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

By: Croissant, Yves, 1969- [author.]Contributor(s): Millo, Giovanni, 1970- [author.]Material type: TextTextPublication details: First edition. ; Hoboken, NJ : John Wiley & Sons, 2018Description: 1 online resourceISBN: 9781118949177; 111894917X; 9781118949184; 1118949188; 9781119504641; 1119504643Subject(s): Econometrics | Panel analysis | R (Computer program language) | Econometrics | Panel analysis | R (Computer program language) | MATHEMATICS / Probability & Statistics / GeneralOnline resources: Wiley Online Library
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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Item type Current library Call number Status Date due Barcode Item holds
e-Books e-Books Central Library, Sikkim University
Not for loan E-2692
Total holds: 0

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.

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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