Regression and factor analysis applied in econometrics

Regression and factor analysis applied in econometrics

Author: J.H.F. Schilderinck

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 247

ISBN-13: 1461340519

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This book deals with the methods and practical uses of regression and factor analysis. An exposition is given of ordinary, generalized, two- and three-stage estimates for regression analysis, the method of principal components being applied for factor analysis. When establishing an econometric model, the two ways of analysis complement each other. The model was realized as part of the 'Interplay' research project concerning the economies of the European Common Market countries at the Econometrics Department of the Tilburg School of Economics. The Interplay project aims at: a. elaborating more or less uniformly defined and estimated models; b. clarifying the economic structure and the economic policy possible with the linked models of the European Community countries. Besides the model for the Netherlands published here, the models for Belgium, Italy, West Germany and the United Kingdom are ready for linking and for publishing later on. The econometric model presented in this book and upon which the Interplay model is based comprises eleven structural and twenty-one definitional equations; it is estimated with ordinary, two- and three-stage least squares. The analysis of the model is directed at eliminating multicollinearity, accor ding to D.E. Farrar's and R. Glauber's method. In practice, however, complete elimination of multicollinearity leads to an exclusion of certain relations which is not entirely satisfactory. Economic relations can be dealt with more fully by analyzing the variables involved in detail by factor analysis. In this study factor analysis is also a suitable method for a comparative analysis of different periods.


Essential Statistics, Regression, and Econometrics

Essential Statistics, Regression, and Econometrics

Author: Gary Smith

Publisher: Academic Press

Published: 2015-06-08

Total Pages: 397

ISBN-13: 0128034920

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Essential Statistics, Regression, and Econometrics, Second Edition, is innovative in its focus on preparing students for regression/econometrics, and in its extended emphasis on statistical reasoning, real data, pitfalls in data analysis, and modeling issues. This book is uncommonly approachable and easy to use, with extensive word problems that emphasize intuition and understanding. Too many students mistakenly believe that statistics courses are too abstract, mathematical, and tedious to be useful or interesting. To demonstrate the power, elegance, and even beauty of statistical reasoning, this book provides hundreds of new and updated interesting and relevant examples, and discusses not only the uses but also the abuses of statistics. The examples are drawn from many areas to show that statistical reasoning is not an irrelevant abstraction, but an important part of everyday life. - Includes hundreds of updated and new, real-world examples to engage students in the meaning and impact of statistics - Focuses on essential information to enable students to develop their own statistical reasoning - Ideal for one-quarter or one-semester courses taught in economics, business, finance, politics, sociology, and psychology departments, as well as in law and medical schools - Accompanied by an ancillary website with an instructors solutions manual, student solutions manual and supplementing chapters


Exploratory Factor Analysis

Exploratory Factor Analysis

Author: Leandre R. Fabrigar

Publisher: Oxford University Press

Published: 2012-01-12

Total Pages: 170

ISBN-13: 0199734178

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This book provides a non-mathematical introduction to the theory and application of Exploratory Factor Analysis. Among the issues discussed are the use of confirmatory versus exploratory factor analysis, the use of principal components analysis versus common factor analysis, and procedures for determining the appropriate number of factors.


Large Dimensional Factor Analysis

Large Dimensional Factor Analysis

Author: Jushan Bai

Publisher: Now Publishers Inc

Published: 2008

Total Pages: 90

ISBN-13: 1601981449

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Large Dimensional Factor Analysis provides a survey of the main theoretical results for large dimensional factor models, emphasizing results that have implications for empirical work. The authors focus on the development of the static factor models and on the use of estimated factors in subsequent estimation and inference. Large Dimensional Factor Analysis discusses how to determine the number of factors, how to conduct inference when estimated factors are used in regressions, how to assess the adequacy pf observed variables as proxies for latent factors, how to exploit the estimated factors to test unit root tests and common trends, and how to estimate panel cointegration models.


Applied Econometrics with R

Applied Econometrics with R

Author: Christian Kleiber

Publisher: Springer Science & Business Media

Published: 2008-12-10

Total Pages: 229

ISBN-13: 0387773185

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R is a language and environment for data analysis and graphics. It may be considered an implementation of S, an award-winning language initially - veloped at Bell Laboratories since the late 1970s. The R project was initiated by Robert Gentleman and Ross Ihaka at the University of Auckland, New Zealand, in the early 1990s, and has been developed by an international team since mid-1997. Historically, econometricians have favored other computing environments, some of which have fallen by the wayside, and also a variety of packages with canned routines. We believe that R has great potential in econometrics, both for research and for teaching. There are at least three reasons for this: (1) R is mostly platform independent and runs on Microsoft Windows, the Mac family of operating systems, and various ?avors of Unix/Linux, and also on some more exotic platforms. (2) R is free software that can be downloaded and installed at no cost from a family of mirror sites around the globe, the Comprehensive R Archive Network (CRAN); hence students can easily install it on their own machines. (3) R is open-source software, so that the full source code is available and can be inspected to understand what it really does, learn from it, and modify and extend it. We also like to think that platform independence and the open-source philosophy make R an ideal environment for reproducible econometric research.


Panel Data Econometrics

Panel Data Econometrics

Author: Donggyu Sul

Publisher: Routledge

Published: 2019-02-07

Total Pages: 150

ISBN-13: 0429752989

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In the last 20 years, econometric theory on panel data has developed rapidly, particularly for analyzing common behaviors among individuals over time. Meanwhile, the statistical methods employed by applied researchers have not kept up-to-date. This book attempts to fill in this gap by teaching researchers how to use the latest panel estimation methods correctly. Almost all applied economics articles use panel data or panel regressions. However, many empirical results from typical panel data analyses are not correctly executed. This book aims to help applied researchers to run panel regressions correctly and avoid common mistakes. The book explains how to model cross-sectional dependence, how to estimate a few key common variables, and how to identify them. It also provides guidance on how to separate out the long-run relationship and common dynamic and idiosyncratic dynamic relationships from a set of panel data. Aimed at applied researchers who want to learn about panel data econometrics by running statistical software, this book provides clear guidance and is supported by a full range of online teaching and learning materials. It includes practice sections on MATLAB, STATA, and GAUSS throughout, along with short and simple econometric theories on basic panel regressions for those who are unfamiliar with econometric theory on traditional panel regressions.


Statistical Factor Analysis and Related Methods

Statistical Factor Analysis and Related Methods

Author: Alexander T. Basilevsky

Publisher: John Wiley & Sons

Published: 2009-09-25

Total Pages: 770

ISBN-13: 0470317736

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Statistical Factor Analysis and Related Methods Theory andApplications In bridging the gap between the mathematical andstatistical theory of factor analysis, this new work represents thefirst unified treatment of the theory and practice of factoranalysis and latent variable models. It focuses on such areasas: * The classical principal components model and sample-populationinference * Several extensions and modifications of principal components,including Q and three-mode analysis and principal components in thecomplex domain * Maximum likelihood and weighted factor models, factoridentification, factor rotation, and the estimation of factorscores * The use of factor models in conjunction with various types ofdata including time series, spatial data, rank orders, and nominalvariable * Applications of factor models to the estimation of functionalforms and to least squares of regression estimators


Applied Linear Statistical Models

Applied Linear Statistical Models

Author: Michael H. Kutner

Publisher: McGraw-Hill/Irwin

Published: 2005

Total Pages: 1396

ISBN-13: 9780072386882

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Linear regression with one predictor variable; Inferences in regression and correlation analysis; Diagnosticis and remedial measures; Simultaneous inferences and other topics in regression analysis; Matrix approach to simple linear regression analysis; Multiple linear regression; Nonlinear regression; Design and analysis of single-factor studies; Multi-factor studies; Specialized study designs.


The SAGE Handbook of Regression Analysis and Causal Inference

The SAGE Handbook of Regression Analysis and Causal Inference

Author: Henning Best

Publisher: SAGE

Published: 2013-12-20

Total Pages: 425

ISBN-13: 1473908353

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′The editors of the new SAGE Handbook of Regression Analysis and Causal Inference have assembled a wide-ranging, high-quality, and timely collection of articles on topics of central importance to quantitative social research, many written by leaders in the field. Everyone engaged in statistical analysis of social-science data will find something of interest in this book.′ - John Fox, Professor, Department of Sociology, McMaster University ′The authors do a great job in explaining the various statistical methods in a clear and simple way - focussing on fundamental understanding, interpretation of results, and practical application - yet being precise in their exposition.′ - Ben Jann, Executive Director, Institute of Sociology, University of Bern ′Best and Wolf have put together a powerful collection, especially valuable in its separate discussions of uses for both cross-sectional and panel data analysis.′ -Tom Smith, Senior Fellow, NORC, University of Chicago Edited and written by a team of leading international social scientists, this Handbook provides a comprehensive introduction to multivariate methods. The Handbook focuses on regression analysis of cross-sectional and longitudinal data with an emphasis on causal analysis, thereby covering a large number of different techniques including selection models, complex samples, and regression discontinuities. Each Part starts with a non-mathematical introduction to the method covered in that section, giving readers a basic knowledge of the method’s logic, scope and unique features. Next, the mathematical and statistical basis of each method is presented along with advanced aspects. Using real-world data from the European Social Survey (ESS) and the Socio-Economic Panel (GSOEP), the book provides a comprehensive discussion of each method’s application, making this an ideal text for PhD students and researchers embarking on their own data analysis.