Happy to see our paper "The Choice of Control Variables: How Causal Graphs Can Inform the Decision" (w/ @beyers_louw & M. Rönkkö) included in the best paper proceedings of the 82nd Annual Meeting of the Academy of Management. #AOM2022 @AOMConnect journals.aom.org/doi/epdf/10.54… 1/5
We present practical recommendations on how to choose suitable control variables for regression analyses – a topic which seems to cause quite some confusion in the management literature (if you ever read the phrase "if in doubt leave out" you know what I'm talking about). 2/5 Image
The best paper proceedings include abridged versions (max. 6 pages) of selected papers that will be presented at #AOM2022. Our session (#1088) is scheduled for Aug 8 2022 from 8:00AM to 9:30AM local Seattle time. You are all very welcome to join! 3/5 Image
The taxonomy of controls I showed above borrows heavily from this excellent paper by @analisereal, A. Forney & @yudapearl: journals.sagepub.com/doi/full/10.11… In the final paper, which we will hopefully be able to submit soon, we go deeper into the topic of how you can actually .. 4/5
.. come up with a causal diagram for your research setting. We demonstrate this process with the help of a concrete example that we hope will provide valuable guidance to applied researchers who want to brush up on their causal inference skills. Stay tuned. 5/5 Image

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More from @PHuenermund

Jul 12
Jetzt kann man natürlich der Meinung sein, dass es keine gute Sache ist, wenn Professor:innen so viel nebenbei machen. Für den Wissenstransfer muss das aber gar nicht so schlecht sein. 🧵 1/9
Eine interessante Fallstudie dazu liefert die Abschaffung des sogenannten "Professorenprivilegs" in 2002. Mein ehemaliger Advisor an der KU Leuven, Dirk Czarnitzki, hat dazu ein interessantes Papier. papers.ssrn.com/sol3/papers.cf… 2/9 Image
Das Professorenprivileg erlaubte es Lehrstuhlinhabern, anders als anderen Angestellten nach dem deutschen Erfindergesetz, über die Vermarktung von Erfindungen die während der Ausführung der beruflichen Tätigkeit gemacht werden, frei zu entscheiden. 3/9 Image
Read 9 tweets
Jun 24
This is my favorite teaching example for showing the importance of #CausalInference: @Google conducts an annual pay equity analysis in which they use fairly advanced statistical techniques. In 2019 they found that they were actually underpaying MEN?! npr.org/2019/03/05/700… 1/ Image
What do they do specifically? They collect a lot of data (as Google does) and then run OLS regressions of annual compensation on demographic variables (gender, race) and other explanatory variables such as tenure, location, and performance. services.google.com/fh/files/blogs… 2/ Image
If they find statistically meaningful differences, @Google is actually committed to make upward adjustments for the disadvantaged groups. In this case it was male, level-4 software engineers who got a raise. 3/ Image
Read 13 tweets

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