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Эконометрика - наука о применении статистических и математических методов в экономическом анализе для проверки правильности экономических теоретических моделей и способов решения экономических проблем. (подробнее...)
Всего публикаций в данном разделе: 468

Опубликовано на портале: 30-07-2004
This book provides a new approach to the identification and the estimation of structural VAR models. The role of deterministic variables and the connection with the concept of cointegration is discussed at length. The book also provides criteria to select among alternative structures. In addition, the asymptotic distributions of the structural estimates of impulse response functions and forecast error variance decomposition coefficients are obtained and used to construct asymptotically based confidence intervals around the maximum likelihood estimates. Moreover, the book contains a critical evaluation of the problem of non-fundamental representations and of their relevance on the interpretability of the results of structural VAR analysis. Finally, the book contains applied examples.

Опубликовано на портале: 30-07-2004
Introduction to Econometrics provides a step by step introductory guide to the core areas of this subject.This new edition of Dougherty's highly successful textbook has been substantially updated and revised with the inclusion of new material on specification tests, binary choice models, tobit analysis, sample selection bias, nonstationary time series, and unit root tests and cointegration. In addition, the book will be acompanied by a website containing graphical treatment of all the topics covered in the text.
ресурс содержит графическое изображение (иллюстрацию)

Опубликовано на портале: 30-07-2004
Currently the standard source in Economics, Sociology, Political Science, Medical Research, Transport Research, and Environmental Economics, to name just a few, the fourth edition of Econometric Analysis provides a comprehensive survey of econometrics, with signifcant pedagogical work that will continue to serve as a modern, up-to-date text and reference for future practioners.
ресурс содержит графическое изображение (иллюстрацию)

Опубликовано на портале: 30-07-2004
Gujarati's Basic Econometrics provides an elementary but comprehensive introduction to econometrics without resorting to matrix algebra, calculus, or statistics beyond the elementary level. Because of the way the book is organized, it may be used at a variety of levels of rigor. A CD of data sets is provided with the text.
ресурс содержит графическое изображение (иллюстрацию)

Опубликовано на портале: 30-07-2004
Time Series Models is a companion volume to Andrew Harvey's highly successful Econometric Analysis of Time Series. It takes students to another level from the first book, focusing on the estimation, testing, and specification of both univariate and multivariate time series models. The emphasis is on understanding how time series are analyzed and models constructed. Familiarity with calculus, linear algebra, and statistical interference is assumed.
Although Time Series Models pairs well with Harvey's earlier text, it is self-contained. For the second edition, the author has added new sections on nonlinear models, unit roots, structural time series models, intervention analysis, and cointegration. He has addressed new developments, rearranged some material, and changed the emphasis in certain areas.

Опубликовано на портале: 30-07-2004
Introductory Econometrics with Applications, Fifth Edition, by Ramu Ramanathan, provides the perfect blend between econometric theory and hands-on practical training for a B.A., M.A., or M.B.A. course on econometrics that does not use matrix algebra.
The book is self-contained, with background information on mathematics, probability, and statistics, covered in Chapter 2 and later chapters so that students need not refer to their old notes or textbooks.
Practical applications are emphasized without sacrificing theoretical underpinnings. Numerous real-world examples walk the students through model specification, estimation, and hypothesis testing, using a logical step-by-step approach. Instead of showing only final polished results, the book shows intermediate failures and unexpected results, along with suggestions about how model specification and estimation can be improved by using diagnostic testing.
Annotated computer outputs are included in the text so that students can see exactly how econometric techniques are implemented in practice.
An entire chapter is devoted to the various steps involved in carrying out an empirical research project, namely, selection of a topic, literature review, model formulation, data gathering, estimation, hypothesis testing, and report writing. Because an empirical study is time-consuming and a student need not wait to read the whole book to start the project, suggestions are given in selected chapters so that the process is smooth and orderly and does not cause unnecessary delays.
94 data sets on real-world topics are available in the disk accompanying the text as well as on the Web page set up for the book. The data are in ASCII, B34S, EVIEWS, EXCEL, GRETL, PcGive, and SHAZAM formats so that a user can access them easily from a variety of well-known regression programs to reproduce the examples in the book and to carry out additional analyses.
Professor Allin Cottrell of Wake Forest University has graciously agreed to include a free open-source econometrics software package, GRETL (Gnu Regression, Econometric, and Time-series Library), in the disk that accompanies each copy of the book. Appendix C has more information on this program.
ресурс содержит полный текст, либо отрывок из него ресурс содержит графическое изображение (иллюстрацию)

Опубликовано на портале: 30-07-2004
Concise, complete, nontechnicalthe ideal introduction to an increasingly important topic.
In recent years, the use of statistical methods for categorical data has increased dramatically in a variety of areas and applications. This book provides an applied introduction to the most important methods for analyzing categorical data. It summarizes methods that have long played a prominent role, such as chi-squared tests, but places special emphasis on logistic regression and loglinear modeling techniques.
Special features of the book include:
emphasis on logistic regression modeling of binary data and Poisson regression modeling of count data; a unified perspective, based on generalized linear models, that connects these methods with standard regression methods for normally-distributed data; an appendix showing the use of a new SAS procedure (GENMOD) for generalized linear modeling that can conduct nearly all methods presented in the book; an entertaining historical perspective of the development of the methods Specialized methods for ordinal data, small samples, multicategory data, and matched pairs; more than 100 examples of real data sets and more than 200 exercises Writing in an applied, nontechnical style, Alan Agresti illustrates methods using a wide variety of real data, including alcohol, cigarette, and marijuana use by teenagers; AZT use and delay of AIDS; space shuttle launches and O-ring failure; passive smoking and lung cancer; and much more. An Introduction to Categorical Data Analysis is an invaluable tool for social, behavioral, and biomedical scientists, as well as researchers in public health, marketing, education, biological and agricultural sciences, and industrial quality control.
ресурс содержит графическое изображение (иллюстрацию)

Опубликовано на портале: 30-07-2004
This econometrics text helps the reader to apply econometric techniques to a variety of empirical problems, using classic and contemporary data sets provided on a diskette. Each chapter begins with a discussion of economic theory underlying an application. It then summarizes the most important empirical findings, and involves the reader in a carefully designed set of exercises involving replication and extension of typical empirical findings. To assist the reader in hands-on applications, special manuals are available for purchase that implement the exercises on the widely-used computer econometric software programs, MicroTSP and SHAZAM.

Опубликовано на портале: 27-07-2004
Applied Nonparametric Regression brings together in one place the techniques for regression curve smoothing involving more than one variable. The computer and the development of interactive graphics programs has made curve estimation popular. This volume focuses on the applications and practical problems of two central aspects of curve smoothing: the choice of smoothing parameters and the construction of confidence bounds. The methods covered in this text have numerous applications in many areas using statistical analysis. Examples are drawn from economics--such as the estimation of Engel curves--as well as other disciplines including medicine and engineering. For practical applications of these methods a computing environment for exploratory Regression--XploRe--is described.

"Professor Härdle has provided us with an important book, one that will be appreciated both by applied statisticians who want to implement nonparametric regression techniques and by theoreticians interested in becoming knowledgeable in this growing field. Applied Nonparametric Regression is a very welcome addition to the literature." Journal of the American Statistical Association

"Nonparametric regression analysis has become central to economic theory. Härdle, by writing the first comprehensive and accessible book on the subject, has contributed enormously to making nonparametric regression equally central to econometric practice." Charles F. Manski, University of Wisconsin, Madison

"This book represents an optimally estimated common thread for the numerous topics and results in the fast-growing area of nonparametric regression. The user-friendly approach taken by the author has successfully smoothed out most of the formidable asymptotic elaboration in developing the theory. This is an excellent collection for both beginners and experts." Ker-Chau Li, University of California, Los Angeles

"This monograph on nonparametric regression presents a particularly clear and balanced view of the methodology and practice of this very important subject, and so is of use to theoreticians and practitioners alike." Peter Hall, University of Glasgow

"This book makes the main ideas and methodologies of nonparametric regression easily accessible to nonexperts, and is a valuable reference source for experts as well because of its wide scope." J.S. Marron
ресурс содержит графическое изображение (иллюстрацию) ресурс содержит прикрепленный файл

Опубликовано на портале: 23-07-2004
Panel data models have become increasingly popular among applied researchers due to their heightened capacity for capturing the complexity of human behavior, as compared to cross-sectional or time series data models. This second edition represents a substantial revision of the highly successful first edition (1986). Recent advances in panel data research are presented in an accessible manner and are carefully integrated with the older material. The thorough discussion of theory and the judicious use of empirical examples make this book useful to graduate students and advanced researchers in economics, business, sociology and political science.

"Cheng Hsiao has made many significant and important contributions to panel data econometrics, both methodological and applied, beginning with his 1972 dissertation, in numerous articles, and in his masterful and magisterial 1986 monograph, long a standard reference and popular graduate text. (cont.)

Not only has Hsiao significantly revised the material covered in his original monograph, he has added major new chapters on nonlinear panel models of discrete choice and sampl selection, and included new material on the Bayesian treatment of models with fixed and random coefficients, pseudopanels, simulation methods of estimation, and more extensive treatment of dynamic models. Throughout, Hsiao provides applied examples, which greatly enhance the reader's understanding and intuition. The clarity of his exposition and organization is exemplary. All of us who work in the field of panel data econometrics have been, and will now more than ever continue to be in Hsiao's debt." Marc Nerlove, University of Maryland

"The literature on panel data modeling has seen unprecendented growth over the past decade and Cheng Hsiao, himself one of the leading contributors to this literature, is to be congratulated for providing us with a comprehensive and timely update of his classic text. This version not only presents a substantial revision of the 1986 edition, but also offers major additions covering non-linear panel data models dealing with useful overviews of unit root and cointegration in dynamic heterogeneous panels. It should prove invaluable to students and teachers of advanced undergraduate and graduate economic courses." Hashem Perasan, Trinity College, Cambridge

"The first edition of Analysis of Panel Data by Cheng Hsiao has been necessary reading and a landmark for 15 years. The revised and much expanded second edition splendidly integrates the important new developments in the field. One can be sure it will stay a landmark for 15 years to come." Jacques Mairesse, ENSAE, France

"Cheng Hsiao has done a great service to the profession by expanding his highly successful first edition to include the important results that have been obtained by him and other researchers since the publication of the first edition. Escpecially noteworthy in this edition is the application of panel data analysis to qualitative response and sample selection models. Cheng has admirably succeeded in presenting the mathematical results both rigorously and lucidly. Many theoretical results are illustrated by interesting empirical examples. This edition should prove to be an extremely useful reference for the experts in the field as well as graduate students." Takeshi Amemiya, Stanford University
ресурс содержит графическое изображение (иллюстрацию) ресурс содержит прикрепленный файл

Опубликовано на портале: 23-07-2004
This volume collects seven of Nerlove's previously published essays on panel data econometrics written over the past thirty-five years, with a new essay on the history of the subject, which began with George Biddell Airey's monograph in 1861. Since his 1966 Econometrica paper with Pietro Balestra, panel data and methods of econometric analysis have become important in the discipline. The principal factors in the research environment affecting the future course of panel data econometrics are the growth in the computational power available to the individual researcher at his desktop and the ready availability of data sets via the Internet. The best way to formulate statistical models for inference is motivated and shaped by substantive problems and our understanding of the processes generating the data at hand to resolve them. The essays illustrate the substantive context in shaping appropriate methods of inference and the increasing importance of computer-intensive methods.

"Marc Nerlove, more than any other economist, pioneered the econometric analysis of panel data. This book presents many of his classic papers and provides a valuable synthesis of panel data econometrics starting with early work and including the latest developments in the field. It can be read at many levels eas a history of an important line of econometric research, as a guide to a vast literature and as a resource for solving specific empirical problems that arise in analyzing panel data. The blend of theory, data and econometrics is superb. This is a masterful work." James Heckman, Nobel Laureate, University of Chicago

"This volume draws together related research on panel data econometrics over the last thirty five years with a new essay on the history by its initiator and one of the most creative econometricians of our time. Written with rigor, force and elegance, it captures the excitement and insight that has led to many major research programs. Combining rich history and fresh ideas, each chapter is a classic. The volume is a source of inspiration for both empirical and theoretical researchers. It will be an indispensable addition to every economics library." Cheng Hsiao, University of Southern California

"The analysis of panel data has been one of the fastest growing and intensively studied fields in econometrics for over thirty years. These Essays in Panel Data Econometrics are the foundation of the field. From the classic Balestra-Nerlove study of 1966 through the contemporary work described in this book, dynamic modeling with panel data has attracted some of the most active and innovative research in econometrics. Students and practitioners will find in this collection a wealth of useful results and a fascinating tour of the intellectual development of this important branch of econometrics." William Greene, Stern School of Business, New York University

"This is a collection of first rate papers in and on panel data econometrics. For the general econometrician who wants to go beyond what he can find in the available textbooks, it should be challenging and instructive reading." Jacques Mairesse, CREST-ENSAE, France

"Marc Nerlove has been a pioneer in many important econometric models, especially the panel data models discussed in this book. His seminal paper with Balestra and the two follow-up papers have had a great impact on the econometricians and led to a rapid growth of the analysis of panel data. Nerlove's research is characterized by the thorough analysis and the keen insight that cut through apparently impregnable problems and has been singularly successful in the analysis of panel data, which presents a host of complicated statistical issues. Everyone interested in panel data will welcome this volume, in which Nerlove has newly written a characteristically thorough survey of the area and put together his previously published articles, some of which are not so easily accessible." Takeshi Amemiya, Stanford University
ресурс содержит полный текст, либо отрывок из него ресурс содержит графическое изображение (иллюстрацию) ресурс содержит прикрепленный файл

Опубликовано на портале: 23-07-2004
This broadly based graduate-level textbook covers the major models and statistical tools currently used in the practice of econometrics. It examines the classical, the decision theory, and the Bayesian approaches, and contains material on single equation and simultaneous equation econometric models. Includes an extensive reference list for each topic.
ресурс содержит графическое изображение (иллюстрацию)

Опубликовано на портале: 23-07-2004
In this book, Andrew Harvey sets out to provide a unified and comprehensive theory of structural time series models. Unlike the traditional ARIMA models, structural time series models consist explicitly of unobserved components, such as trends and seasonals, which have a direct interpretation. As a result the model selection methodology associated with structural models is much closer to econometric methodology. The link with econometrics is made even closer by the natural way in which the models can be extended to include explanatory variables and to cope with multivariate time series. From the technical point of view, state space models and the Kalman filter play a key role in the statistical treatment of structural time series models. The book includes a detailed treatment of the Kalman filter. This technique was originally developed in control engineering, but is becoming increasingly important in fields such as economics and operations research. This book is concerned primarily with modelling economic and social time series, and with addressing the special problems which the treatment of such series poses. The properties of the models and the methodological techniques used to select them are illustrated with various applications. These range from the modellling of trends and cycles in US macroeconomic time series to to an evaluation of the effects of seat belt legislation in the UK.
ресурс содержит графическое изображение (иллюстрацию)

Опубликовано на портале: 23-07-2004
The first textbook to teach introductory econometrics to finance majors. The text is data- and problem-driven, giving students the skills to estimate and interpret models, whilst having an intuitive grasp of the underlying theoretical concepts.
The approach of Dr Brooks, based on the successful course he teaches at the ISMA Centre, one of Europe's leading finance schools, ensures that the text focuses squarely on the needs of finance students, including advice on planning and executing a project in empirical finance. The book assumes no prior knowledge of econometrics, and covers important modern topics such as time-series forecasting, volatility modelling, switching models and simulation methods. It includes detailed examples and case studies from the finance literature. Sample instructions and output from two popular and widely available computer packages (EViews and WinRATS) are presented as an integral part of the text. Extensive web-based supporting materials are available free of charge.
ресурс содержит гиперссылку на сайт, на котором можно найти дополнительную информацию ресурс содержит графическое изображение (иллюстрацию) ресурс содержит прикрепленный файл

Опубликовано на портале: 23-07-2004
Although there has been a surge of interest in density estimation in recent years, much of the published research has been concerned with purely technical matters with insufficient emphasis given to the technique's practical value. Furthermore, the subject has been rather inaccessible to the general statistician.
The account presented in this book places emphasis on topics of methodological importance, in the hope that this will facilitate broader practical application of density estimation and also encourage research into relevant theoretical work. The book also provides an introduction to the subject for those with general interests in statistics. The important role of density estimation as a graphical technique is reflected by the inclusion of more than 50 graphs and figures throughout the text.
Several contexts in which density estimation can be used are discussed, including the exploration and presentation of data, nonparametric discriminant analysis, cluster analysis, simulation and the bootstrap, bump hunting, projection pursuit, and the estimation of hazard rates and other quantities that depend on the density.
This book includes general survey of methods available for density estimation. The Kernel method, both for univariate and multivariate data, is discussed in detail, with particular emphasis on ways of deciding how much to smooth and on computation aspects.
Attention is also given to adaptive methods, which smooth to a greater degree in the tails of the distribution, and to methods based on the idea of penalized likelihood.
ресурс содержит гиперссылку на сайт, на котором можно найти дополнительную информацию ресурс содержит графическое изображение (иллюстрацию)

Анализ регрессионный [словарная статья]
Опубликовано на портале: 21-07-2004
К.Д. Аргунова, Юлиана Николаевна Толстова АНАЛИЗ РЕГРЕССИОННЫЙ - статистический метод исследования зависимости (регрессии) между зависимым признаком Y и независимыми (регрессорами, предикторами) . Строго регрессионную зависимость можно определить следующим образом. Пусть Y, случайные величины с заданным совместным распределением вероятностей . Если для каждого

Обновлено: 09-12-2010


Основное внимание уделяется трем темам - информация о современных статистических методах; сообщения о событиях в эконометрическом мире; ответы на письма участников рассылки. Рассылкой руководит профессор Орлов Александр Иванович, 1949 г.р., доктор технических наук.

Обновлено: 09-12-2010


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Обновлено: 09-12-2010


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Обновлено: 09-12-2010


На сайте института размещена информация об учебных курсах для студентов различных уровней обучения, списки публикаций преподавателей института, программы семинаров. Некоторые статьи и препринты находятся в открытом доступе. В разделе "Academic Groups" можно ознакомиться с разработками сотрудников Института, приведены гиперссылки на материалы к учебным курсам по прикладной математике, экономической статистике и т.д.