Econometrics of Panel Data 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024


Econometrics of Panel Data

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Erik Biørn 作者
Oxford University Press
译者
2016-11-27 出版日期
416 页数
USD 90.00 价格
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丛书系列
9780198753445 图书编码

Econometrics of Panel Data 在线电子书 图书标签: Econometrics   


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发表于2024-11-14


Econometrics of Panel Data 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Econometrics of Panel Data 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Econometrics of Panel Data 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024



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Econometrics of Panel Data 在线电子书 著者简介

Erik Biørn is Professor Emeritus at the University of Oslo. From 1986 to 2014 he taught econometrics at all levels at this university. Previously he was a researcher at Statistics Norway. His publications include several articles on empirical and theoretical topics in panel data analysis, and the book Taxation, Technology, and the User Cost of Capital (1989, Elsevier).


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Econometrics of Panel Data 在线电子书 pdf 下载 txt下载 epub 下载 mobi 在线电子书下载

Econometrics of Panel Data 在线电子书 图书描述

Panel data is a data type increasingly used in research in economics, social sciences, and medicine. Its primary characteristic is that the data variation goes jointly over space (across individuals, firms, countries, etc.) and time (over years, months, etc.). Panel data allow examination of problems that cannot be handled by cross-section data or time-series data. Panel data analysis is a core field in modern econometrics and multivariate statistics, and studies based on such data occupy a growing part of the field in many other disciplines.

The book is intended as a text for master and advanced undergraduate courses. It may also be useful for PhD-students writing theses in empirical and applied economics and readers conducting empirical work on their own. The book attempts to take the reader gradually from simple models and methods in scalar (simple vector) notation to more complex models in matrix notation. A distinctive feature is that more attention is given to unbalanced panel data, the measurement error problem, random coefficient approaches, the interface between panel data and aggregation, and the interface between unbalanced panels and truncated and censored data sets. The 12 chapters are intended to be largely self-contained, although there is also natural progression.

Most of the chapters contain commented examples based on genuine data, mainly taken from panel data applications to economics. Although the book, inter alia, through its use of examples, is aimed primarily at students of economics and econometrics, it may also be useful for readers in social sciences, psychology, and medicine, provided they have a sufficient background in statistics, notably basic regression analysis and elementary linear algebra.

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