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Books > Business & Economics > Economics > Econometrics > General
Students in both social and natural sciences often seek regression methods to explain the frequency of events, such as visits to a doctor, auto accidents, or new patents awarded. This book provides the most comprehensive and up-to-date account of models and methods to interpret such data. The authors have conducted research in the field for more than twenty-five years. In this book, they combine theory and practice to make sophisticated methods of analysis accessible to researchers and practitioners working with widely different types of data and software in areas such as applied statistics, econometrics, marketing, operations research, actuarial studies, demography, biostatistics, and quantitative social sciences. The book may be used as a reference work on count models or by students seeking an authoritative overview. Complementary material in the form of data sets, template programs, and bibliographic resources can be accessed on the Internet through the authors' homepages. This second edition is an expanded and updated version of the first, with new empirical examples and more than one hundred new references added. The new material includes new theoretical topics, an updated and expanded treatment of cross-section models, coverage of bootstrap-based and simulation-based inference, expanded treatment of time series, multivariate and panel data, expanded treatment of endogenous regressors, coverage of quantile count regression, and a new chapter on Bayesian methods.
Stochastic Volatility in Financial Markets presents advanced topics in financial econometrics and theoretical finance, and is divided into three main parts. The first part aims at documenting an empirical regularity of financial price changes: the occurrence of sudden and persistent changes of financial markets volatility. This phenomenon, technically termed stochastic volatility', or conditional heteroskedasticity', has been well known for at least 20 years; in this part, further, useful theoretical properties of conditionally heteroskedastic models are uncovered. The second part goes beyond the statistical aspects of stochastic volatility models: it constructs and uses new fully articulated, theoretically-sounded financial asset pricing models that allow for the presence of conditional heteroskedasticity. The third part shows how the inclusion of the statistical aspects of stochastic volatility in a rigorous economic scheme can be faced from an empirical standpoint.
What part does technological knowledge accumulation play in modern economic growth? This book investigates and examines the predictions of new growth theory, using OECD manufacturing data. Its empirical findings portray a novel and complex picture of the features of long-term growth, where technological knowledge production and diffusion play a central part, alongside variations in capital and employment. A parallel examination of long-run trade patterns and government policy issues completes a broader account of how knowledge-based growth in industrial output is at the heart of modern economic prosperity.
The primary goal of this book is to present the research
findings and conclusions of physicists, economists, mathematicians
and financial engineers working in the field of "Econophysics" who
have undertaken agent-based modelling, comparison with empirical
studies and related investigations.
The contributions in this volume, by leading economists from major universities in Europe and USA, cover research at the front line of econometric analysis and labour market applications. The volume includes several papers on equilibrium search models (a relatively new field), and job matching, both seen from a theoretical and from an applied point of view. Methods on and empirical analyses of unemployment durations are also discussed. Finally, a large group of papers examine the structure and the dynamics of the labour market in a number of countries using panel data. This group includes papers on data quality and policy evaluation. The high unemployment in most countries makes it necessary to come up with studies and methods for analysing the impact of different elements of economic policies. This volume is intended to contribute to further development in the use of panel data in economic analyses.
This book provides an essential toolkit for all students wishing to know more about the modelling and analysis of financial data. Applications of econometric techniques are becoming increasingly common in the world of finance and this second edition of an established text covers the following key themes: - unit roots, cointegration and other developments in the study of time series models - time varying volatility models of the GARCH type and the stochastic volatility approach - analysis of shock persistence and impulse responses - Markov switching and Kalman filtering - spectral analysis - present value relations and rationality - discrete choice models - analysis of truncated and censored samples - panel data analysis. This updated edition includes new chapters which cover limited dependent variables and panel data. It continues to be an essential guide for all graduate and advanced undergraduate students of econometrics and finance.
The availability of financial data recorded on high-frequency level has inspired a research area which over the last decade emerged to a major area in econometrics and statistics. The growing popularity of high-frequency econometrics is driven by technological progress in trading systems and an increasing importance of intraday trading, liquidity risk, optimal order placement as well as high-frequency volatility. This book provides a state-of-the art overview on the major approaches in high-frequency econometrics, including univariate and multivariate autoregressive conditional mean approaches for different types of high-frequency variables, intensity-based approaches for financial point processes and dynamic factor models. It discusses implementation details, provides insights into properties of high-frequency data as well as institutional settings and presents applications to volatility and liquidity estimation, order book modelling and market microstructure analysis.
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 IT contains Theil's contributions to demand analysis and information theory. Volume ITI 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 67th 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 the top 10 researchers (ranked according to number of times cited) in the world in various disciplines.
Mathematical Statistics for Economics and Business, Second Edition, provides a comprehensive introduction to the principles of mathematical statistics which underpin statistical analyses in the fields of economics, business, and econometrics. The selection of topics in this textbook is designed to provide students with a conceptual foundation that will facilitate a substantial understanding of statistical applications in these subjects. This new edition has been updated throughout and now also includes a downloadable Student Answer Manual containing detailed solutions to half of the over 300 end-of-chapter problems. After introducing the concepts of probability, random variables, and probability density functions, the author develops the key concepts of mathematical statistics, most notably: expectation, sampling, asymptotics, and the main families of distributions. The latter half of the book is then devoted to the theories of estimation and hypothesis testing with associated examples and problems that indicate their wide applicability in economics and business. Features of the new edition include: a reorganization of topic flow and presentation to facilitate reading and understanding; inclusion of additional topics of relevance to statistics and econometric applications; a more streamlined and simple-to-understand notation for multiple integration and multiple summation over general sets or vector arguments; updated examples; new end-of-chapter problems; a solution manual for students; a comprehensive answer manual for instructors; and a theorem and definition map. This book has evolved from numerous graduate courses in mathematical statistics and econometrics taught by the author, and will be ideal for students beginning graduate study as well as for advanced undergraduates.
This book contains a systematic analysis of allocation rules related to cost and surplus sharing problems. Broadly speaking, it examines various types of rules for allocating a common monetary value (cost) between individual members of a group (or network) when the characteristics of the problem are somehow objectively given. Without being an advanced text it o?ers a comprehensive mathematical analysis of a series of well-known allocation rules. The aim is to provide an overview and synthesis of current kno- edge concerning cost and surplus sharing methods. The text is accompanied by a description of several practical cases and numerous examples designed to make the theoretical results easily comprehensible for both students and practitioners alike. The book is based on a series of lectures given at the University of Copenhagen and Copenhagen Business School for graduate students joining the math/econ program. I am indebted to numerous colleagues, conference participants and s- dents who during the years have shaped my approach and interests through collaboration, commentsandquestionsthatweregreatlyinspiring.Inparti- lar, I would like to thank Hans Keiding, Maurice Koster, Tobias Markeprand, Juan D. Moreno-Ternero, Herv e Moulin, Bezalel Peleg, Lars Thorlund- Petersen, Jorgen Tind, Mich Tvede and Lars Peter Osterdal."
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 ranA--dom 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 of data.
The field of econometrics has gone through remarkable changes during the last thirty-five years. Widening its earlier focus on testing macroeconomic theories, it has become a rather comprehensive discipline concemed with the development of statistical methods and their application to the whole spectrum of economic data. This development becomes apparent when looking at the biography of an econometrician whose illustrious research and teaching career started about thirty-five years ago and who will retire very soon after his 65th birthday. This is Gerd Hansen, professor of econometrics at the Christian Albrechts University at Kiel and to whom this volume with contributions from colleagues and students has been dedicated. He has shaped the econometric landscape in and beyond Germany throughout these thirty-five years. At the end of the 1960s he developed one of the first econometric models for the German econ omy which adhered c10sely to the traditions put forth by the Cowles commission."
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.
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 impressive areas of applied econometrics. This book presents a large number of applications of recent innovations in the area. The database used consist of about 18 annual observations for 10 commodities in 18 OECO countries (more than 3,100 data points). Such a large body of data should provide convincing evidence, one way or the other, about the validity of consumption theory. A PREVIEW OF THE BOOK The overall importance of the analysis presented in the book can be seen from the following table which shows the signifIcant contribution of the OECO to the world economy. As can be seen, the 24 member countries account for about 50 percent of world GOP in 1975. In this book we present an extensive analysis of the consumption patterns of the OECO countries.
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.
Charles de Gaulle commence ses Memoires d'Espoir, ainsi: 'La France vient du fond des ages. Elle vito Les Siecles l'appellent. Mais elle demeure elle-meme au long du temps. Ses limites peuvent se modifier sans que changent Ie relief, Ie climat, les fleuves, les mers, qui la marquent indefmiment. Y habitent des peuples qu'etreignent, au cours de l'Histoire, les epreuves les plus diverses, mais que la nature des choses, utilisee par la politique, petrit sans cesse en une seule nation. Celle-ci a embrasse de nombreuses generations. Elle en comprend actuellement plusieurs. Elle en enfantera beaucoup d'autres. Mais, de par la geograpbie du pays qui est Ie sien, de par Ie genie des races qui la composent, de par les voisinages qui l'entourent, elle revet un caractere constant qui fait dependre de leurs peres les Fran ais de chaque epoque et les engage pour leurs descendants. A moins de se rompre, cet ensemble humain, sur ce territoire, au sein de cet univers, comporte donc un passe, un present, un avenir, indissolubles. Aussi l'ttat, qui repond de la France, est-il en charge, a la fois, de son heritage d'bier, de ses interets d'aujourd'hui et de ses espoirs de demain. ' A la lurniere de cette idee de nation, il est clair, qu'un dialogue entre nations est eminemment important et que la Semaine Universitaire Franco Neerlandaise est une institution pour stimuler ce dialogue."
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."
Economists are regularly confronted with results of quantitative economics research. Econometrics: Theory and Applications with EViews provides a broad introduction to quantitative economic methods, for example how models arise, their underlying assumptions and how estimates of parameters or other economic quantities are computed. The author combines econometric theory with practice by demonstrating its use with the software package EViews through extensive use of screen shots. The emphasis is on understanding how to select the right method of analysis for a given situation, and how to actually apply the theoretical methodology correctly. The EViews software package is available from 'Quantitive Micro Software'. Written for any undergraduate or postgraduate course in Econometrics.
In 1945, very early in the history of the development of a rigorous analytical theory of probability, Feller (1945) wrote a paper called "The fundamental limit theorems in probability" in which he set out what he considered to be "the two most important limit theorems in the modern theory of probability: the central limit theorem and the recently discovered ... 'Kolmogoroff's cel ebrated law of the iterated logarithm' ." A little later in the article he added to these, via a charming description, the "little brother (of the central limit theo rem), the weak law of large numbers," and also the strong law of large num bers, which he considers as a close relative of the law of the iterated logarithm. Feller might well have added to these also the beautiful and highly applicable results of renewal theory, which at the time he himself together with eminent colleagues were vigorously producing. Feller's introductory remarks include the visionary: "The history of probability shows that our problems must be treated in their greatest generality: only in this way can we hope to discover the most natural tools and to open channels for new progress. This remark leads naturally to that characteristic of our theory which makes it attractive beyond its importance for various applications: a combination of an amazing generality with algebraic precision."
Gini's mean difference (GMD) was first introduced by Corrado Gini in 1912 as an alternative measure of variability. GMD and the parameters which are derived from it (such as the Gini coefficient or the concentration ratio) have been in use in the area of income distribution for almost a century. In practice, the use of GMD as a measure of variability is justified whenever the investigator is not ready to impose, without questioning, the convenient world of normality. This makes the GMD of critical importance in the complex research of statisticians, economists, econometricians, and policy makers. This book focuses on imitating analyses that are based on variance by replacing variance with the GMD and its variants. In this way, the text showcases how almost everything that can be done with the variance as a measure of variability, can be replicated by using Gini. Beyond this, there are marked benefits to utilizing Gini as opposed to other methods. One of the advantages of using Gini methodology is that it provides a unified system that enables the user to learn about various aspects of the underlying distribution. It also provides a systematic method and a unified terminology. Using Gini methodology can reduce the risk of imposing assumptions that are not supported by the data on the model. With these benefits in mind the text uses the covariance-based approach, though applications to other approaches are mentioned as well.
This book is an extension of the author's first book and serves as a guide and manual on how to specify and compute 2-, 3-, and 4-Event Bayesian Belief Networks (BBN). It walks the learner through the steps of fitting and solving fifty BBN numerically, using mathematical proof. The author wrote this book primarily for inexperienced learners as well as professionals, while maintaining a proof-based academic rigor. The author's first book on this topic, a primer introducing learners to the basic complexities and nuances associated with learning Bayes' theorem and inverse probability for the first time, was meant for non-statisticians unfamiliar with the theorem-as is this book. This new book expands upon that approach and is meant to be a prescriptive guide for building BBN and executive decision-making for students and professionals; intended so that decision-makers can invest their time and start using this inductive reasoning principle in their decision-making processes. It highlights the utility of an algorithm that served as the basis for the first book, and includes fifty 2-, 3-, and 4-event BBN of numerous variants.
New Directions in Computational Economics brings together for the first time a diverse selection of papers, sharing the underlying theme of application of computing technology as a tool for achieving solutions to realistic problems in computational economics and related areas in the environmental, ecological and energy fields. Part I of the volume addresses experimental and computational issues in auction mechanisms, including a survey of recent results for sealed bid auctions. The second contribution uses neural networks as the basis for estimating bid functions for first price sealed bid auctions. Also presented is the smart market' computational mechanism which better matches bids and offers for natural gas. Part II consists of papers that formulate and solve models of economics systems. Amman and Kendrick's paper deals with control models and the computational difficulties that result from nonconvexities. Using goal programming, Nagurney, Thore and Pan formulate spatial resource allocation models to analyze various policy issues. Thompson and Thrall next present a rigorous mathematical analysis of the relationship between efficiency and profitability. The problem of matching uncertain streams of assets and liabilities is solved using stochastic optimization techniques in the following paper in this section. Finally, Part III applies economic concepts to issues in computer science in addition to using computational techniques to solve economic models.
World-renowned experts in spatial statistics and spatial econometrics present the latest advances in specification and estimation of spatial econometric models. This includes information on the development of tools and software, and various applications. The text introduces new tests and estimators for spatial regression models, including discrete choice and simultaneous equation models. The performance of techniques is demonstrated through simulation results and a wide array of applications related to economic growth, international trade, knowledge externalities, population-employment dynamics, urban crime, land use, and environmental issues. An exciting new text for academics with a theoretical interest in spatial statistics and econometrics, and for practitioners looking for modern and up-to-date techniques.
Elementary Bayesian Statistics is a thorough and easily accessible introduction to the theory and practical application of Bayesian statistics. It presents methods to assist in the collection, summary and presentation of numerical data.Bayesian statistics are becoming an increasingly important and more frequently used method for analysing statistical data. The author defines concepts and methods with a variety of examples and uses a stage-by-stage approach to coach the reader through the applied examples. Also included are a wide range of problems to challenge the reader and the book makes extensive use of Minitab to apply computational techniques to statistical problems. Issues covered include probability, Bayes's Theorem and categorical states, frequency, the Bernoulli process and Poisson process, estimation, testing hypotheses and the normal process with known parameters and uncertain parameters. Elementary Bayesian Statistics will be an essential resource for students as a supplementary text in traditional statistics courses. It will also be welcomed by academics, researchers and econometricians wishing to know more about Bayesian statistics. |
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