Indira Gandhi National Tribal University, Amarkantak

Prof. Ram Dayal Munda Central Library

Online Public Access Catalogue

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Panel data econometrics with R / Yves Croissant, Giovanni Millo.

By: Contributor(s): Material type: TextTextPublisher: Hoboken, NJ : John Wiley & Sons, 2018Edition: First editionDescription: 1 online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781118949177
  • 111894917X
  • 9781118949184
  • 1118949188
  • 9781119504641
  • 1119504643
Subject(s): Genre/Form: Additional physical formats: Print version:: Panel data econometrics with R.DDC classification:
  • 330.0285/5133 23
LOC classification:
  • HB139
Online resources:
Contents:
The Error Component Model -- Advanced Error Components Models -- Tests on Error Component Models -- Robust Inference and Estimation for Non-spherical Errors -- Endogeneity -- Estimation of a Dynamic Model -- Panel Time Series -- Count Data and Limited Dependent Variables -- Spatial Panels.
Summary: 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.
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The Error Component Model -- Advanced Error Components Models -- Tests on Error Component Models -- Robust Inference and Estimation for Non-spherical Errors -- Endogeneity -- Estimation of a Dynamic Model -- Panel Time Series -- Count Data and Limited Dependent Variables -- Spatial Panels.

Includes index.

Print version record and CIP data provided by publisher; resource not viewed.

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.

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