Learning microeconometrics with R
Adams, Christopher P.
creator
Chambers, John M.
Series Editor
Hothorn, Torsten
Series Editor
Lang, Duncan Temple
Series Editor
Wickham, Hadley
Series Editor
text
Boca Raton
CRC Press
2021
monographic
| 0
xxx, 368 p. Includes index and bibliographic references
This book provides an introduction to the field of microeconometrics through the use of R. The focus is on applying current learning from the field to real world problems. It uses R to both teach the concepts of the field and show the reader how the techniques can be used. It is aimed at the general reader with the equivalent of a bachelorâ€™s degree in economics, statistics or some more technical field. It covers the standard tools of microeconometrics, OLS, instrumental variables, Heckman selection and difference in difference. In addition, it introduces bounds, factor models, mixture models and empirical Bayesian analysis.
Key Features:
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 some of the standard statistical concepts and R programming used in the book
https://www.taylorfrancis.com/books/mono/10.1201/9780429288333/learning-microeconometrics-christopher-adams
Table of contents
Introduction
Part Part I
Experiments
Chapter 1|
Ordinary Least Squares
Chapter 2|
Multiple Regression
Chapter 3|
Instrumental Variables
Chapter 4|
Bounds Estimation
Part Part II|
Structural Estimation
Chapter 5|
Estimating Demand
Chapter 6|
Estimating Selection Models
Chapter 7|
Demand Estimation with IV
Chapter 8|
Estimating Games
Chapter 9|
Estimating Auction Models
Part Part III|
Repeated Measurement
Chapter 10|
Panel Data
Chapter 11|
Synthetic Controls
Chapter 12|
Mixture Models
Econometrics
Statistics - Computer programs
R - Computer program language
338.5015195 A2L3
Chapman & Hall/CRC the R series
9780367255381
210722