This 2005 volume contains the papers presented in honor of the lifelong achievements of Thomas J. Rothenberg on the occasion of his retirement. The authors of the chapters include many of the leading econometricians of our day, and the chapters address topics of current research significance in econometric theory. The chapters cover four themes: identification and efficient estimation in econometrics, asymptotic approximations to the distributions of econometric estimators and tests, inference involving potentially nonstationary time series, such as processes that might have a unit autoregressive root, and nonparametric and semiparametric inference. Several of the chapters provide overviews and treatments of basic conceptual issues, while others advance our understanding of the properties of existing econometric procedures and/or propose others. Specific topics include identification in nonlinear models, inference with weak instruments, tests for nonstationary in time series and panel data, generalized empirical likelihood estimation, and the bootstrap.

This book deals with the omitted variable tests for a multivariate time-series regression model. What are the consequences of testing for the omission of a variable when the model is dynamically misspecified? What is the small sample bias of the omitted variable test when the model dynamics is correctly specificfied? The answers to these questions are proposed in this book. As an empirical illustration, the analysis is applied to the homogeneity test of a demand system. I particularly thank Professor Dr. Philippe J. Deschamps who draw my attention on this subject and who made very helpful comments and sugges- tions. Additionally, I would like to thank Professor Dr. Reiner Wolff for his comments especially on the chapter dealing with consumer theory. Special thanks go to Maria Jose Redondo, who read this book several times and for the inspiring discussions with her. I would also like to thank Dr. Ali Vak- ili (always ready to answer any questions in mathematics), Prof. Dr. Hans Wolf gang Brachinger, Curzio De Gottardi, Peter Mantsch, Dr. Paul-Andre Monney, Dr. Uwe Steinhauser, Leon Stroeks and Dr. Peter Windlin. Frances Angell improved the English of this work. The research for this book had been financially suppurted by the Univer- site de Fribourg (Switzerland). Finally, I appreciated the support from Springer-Verlag and I thank Dr.

The book reports experimental studies and a theoretical investigation of non-cooperative bargaining games with joint production. Such games have rarely been studied within laboratory experiments despite being more general and more natural than bargaining without production. It is shown that equity theory is a good predictor of subjects' behavior. Furthermore subjects exhibit different equity notions. One chapter addresses problems of statistical data analysis that are specific to experiments. Applying evolutionary game theory within a model of bargaining with production it is shown theoretically that altruistic preferences, which generate moderate bargaining behavior, can survive the process of evolution.

In the past few decades, methods of linear algebra have become central to economic analysis, replacing older tools such as the calculus. David Gale has provided the first complete and lucid treatment of important topics in mathematical economics which can be analyzed by linear models. This self-contained work requires few mathematical prerequisites and provides all necessary groundwork in the first few chapters. After introducing basic geometric concepts of vectors and vector spaces, Gale proceeds to give the main theorems on linear inequalities--theorems underpinning the theory of games, linear programming, and the Neumann model of growth. He then explores such subjects as linear programming; the theory of two-person games; static and dynamic theories of linear exchange models, including problems of equilibrium prices and dynamic stability; and methods of play, optimal strategies, and solutions of matrix games. This book should prove an invaluable reference source and text for mathematicians, engineers, economists, and those in many related areas.

The use of computer simulations to study social phenomena has grown rapidly during the last few years. Many social scientists from the fields of economics, sociology, psychology and other disciplines now use computer simulations to study a wide range of social phenomena. The availability of powerful personal computers, the development of multidisciplinary approaches and the use of artificial intelligence models have all contributed to this development. The benefits of using computer simulations in the social sciences are obvious. This holds true for the use of simulations as tools for theory building and for its implementation as a tool for sensitivity analysis and parameter optimization in application-oriented models. In both, simulation provides powerful tools for the study of complex social systems, especially for dynamic and multi-agent social systems in which mathematical tractability is often impossible. The graphical display of simulation output renders it user friendly to many social scientists that lack sufficient familiarity with the language of mathematics. The present volume aims to contribute in four directions: (1) To examine theoretical and methodological issues related to the application of simulations in the social sciences. By this we wish to promote the objective of designing a unified, user-friendly, simulation toolkit which could be applied to diverse social problems. While no claim is made that this objective has been met, the theoretical issues treated in Part 1 of this volume are a contribution towards this objective.

A novel methodology is put forward in this book, which empowers researchers to investigate and identify potential spatial processes among a set of regions. Spatial processes and their underlying functional spatial relationships are commonly observed in the geosciences and related disciplines. Examples are spatially autocorrelated random variables manifesting themselves in distinct global patterns as well as local clusters and hot spots, or spatial interaction leading to stochastic ties among the regions. An example from observational epidemiology demonstrates the flexibility of Moran's approach by analyzing the spatial distribution of cancer data from several perspectives. Recent advances in computing technology, computer algorithms, statistical techniques and global and local spatial patterns by means of Moran's "I" feasability. Moran's "I" is an extremely versatile tool for exploring and analyzing spatial data and testing spatial hypotheses.

Neural networks have had considerable success in a variety of disciplines including engineering, control, and financial modelling. However a major weakness is the lack of established procedures for testing mis-specified models and the statistical significance of the various parameters which have been estimated. This is particularly important in the majority of financial applications where the data generating processes are dominantly stochastic and only partially deterministic. Based on the latest, most significant developments in estimation theory, model selection and the theory of mis-specified models, this volume develops neural networks into an advanced financial econometrics tool for non-parametric modelling. It provides the theoretical framework required, and displays the efficient use of neural networks for modelling complex financial phenomena. Unlike most other books in this area, this one treats neural networks as statistical devices for non-linear, non-parametric regression analysis.

In the mid-eighties Mehra and Prescott showed that the risk premium earned by American stocks cannot reasonably be explained by conventional capital market models. Using time additive utility, the observed risk pre mium can only be explained by unrealistically high risk aversion parameters. This phenomenon is well known as the equity premium puzzle. Shortly aft erwards it was also observed that the risk-free rate is too low relative to the observed risk premium. This essay is the first one to analyze these puzzles in the German capital market. It starts with a thorough discussion of the available theoretical mod els and then goes on to perform various empirical studies on the German capital market. After discussing natural properties of the pricing kernel by which future cash flows are translated into securities prices, various multi period equilibrium models are investigated for their implied pricing kernels. The starting point is a representative investor who optimizes his invest ment and consumption policy over time. One important implication of time additive utility is the identity of relative risk aversion and the inverse in tertemporal elasticity of substitution. Since this identity is at odds with reality, the essay goes on to discuss recursive preferences which violate the expected utility principle but allow to separate relative risk aversion and intertemporal elasticity of substitution."

This study was written while I was a doctoral student in the Graduier- tenkolleg Finanz-und Gutermiirkte at the University of Mannheim; it has been accepted as a doctoral dissertation in February 1997. I am indebted to my advisors, Professors Axel Borsch-Supan and Martin Hellwig at Mannheim and John Rust at Madison, for their encouragement and for many helpful discussions and comments. At various stages, I benefited from comments on portions of the manu- script by, and from discussions with, Thomas Astebro, Charles Calomiris, Timothy Dunne, Frank Gerhard, Annette Kohler, Jens Koke, Stephan Monissen, Gordon Phillips, Winfried Pohlmeier, Kenneth Troske, Wol- fram Wissler and seminar participants at Columbia Business School, the University of Mannheim, the University of Tiibingen, the University of Wisconsin at Madison, Yale University, the ENTER Jamborees at Uni- versity College London, January 1995, and at Tilburg University, January 1997, at a Meeting of the DFG-Schwerpunktprogramm Industrieokonomik und Inputmiirkte, Heidelberg, November 1996, and at the annual meeting of the Verein fur Socialpolitik, Bern, September 1997. Silke Januszewski and Melanie Liihrmann provided dedicated assistence during the prepa- ration of the final version of the manuscript.

This book comprises the articles of the 6th Econometric Workshop in Karlsruhe, Germany. In the first part approaches from traditional econometrics and innovative methods from machine learning such as neural nets are applied to financial issues. Neural Networks are successfully applied to different areas such as debtor analysis, forecasting and corporate finance. In the second part various aspects from Value-at-Risk are discussed. The proceedings describe the legal framework, review the basics and discuss new approaches such as shortfall measures and credit risk.

Many econometric models contain unknown functions as well as finite- dimensional parameters. Examples of such unknown functions are the distribution function of an unobserved random variable or a transformation of an observed variable. Econometric methods for estimating population parameters in the presence of unknown functions are called "semiparametric." During the past 15 years, much research has been carried out on semiparametric econometric models that are relevant to empirical economics. This book synthesizes the results that have been achieved for five important classes of models. The book is aimed at graduate students in econometrics and statistics as well as professionals who are not experts in semiparametic methods. The usefulness of the methods will be illustrated with applications that use real data.

Researchers often have difficulties collecting enough data to test their hypotheses, either because target groups are small or hard to access, or because data collection entails prohibitive costs. Such obstacles may result in data sets that are too small for the complexity of the statistical model needed to answer the research question. This unique book provides guidelines and tools for implementing solutions to issues that arise in small sample research. Each chapter illustrates statistical methods that allow researchers to apply the optimal statistical model for their research question when the sample is too small. This essential book will enable social and behavioral science researchers to test their hypotheses even when the statistical model required for answering their research question is too complex for the sample sizes they can collect. The statistical models in the book range from the estimation of a population mean to models with latent variables and nested observations, and solutions include both classical and Bayesian methods. All proposed solutions are described in steps researchers can implement with their own data and are accompanied with annotated syntax in R. The methods described in this book will be useful for researchers across the social and behavioral sciences, ranging from medical sciences and epidemiology to psychology, marketing, and economics.

This manuscript is about the joint dynamics of stock returns and trading volume. It grew out of my attempt to construct an intertemporal asset pricing model with rational agents which can. explain the relation between volume, volatility and persistence of stock return documented in empirical literature. Most part of the manuscript is taken from my thesis. I wish to express my deep appreciation to Peter Kugler and Benedikt Poetscher, my advisors of the thesis, for their invaluable guidance and support. I wish to thank Gerhard Orosel and Gerhard Sorger for their encouraging and helpful discussions. Finally, my thanks go to George Tauchen who has been generous in giving me the benefit of his numerical and computational experience, in providing me with programs and in his encouragement. Contents 1 Introduction 1 7 2 Efficient Stock Markets Equilibrium Models of Asset Pricing 8 2. 1 2. 1. 1 The Martigale Model of Stock Prices 8 2. 1. 2 Lucas' Consumption Based Asset Pricing Model 9 2. 2 Econometric Tests of the Efficient Market Hypothesis 13 2. 2. 1 Autocorrelation Based Tests 14 16 2. 2. 2 Volatility Tests Time-Varying Expected Returns 25 2. 2. 3 3 The Informational Role of Volume 29 3. 1 Standard Grossman-Stiglitz Model 31 3. 2 The No-Trad Result of the BEO Model 34 A Model with Nontradable Asset 37 3. 3 4 Volume and Volatility of Stock Returns 43 4. 1 Empirical and Numerical Results 45 4.

This volume contains revised versions of 43 papers presented during the 21st Annual Conference of the Gesellschaft fur Klassifikation (GfKl), the German Classification Society. The conference took place at the University of Pots- dam (Germany) in March 1997; the local organizer was Prof. 1. Balderjahn, Chair of Business Administration and Marketing at Potsdam. The scientific program of the conference included 103 plenary and con- tributed papers, software and book presentations as well as special (tutorial) courses. Researchers and practitioners interested in data analysis and clus- tering methods, information sciences and database techniques, and in the main topic of the conference: data highways and their importance for classifi- cation and data analysis, had the opportunity to discuss recent developments and to establish cross-disciplinary cooperation in these fields. The conference owed much to its sponsors - Berliner Volksbank - Daimler Benz AG - Deutsche Telekom AG Direktion Potsdam - Dresdner Bank AG Filiale Potsdam - Henkel KGaA - Landeszentralbank in Berlin und Brandenburg - Ministerium fur Wissenschaft, Forschung und Kultur des Landes Brandenburg - Sci con GmbH - Siemens AG - Universitat Potsdam - Unternehmensgruppe Roland Ernst who helped in many ways. Their generous support is gratefully acknowl- edged. In the present proceedings volume, selected and peer-reviewed papers are presented in six chapters as follows.

Enders continues to provide business professionals with an accessible introduction to time-series analysis. Clearly shows them how to develop models capable of forecasting, interpreting, and testing hypotheses concerning economic data using the latest techniques.Includes new discussions on parameter instability and structural breaks as well as out-of-sample forecasting methods.New developments in unit root test and cointegration tests are covered. Multivariate GARCH models are also presented. In addition, several statistical examples have been updated with real-world data to help business professionals understand the relevance of the material

Economic forecasting involves choosing simple yet robust models to best approximate highly complex and evolving data-generating processes. This poses unique challenges for researchers in a host of practical forecasting situations, from forecasting budget deficits and assessing financial risk to predicting inflation and stock market returns. Economic Forecasting presents a comprehensive, unified approach to assessing the costs and benefits of different methods currently available to forecasters. This text approaches forecasting problems from the perspective of decision theory and estimation, and demonstrates the profound implications of this approach for how we understand variable selection, estimation, and combination methods for forecasting models, and how we evaluate the resulting forecasts. Both Bayesian and non-Bayesian methods are covered in depth, as are a range of cutting-edge techniques for producing point, interval, and density forecasts. The book features detailed presentations and empirical examples of a range of forecasting methods and shows how to generate forecasts in the presence of large-dimensional sets of predictor variables. The authors pay special attention to how estimation error, model uncertainty, and model instability affect forecasting performance. * Presents a comprehensive and integrated approach to assessing the strengths and weaknesses of different forecasting methods* Approaches forecasting from a decision theoretic and estimation perspective* Covers Bayesian modeling, including methods for generating density forecasts* Discusses model selection methods as well as forecast combinations* Covers a large range of nonlinear prediction models, including regime switching models, threshold autoregressions, and models with time-varying volatility* Features numerous empirical examples* Examines the latest advances in forecast evaluation* Essential for practitioners and students alike

One aim of this book is to examine the causes of fluctuations in the mark/dollar, pound/dollar, and yen/dollar real exchange rates for the period 1972-1994 with quarterly data to determine appropriate policy recommendations to reduce these movements. A second aim is to investigate whether the three real exchange rates are covariance-stationary or not and to which extent they are covariance-stationary, respectively. These aims are reached by using a two-country overshooting model for real exchange rates with real government expenditure and by applying Johansen's maximum likelihood cointegration procedure and a factor model of Gonzalo and Granger to this model.

Considerable work has been done on chaotic dynamics in the field of economic growth and dynamic macroeconomic models during the last two decades. This book considers numerous new developments: introduction of infrastructure in growth models, heterogeneity of agents, hysteresis systems, overlapping models with "pay-as-you-go" systems, keynesian approaches with finance considerations, interactions between relaxation cycles and chaotic dynamics, methodological issues, long memory processes and fractals... A volume of contributions which shows the relevance and fruitfulness of non-linear analysis for the explanation of complex dynamics in economic systems.

The present book was accepted as a dissertation at the Humboldt Universitat zu Berlin in summer 1996. I am very much obliged to thank my advisor, Professor Wolfgang Hardie, for the continuous, always inspiring support and for opening me the world of non parametric statistics. Without him I probably would have worked on a different, less exciting topic and this book would not exist. Also, I would like to thank my second advisor, Professor Helmut Liitkepohl, for his excellent introduction to time series analysis and for always helpful comments on my work. This work was financially supported by the Deutsche Forschungsgemein schaft, in the first stage while I was a member of the Graduiertenkolleg "Ap plied Microeconomics," and later when I came to the Sonderforschungsbereich 373. For an interestingly widespread academic surrounding I want to thank the members of the Graduiertenkolleg and the Sonderforschungsbereich, es pecially Stefan Sperlich and Axel Werwatz. For the use of XploRe and many other issues I received substantial help from my colleagues Sigbert Klinke, Thomas Kotter, Marlene Miiller and Swetlana Schmelzer. Concerning many central topics of this dissertation, helpful and improving comments were given by Jorg Breitung, Helmut Herwartz, RolfTschernig and Lijian Yang, who also revised most parts of the manuscript. I have much reason to thank them for their help. Of course, all remaining errors are mine. Berlin, July 1997 CHRISTIAN M 0 HAFNER Contents Preface . . . . . IX List of Tables ."

Since there exists a multi-level policy making system in the market economies, choices of decision makers at different levels should be considered explicitly in the formulation of sectoral plans and policies. To support the hypothesis, a theoretical energy planning approach is developed within the framework of the theory of economic policy planning, policy systems analysis and multi-level programming. The Parametric Programming Search Algorithm has been developed. On the basis of this theoretical model, an Australian Energy Policy System Optimisation Model (AEPSOM) has been developed and is used to formulate an Australian multi-level energy plan.

This book presents an extensive survey of the theory and empirics of international parity conditions which are critical to our understanding of the linkages between world markets and the movement of interest and exchange rates across countries. The book falls into three parts dealing with the theory, methods of econometric testing and existing empirical evidence. Although it is intended to provide a consensus view on the subject, the authors also make some controversial propositions, particularly on the purchasing power parity conditions.

1.1 Economic issues to be analyzed This research examines two elements of the Swiss market for electricity: the residential electricity demand by time-of-use and the cost structure of municipal electricity distribution utilities. The empirical results of demand and cost elasticities allow the investigation of interesting economic and policy issues such as the desirability of a widespread introduction of time-of-use pricing for residential customers, the desirability of side-by-side competition in the distribution of electricity and, more generally, the economic effects of a reduction of the load factor and of mergers between electric distribution utilities on costs. Desirability of time-of-use pricing In the last decade there has been an intensifying debate in Switzerland about efficacy of electricity rate reforms in order to improve the efficiency of electricity use. This debate was initiated by two main events. First, there was an important growth of electricity consumption. Second, the Chernobyl accident in 1986 aroused widespread public concern about the problems associated with nuclear power and waste disposal. As a result, in 1991 the Swiss voted, in a referendum, a lO-year moratorium on the 2 construction of new nuclear power plants. Moreover, plans to expand production of hydroelectric power (construction of new dams or expanding existing ones) have been stiffly opposed by environmental groups. These developments have consistently curtailed potential expansion of domestic electricity supply. As a result, Switzerland during the winter has to import electricity from foreign countries.

Subject is the description of unvariate and multivariate business cycle stylized facts. A spectral analysis method (Maximum Entropy spectral estimation) novel in the analysis of economic time series is described and utilized. The method turns out to be superior to widely used time domain methods and the "classical" spectral estimate, the periodogram. The results for eleven OECD countries confirm and extend the basic set of stylized facts of traditional business cycle theory. The changing characteristics of the business cycle are analyzed by comparing the cyclical structure for the postwar and the prewar period. The results show that business cycle is mainly due to investment fluctuations.

We live in a time of economic virtualism, whereby our lives are made to conform to the virtual reality of economic thought. Globalization, transnational capitalism, structural adjustment programmes and the decay of welfare are all signs of the growing power of economics, one of the most potent forces of recent decades. In the last thirty years, economics has ceased to be just an academic discipline concerned with the study of economy, and has come to be the only legitimate way to think about all aspects of society and how we order our lives. Economic models are no longer measured against the world they seek to describe, but instead the world is measured against them, found wanting and made to conform.This profound and dangerous change in the power of abstract economics to shape the lives of people in rich and poor countries alike is the subject of this interdisciplinary study. Contributors show how economics has come to portray a virtual reality -- a world that seems real but is merely a reflection of a neo-classical model -- and how governments, the World Bank and the IMF combine to stamp the world with a virtual image that condemns as irrational our local social and cultural arrangements. Further, it is argued that virtualism represents the worrying emergence of new forms of abstraction in the political economy, of which economics is just one example.