GGS-Workshop: R – Causal Inference using Difference-in-Difference and Regression Discontinuity Designs

Learn when and how to apply two important methods for causal inference: Difference-in-Difference (DID) Designs and Regression Discontinuity (RD) Designs. Learn how to implement these designs using the statistical software R.

Please note:

It is required that the participants have basic R knowledge and have made their first experiences in applying R in their research projects. In particular, the participants should be familiar with the following R concepts and packages:

-          Using the Software R Studio

-          dplyr: particularly the dplyr verbs select, arrange, filter

-          ggplot2

-          Linear regression using the function lm(), including the use of formulars, factors and interactions

-          Working with lists and lists of data.frames: lapply, do.call, rbind

Further information is available on the course description "R – Causal Inference using Difference-in-Difference and Regression Discontinuity Designs".