原版著作及note 买原著送note
名称1：Panel Data Econometrics
general editor：Manuel arellano， Guido imbens，mark Watson
advisory editor： C.W.J. Granger
出版社：Oxford university press
大小：22.5mb
格式：pdf
Manuel Arellano
[url=http://ukcatalogue.oup.com/category/academic/series/economics/ate.do]Advanced Texts in Econometrics[/url]
256 pages | 1 figure and numerous tables | 234x156mm
978-0-19-924529-1 | Paperback | 26 June 2003
Also available as:
Hardback
Price: £21.00
简介 · · · · · · Panel data econometrics uses both time series and cross-sectional data sets that have repeated observations over time for the same individuals (individuals can be workers, households, firms, industries, regions, or countries). This book reviews the most important topics in the subject. The three parts, dealing with static models, dynamic models, and discrete choice and related models are organized around the themes of controlling for unobserved heterogeneity and modelling dynamic responses and error components.
- Panel Data analysis is becoming increasingly important in econometrics
- Relatively few exisiting texts in this field
- Internationally known and respected author
This book, by one of the world's leading experts on dynamic panel data, presents a modern review of some of the main topics in panel data econometrics. The author concentrates on linear models, and emphasizes the roles of heterogeneity and dynamics in panel data modelling. The book combines methods and applications, so will appeal to both the academic and practitioner markets.
The book is divided in four parts. Part I concerns static models, and deals with the problem of unobserved heterogeneity and how the availability of panel data helps to solve it, error component models, and error in variables in panel data.
Part II looks at time series models with error components. Its chapters deal with the problem of distinguishing between unobserved heterogeneity and individual dynamics in short panels, modelling strategies of time effects, moving average models, inference from covariance structures, the specification and estimation of autoregressive models with heterogeneous intercepts, and the impact of assumptions about initial conditions and heteroskedacity on estimation.
Part III examines dynamics and predeterminedness. Its two chapters consider alternative approaches to estimation from small and large T perspectives, looking at models with both strictly exogenous and lagged dependent variables allowing for autocorrelation of unknown form, models in which the errors are mean independent of current and lagged values of certain conditioning variables but not with their future values.
Together Parts II and III provide a synthesis, and unified perspective, of a vast literature that has had a significant impact on recent econometric practice. Part IV reviews the main results in the theory of generalized method of moments estimation and optimal instrumental variables.
Readership: Researchers and graduate students of econometrics. Applied researchers in government and industry.
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目录：
1 introduction
第一篇static models
2 unobserved heterogeneity
3 error component
4error invariables
第二篇 time series models with error components
5 covariance structures for dynamic error components
6autoregression models with individual effects
第三篇dynamics and predertermindness
7 models with both strictly exogenous and lagged dependent
8 predetermined variables
附录
a generalized method of moments estimation
optimal instructions inconditional model
名称2：Note on Panel Data Econometrics
格式：pdf
大小：250k
作者：Sebastian Buhai（Tinbergen Institute and Erasmus University Rotterdam;）
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