Rachel Leah Childers
@donskerclass.bsky.social
2.3K followers 360 following 500 posts
Econometrics, Statistics, Computational Economics, etc University of Zurich http://donskerclass.github.io 🇺🇲 in 🇨🇭. 🏳️‍⚧️
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donskerclass.bsky.social
For the Spring semester, I am restarting my free weekly open office-hours for anyone in the world with Econometrics questions. Wednesdays 10-12AM Eastern or by appointment; sign up and drop by!

Details and sign up at donskerclass.github.io/OfficeHours....
Free Weekly Econometrics Office Hours

Email: rachelleahchilders@gmail.com or Sign up form: https://forms.gle/XS55FASiGGHqAZKa6

Time: Wednesdays 10:00-12:00AM Eastern US (or by appointment)

Location: Zoom Link https://bowdoin.zoom.us/j/96039587180

Who: Anyone. Grad students, researchers, government workers. Private sector is okay but in that case if your question requires work that exceeds the allotted time I may request to negotiate a consulting fee.

What I can probably help with: Theory questions. Research design. Modeling.

Particular expertise: Time series. Causal inference. Bayes. Structural approaches. Machine learning.

Theory: Asymptotics. Statistical learning. Bayes/MCMC. Identification. Decision theory. Semiparametrics.

Fields: I know most about macro (DSGE, heterogeneous agents, VARs, etc), but can follow along in applied micro (labor, development, health, etc) & some finance.

Code: I think in R, can write Julia, and can get by in Python. I am likely to suggest you build a model in Stan. I know Stata but if it’s relevant to your question I suspect you can get better help elsewhere.
donskerclass.bsky.social
Dynamic investment under rational expectations: Yale preparing press materials in advance for Sveriges Riksbank season.
yaleeconomics.bsky.social
To celebrate Professor Steve Berry and his lifetime of accomplishments, we interviewed many colleagues and students and wrote about the lasting impact of his work, in the words of those who know him best: tobin.yale.edu/news/250930/...
The Lasting Impact of Steve Berry’s Work — Through the Eyes of Colleagues and Students
tobin.yale.edu
donskerclass.bsky.social
I’m still partial to heavy-tailed priors in many applications, which can approximate sparsity, but existing evidence and plausible models don’t support many exact 0s. doi.org/10.3982/ECTA...
Economic Predictions with Big Data: The Illusion of Sparsity - The Econometric Society
doi.org
donskerclass.bsky.social
Disagree about people not proposing competing ideas to KL divergence. I was once flown out for a talk specifically so that Florian Gunsilius could spend a day evangelizing Wasserstein distances to me. I'm not yet a card-carrying member of the Optimal Transport cult, but compelling points were made.
donskerclass.bsky.social
L^∞ is just sup norm, which is cursed because it may not be measurable or well-defined and can be a pain to bound.
Most of my PhD thesis was about extending results from Frobenius norm to operator norm (the L^∞ of Schatten norms). Frobenius makes perturbation very easy if you can show it's finite.
donskerclass.bsky.social
I've been at this a long time....
Tweet from Rachel Leah Childers, @donskerclass

Favorite Banach spaces, ranked (partial order): W^k_2, Cameron-Martin space (any), L^2, L^∞, L^p (2<p<∞), W^k_p,..., L^1, L^p (1<p<2)

9:18 PM, August 27, 2015

Ranking does not necessarily reflect current views of the author. Apologies due to L^1 and their friends and loved ones....
donskerclass.bsky.social
Drop your favorite distances. Lately I've been thinking about Fisher-Rao divergence (not a distance), Kernel Stein Discrepancy, L^∞ (cursed, evil), etc.
donskerclass.bsky.social
For today's meeting of the UZH ML+Macro Finance reading group, I read about Forward-Backward Stochastic Differential Equations. Among other things, these allow for a stochastic version of Pontryagin's maximum principle for optimal control along a path.
Some notes I made explaining how they work:
donskerclass.github.io
donskerclass.bsky.social
This post by Nan Jiang, nanjiang.cs.illinois.edu/2025/09/29/p... who knows more about RL theory than I ever will, on gaps in standard justifications for Policy Gradient, reassures me as I go through the PG lectures in interactive-learning-algos.github.io that its use is indeed a bit weird.
Office meme from Nan Jiang blog post
Frame 1: Two cards reading "policy gradient with 100 tweaks" and "policy gradient with another different 100 tweaks", respectively. "Corporate needs you to find the differences between this picture and this picture." 
Frame 2: Pam Office: "They're the same picture"
donskerclass.bsky.social
I remember feeling like I needed to hide it even though it would be years until I was self-aware enough to know why.

Pictured: my entire self-justification for watching every show or movie about trans people I could find as a teen:
marge simpson from the simpsons is holding a potato and saying i just think they 're neat
Alt: Pictured: Marge Simpson from the Simpsons is holding a potato and saying "I just think they're neat"
media.tenor.com
donskerclass.bsky.social
Eh, ok fine.
Hi @gabbiegibson.bsky.social! There is a large crowd of women here who saw a clip from your documentary and seem to like you quite a lot.
donskerclass.bsky.social
I found her @, and she seems to be doing fine, but it seems invasive to tag her even to let her know how many people think she's incredibly cool...
donskerclass.bsky.social
It was pretty much literally just that. It was a documentary where they followed 4 random college students and had them talk about being trans. 2005 was a different world… en.m.wikipedia.org/wiki/TransGe...
TransGeneration - Wikipedia
en.m.wikipedia.org
donskerclass.bsky.social
Core memory unlocked! I had this show DVRed as a teenager and watched it when my parents weren't home. I had totally forgotten about the dancing bit but can assure you that DDR was huge with the trans girls I knew around 2003-2004...
donskerclass.bsky.social
Sounds pretty standard. The author list on that new book looks very promising! You didn't hear it from me, but these dynamic methods have been much more empirically successful for social-insurance style questions (your forté anyway) than for business cycles, so I'd focus more on those chapters.
donskerclass.bsky.social
Nice! What textbook/materials are you using? I’ve found Stachurski johnstachurski.net/edtc to be much cleaner and simpler than the Stokey-Lucas/Ljungqvist-Sargent tomes I used around that era, but there are a lot of good intros nowadays. Is there a particular macro topic you’re targeting?
donskerclass.bsky.social
On Halley, I'm reminded of Cosma's old post on whether Copernicus should have used AIC or the LASSO bactra.org/weblog/922.h...
Ockham Workshop, Day 2
bactra.org
donskerclass.bsky.social
Agreed, though the word "parsimonious" is just as slippery as "overfitting". I like to operationalize it using entropy integrals, but for some reason this makes philosophers of science's eyelids twitch.
donskerclass.bsky.social
In the context of probability theory, these are distinct based on whether we maintain the assumption of a common distribution; Ben, not a fan of probability models, clearly does not like that distinction www.argmin.net/p/thou-shalt...
I'm ok with it but teach them as views of the same phenomenon:
Sample Selection and External Validity
donskerclass.github.io
donskerclass.bsky.social
There's nothing wrong with benchmarks, but taking them as the only paradigm is a bit limiting.
How temporally unstable are the laws of physics? Basic chemistry and biology? Those are models too. Maybe they'll stop working tomorrow too: it is time t+1, after all.
emmiemalone.bsky.social
I’ve been training my whole life for this moment
A screenshot of an article published in popular science. It reads: “First known wild 'grue jay' hybrid spotted in Texas. Green and blue jays are crossing paths as temperatures rise.”
donskerclass.bsky.social
Dataset shift is just external validity, but underspecification refers specifically to multiple indistinguishable predictors. For that to matter, you need some setting that isn't your train-test set to distinguish, which is an external validity problem, but defined in terms of a model class.
donskerclass.bsky.social
Several years ago a team of about 40 Google engineers rediscovered non-identification and some of the issues it causes and called it "underspecification". An illuminating glimpse into ML priorities and blind spots.
See also "dataset shift" for "it worked on train & test then failed in production"
Underspecification Presents Challenges for Credibility in Modern Machine Learning
www.jmlr.org
Reposted by Rachel Leah Childers
emmiemalone.bsky.social
I’ve been training my whole life for this moment
A screenshot of an article published in popular science. It reads: “First known wild 'grue jay' hybrid spotted in Texas. Green and blue jays are crossing paths as temperatures rise.”
donskerclass.bsky.social
At a bigger city festival that time is shortly after noon. :(
donskerclass.bsky.social
I was incredibly glad to catch #jasmine4t on tour last night! They put on an amazing live show, including new tracks from the extended album, out today!
Set list for jasmine.4.t's show in Zurich last night, given to me by the band afterwards

Skin on Skin
Tall Girl
Breaking In Reverse
Find Ur Pppl
I Can't Believe
I Don't Think
Kitchen
You Are The Morning
Tesco
Elephant
Woman
Did U No
donskerclass.bsky.social
Yeah, I was also inspired to revisit the back catalog and take a look at this again after the Tiny Desk concert.
economeager.bsky.social
breaking news pinkpantheress is the child of the bayesian statistician stephen g walker !!!!!!
jcht.bsky.social
As if we couldn’t stan Pinkpantheress more 😍😍😍