Learning Microeconometrics with R
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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 bachelor'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 a...
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 bachelor'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.
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.
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