Happy participants spend $1.20 more on average. Say that in an experiment, participants are put in a happy vs sad mood and then they go shopping. Let's get a sense of how randomization tests work. Randomization tests are often attributed to Ronald Fisher, which is why the QJE paper's title begins with ' Channeling Fisher', but this footnote explains why that may not be quite right. Then I describe my re-analysis of the QJE paper.ДЄll scripts and files for this post are available from

In what follows I briefly explain randomization tests, then briefly explain the need for robust standard errors. Randomization is not superior, Stata's default is inferior.

htm), the supposed superiority of the randomization test goes away. I n contrast, when regression results are computed using the default setting in R, a setting that's also available in Stata, a setting shown over 20 years ago to be more appropriate than the one used by Stata (Long & Ervin 2000. In this post I show that this conclusion only holds when relying on an unfortunate default setting in Stata. is superior to all other methods ' (p.585). ' show the clear advantages of randomization inference. To get correct p-values, the article explains, they need to run, instead of regressions, something called 'randomization tests' (I briefly describe randomization tests in the next subsection). It delivers bad news to economists running experiments: their p-values are wrong. htm) is currently the most cited 2019 article in the Quarterly Journal of Economics (372 Google cites). The paper titled ' Channeling Fisher: Randomization Tests and the Statistical Insignificance of Seemingly Significant Experimental Results' (.

Cluster standard errors stata