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Titlebook: Econometric Analysis of Panel Data; Badi H. Baltagi Textbook 2021Latest edition The Editor(s) (if applicable) and The Author(s), under exc

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發(fā)表于 2025-3-21 18:06:18 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Econometric Analysis of Panel Data
編輯Badi H. Baltagi
視頻videohttp://file.papertrans.cn/302/301436/301436.mp4
概述Provides up-to-date coverage of panel data analysis.Includes several applications in economics, illustrated with Stata and EViews, highlighting the content’s practical value.Covers important topics in
叢書名稱Springer Texts in Business and Economics
圖書封面Titlebook: Econometric Analysis of Panel Data;  Badi H. Baltagi Textbook 2021Latest edition The Editor(s) (if applicable) and The Author(s), under exc
描述.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 dat
出版日期Textbook 2021Latest edition
關(guān)鍵詞Spatial panel data; Nonstationary panel data; Dynamic panel data; Panel data applications in economics;
版次6
doihttps://doi.org/10.1007/978-3-030-53953-5
isbn_ebook978-3-030-53953-5Series ISSN 2192-4333 Series E-ISSN 2192-4341
issn_series 2192-4333
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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發(fā)表于 2025-3-21 22:05:56 | 只看該作者
The Two-Way Error Component Regression Model,s specification. It also discusses maximum likelihood estimation under normality and best linear unbiased prediction. It illustrates these methods with three empirical examples. The first is an investment equation using panel data on firms. The second is a gasoline demand equation using panel data o
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發(fā)表于 2025-3-22 04:07:44 | 只看該作者
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發(fā)表于 2025-3-22 05:19:48 | 只看該作者
Heteroskedasticity and Serial Correlation in the Error Component Model,oss time and individuals. This may be a restrictive assumption for panels, where the cross-sectional units may be of varying size and as a result may exhibit different variations. For example, when dealing with gasoline demand across OECD countries, steam electric generation across various size util
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發(fā)表于 2025-3-22 10:40:59 | 只看該作者
Simultaneous Equations with Error Components,rs and the disturbances. This may be due to the omission of relevant variables, measurement error, sample selectivity, self-selection, or other reasons. Endogeneity causes inconsistency of the usual OLS estimates and requires instrumental variable (IV) methods like two-stage least squares (2SLS) to
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發(fā)表于 2025-3-22 13:09:40 | 只看該作者
Unbalanced Panel Data Models,ncomplete panels are more likely to be the norm in typical economic empirical settings. For example, in collecting data on US airlines over time, a researcher may find that some firms have dropped out of the market while new entrants emerged over the sample period observed.
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發(fā)表于 2025-3-22 20:05:21 | 只看該作者
Nonstationary Panels,s feasible. Various first generation panel unit root tests are studied. These assume cross-sectional independence and are illustrated using EViews and Stata. Next, second generation panel unit root tests are considered which allow for cross-sectional dependence. Spurious regressions and cointegratio
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