Download or read book Analysis of Panels and Limited Dependent Variable Models written by Cheng Hsiao and published by Cambridge University Press. This book was released on 1999-07-29 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: This important collection brings together leading econometricians to discuss advances in the areas of the econometrics of panel data. The papers in this collection can be grouped into two categories. The first, which includes chapters by Amemiya, Baltagi, Arellano, Bover and Labeaga, primarily deal with different aspects of limited dependent variables and sample selectivity. The second group of papers, including those by Nerlove, Schmidt and Ahn, Kiviet, Davies and Lahiri, consider issues that arise in the estimation of dyanamic (possibly) heterogeneous panel data models. Overall, the contributors focus on the issues of simplifying complex real-world phenomena into easily generalisable inferences from individual outcomes. As the contributions of G. S. Maddala in the fields of limited dependent variables and panel data were particularly influential, it is a fitting tribute that this volume is dedicated to him.
Download or read book Analysis of Panels and Limited Dependent Variable Models written by Cheng Hsiao and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Panel Data Econometrics written by Myoung-jae Lee and published by Emerald Group Pub Limited. This book was released on 2002 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: Disk contains: Four data sets -- Ten GAUSS programs for empirical examples in text.
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 Topics in Identification Limited Dependent Variables Partial Observability Experimentation and Flexible Modeling written by Ivan Jeliazkov and published by Emerald Group Publishing. This book was released on 2019-10-18 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: Volume 40B of Advances in Econometrics examines innovations in stochastic frontier analysis, nonparametric and semiparametric modeling and estimation, A/B experiments, big-data analysis, and quantile regression.
Download or read book Limited Dependent and Qualitative Variables in Econometrics written by G. S. Maddala and published by Cambridge University Press. This book was released on 1986-06-27 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the econometric analysis of single-equation and simultaneous-equation models in which the jointly dependent variables can be continuous, categorical, or truncated. Despite the traditional emphasis on continuous variables in econometrics, many of the economic variables encountered in practice are categorical (those for which a suitable category can be found but where no actual measurement exists) or truncated (those that can be observed only in certain ranges). Such variables are involved, for example, in models of occupational choice, choice of tenure in housing, and choice of type of schooling. Models with regulated prices and rationing, and models for program evaluation, also represent areas of application for the techniques presented by the author.
Download or read book Econometric Analysis of Panal Data written by Badi H. Baltagi and published by John Wiley & Sons. This book was released on 2001-10-31 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new edition of this established textbook reflects the rapid developments in the field covering the vast research that has been conducted on panel data since its initial publication. The book is packed with the most recent empirical examples from panel data literature and includes new data sets. The use of the standard software packages in the field i.e. STATA, LIMDEP, TSP & SAS are illustrated with new examples. The text has also been fully updated with new material on: non-stationary models, unit roots in panels and cointegration, prediction in panels, serial correlation, heteroskedasticity, and new results on GMM in dynamic panel data models. There is also website providing supplementary material for lecturers.
Download or read book Micro Econometrics written by Myoung-jae Lee and published by Springer Science & Business Media. This book was released on 2009-09-28 with total page 789 pages. Available in PDF, EPUB and Kindle. Book excerpt: Up-to-date coverage of most micro-econometric topics; first half parametric, second half semi- (non-) parametric Many empirical examples and tips in applying econometric theories to data Essential ideas and steps shown for most estimators and tests; well-suited for both applied and theoretical readers
Download or read book Regression Models for Categorical and Limited Dependent Variables written by J. Scott Long and published by SAGE. This book was released on 1997-01-09 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: Evaluates the most useful models for categorical and limited dependent variables (CLDVs), emphasizing the links among models and applying common methods of derivation, interpretation, and testing. The author also explains how models relate to linear regression models whenever possible. Annotation c.
Download or read book Econometrics in Theory and Practice written by Panchanan Das and published by Springer Nature. This book was released on 2019-09-05 with total page 565 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces econometric analysis of cross section, time series and panel data with the application of statistical software. It serves as a basic text for those who wish to learn and apply econometric analysis in empirical research. The level of presentation is as simple as possible to make it useful for undergraduates as well as graduate students. It contains several examples with real data and Stata programmes and interpretation of the results. While discussing the statistical tools needed to understand empirical economic research, the book attempts to provide a balance between theory and applied research. Various concepts and techniques of econometric analysis are supported by carefully developed examples with the use of statistical software package, Stata 15.1, and assumes that the reader is somewhat familiar with the Strata software. The topics covered in this book are divided into four parts. Part I discusses introductory econometric methods for data analysis that economists and other social scientists use to estimate the economic and social relationships, and to test hypotheses about them, using real-world data. There are five chapters in this part covering the data management issues, details of linear regression models, the related problems due to violation of the classical assumptions. Part II discusses some advanced topics used frequently in empirical research with cross section data. In its three chapters, this part includes some specific problems of regression analysis. Part III deals with time series econometric analysis. It covers intensively both the univariate and multivariate time series econometric models and their applications with software programming in six chapters. Part IV takes care of panel data analysis in four chapters. Different aspects of fixed effects and random effects are discussed here. Panel data analysis has been extended by taking dynamic panel data models which are most suitable for macroeconomic research. The book is invaluable for students and researchers of social sciences, business, management, operations research, engineering, and applied mathematics.
Download or read book Handbook of Statistical Modeling for the Social and Behavioral Sciences written by G. Arminger and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 603 pages. Available in PDF, EPUB and Kindle. Book excerpt: Contributors thoroughly survey the most important statistical models used in empirical reserch in the social and behavioral sciences. Following a common format, each chapter introduces a model, illustrates the types of problems and data for which the model is best used, provides numerous examples that draw upon familiar models or procedures, and includes material on software that can be used to estimate the models studied. This handbook will aid researchers, methodologists, graduate students, and statisticians to understand and resolve common modeling problems.
Download or read book Dynamic Limited Dependent Variable Models Using Panel Data with Applications to Corporate Dividends written by Fude Cheng and published by . This book was released on 2002 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The Oxford Handbook of Panel Data written by Badi Hani Baltagi and published by . This book was released on 2015 with total page 705 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Oxford Handbook of Panel Data examines new developments in the theory and applications of panel data. It includes basic topics like non-stationary panels, co-integration in panels, multifactor panel models, panel unit roots, measurement error in panels, incidental parameters and dynamic panels, spatial panels, nonparametric panel data, random coefficients, treatment effects, sample selection, count panel data, limited dependent variable panel models, unbalanced panel models with interactive effects and influential observations in panel data. Contributors to the Handbook explore applications of panel data to a wide range of topics in economics, including health, labor, marketing, trade, productivity, and macro applications in panels. This Handbook is an informative and comprehensive guide for both those who are relatively new to the field and for those wishing to extend their knowledge to the frontier. It is a trusted and definitive source on panel data, having been edited by Professor Badi Baltagi-widely recognized as one of the foremost econometricians in the area of panel data econometrics. Professor Baltagi has successfully recruited an all-star cast of experts for each of the well-chosen topics in the Handbook.
Download or read book Panel Data Econometrics written by Mike Tsionas and published by Academic Press. This book was released on 2019-06-19 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: Panel Data Econometrics: Theory introduces econometric modelling. Written by experts from diverse disciplines, the volume uses longitudinal datasets to illuminate applications for a variety of fields, such as banking, financial markets, tourism and transportation, auctions, and experimental economics. Contributors emphasize techniques and applications, and they accompany their explanations with case studies, empirical exercises and supplementary code in R. They also address panel data analysis in the context of productivity and efficiency analysis, where some of the most interesting applications and advancements have recently been made. Provides a vast array of empirical applications useful to practitioners from different application environments Accompanied by extensive case studies and empirical exercises Includes empirical chapters accompanied by supplementary code in R, helping researchers replicate findings Represents an accessible resource for diverse industries, including health, transportation, tourism, economic growth, and banking, where researchers are not always econometrics experts
Download or read book The Econometrics of Panel Data written by Lászlo Mátyás and published by Springer Science & Business Media. This book was released on 2008-04-06 with total page 966 pages. Available in PDF, EPUB and Kindle. Book excerpt: This restructured, updated Third Edition provides a general overview of the econometrics of panel data, from both theoretical and applied viewpoints. Readers discover how econometric tools are used to study organizational and household behaviors as well as other macroeconomic phenomena such as economic growth. The book contains sixteen entirely new chapters; all other chapters have been revised to account for recent developments. With contributions from well known specialists in the field, this handbook is a standard reference for all those involved in the use of panel data in econometrics.
Download or read book Analysis of Microdata written by Rainer Winkelmann and published by Springer Science & Business Media. This book was released on 2006-09-21 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: The availability of microdata has increased rapidly over the last decades, and standard statistical and econometric software packages for data analysis include ever more sophisticated modeling options. The goal of this book is to familiarize readers with a wide range of commonly used models, and thereby to enable them to become critical consumers of current empirical research, and to conduct their own empirical analyses. The focus of the book is on regression-type models in the context of large cross-section samples. In microdata applications, dependent variables often are qualitative and discrete, while in other cases, the sample is not randomly drawn from the population of interest and the dependent variable is censored or truncated. Hence, models and methods are required that go beyond the standard linear regression model and ordinary least squares. Maximum li- lihood estimation of conditional probability models and marginal probability e?ects are introduced here as the unifying principle for modeling, estimating and interpreting microdata relationships. We consider the limitation to m- imum likelihood sensible, from a pedagogical point of view if the book is to be used in a semester-long advanced undergraduate or graduate course, and from a practical point of view because maximum likelihood estimation is used in the overwhelming majority of current microdata research. In order to introduce and explain the models and methods, we refer to a number of illustrative applications. The main examples include the deter- nants of individual fertility, the intergenerational transmission of secondary schoolchoices,andthewageelasticityoffemalelaborsupply.
Download or read book Panel Methods for Finance written by Marno Verbeek and published by de Gruyter. This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Financial data are typically characterised by a time-series dimension and a cross-sectional dimension. For example, we may observe financial information on a group of firms over a number of years, or we may observe returns of all stocks traded at NYSE over a period of 120 months. Accordingly, econometric modelling in finance requires appropriate attention to these two -- or occasionally more than two -- dimensions of the data. Panel data techniques are developed to do exactly this. This book provides an overview of commonly applied panel methods for financial applications. The use of panel data has many advantages, in terms of the flexibility of econometric modeling and the ability to control for unobserved heterogeneity. It also involves a number of econometric issues that require specific attention. This includes cross-sectional dependence, robust and clustered standard errors, parameter heterogeneity, fixed effects, dynamic models with a short time dimension, instrumental variables, differences-in-differences and other approaches for causal inference. After an introductory chapter reviewing the classical linear regression model with particular attention to its use in a panel data context, including several standard estimators (pooled OLS, Fama-MacBeth, random effects, first-differences, fixed effects), the book continues with a more elaborate treatment of fixed effects approaches. While first-differencing and fixed effects estimators are attractive because of their removal of time-invariant unobserved heterogeneity (e.g. manager quality, firm culture), consistency of such estimators imposes strict exogeneity of the explanatory variables (for a finite number of time periods). This is often violated in practice, for example, some explanatory variable explaining firm performance may be partly determined by historical firm performance. An obvious case where this assumption is violated arises when the model contains a lagged dependent variable. A separate chapter will focus on dynamic models, which have received specific attention in the literature, also in the context of financial applications, like the dynamics of capital structure choices. Estimation mostly relies on instrumental variables or GMM techniques. Identification and estimation of such models is often fragile, and the small sample properties may be disappointing. The book continues with a chapter on models with limited dependent variables, including binary response models. The cross-sectional dependence that is likely to be present complicates estimation, and the author discusses pooled estimation, random effects and fixed effects approaches, including the possibility to include lagged dependent variables. This chapter will also discuss problems of attrition and sample selection bias, as well as unbalanced panels in general. Identifying causal effects in empirical work based on non-experimental data is often challenging, and causal inference has received substantial attention in the recent literature. The availability of panel data plays an important role in many approaches. Starting with simple differences-in-differences approaches, a dedicated chapter discusses instrumental variables estimators, matching and propensity scores, regression discontinuity and related approaches.
