Download or read book On the Maximum Likelihood Estimation of Multivariate Regression Models Containing Serially Correlated Error Components written by Jan R. Magnus and published by . This book was released on 1987 with total page 35 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book On the Maximum Likelihood Estimation of Multivariate Regression Models Containing Serially Correlated Error Components written by Jan R. Magnus and published by . This book was released on 1989 with total page 19 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Maximum Likelihood Estimation of Misspecified Models written by T. Fomby and published by Elsevier. This book was released on 2003-12-12 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: Comparative study of pure and pretest estimators for a possibly misspecified two-way error component model / Badi H. Baltagi, Georges Bresson, Alain Pirotte -- Estimation, inference, and specification testing for possibly misspecified quantile regression / Tae-Hwan Kim, Halbert White -- Quasimaximum likelihood estimation with bounded symmetric errors / Douglas Miller, James Eales, Paul Preckel -- Consistent quasi-maximum likelihood estimation with limited information / Douglas Miller, Sang-Hak Lee -- An examination of the sign and volatility switching arch models under alternative distributional assumptions / Mohamed F. Omran, Florin Avram -- estimating a linear exponential density when the weighting matrix and mean parameter vector are functionally related / Chor-yiu Sin -- Testing in GMM models without truncation / Timothy J. Vogelsang -- Bayesian analysis of misspecified models with fixed effects / Tiemen Woutersen -- Tests of common deterministic trend slopes applied to quarterly global temperature data / Thomas B. Fomby, Timothy J. Vogelsang -- The sandwich estimate of variance / James W. Hardin -- Test statistics and critical values in selectivity models / R. Carter Hill, Lee C. Adkins, Keith A. Bender -- Introduction / Thomas B Fomby, R. Carter Hill.

Download or read book Regression Analysis of Count Data written by A. Colin Cameron and published by Cambridge University Press. This book was released on 2013-05-27 with total page 597 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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, now in its second edition, provides the most comprehensive and up-to-date account of models and methods to interpret such data. The authors 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 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.

Download or read book Maximum Likelihood Estimation in a Linear Model with Serially Correlated Errors when Observations are Missing written by Tom Wansbeek and published by . This book was released on 1980 with total page 19 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Multivariate Reduced Rank Regression written by Gregory C. Reinsel and published by Springer Nature. This book was released on 2022-11-30 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an account of multivariate reduced-rank regression, a tool of multivariate analysis that enjoys a broad array of applications. In addition to a historical review of the topic, its connection to other widely used statistical methods, such as multivariate analysis of variance (MANOVA), discriminant analysis, principal components, canonical correlation analysis, and errors-in-variables models, is also discussed. This new edition incorporates Big Data methodology and its applications, as well as high-dimensional reduced-rank regression, generalized reduced-rank regression with complex data, and sparse and low-rank regression methods. Each chapter contains developments of basic theoretical results, as well as details on computational procedures, illustrated with numerical examples drawn from disciplines such as biochemistry, genetics, marketing, and finance. This book is designed for advanced students, practitioners, and researchers, who may deal with moderate and high-dimensional multivariate data. Because regression is one of the most popular statistical methods, the multivariate regression analysis tools described should provide a natural way of looking at large (both cross-sectional and chronological) data sets. This book can be assigned in seminar-type courses taken by advanced graduate students in statistics, machine learning, econometrics, business, and engineering.

Download or read book Convenient Methods for Estimation of Linear Regression Models with MA 1 Errors written by Glenn M. MacDonald and published by Kingston, Ont. : Institute for Economic Research, Queen's University. This book was released on 1983 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Inference in Multivariate Student T Models with Serial Correlation and Dynamic Heteroskedasticity written by Trevor S. Breusch and published by . This book was released on 1993 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book The Econometrics of Panel Data written by László Mátyás and published by Springer Science & Business Media. This book was released on 2013-12-01 with total page 944 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 Edwin Kuh (1959), Yair Mundlak (1961), Irving Hoch (1962), and Pietro Balestra and Marc Nerlove (1966), the pooling of cross sections 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 pro bit models, latent variable models, duration and count data models, incomplete panels and selectivity bias, point processes, and simulation techniques.

Download or read book Panel Data Analysis written by Baldev Raj and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 223 pages. Available in PDF, EPUB and Kindle. Book excerpt: A number of advances have taken place in panel data analysis during the pastthree decades and it continues to be one of the most active areas of research. This volume contains 13 significant contributions focusing on modelling strategies, data issues, theoretical analysis and applications. Applied econometrics papers on the economics of labor, health, telecommunications, finance and macroeconomics are provided as well as a survey of recent theoretical developments in panal data analysis. Contributors include both well known scholars and younger researchers from Australia, Canada, Europe and the United States of America.

Download or read book Econometric Analysis of Panel Data written by Badi Baltagi and published by John Wiley & Sons. This book was released on 2008-06-30 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by one of the world's leading researchers and writers in the field, Econometric Analysis of Panel Data has become established as the leading textbook for postgraduate courses in panel data. This new edition reflects the rapid developments in the field covering the vast research that has been conducted on panel data since its initial publication. Featuring the most recent empirical examples from panel data literature, data sets are also provided as well as the programs to implement the estimation and testing procedures described in the book. These programs will be made available via an accompanying website which will also contain solutions to end of chapter exercises that will appear in the book. The text has been fully updated with new material on dynamic panel data models and recent results on non-linear panel models and in particular work on limited dependent variables panel data models.

Download or read book Multivariate Reduced Rank Regression written by Raja Velu and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the area of multivariate analysis, there are two broad themes that have emerged over time. The analysis typically involves exploring the variations in a set of interrelated variables or investigating the simultaneous relation ships between two or more sets of variables. In either case, the themes involve explicit modeling of the relationships or dimension-reduction of the sets of variables. The multivariate regression methodology and its variants are the preferred tools for the parametric modeling and descriptive tools such as principal components or canonical correlations are the tools used for addressing the dimension-reduction issues. Both act as complementary to each other and data analysts typically want to make use of these tools for a thorough analysis of multivariate data. A technique that combines the two broad themes in a natural fashion is the method of reduced-rank regres sion. This method starts with the classical multivariate regression model framework but recognizes the possibility for the reduction in the number of parameters through a restrietion on the rank of the regression coefficient matrix. This feature is attractive because regression methods, whether they are in the context of a single response variable or in the context of several response variables, are popular statistical tools. The technique of reduced rank regression and its encompassing features are the primary focus of this book. The book develops the method of reduced-rank regression starting from the classical multivariate linear regression model.

Download or read book Die Erfassung der langfristigen Absatzm glichkeiten mit Hilfe des Lebenszyklus eines Produktes written by Badi H. Baltagi and published by Springer Science & Business Media. This book was released on 2004-04-16 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt: The present book is a collection of panel data papers, both theoretical and applied. Theoretical topics include methodology papers on panel data probit models, treatment models, error component models with an ARMA process on the time specific effects, asymptotic tests for poolability and their bootstrapped versions, confidence intervals for a doubly heteroskedastic stochastic production frontiers, estimation of semiparametric dynamic panel data models and review of survey attrition and nonresponse in the European Community Household Panel. Applications include the impact of uncertainty on UK investment, a Tobin-q investment model using US firm data, technical change in the Japanese chemical industry, cost efficiency of Spanish banks, the problem of immigrant integration in Canada, an analysis of the dynamics of individual health in the UK, the relationship between inflation and growth among OECD and APEC countries, modeling corner solutions in the industrial energy demand in the pulp and paper sector in France, technical efficiency of cereal farms in England, employment-supported training in Canada, earnings trends across skill groups and industries in West Germany, employment effects of education for disabled workers in Norway, a three-way gravity model with bilateral interaction effects for APEC countries and a panel cointegration approach to the Feldstein-Horioka investment-saving puzzle.

Download or read book Local Regression and Likelihood written by Clive Loader and published by Springer Science & Business Media. This book was released on 2006-05-09 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: Separation of signal from noise is the most fundamental problem in data analysis, arising in such fields as: signal processing, econometrics, actuarial science, and geostatistics. This book introduces the local regression method in univariate and multivariate settings, with extensions to local likelihood and density estimation. Practical information is also included on how to implement these methods in the programs S-PLUS and LOCFIT.

Download or read book Multivariate Error Components Analysis of Linear and Nonlinear Regression Models by Maximum Likelihood written by Jan R. Magnus and published by . This book was released on 1980 with total page 60 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Introduction to Spatial Econometrics written by James LeSage and published by CRC Press. This book was released on 2009-01-20 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although interest in spatial regression models has surged in recent years, a comprehensive, up-to-date text on these approaches does not exist. Filling this void, Introduction to Spatial Econometrics presents a variety of regression methods used to analyze spatial data samples that violate the traditional assumption of independence between observat

Download or read book Econometric Analysis of Panel Data written by Badi H. Baltagi and published by Springer Nature. This book was released on 2021-03-16 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook offers a comprehensive introduction to panel data econometrics, an area that has enjoyed considerable growth over the last two decades. Micro and Macro panels are becoming increasingly available, and methods for dealing with these types of data are in high demand among practitioners. Software programs have fostered this growth, including freely available programs in R and numerous user-written programs in both Stata and EViews. Written by one of the world’s leading researchers and authors in the field, Econometric Analysis of Panel Data has established itself as the leading textbook for graduate and postgraduate courses on panel data. It provides up-to-date coverage of basic panel data techniques, illustrated with real economic applications and datasets, which are available at the book’s website on springer.com. This new sixth edition has been fully revised and updated, and includes new material on dynamic panels, limited dependent variables and nonstationary panels, as well as spatial panel data. The author also provides empirical illustrations and examples using Stata and EViews. “This is a definitive book written by one of the architects of modern, panel data econometrics. It provides both a practical introduction to the subject matter, as well as a thorough discussion of the underlying statistical principles without taxing the reader too greatly." Professor Kajal Lahiri, State University of New York, Albany, USA. "This book is the most comprehensive work available on panel data. It is written by one of the leading contributors to the field, and is notable for its encyclopaedic coverage and its clarity of exposition. It is useful to theorists and to people doing applied work using panel data. It is valuable as a text for a course in panel data, as a supplementary text for more general courses in econometrics, and as a reference." Professor Peter Schmidt, Michigan State University, USA. “Panel data econometrics is in its ascendancy, combining the power of cross section averaging with all the subtleties of temporal and spatial dependence. Badi Baltagi provides a remarkable roadmap of this fascinating interface of econometric method, enticing the novitiate with technical gentleness, the expert with comprehensive coverage and the practitioner with many empirical applications.” Professor Peter C. B. Phillips, Cowles Foundation, Yale University, USA.