA, the UK, and Japan. These are used as a basis for the discussion of various topics in economic theory, such as: the existence and stability or instability of the neoclassical path of full employment growth equilibrium and a von Neumann-type path of balanced growth at constant proces; the antimony between price-stability and full employment; the Samuelson-LeChatelier principle; the theory of the balanced-budget multiplier; the three Hicksian laws of the gross substitutes system; the Brown-Jones super-multipliers of international trade, and so on. In addition, this 1972 work makes a quantitative evaluation for the US economy of monetary and fiscal policies as short-run measures for achieving full employment; the effectiveness of built-in flexibility of taxes in the UK economy is discussed; and estimates are made of the rapid decrease in disguised unemployment in post-war Japan.

This tutorial presents a hands-on introduction to a new discrete choice modeling approach based on the behavioral notion of regret-minimization. This so-called Random Regret Minimization-approach (RRM) forms a counterpart of the Random Utility Maximization-approach (RUM) to discrete choice modeling, which has for decades dominated the field of choice modeling and adjacent fields such as transportation, marketing and environmental economics. Being as parsimonious as conventional RUM-models and compatible with popular software packages, the RRM-approach provides an alternative and appealing account of choice behavior. Rather than providing highly technical discussions as usually encountered in scholarly journals, this tutorial aims to allow readers to explore the RRM-approach and its potential and limitations hands-on and based on a detailed discussion of examples. This tutorial is written for students, scholars and practitioners who have a basic background in choice modeling in general and RUM-modeling in particular. It has been taken care of that all concepts and results should be clear to readers that do not have an advanced knowledge of econometrics.

This book was first published in 1989. Inference and prediction in human affairs are characterised by a cognitive and reactive sample space, the elements of which are aware both of the statistician and of each other. It is therefore not surprising that methodologies borrowed from classical statistics and the physical sciences have yielded disappointingly few lasting empirical insights and have sometimes failed in predictive mode. This book puts the underlying methodology of socioeconomic statistics on a firmer footing by placing it within the ambit of inferential and predictive games. It covers such problems as learning, publication, non-response, strategic response, the nature and possibility of rational expectations, time inconsistency, intrinsic nonstationarity, and the existence of probabilities. Ideas are introduced such as real-time survey schemes, argument instability and reaction-proof forecasting based on stochastic approximation. Applications are canvassed to such topics as attitude measurement, political polling, econometric modelling under heterogeneous information, and the forecasting of hallmark events.