JonasSend / RTutorTopIncomeTaxation

RTutor problem set based on the paper "Optimal Taxation of Top Labor Incomes: A Tale of Three Elasticities" by Thomas Piketty, Emmanuel Saez and Stefanie Stantcheva (2014); Developed in the course of my bachelor thesis, Implemented with the R package "RTutor" (see https://github.com/skranz/RTutor). Also available as online version https://jonassend.shinyapps.io/RTutorTopIncomeTaxation/

Geek Repo:Geek Repo

Github PK Tool:Github PK Tool

Author: Jonas Send

In their paper "Optimal Taxation of Top Labor Incomes: A Tale of Three Elasticities" Thomas Piketty, Emmanuel Saez and Stefanie Stantcheva (2014) analyse the response of top earners to taxes and derive optimal tax rate formulas from their findings. In this interactive offline R Tutorial, we are going to gradually reproduce their study and discuss it.

1. Installation

To install RTutor and this problem set, run in R the code:

if (!require(devtools))
  install.packages("devtools")
source_gist("gist.github.com/skranz/fad6062e5462c9d0efe4")
install.rtutor(update.github=TRUE)
  
install_github("JonasSend/RTutorTopIncomeTaxation")

2. Show and work on the problem set

To start the problem set first pick a directory in which you want to store files related to the problem set and your solution. Then adapt and run the following code.

library(RTutorTopIncomeTaxation)

# Adapt your working directory to an existing folder
setwd("C:/problemsets")
# Adapt your user name
run.ps(user.name="Jon Doe", package="RTutorTopIncomeTaxation")
       

If everything works fine, a browser window should open, in which you can start exploring the problem set.

About

RTutor problem set based on the paper "Optimal Taxation of Top Labor Incomes: A Tale of Three Elasticities" by Thomas Piketty, Emmanuel Saez and Stefanie Stantcheva (2014); Developed in the course of my bachelor thesis, Implemented with the R package "RTutor" (see https://github.com/skranz/RTutor). Also available as online version https://jonassend.shinyapps.io/RTutorTopIncomeTaxation/


Languages

Language:R 100.0%