Download or read book Essays on Non normality Nonparametrics and Cross Sectional Dependence in Panel Data written by Xiao Huang and published by . This book was released on 2005 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Dissertation Abstracts International written by and published by . This book was released on 2007-10 with total page 784 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Econometric Analysis of Cross Section and Panel Data second edition written by Jeffrey M. Wooldridge and published by MIT Press. This book was released on 2010-10-01 with total page 1095 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second edition of a comprehensive state-of-the-art graduate level text on microeconometric methods, substantially revised and updated. The second edition of this acclaimed graduate text provides a unified treatment of two methods used in contemporary econometric research, cross section and data panel methods. By focusing on assumptions that can be given behavioral content, the book maintains an appropriate level of rigor while emphasizing intuitive thinking. The analysis covers both linear and nonlinear models, including models with dynamics and/or individual heterogeneity. In addition to general estimation frameworks (particular methods of moments and maximum likelihood), specific linear and nonlinear methods are covered in detail, including probit and logit models and their multivariate, Tobit models, models for count data, censored and missing data schemes, causal (or treatment) effects, and duration analysis. Econometric Analysis of Cross Section and Panel Data was the first graduate econometrics text to focus on microeconomic data structures, allowing assumptions to be separated into population and sampling assumptions. This second edition has been substantially updated and revised. Improvements include a broader class of models for missing data problems; more detailed treatment of cluster problems, an important topic for empirical researchers; expanded discussion of "generalized instrumental variables" (GIV) estimation; new coverage (based on the author's own recent research) of inverse probability weighting; a more complete framework for estimating treatment effects with panel data, and a firmly established link between econometric approaches to nonlinear panel data and the "generalized estimating equation" literature popular in statistics and other fields. New attention is given to explaining when particular econometric methods can be applied; the goal is not only to tell readers what does work, but why certain "obvious" procedures do not. The numerous included exercises, both theoretical and computer-based, allow the reader to extend methods covered in the text and discover new insights.
Download or read book Essays in Honor of Aman Ullah written by R. Carter Hill and published by Emerald Group Publishing. This book was released on 2016-06-29 with total page 680 pages. Available in PDF, EPUB and Kindle. Book excerpt: Volume 36 of Advances in Econometrics recognizes Aman Ullah's significant contributions in many areas of econometrics and celebrates his long productive career.
Download or read book Journal of Economic Literature written by and published by . This book was released on 2005-12 with total page 304 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 with R written by Yves Croissant and published by John Wiley & Sons. This book was released on 2018-08-10 with total page 435 pages. Available in PDF, EPUB and Kindle. Book excerpt: Panel Data Econometrics with R provides a tutorial for using R in the field of panel data econometrics. Illustrated throughout with examples in econometrics, political science, agriculture and epidemiology, this book presents classic methodology and applications as well as more advanced topics and recent developments in this field including error component models, spatial panels and dynamic models. They have developed the software programming in R and host replicable material on the book’s accompanying website.
Download or read book Three Essays on Panel Data Analysis written by Minyu Han and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first chapter, Two-Way Fixed Effects versus Panel Factor Augmented Estimators: Asymptotic Comparison among Pre-testing Procedures, provides asymptotic analyses of pretesting procedures when the slope coefficients are heterogeneous across cross-sectional units. Empirical researchers may wonder whether or not a two-way fixed effects estimator (with individual and time fixed effects) is sufficiently sophisticated to isolate the influence of common shocks on the estimation of slope coefficients. If it is not, practitioners need to run the so-called panel factor augmented regression instead. There are two pre-testing procedures available in the literature: the use of the estimated number of factors and the direct test of estimated factor loading coefficients. This chapter compares the two pre-testing methods asymptotically. Under the presence of the heterogeneous factor loadings, both pre-testing procedures suggest using the Common Correlated Effects (CCE) estimator. By comparing asymptotic variances, this chapter finds that when the slope coefficients are heterogeneous with homogeneous factor loadings, the CCE estimation is, surprisingly, more efficient than the two-way fixed effects estimation. The second chapter, A New Test for Slope Homogeneity in a Panel Regression with Interactive Fixed Effects, proposes a new test for slope homogeneity in a panel regression with interactive fixed effects without any restriction on the relative expansion rate of n, the number of cross-sectional units, and T, the number of periods.This test is based on a comparison of the estimated number of common factors from two regression residuals. The first regression is an unconstrained regression with heterogeneous slope parameters. The second regression is a pooled regression based on the principal components mean group method. Under the slope heterogeneity, this chapter shows that the estimated number of common factors from the first regression residuals is asymptotically smaller than that of the second regression residuals. In the third chapter, Identification of Outliers for Testing Weak ϳ-Convergence, the authors suggest three novel procedures for separating the divergent series from a convergent club. Weak ϳ8́2convergence test is designed to detect whether cross-sectional variances of a panel data of interest show consistent diminution over time. When the panel data of interest includes divergent series, the cross-sectional variances become contaminated, which results in a seemingly divergent behavior. This chapter deals with this problem. We propose three novel detection procedures for identifying divergence series and provide the asymptotic justification. Utilizing Monte Carlo simulations, the finite sample properties are examined. We demonstrate the effectiveness of the newly proposed methods by using infant mortality rates in 42 countries. Even though all infant mortality rates have shown a downward trending behavior over time, the cross-sectional variance of log infant mortality rates is diverging over time. By using the proposed sieving methods, we identify six outliers. After excluding these outliers, the rest of the infant mortality rates are weakly ϳ-converging over time. Altogether, this dissertation provides methods for a better understanding of the source and nature of the cross-sectional dependence in panel data models.
Download or read book A Bias corrected CD Test for Error Cross sectional Dependence in Panel Data Models with Latent Factors written by M. Hashem Pesaran and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Microeconometrics written by A. Colin Cameron and published by Cambridge University Press. This book was released on 2005-05-09 with total page 1058 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides the most comprehensive treatment to date of microeconometrics, the analysis of individual-level data on the economic behavior of individuals or firms using regression methods for cross section and panel data. The book is oriented to the practitioner. A basic understanding of the linear regression model with matrix algebra is assumed. The text can be used for a microeconometrics course, typically a second-year economics PhD course; for data-oriented applied microeconometrics field courses; and as a reference work for graduate students and applied researchers who wish to fill in gaps in their toolkit. Distinguishing features of the book include emphasis on nonlinear models and robust inference, simulation-based estimation, and problems of complex survey data. The book makes frequent use of numerical examples based on generated data to illustrate the key models and methods. More substantially, it systematically integrates into the text empirical illustrations based on seven large and exceptionally rich data sets.
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 434 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 Large dimensional Panel Data Econometrics Testing Estimation And Structural Changes written by Feng Qu and published by World Scientific. This book was released on 2020-08-24 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims to fill the gap between panel data econometrics textbooks, and the latest development on 'big data', especially large-dimensional panel data econometrics. It introduces important research questions in large panels, including testing for cross-sectional dependence, estimation of factor-augmented panel data models, structural breaks in panels and group patterns in panels. To tackle these high dimensional issues, some techniques used in Machine Learning approaches are also illustrated. Moreover, the Monte Carlo experiments, and empirical examples are also utilised to show how to implement these new inference methods. Large-Dimensional Panel Data Econometrics: Testing, Estimation and Structural Changes also introduces new research questions and results in recent literature in this field.
Download or read book Spatial Econometrics written by J. Paul Elhorst and published by Springer Science & Business Media. This book was released on 2013-09-30 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an overview of three generations of spatial econometric models: models based on cross-sectional data, static models based on spatial panels and dynamic spatial panel data models. The book not only presents different model specifications and their corresponding estimators, but also critically discusses the purposes for which these models can be used and how their results should be interpreted.
Download or read book Nonparametric Tests for Event Studies Under Cross Sectional Dependence written by Matteo M. Pelagatti and published by . This book was released on 2013 with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt: We propose three nonparametric tests for the null of no event-induced shifts in the distribution of stock returns. One test is the natural extension of the popular Corrado rank test to the case of cross-sectionally dependent returns, while the other two are based on new ideas. Unfortunately only for one of these tests a solid theory for approximating the distribution of the statistic can be derived, but some simulation experiments confirm that normality is a good approximation also for the other two. The new tests are compared to a widely used parametric test (Patell) through simulation experiments and are shown to compare favorably in terms of power. Simulation results are based on bootstrapping daily stock returns from the S&P100 and NASDAQ indexes.
Download or read book Large Dimensional Factor Analysis written by Jushan Bai and published by Now Publishers Inc. This book was released on 2008 with total page 90 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
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 Longitudinal and Panel Data written by Edward W. Frees and published by Cambridge University Press. This book was released on 2004-08-16 with total page 492 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to foundations and applications for quantitatively oriented graduate social-science students and individual researchers.
