At which level should one cluster standard errors? What's good empirical practice? Have you ever heard about placebo regressions in this context? Here is a very useful guide that was recently published in the JoE doi.org/10.1016/j.jeco…. 🧵 with a short summary. #EconTwitter 1/9 The general idea is of course that we divide the sample into clusters and that we allow for heteroskedasticity/dependence within clusters while assuming independence across clusters. 2/9

We have a new working paper on the dependence of search result quality on the amount of user-generated data. This picture here shows the main result. Let me explain. 🧵1/14 The central question we answer is: Do some search engines produce better search results because their algorithm is better, or because they have access to more data from past searches? 2/14

#EconTwitter: we need your help. We're doing a research project on online ratings. We're interested in how people interpret them.

For this, we have set up a very short survey, which we are currently piloting (just to make sure it all makes sense). 1/4 It would be absolutely fantastic if many of you could take a couple of minutes and answer our 4 short questions. 2/4

#EconTwitter: this is really useful advice by Neale Mahoney for those who want to write an applied economics paper 📝

just came out in JEP

pubs.aeaweb.org/doi/pdfplus/10…

In the following mini 🧵 I summarize his 5 ✅ principles The 5 principles are:
✅ show your variation with descriptive analysis
✅ use the descriptive evidence to provide preliminary evidence
✅ use the descriptive analysis to guide choices of what you model (and not model)
✅ clearly articulate the value added of the model and …

#EconTwitter:
I wish I had seen this one-pager 📄 on how to write excellent papers while I was doing my Ph.D.: scholar.harvard.edu/files/shapiro/…
Jesse Shapiro suggests doing this in 4 steps.
Here is a summary. 🧵 Step 1:
dream up a somewhat realistic introduction with a description of results and so on
if it does not excite you, abandon the project (very! important advice)