Learning microeconometrics with R
Author(s)
Bibliographic Information
Learning microeconometrics with R
(The R series)(A Chapman & Hall book)
CRC Press, 2021
- : hbk
Available at 30 libraries
  Aomori
  Iwate
  Miyagi
  Akita
  Yamagata
  Fukushima
  Ibaraki
  Tochigi
  Gunma
  Saitama
  Chiba
  Tokyo
  Kanagawa
  Niigata
  Toyama
  Ishikawa
  Fukui
  Yamanashi
  Nagano
  Gifu
  Shizuoka
  Aichi
  Mie
  Shiga
  Kyoto
  Osaka
  Hyogo
  Nara
  Wakayama
  Tottori
  Shimane
  Okayama
  Hiroshima
  Yamaguchi
  Tokushima
  Kagawa
  Ehime
  Kochi
  Fukuoka
  Saga
  Nagasaki
  Kumamoto
  Oita
  Miyazaki
  Kagoshima
  Okinawa
  Korea
  China
  Thailand
  United Kingdom
  Germany
  Switzerland
  France
  Belgium
  Netherlands
  Sweden
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  United States of America
Note
Includes bibliographical references (p. 357-362) and indexes
Description and Table of Contents
Description
Focuses on the assumptions underlying the algorithms rather than their statistical properties
Presents cutting-edge analysis of factor models and finite mixture models.
Uses a hands-on approach to examine the assumptions made by the models and when the models fail to estimate accurately
Utilizes interesting real-world data sets that can be used to analyze important microeconomic problems
Introduces R programming concepts throughout the book.
Includes appendices that discuss many of the concepts introduced in the book, as well as measures of uncertainty in microeconometrics.
Table of Contents
I. Experiments.
1. Ordinary Least Squares.
2. Multiple Regression.
3. Instrumental Variables
4. Bounds Estimation.
II. Structural Estimation.
5. Estimating Demand.
6. Estimating Selection Models.
7. Demand Estimation with IV
8. Estimating Games.
9. Estimating Auction Models
III. Repeated Measurement.
10. Panel data.
11. Synthetic Controls.
12. Mixture Models.
IV. Appendices.
A. Measuring Uncertainty.
B. Statistical Programming in R
Acknowledgements
Bibliography
by "Nielsen BookData"