Using R for Introductory Econometrics - Tapa blanda

Reseña del editor

• Introduces the popular, powerful and free programming language and software package R
• Focus: implementation of standard tools and methods used in econometrics
• Compatible with "Introductory Econometrics" by Jeffrey M. Wooldridge in terms of topics, organization, terminology and notation
• Companion website with full text, all code for download and other goodies

Praise:

• "A very nice resource for those wanting to use R in their introductory econometrics courses." (Jeffrey M. Wooldridge)
• Using R for Introductory Econometrics is a fabulous modern resource. I know I'm going to be using it with my students, and I recommend it to anyone who wants to learn about econometrics and R at the same time." (David E. Giles in his blog "Econometrics Beat")

Topics:

• A gentle introduction to R
• Simple and multiple regression in matrix form and using black box routines
• Inference in small samples and asymptotics
• Monte Carlo simulations
• Heteroscedasticity
• Time series regression
• Pooled cross-sections and panel data
• Instrumental variables and two-stage least squares
• Simultaneous equation models
• Limited dependent variables: binary, count data, censoring, truncation, and sample selection
• Formatted reports and research papers combining R with R Markdown or LaTeX

Reseña del editor

"A very nice resource for those wanting to use R in their introductory econometrics courses." (Jeffrey M. Wooldridge)

"Using R for Introductory Econometrics is a fabulous modern resource. I know I'm going to be using it with my students, and I recommend it to anyone who wants to learn about econometrics and R at the same time." (David E. Giles in his blog "Econometrics Beat")

This book introduces the popular, powerful and free programming language and software package R with a focus on the implementation of standard tools and methods used in econometrics. Unlike other books on similar topics, it does not attempt to provide a self-contained discussion of econometric models and methods. Instead, it builds on the excellent and popular textbook “Introductory Econometrics” by Jeffrey M. Wooldridge. It is compatible in terms of topics, organization, terminology and notation, and is designed for a seamless transition from theory to practice.

The first chapter provides a gentle introduction to R, covers some of the topics of fundamental statistics and probability, and introduces Monte Carlo simulation as an additional tool. The other chapters have the same names and cover the same material as the respective chapters in Wooldridge’s textbook. Assuming the reader has worked through the material discussed there, this book explains and demonstrates how to implement everything in R and replicates many textbook examples. We also open some black boxes of the built-in functions for estimation and inference by directly applying the formulas known from the textbook to reproduce the results. Some supplementary analyses provide additional intuition and insights.

The book is designed mainly for students of introductory econometrics who ideally use Wooldridge’s “Introductory Econometrics” as their main textbook. It can also be useful for readers who are familiar with econometrics and possibly other software packages, such as Stata. For them, it offers an introduction to R and can be used to look up the implementation of standard econometric methods.

All computer code used in this book can be downloaded to make it easier to replicate the results and tinker with the specifications.