Chapter 12 Next Steps

If you read this far, thank you! I put in a lot of work into writing this book, and I’m hopeful that the combination of econometrics, R, bad jokes, and memes was valuable to you.

While this book may have been heavy on memes and building intuition, I am aware that it is fairly light in a number of areas as well. It was, after all, a book designed for a single semester of a college course, so some things definitely needed to be cut.

With respect to R, the focus was almost entirely on data analysis, with little emphasis on programming or data wrangling. On the econometric side, there was very little math, almost no calculus, and no proofs. There was little emphasis on contemporary issues in causality, natural experiments, and the like.

For the interested reader, this short chapter presents a set of resources that I would suggest should be your next steps if you want to further your knowledge of the material in this book.

12.1 More R

One of the great things about R is that it is open source. One of the other great things about R is that people who write books about R usually do them in open source as well. Here is a short list of outstanding resources:

  • R for Data Science - Written by Hadley Wickham and Garrett Grolemund, this is an outstanding general intro to R.

  • ggplot2: Elegant Graphics for Data Analysis - Another book by hadley Wickham, this is essentially the ggplot2 bible.

  • R Markdown: The Definitive Guide - Yihui Xie, J.J. Allaire, and Garrett Grolemund authored this guide to R Markdown; Yihui Xie and J.J. Allaire are RStudio engineers who wrote R Markdown, so this is another outstanding reference. I’ve had students in the past who decided to switch from MS Word to using R Markdown for all of their classwork!

  • bookdown: Authoring Books and Technical Documents with R Markdown - Yihui Xie wrote the bookdown package, he wrote the book about the bookdown package, he used the bookdown package to write the book about the bookdown package … you see where this is going. If you are interested in writing lengthier stuff using R Markdown, go here.

12.2 More Econometrics

If you are interested in graduate studies in economics, you will need a more mathematically intensive introduction to econometrics. I’ll group these resources into a few categories.

To my knowledge, these are the major players in the world of undergraduate-level textbooks:

  • Introductory Econometrics: A modern Approach - Jeffery Wooldridge

  • Basic Econometrics: Damodar Gujarati

  • Introduction to Econometrics - Stock and Watson

A decent hybrid R and undergraduate Econometrics text:

For graduate-level textbooks, we are looking at:

  • Econometric Analysis - William Greene

  • Microeconometrics - Cameron and Trivedi

  • Econometrics - Fumio Hayashi

Moving on, one of the best books for developing intuition:

  • A Guide to Econometrics - Peter Kennedy

Finally, a few books on more modern notions of causal inference that are very important reads for individuals interested in graduate studies:

12.3 The End

Couldn’t end without one more meme.