You’ve got Dreze and Sen 1989 already? That’s the touchstone for modern political economy treatments.

Yes I see that — that’s what the follow on replies were getting at.

Fair. Simmons is responding to scholars on the terms they are arguing (“anything can be significant”), whereas I’m proposing a different set of terms.

In that regard I disagree with Simmons’s claim that a study can never be “overpowered.” If the minimally meaningful effect is 10 ppt and you are powered for 1 ppt, at best you’ve wasted resources.

I teach power analysis in terms of “what is a minimally meaningful effect size? Are you powered for that?” A minimally meaningful effect size can be deduced from principles (eg cost-benefit), eliminating the kind of guesswork you mentioned.

🚨Replication alert🚨
I'm pleased to announce that my replication of Moretti (2021) is now accepted as a comment at AER.

I find ten issues in the paper. My comment focuses on two major problems; in the appendix, I document eight (relatively) minor problems.

1/

There is a theoretical literature on platform design, such as Baldwin-Clark modularity framework, that may help in thinking through the scaling challenge.

In current work in the same domain, we are looking at how to scale administration of remote learning communications to an SMS tech stack platform (with limited success).

Can Communities Take Charge? Testing Community-Based Governance to Sustain Schools in War-Affected Afghanistan | The Journal of Politics: Vol 0, No ja

A way to think about scaling, and one the Rasul doesn’t seem to pick up on, is in terms of *platforms*. Eg, in past work we’ve looked at CDD institutions as a platform for transferring administration of basic services at scale: www.journals.uchicago.edu/doi/10.1086/...

From field experiments to policy interventions at scale A major advance in recent decades in the social sciences has been the use of field experiments for causal evaluation of policy interventions. Such interventions might be targeted to individuals, house...

Useful rundown of issues in the “science of scaling” interventions, from Rasul.

www.science.org/doi/10.1126/...

Had no idea that the best data science podcast is back 😀

podcasts.apple.com/us/podcast/l...

What?? Very exciting!

Battery life?

A solution could be to legislate authority away from that post. But this is a complicated coordination problem.

The regime rules through institutions, but over the years of Khamenei’s leadership the institutions were organized in a way that concentrated authority in his office. Now there is trepidation about appointing someone to a post with such concentrated authority.

Ayatollah Khamenei’s Deadly Legacy Pegah Banihashemi thinks Ayatollah Ali Khamenei’s death will bring meaningful change only if his governing framework is dismantled.

Good analysis of the institutional conundrum facing the Iranian leadership after Khamenei’s death: www.project-syndicate.org/commentary/k...

If you are looking for a way to do something meaningful amidst the current events, I’ll suggest again for you to just sit and watch “It Was Just an Accident.”

Yes 🙌

Re the age of AI issues, we do a lot of pen and paper work in class now. I want to see that students can at least get started on mapping out formal analyses using potential outcomes, DAGs, etc and probability/asymptotic operations.

You’re right re Rosenbaum. I tend to stay in the Neymanian framework. That said I particularly appreciate Rosenbaum’s insights in evidence factors and nested testing.

Yes that is very much my inferential foundation.

In all seriousness though, I’m rarely (not never, but rarely) convinced that identification strategies like IV, DID, or RD get us *all the way* to our target quantities. So modeling with covariates comes in to play more than Mostly Harmless teaches.

Excellent. Let’s see if we can arrange a talk. I’ll reach out when we are closer to when I’ll be discussing this.

I had also done extended DID lectures, following the frenzy of papers. I will condense that too, getting quickly to the counterfactual estimation perspective and trajectory balancing, and open up space for g computation. Aside from IV, we are nearing full “post Mostly Harmless.”

Update to my Quant 2 course: I used to do an Angrist and Pischke style discussion of regression models and treatment effects. Dumped that (or actually made it a recitation/review), brought in double machine learning instead. cyrussamii.com?page_id=4190

“Affective polarization” is a lot of syllables when the word “hate” is right there.

For anyone looking for postdocs for their students, over the next few months LSE “fellow” positions will start being listed. Research + teaching but 2-3 year runway.

The new Global School of Sustainability has 5 new ones posted now! jobs.lse.ac.uk/Vacancies/W/...

Seems it is still going strong so if you email the folks at SIWPS they’d probably have it to share: www.siwps.org/programs/sum...

Excited to see this out. The paper was a huge lift. If you’d be surprised that citizen empowerment *increases* the share that pay taxes in a place like Kinshasa, check out the details in Soeren’s thread.

This will be chapter 1 in my regression textbook.