Valuing and Investing in Equities: CROCI: Cash Return on Capital Investment develops a common-sense framework for value investors. By distinguishing investors from speculators, it acknowledges the variety of styles and goals in the financial markets. After explaining the intuition behind due diligence, portfolio construction, and stock picking, it shows the reader how to perform these steps and how to evaluate their results. Francesco Curto illuminates the costs and opportunities afforded by valuation strategies, inflation, and bubbles, emphasizing their effects on each other within the CROCI framework. Balancing analytics with an engaging clarity, the book neatly describes a comprehensive, time-tested approach to investing. Annual returns from this investment approach demand everyone's attention.

Population aging raises a number of issues regarding the optimality of public debt policy and the systems of public pension provisions that are in use in developed countries. The studies in this book address these questions using computable general equilibrium models. They give illuminating insights and new empirical estimates of future prospects of pay-as-you-go pension schemes in the "big seven" OECD countries, the possible distortions introduced by the pension systems in four large European economies, the effects of lifetime uncertainty in analyzing a potential reform of the Dutch pension system, effects of increasing international mobility of financial capital to pension policies, and public debt reduction policies in relation to possible adverse effects of taxation on wage formation and unemployment.

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.

Getting accurate data on less developed countries has created great problems for studying these areas. Yet until recently students of development economics have relied on standard econometrics texts, which assume a Western context. Econometrics and Data Analysis for Developing Countries solves this problem. It will be essential reading for all advanced students of development economics.

1. 1 Introduction In economics, one often observes time series that exhibit different patterns of qualitative behavior, both regular and irregular, symmetric and asymmetric. There exist two different perspectives to explain this kind of behavior within the framework of a dynamical model. The traditional belief is that the time evolution of the series can be explained by a linear dynamic model that is exogenously disturbed by a stochastic process. In that case, the observed irregular behavior is explained by the influence of external random shocks which do not necessarily have an economic reason. A more recent theory has evolved in economics that attributes the patterns of change in economic time series to an underlying nonlinear structure, which means that fluctua tions can as well be caused endogenously by the influence of market forces, preference relations, or technological progress. One of the main reasons why nonlinear dynamic models are so interesting to economists is that they are able to produce a great variety of possible dynamic outcomes - from regular predictable behavior to the most complex irregular behavior - rich enough to meet the economists' objectives of modeling. The traditional linear models can only capture a limited number of possi ble dynamic phenomena, which are basically convergence to an equilibrium point, steady oscillations, and unbounded divergence. In any case, for a lin ear system one can write down exactly the solutions to a set of differential or difference equations and classify them."

Migration, commuting, and tourism are prominent phenomena demonstrating the political and economic relevance of the spatial choice behavior of households. The identification of the determinants and effects of the households' location choice is necessary for both entrepreneurial and policy planners who attempt to predict (or regulate) the future demand for location-specific commodities, such as infrastructure, land, or housing, and the supply of labor. Microeconomic studies of the spatial behavior of individuals have typically focused upon the demand for a single, homogeneous, yet location-specific com 2 modity (such as land or housing ) or their supply of labor3 and investigated the formation of location-specific prices and wages in the presence of transportation and migration costs or analyzed the individual-and location-specific character istics triggering spatial rather than quantitative or temporal adjustments. In contrast to many theoretical analyses, empirical studies of the causes or con sequences of individual demand for location-specific commodities have often considered several "brands" of a heterogeneous good that are offered at various locations, are perfect substitutes, and may be produced by varying production 4 technologies. lCf. Alonso (1964) 2Cf. Muth (1969). 3Cf. Sjaastad (1962) and Greenwood (1975)."

The papers collected in this volume are contributions to T.I.Tech./K.E.S. Conference on Nonlinear and Convex Analysis in Economic Theory, which was held at Keio University, July 2-4, 1993. The conference was organized by Tokyo Institute of Technology (T. I. Tech.) and the Keio Economic Society (K. E. S.) , and supported by Nihon Keizai Shimbun Inc .. A lot of economic problems can be formulated as constrained optimiza tions and equilibrations of their solutions. Nonlinear-convex analysis has been supplying economists with indispensable mathematical machineries for these problems arising in economic theory. Conversely, mathematicians working in this discipline of analysis have been stimulated by various mathematical difficulties raised by economic the ories. Although our special emphasis was laid upon "nonlinearity" and "con vexity" in relation with economic theories, we also incorporated stochastic aspects of financial economics in our project taking account of the remark able rapid growth of this discipline during the last decade. The conference was designed to bring together those mathematicians who were seriously interested in getting new challenging stimuli from economic theories with those economists who were seeking for effective mathematical weapons for their researches. Thirty invited talks (six of them were plenary talks) given at the conf- ence were roughly classified under the following six headings : 1) Nonlinear Dynamical Systems and Business Fluctuations, . 2) Fixed Point Theory, 3) Convex Analysis and Optimization, 4) Eigenvalue of Positive Operators, 5) Stochastic Analysis and Financial Market, 6) General Equilibrium Analysis.

As a new type of technique, simplicial methods have yielded extremely important contributions toward solutions of a system of nonlinear equations. Theoretical investigations and numerical tests have shown that the performance of simplicial methods depends critically on the triangulations underlying them. This monograph describes some recent developments in triangulations and simplicial methods. It includes the D1-triangulation and its applications to simplicial methods. As a result, efficiency of simplicial methods has been improved significantly. Thus more effective simplicial methods have been developed.

The problem of disparities between different estimates of GDP is, according to this text, well-known and widely discussed. Here, the authors describe a method for examining the discrepancies using a technique allocating them with reference to data reliability. The method enhances the reliability of the underlying data and leads to maximum-likelihood estimates. It is illustrated by application to the UK national accounts for the period 1920-1990. The book includes a full set of estimates for this period, including runs of industrial data for the period 1948-1990 which are longer than those available from any other source. The statistical technique allows estimates of standard errors of the data to be calculated and verified; these are presented both for data in levels and for changes in variables over one-, two- and five-year periods. A disk with the dataset in machine readable form is available separately.

This book brings together a wide range of topics and perspectives in the growing field of Classification and related methods of Exploratory and Multivariate Data Analysis. It gives a broad view on the state ofthe art, useful for those in the scientific community who gather data and seek tools for analyzing and interpreting large sets of data. As it presents a wide field of applications, this book is not only of interest for data analysts, mathematicians and statisticians, but also for scientists from many areas and disciplines concerned with real data, e. g. , medicine, biology, astronomy, image analysis, pattern recognition, social sciences, psychology, marketing, etc. It contains 79 invited or selected and refereed papers presented during the Fourth Bi- ennial Conference of the International Federation of Classification Societies (IFCS'93) held in Paris. Previous conferences were held at Aachen (Germany), Charlottesville (USA) and Edinburgh (U. K. ). The conference at Paris emerged from the elose coop- eration between the eight members of the IFCS: British Classification Society (BCS), Classification Society of North America (CSNA), Gesellschaft fur Klassifikation (GfKl), J apanese Classification Society (J CS), Jugoslovenska Sekcija za Klasifikacije (JSK), Societe Francophone de Classification (SFC), Societa. Italiana di Statistica (SIS), Vereniging voor Ordinatie en Classificatie (VOC), and was organized by INRIA ("Institut National de Recherche en Informatique et en Automatique"), Rocquencourt and the "Ecole Nationale Superieure des Telecommuni- cations," Paris.

This two-volume work aims to present as completely as possible the methods of statistical inference with special reference to their economic applications. It is a well-integrated textbook presenting a wide diversity of models in a coherent and unified framework. The reader will find a description not only of the classical concepts and results of mathematical statistics, but also of concepts and methods recently developed for the specific needs of econometrics. Although the two volumes do not demand a high level of mathematical knowledge, they do draw on linear algebra and probability theory. The breadth of approaches and the extensive coverage of this two-volume work provide for a thorough and entirely self-contained course in modern economics. Volume 1 provides an introduction to general concepts and methods in statistics and econometrics, and goes on to cover estimation and prediction. Volume 2 focuses on testing, confidence regions, model selection, and asymptotic theory.

This study is a revised version of my doctoral dissertation at the Economics Department of the University of Munich. I want to take the opportunity to express my gratitude to some people who have helped me in my work. My greatest thanks go to the supervisor of this dissertation, Professor Claude Billinger. Bis ideas have formed the basis of my work. Be permanently sup ported it with a host of ideas, criticism and encouragement. Furthermore, he provided a stimulating research environment at SEMECON. This study would not have been possible in this form without the help of my present and former colleagues at SEMECON. I am indebted to Rudolf Kohne-Volland, Monika Sebold-Bender and Ulrich Woitek for providing soft ware and guidance for the data analysis. Discussions with them and with Thilo Weser have helped me to take many hurdles, particularly in the early stages of the project. My sincere thanks go to them all. I had the opportunity to present a former version of my growth model at a workshop of Professor Klaus Zimmermann. I want to thank all the parti cipants for their helpful comments. I also acknowledge critical and constructive comments from an anonymous referee. Table of Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Part I. Methodology 1. Importance of Stylized Facts. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 1.1 Limitations of statistical testing. . . . . . . . . . . . . . . . . . . . . . . . . . 9 1.2 Evaluating economic models. . . . . . . . . . . . . . . . . . .. . . . 11 . . . . . . 2. Further Methodological Issues . . . . . . . . . . . . . . . . . .. . . . 13 . . . . . ."

In this compelling 1995 book, David Hendry and Mary Morgan bring together the classic papers of the pioneer econometricians. Together, these papers form the foundations of econometric thought. They are essential reading for anyone seeking to understand the aims, method and methodology of econometrics and the development of this statistical approach in economics. However, because they are technically straightforward, the book is also accessible to students and non-specialists. An editorial commentary places the readings in their historical context and indicates the continuing relevance of these early, yet highly sophisticated, works for current econometric analysis. While this book provides a companion volume to Mary Morgan's acclaimed The History of Econometric Ideas, the editors' commentary both adds to that earlier volume and also provides a stand-alone and synthetic account of the development of econometrics.

A discussion of various aspects of dynamic behavior of empirical macroeconomic, and in particular, macroeconometric models, is presented in this book. The book addresses in depth several theoretical and practical aspects concerning the modeling and analysis of long-run equilibrium behavior, adjustment dynamics and stability. Tools are developed to identify and interpret the main determinants of the dynamics of models. The tools involve, among others, error-correction mechanisms, eigenvalue analysis, feedback closure rules, graph theory, learning behavior, steady-state analysis, and stochastic simulation. Their usefulness is demonstrated by interesting applications to a number of well-known national and multi-national models.

'This most commendable volume brings together a set of papers which permits ready access to the means of estimating quantitative relationships using cointegration and error correction procedures. Providing the data to show fully the basis for calculation, this approach is an excellent perception of the needs of senior undergraduates and graduate students.' - Professor W.P. Hogan, The University of Sydney Applied economists, with modest econometric background, are now desperately looking for expository literature on the unit roots and cointegration techniques. This volume of expository essays is written for them. It explains in a simple style various tests for the existence of unit roots and how to estimate cointegration relationships. Original data are given to enable easy replications. Limitations of some existing unit root tests are also discussed.

Many models in this volume can be used in solving portfolio problems, in assessing forecasts, in understanding the possible effects of shocks and disturbances.

As large physical capital stock projects need long periods to be built, a time-to-build specification is incorporated in factor demand models. Time-to-build and adjustment costs dynamics are identified since by the first moving average dynamics, whereas by the latter autoregressive dynamics are induced. Empirical evidence for time-to-build is obtained from data from the Dutch construction industry and by the estimation result from the manufacturing industry of six OECD countries.

1. 1 Integrating results The empirical study of macroeconomic time series is interesting. It is also difficult and not immediately rewarding. Many statistical and economic issues are involved. The main problems is that these issues are so interrelated that it does not seem sensible to address them one at a time. As soon as one sets about the making of a model of macroeconomic time series one has to choose which problems one will try to tackle oneself and which problems one will leave unresolved or to be solved by others. From a theoretic point of view it can be fruitful to concentrate oneself on only one problem. If one follows this strategy in empirical application one runs a serious risk of making a seemingly interesting model, that is just a corollary of some important mistake in the handling of other problems. Two well known examples of statistical artifacts are the finding of Kuznets "pseudo-waves" of about 20 years in economic activity (Sargent (1979, p. 248)) and the "spurious regression" of macroeconomic time series described in Granger and Newbold (1986, 6. 4). The easiest way to get away with possible mistakes is to admit they may be there in the first place, but that time constraints and unfamiliarity with the solution do not allow the researcher to do something about them. This can be a viable argument."

This book presents a review of recent developments in the theory and construction of index numbers using the stochastic approach, demonstrating the versatility of this approach in handling various index number problems within a single conceptual framework. It also contains a brief, but complete, review of the existing approaches to index numbers with illustrative numerical examples.;The stochastic approach considers the index number problem as a signal extraction problem. The strength and reliability of the signal extracted from price and quantity changes for different commodities depends on the messages received and the information content of the messages. The most important applications of the new approach are to be found in the context of measuring rate of inflation and fixed and chain base index numbers for temporal comparisons and for spatial inter-country comparisons - the latter generally require special index number formulae that result in transitive and base invariant comparisons.

This book describes a series of laboratory experiments (with a total of 167 independent subjects) on forecasting behavior. In all experiments, the time series to be forecasted was generated by an abstract econometric model involving two or three artificial exogenous variables. This designprovides an optimal background for rational expectations and least-squares learning. As expected, these hypotheses do not explain observed forecasting behavior satisfactorily. Some phenomena related to this lack of rationality are studied: Concentration on changes rather than levels, underestimation of changes and overvaluation of volatile exogenous variables. Some learning behavior is observed. Finally, some aspects of individual forecasts such as prominence of "round" number, dispersion, etc., are studied.

This book provides advanced theoretical and applied tools for the implementation of modern micro-econometric techniques in evidence-based program evaluation for the social sciences. The author presents a comprehensive toolbox for designing rigorous and effective ex-post program evaluation using the statistical software package Stata. For each method, a statistical presentation is developed, followed by a practical estimation of the treatment effects. By using both real and simulated data, readers will become familiar with evaluation techniques, such as regression-adjustment, matching, difference-in-differences, instrumental-variables, regression-discontinuity-design, and synthetic control method, and are given practical guidelines for selecting and applying suitable methods for specific policy contexts. The second revised and extended edition features two new chapters on some recent development of difference-in-differences. Specifically, chapter 5 introduces advanced difference-in-differences methods when many times are available and treatment can be either time-varying or fixed at a specific time. Chapter 6 introduces the synthetic control method, a treatment effect estimation approach suitable when only one unit is treated. Both chapters present applications using the software Stata.

This Fourth Edition updates the "Solutions Manual for Econometrics" to match the Sixth Edition of the Econometrics textbook. It adds problems and solutions using latest software versions of Stata and EViews. Special features include empirical examples replicated using EViews, Stata as well as SAS. The book offers rigorous proofs and treatment of difficult econometrics concepts in a simple and clear way, and provides the reader with both applied and theoretical econometrics problems along with their solutions. These should prove useful to students and instructors using this book.

A macroeconomic disequilibrium model is developed for the Federal Republic of Germany. Starting with a microeconomic model of firm's behaviour, the optimal dynamic adjustment of employment and investment is derived. The model of the firm is complemented by an explicite aggregation procedure which allows to derive macroeconomic relations. The model is estimated with macroeconomic data for the Federal Republic of Germany. An important feature is the consistent introduction of dynamic adjustment into a model of the firm. A new method is the particular approach of a delayed adjustment of employment and investment. The estimation results show significant underutilizations of labour and capital and indicate the importance of supply constraints for imports and exports. As the most prominent result, they reveal the importance of the slow adjustment of employment and investment for the macroeconomic situation in Germany and especially for the persistence of high unemployment in the eighties.

It has been quite a challenge for econometricians to model economies in transition. There is no textbook at hand to master that task. Economic theory cannot be applied without adaptations to the characteristic change of a whole economic system. Regression analysis, taking into account past economic development only, is of limited use for the econometrician. Having econometric models at hand would be very helpful for an active economic policy to guide the transition process. Various scenarios representing strategies could be simulated in their consequences to the economy. The best alternative in respect to the government's objectives could be chosen. This very situation has born the idea of co-operation between L6dz and Frankfurt in 1990. There are problems of this kind in Poland and in Germany. The German situation is somewhat better than that of Poland as a relatively small centrally planned economy is being united with a substantial social market economy taking over a lot of the burden of the former mismanagement. Thus, it might be possible to share the experience in modelling the united Germany and preparing forecasts with the Polish model builders. In addition, it would be prOfitable for both model establishing teams to link their models in order to improve the forecasting potential. Moreover, the Polish partner has a broad national and international experience in econometric model building which makes co-operation smooth and fruitful. His experience in modelling countries with a centrally planned economy would also help to master the transition problems.

The book is an in-depth review of the theory and empirics of the demand for money and other financial assets. The different theoretical approaches to the portfolio choice problem are described, together with an up-to-date survey of the results obtained from empirical studies of asset choice behaviour. Both single-equation studies and the more complete multi-asset portfolio models, are analysed.