I had a few hours of free time this weekend, which I used to read a new working paper by Abadie et al. (2017) titled “When Should You Adjust Standard Errors for Clustering?” I’m a little bit late to the party–David McKenzie blogged about this almost a full month ago–but doing all of my teaching in one semester leaves me considerably behind on reading new papers, which then leaves me behind on blogging.
This is a very nice paper, and it has seriously changed my understanding of clustering. Abadie et al. start with two common misconceptions regarding clustering:
- Clustering matters only if the residuals and the regressors are both correlated within clusters, and
- If clustering makes a difference in your standard errors, you should cluster.