Panel Data Analysis Using EViews

Panel Data Analysis Using EViews

Editor(s): I Gusti Ngurah Agung

Published Online: 20 DEC 2013

Print ISBN: 9781118715581

Online ISBN: 9781118715543

DOI: 10.1002/9781118715543

About this Book

A comprehensive and accessible guide to panel data analysis using EViews software

This book explores the use of EViews software in creating panel data analysis using appropriate empirical models and real datasets. Guidance is given on developing alternative descriptive statistical summaries for evaluation and providing policy analysis based on pool panel data. Various alternative models based on panel data are explored, including univariate general linear models, fixed effect models and causal models, and guidance on the advantages and disadvantages of each one is given.

Panel Data Analysis using EViews:

  • Provides step-by-step guidance on how to apply EViews software to panel data analysis using appropriate empirical models and real datasets.  
  • Examines a variety of panel data models along with the author's own empirical findings, demonstrating the advantages and limitations of each model.
  • Presents growth models, time-related effects models, and polynomial models, in addition to the models which are commonly applied for panel data.
  • Includes more than 250 examples divided into three groups of models (stacked, unstacked, and structured panel data), together with notes and comments.
  • Provides guidance on which models not to use in a given scenario, along with advice on viable alternatives.
  • Explores recent new developments in panel data analysis

An essential tool for advanced undergraduate or graduate students and applied researchers in finance, econometrics and population studies.  Statisticians and data analysts involved with data collected over long time periods will also find this book a useful resource.

Table of contents

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  1. Part One: Panel Data as a Multivariate Time Series by States

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  2. Part Two: Pool Panel Data Analysis

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  3. Part Three: Balanced Panel Data as Natural Experimental Data

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