Measurement Error And Latent Variables In Econometrics

Author : T. Wansbeek,E. Meijer
Publisher : North Holland
Page : 464 pages
File Size : 51,7 Mb
Release : 2000-12-08
Category : Business & Economics
ISBN : STANFORD:36105110175218

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Measurement Error and Latent Variables in Econometrics by T. Wansbeek,E. Meijer Pdf

The book first discusses in depth various aspects of the well-known inconsistency that arises when explanatory variables in a linear regression model are measured with error. Despite this inconsistency, the region where the true regression coeffecients lies can sometimes be characterized in a useful way, especially when bounds are known on the measurement error variance but also when such information is absent. Wage discrimination with imperfect productivity measurement is discussed as an important special case. Next, it is shown that the inconsistency is not accidental but fundamental. Due to an identification problem, no consistent estimators may exist at all. Additional information is desirable. This information can be of various types. One type is exact prior knowledge about functions of the parameters. This leads to the CALS estimator. Another major type is in the form of instrumental variables. Many aspects of this are discussed, including heteroskedasticity, combination of data from different sources, construction of instruments from the available data, and the LIML estimator, which is especially relevant when the instruments are weak. The scope is then widened to an embedding of the regression equation with measurement error in a multiple equations setting, leading to the exploratory factor analysis (EFA) model. This marks the step from measurement error to latent variables. Estimation of the EFA model leads to an eigenvalue problem. A variety of models is reviewed that involve eignevalue problems as their common characteristic. EFA is extended to confirmatory factor analysis (CFA) by including restrictions on the parameters of the factor analysis model, and next by relating the factors to background variables. These models are all structural equation models (SEMs), a very general and important class of models, with the LISREL model as its best-known representation, encompassing almost all linear equation systems with latent variables. Estimation of SEMs can be viewed as an application of the generalized method of moments (GMM). GMM in general and for SEM in particular is discussed at great length, including the generality of GMM, optimal weighting, conditional moments, continuous updating, simulation estimation, the link with the method of maximum likelihood, and in particular testing and model evaluation for GMM. The discussion concludes with nonlinear models. The emphasis is on polynomial models and models that are nonlinear due to a filter on the dependent variables, like discrete choice models or models with ordered categorical variables.

Author : Wayne A. Fuller
Publisher : John Wiley & Sons
Page : 474 pages
File Size : 47,9 Mb
Release : 2009-09-25
Category : Mathematics
ISBN : 9780470317334

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Measurement Error Models by Wayne A. Fuller Pdf

The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "The effort of Professor Fuller is commendable . . . [the book] provides a complete treatment of an important and frequently ignored topic. Those who work with measurement error models will find it valuable. It is the fundamental book on the subject, and statisticians will benefit from adding this book to their collection or to university or departmental libraries." -Biometrics "Given the large and diverse literature on measurement error/errors-in-variables problems, Fuller's book is most welcome. Anyone with an interest in the subject should certainly have this book." -Journal of the American Statistical Association "The author is to be commended for providing a complete presentation of a very important topic. Statisticians working with measurement error problems will benefit from adding this book to their collection." -Technometrics " . . . this book is a remarkable achievement and the product of impressive top-grade scholarly work." -Journal of Applied Econometrics Measurement Error Models offers coverage of estimation for situations where the model variables are observed subject to measurement error. Regression models are included with errors in the variables, latent variable models, and factor models. Results from several areas of application are discussed, including recent results for nonlinear models and for models with unequal variances. The estimation of true values for the fixed model, prediction of true values under the random model, model checks, and the analysis of residuals are addressed, and in addition, procedures are illustrated with data drawn from nearly twenty real data sets.

Author : Badi H. Baltagi
Publisher : John Wiley & Sons
Page : 736 pages
File Size : 46,9 Mb
Release : 2008-04-15
Category : Business & Economics
ISBN : 9780470998304

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A Companion to Theoretical Econometrics by Badi H. Baltagi Pdf

A Companion to Theoretical Econometrics provides a comprehensive reference to the basics of econometrics. This companion focuses on the foundations of the field and at the same time integrates popular topics often encountered by practitioners. The chapters are written by international experts and provide up-to-date research in areas not usually covered by standard econometric texts. Focuses on the foundations of econometrics. Integrates real-world topics encountered by professionals and practitioners. Draws on up-to-date research in areas not covered by standard econometrics texts. Organized to provide clear, accessible information and point to further readings.

Author : Klaus Haagen,David J. Bartholomew,Manfred Deistler
Publisher : North Holland
Page : 376 pages
File Size : 44,7 Mb
Release : 1993
Category : Mathematics
ISBN : UOM:39015029845586

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Statistical Modelling and Latent Variables by Klaus Haagen,David J. Bartholomew,Manfred Deistler Pdf

Statistical methods based on models with latent variables play an important role in the analysis of multivariate data. The subject can be approached theoretically or in an empirical, pragmatic way. The statistical problem is to make inferences about the latent variables and the relationships between them. Errors-in-variables models, factor analysis and latent structure models are all examples of this approach. This volume presents a selection of invited and contributed papers which address the problems involved in developing a unifying statistical theory for latent variable models.

Author : Kenneth A. Bollen
Publisher : John Wiley & Sons
Page : 528 pages
File Size : 43,9 Mb
Release : 1989-05-12
Category : Mathematics
ISBN : 9780471011712

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Structural Equations with Latent Variables by Kenneth A. Bollen Pdf

Analysis of Ordinal Categorical Data Alan Agresti Statistical Science Now has its first coordinated manual of methods for analyzing ordered categorical data. This book discusses specialized models that, unlike standard methods underlying nominal categorical data, efficiently use the information on ordering. It begins with an introduction to basic descriptive and inferential methods for categorical data, and then gives thorough coverage of the most current developments, such as loglinear and logit models for ordinal data. Special emphasis is placed on interpretation and application of methods and contains an integrated comparison of the available strategies for analyzing ordinal data. This is a case study work with illuminating examples taken from across the wide spectrum of ordinal categorical applications. 1984 (0 471-89055-3) 287 pp. Regression Diagnostics Identifying Influential Data and Sources of Collinearity David A. Belsley, Edwin Kuh and Roy E. Welsch This book provides the practicing statistician and econometrician with new tools for assessing the quality and reliability of regression estimates. Diagnostic techniques are developed that aid in the systematic location of data points that are either unusual or inordinately influential; measure the presence and intensity of collinear relations among the regression data and help to identify the variables involved in each; and pinpoint the estimated coefficients that are potentially most adversely affected. The primary emphasis of these contributions is on diagnostics, but suggestions for remedial action are given and illustrated. 1980 (0 471-05856-4) 292 pp. Applied Regression Analysis Second Edition Norman Draper and Harry Smith Featuring a significant expansion of material reflecting recent advances, here is a complete and up-to-date introduction to the fundamentals of regression analysis, focusing on understanding the latest concepts and applications of these methods. The authors thoroughly explore the fitting and checking of both linear and nonlinear regression models, using small or large data sets and pocket or high-speed computing equipment. Features added to this Second Edition include the practical implications of linear regression; the Durbin-Watson test for serial correlation; families of transformations; inverse, ridge, latent root and robust regression; and nonlinear growth models. Includes many new exercises and worked examples. 1981 (0 471-02995-5) 709 pp.

Author : John P. Buonaccorsi
Publisher : CRC Press
Page : 465 pages
File Size : 52,9 Mb
Release : 2010-03-02
Category : Mathematics
ISBN : 9781420066586

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Measurement Error by John P. Buonaccorsi Pdf

Over the last 20 years, comprehensive strategies for treating measurement error in complex models and accounting for the use of extra data to estimate measurement error parameters have emerged. Focusing on both established and novel approaches, Measurement Error: Models, Methods, and Applications provides an overview of the main techniques and illu

Author : Peter Kennedy
Publisher : John Wiley & Sons
Page : 608 pages
File Size : 48,7 Mb
Release : 2008-02-19
Category : Business & Economics
ISBN : 9781405182577

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A Guide to Econometrics by Peter Kennedy Pdf

Dieses etwas andere Lehrbuch bietet keine vorgefertigten Rezepte und Problemlösungen, sondern eine kritische Diskussion ökonometrischer Modelle und Methoden: voller überraschender Fragen, skeptisch, humorvoll und anwendungsorientiert. Sein Erfolg gibt ihm Recht.

Author : Wenxin Jiang
Publisher : Unknown
Page : 404 pages
File Size : 41,9 Mb
Release : 1996
Category : Electronic
ISBN : CORNELL:31924077494080

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Aspects of Misspecification in Statistical Models by Wenxin Jiang Pdf

Author : Philip J. Brown,Wayne A. Fuller,American Mathematical Society
Publisher : American Mathematical Soc.
Page : 264 pages
File Size : 43,8 Mb
Release : 1990-12-06
Category : Mathematics
ISBN : 0821854453

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Statistical Analysis of Measurement Error Models and Applications by Philip J. Brown,Wayne A. Fuller,American Mathematical Society Pdf

Measurement error models describe functional relationships among variables observed, subject to random errors of measurement. Examples include linear and nonlinear errors-in-variables regression models, calibration and inverse regression models, factor analysis models, latent structure models, and simultaneous equations models. Such models are used in a wide variety of areas, including medicine, the life sciences, econometrics, chemometrics, geology, sample surveys, and time series. Although the problem of estimating the parameters of such models exists in most scientific fields, there is a need for more sources that treat measurement error models as an area of statistical methodology. This volume is designed to address that need. This book contains the proceedings of an AMS-IMS-SIAM Joint Summer Research Conference in the Mathematical Sciences on Statistical Analysis of Measurement Error Models and Applications. The conference was held at Humboldt State University in Arcata, California in June 1989. The papers in this volume fall into four broad groups. The first group treats general aspects of the measurement problem and features a discussion of the history of measurement error models. The second group focuses on inference for the nonlinear measurement error model, an active area of research which generated considerable interest at the conference. The third group of papers examines computational aspects of estimation, while the final set studies estimators possessing robustness properties against deviations from common model assumptions.

Author : Anders Skrondal,Sophia Rabe-Hesketh
Publisher : CRC Press
Page : 528 pages
File Size : 40,7 Mb
Release : 2004-05-11
Category : Mathematics
ISBN : 9780203489437

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Generalized Latent Variable Modeling by Anders Skrondal,Sophia Rabe-Hesketh Pdf

This book unifies and extends latent variable models, including multilevel or generalized linear mixed models, longitudinal or panel models, item response or factor models, latent class or finite mixture models, and structural equation models. Following a gentle introduction to latent variable modeling, the authors clearly explain and contrast a wi

Author : Brajendra C. Sutradhar
Publisher : Springer Science & Business Media
Page : 224 pages
File Size : 41,9 Mb
Release : 2013-08-13
Category : Mathematics
ISBN : 9781461468714

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ISS-2012 Proceedings Volume On Longitudinal Data Analysis Subject to Measurement Errors, Missing Values, and/or Outliers by Brajendra C. Sutradhar Pdf

This proceedings volume contains nine selected papers that were presented in the International Symposium in Statistics, 2012 held at Memorial University from July 16 to 18. These nine papers cover three different areas for longitudinal data analysis, four dealing with longitudinal data subject to measurement errors, four on incomplete longitudinal data analysis, and the last one for inferences for longitudinal data subject to outliers. Unlike in the independence setup, the inferences in measurement errors, missing values, and/or outlier models, are not adequately discussed in the longitudinal setup. The papers in the present volume provide details on successes and further challenges in these three areas for longitudinal data analysis. This volume is the first outlet with current research in three important areas in the longitudinal setup. The nine papers presented in three parts clearly reveal the similarities and differences in inference techniques used for three different longitudinal setups. Because the research problems considered in this volume are encountered in many real life studies in biomedical, clinical, epidemiology, socioeconomic, econometrics, and engineering fields, the volume should be useful to the researchers including graduate students in these areas.

Author : Maurizio Carpita,Eugenio Brentari,El Mostafa Qannari
Publisher : Springer
Page : 285 pages
File Size : 53,8 Mb
Release : 2015-04-01
Category : Mathematics
ISBN : 9783319029672

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Advances in Latent Variables by Maurizio Carpita,Eugenio Brentari,El Mostafa Qannari Pdf

The book, belonging to the series “Studies in Theoretical and Applied Statistics– Selected Papers from the Statistical Societies”, presents a peer-reviewed selection of contributions on relevant topics organized by the editors on the occasion of the SIS 2013 Statistical Conference "Advances in Latent Variables. Methods, Models and Applications", held at the Department of Economics and Management of the University of Brescia from June 19 to 21, 2013. The focus of the book is on advances in statistical methods for analyses with latent variables. In fact, in recent years, there has been increasing interest in this broad research area from both a theoretical and an applied point of view, as the statistical latent variable approach allows the effective modeling of complex real-life phenomena in a wide range of research fields. A major goal of the volume is to bring together articles written by statisticians from different research fields, which present different approaches and experiences related to the analysis of unobservable variables and the study of the relationships between them.

Author : Grace Y. Yi,Aurore Delaigle,Paul Gustafson
Publisher : CRC Press
Page : 648 pages
File Size : 52,6 Mb
Release : 2021-09-28
Category : Mathematics
ISBN : 9781351588591

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Handbook of Measurement Error Models by Grace Y. Yi,Aurore Delaigle,Paul Gustafson Pdf

Measurement error arises ubiquitously in applications and has been of long-standing concern in a variety of fields, including medical research, epidemiological studies, economics, environmental studies, and survey research. While several research monographs are available to summarize methods and strategies of handling different measurement error problems, research in this area continues to attract extensive attention. The Handbook of Measurement Error Models provides overviews of various topics on measurement error problems. It collects carefully edited chapters concerning issues of measurement error and evolving statistical methods, with a good balance of methodology and applications. It is prepared for readers who wish to start research and gain insights into challenges, methods, and applications related to error-prone data. It also serves as a reference text on statistical methods and applications pertinent to measurement error models, for researchers and data analysts alike. Features: Provides an account of past development and modern advancement concerning measurement error problems Highlights the challenges induced by error-contaminated data Introduces off-the-shelf methods for mitigating deleterious impacts of measurement error Describes state-of-the-art strategies for conducting in-depth research

Author : László Mátyás,Patrick Sevestre
Publisher : Springer Science & Business Media
Page : 564 pages
File Size : 41,7 Mb
Release : 2013-12-01
Category : Business & Economics
ISBN : 9789400903753

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The Econometrics of Panel Data by László Mátyás,Patrick Sevestre Pdf

The aim of this volume is to provide a general overview of the econometrics of panel data, both from a theoretical and from an applied viewpoint. Since the pioneering papers by Kuh (1959), Mundlak (1961), Hoch (1962), and Balestra and Nerlove (1966), the pooling of cross section and time series data has become an increasingly popular way of quantifying economic relationships. Each series provides information lacking in the other, so a combination of both leads to more accurate and reliable results than would be achievable by one type of series alone. Over the last 30 years much work has been done: investigation of the properties of the applied estimators and test statistics, analysis of dynamic models and the effects of eventual measurement errors, etc. These are just some of the problems addressed by this work. In addition, some specific diffi culties associated with the use of panel data, such as attrition, heterogeneity, selectivity bias, pseudo panels etc., have also been explored. The first objective of this book, which takes up Parts I and II, is to give as complete and up-to-date a presentation of these theoretical developments as possible. Part I is concerned with classical linear models and their extensions; Part II deals with nonlinear models and related issues: logit and probit models, latent variable models, incomplete panels and selectivity bias, and point processes.

Author : Grace Y. Yi
Publisher : Springer
Page : 479 pages
File Size : 49,6 Mb
Release : 2017-08-02
Category : Mathematics
ISBN : 9781493966400

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Statistical Analysis with Measurement Error or Misclassification by Grace Y. Yi Pdf

This monograph on measurement error and misclassification covers a broad range of problems and emphasizes unique features in modeling and analyzing problems arising from medical research and epidemiological studies. Many measurement error and misclassification problems have been addressed in various fields over the years as well as with a wide spectrum of data, including event history data (such as survival data and recurrent event data), correlated data (such as longitudinal data and clustered data), multi-state event data, and data arising from case-control studies. Statistical Analysis with Measurement Error or Misclassification: Strategy, Method and Application brings together assorted methods in a single text and provides an update of recent developments for a variety of settings. Measurement error effects and strategies of handling mismeasurement for different models are closely examined in combination with applications to specific problems. Readers with diverse backgrounds and objectives can utilize this text. Familiarity with inference methods—such as likelihood and estimating function theory—or modeling schemes in varying settings—such as survival analysis and longitudinal data analysis—can result in a full appreciation of the material, but it is not essential since each chapter provides basic inference frameworks and background information on an individual topic to ease the access of the material. The text is presented in a coherent and self-contained manner and highlights the essence of commonly used modeling and inference methods. This text can serve as a reference book for researchers interested in statistical methodology for handling data with measurement error or misclassification; as a textbook for graduate students, especially for those majoring in statistics and biostatistics; or as a book for applied statisticians whose interest focuses on analysis of error-contaminated data. Grace Y. Yi is Professor of Statistics and University Research Chair at the University of Waterloo. She is the 2010 winner of the CRM-SSC Prize, an honor awarded in recognition of a statistical scientist's professional accomplishments in research during the first 15 years after having received a doctorate. She is a Fellow of the American Statistical Association and an Elected Member of the International Statistical Institute.