About Me Blog
Dealing with heteroskedasticity; regression with robust standard errors using R Forecasting my weight with R Getting data from pdfs using the pdftools package Imputing missing values in parallel using {furrr} Missing data imputation and instrumental variables regression: the tidy approach {pmice}, an experimental package for missing data imputation in parallel using {mice} and {furrr} Building formulae Functional peace of mind Get basic summary statistics for all the variables in a data frame Getting {sparklyr}, {h2o}, {rsparkling} to work together and some fun with bash Importing 30GB of data into R with sparklyr Introducing brotools It's lists all the way down It's lists all the way down, part 2: We need to go deeper Keep trying that api call with purrr::possibly() Lesser known dplyr 0.7* tricks Lesser known dplyr tricks Lesser known purrr tricks Make ggplot2 purrr Mapping a list of functions to a list of datasets with a list of columns as arguments Predicting job search by training a random forest on an unbalanced dataset Teaching the tidyverse to beginners Why I find tidyeval useful tidyr::spread() and dplyr::rename_at() in action Easy peasy STATA-like marginal effects with R Functional programming and unit testing for data munging with R available on Leanpub How to use jailbreakr My free book has a cover! Work on lists of datasets instead of individual datasets by using functional programming Method of Simulated Moments with R New website! Nonlinear Gmm with R - Example with a logistic regression Simulated Maximum Likelihood with R Bootstrapping standard errors for difference-in-differences estimation with R Careful with tryCatch Data frame columns as arguments to dplyr functions Export R output to a file I've started writing a 'book': Functional programming and unit testing for data munging with R Introduction to programming econometrics with R Merge a list of datasets together Object Oriented Programming with R: An example with a Cournot duopoly R, R with Atlas, R with OpenBLAS and Revolution R Open: which is fastest? Read a lot of datasets at once with R Unit testing with R Update to Introduction to programming econometrics with R Using R as a Computer Algebra System with Ryacas

Introduction to programming econometrics with R

This semester, I’ll be teaching an introduction to applied econometrics with R, so I’ve decided to write a very small book called “Introduction to programming Econometrics with R”. This is primarily intended for bachelor students and the focus is not much on econometric theory, but more on how to implement econometric theory into computer code, using the R programming language. It’s very basic and doesn’t cover any advanced topics in econometrics and is intended for people with 0 previous programming knowledge. It is still very rough around the edges, and it’s missing the last chapter about reproducible research, and the references, but I think it’s time to put it out there; someone else than my students may find it useful. The book’s probably full of typos and mistakes, so don’t hesitate to drop me an e-mail if you find something fishy: contact@brodrigues.co

Also there might be some sections at the beginning that only concern my students. Just ignore that.

Get it here: download

Update (2017-01-22)

You might find the book useful as it is now, but I never had a chance to finish it. I might get back to it once I’ll have more time, and port it to bookdown.