Governor Macklem presents Professor @rjuhasz.bsky.social of the University of British Columbia with the 2025 Governor’s Award at the Fellowship Learning Exchange conference 🏆
Congratulations Professor!
Learn more: bit.ly/3YA2wRP
#cdnecon #economy #awards #BankOfCanada
IMO, one of the most time-saving use cases of LLMs is handling the syntax of a new library, which can be time-consuming to learn if it's only needed, say, once. They can also help save time when finding bugs in code, especially when the bugs are common.
A few comments on the @mark-carney.bsky.social platform released today. You can find it here: liberal.ca/cstrong/.
I provided some 'sounding board' advice here and there to those working on the platform. As always: I disclose, but you can decide what weight to put on that.
Thread below...
Oh we might have our answer to the breakdown, at list. Not sure about the ordering quite yet: bsky.app/profile/tyre...
You can totally see how this mf bankrupted a casino.
I am willing to believe the reverse-engineering of the ridiculous numbers, but is there any sensible theory of the ordering of the list?
Nice research brief on our work - with @annamueller.bsky.social @alex-brewer.bsky.social et al.
Which one of us hasn't had to do at least one Assessment©️ pretty much every day of our work lives?
"Addressing hidden inequalities in workplace assessments can help create a more equitable workplace."
"ChatGPT, please generate a list of countries and islands along with a random number between 0 and 99%. Remove
Russia and ensure it is sorted randomly rather than going by country name or size"
www.theglobeandmail.com/gift/66d740f...
It is an honor to receive a Killam Accelerator Research Fellowship. Thank you to everyone involved!
Understanding causality vs. correlation is genuinely hard especially on complex topics like inflation. Our research finds that 60% of Americans think high interest rates cause high inflation & support rate cuts to fight it. But high rates usually respond to inflation,not cause it
Congratulations to Jane Platt on receiving the Wesbrook Scholarship, one of UBC's most prestigious awards!
Wishing her success as she continues her research in public policy!
Read the announcement: economics.ubc.ca/news/vse-stu...
🎉Congrats to Professor @rjuhasz.bsky.social of the University of British Columbia for winning the 2025 Governor’s Award.
Her research focuses on industrial policy and industrialization, emphasizing their importance in economic studies.
bit.ly/3DLWm9U
#cdnpse #cdnecon @industrialpolicy.bsky.social
Congratulations to our @ubcvse.bsky.social colleague @rjuhasz.bsky.social who has won the 2025 @bankofcanada.bsky.social Governor's Award!
We are proud of and happy for Reka!
bsky.app/profile/bank...
There is a postdoctoral position for research on adversarial robustness at UBC, supervised by Mathias Lecuyer (@mathias-lecuyer.bsky.social), Geoff Pleiss, and Nidhi Hegde. Please spread the word! 🇨🇦
docs.google.com/forms/d/e/1F...
Hey #EconSky
Economists for Ukraine (econ4ua.org) drafted an open letter to the future German chancellor. We call for 🇩🇪 & 🇪🇺 to step up & to ⬆️ support for #Ukraine. Please read & sign (if you agree), the form is at the end of ✉️): tinyurl.com/m9ta2b5d
Please share this letter with your colleagues.
We woke up to find our nihilistic juvenile kittens had pulled this book off the shelf and were trying to trash it. A little on the nose...
Reverse engineering worries me. I love good data work, and I love applied theory - but trying to reverse-engineer a model from stylized facts is ill-posed. Which explanation to use? My sense is that insisting on data+theory+quantiative application has been a detrimental to publishing in econ
One concern is that much of the economics is learned by tinkering with simplifications/FOCs/edge-cases. These tools might make it easy to write down models, solve them numerically/symbolically/etc., but ultimately provide papers with fewer insights. At least for applied-theory papers.
Glad we got through the tariff emergency (at least the first wave of it....).
Also glad that people are bringing creativity, energy, and determination to figuring out a medium and long-run response.
But I want to throw cold water on three ideas I've seen floated. I'll explain...
Prof. Kim Ruhl (UMN PhD 2004) of University of Wisconsin-Madison has been named as one of 3 members of President Trump's Council of Economic Advisors. I admire Kim for his service to our country, and I hope he is able to have a favorable influence on US economic policy.
news.wisc.edu/uw-madison-e...
A snippet of the 5 minute stream of conscious output before it answered my question.
chain of thought is hilarious
(distilled deepseek 14b running via ollama)
Hi Everyone!
We're hosting our Wharton AI and the Future of Work Conference on 5/21-22. Last year was a great event with some of the top papers on AI and work.
Paper submission deadline is 3/3. Come join us! Submit papers here: forms.gle/ozJ5xEaktXDE...
I asked DeepSeek to do a proof, and it felt like getting a portal into Erdős's amphetamine accelerated inner monologue.
Watching chain of thought output is mesmerizing.
Economists need to consider bold new ideas and perspectives which don't fit into existing research templates. If we never pull the multiarmed bandit on crazy ideas, then we can't escape local optima.
The way to make that happen is for journals to publish clean, simple, and new perspectives.
Economists often need to solve the same model an enormous number of times during estimation/calibration - otherwise I know nothing here on the details. But the idea is kept clean, and thanksfully the referees/editors let it stay focused.
I have an AI generated proof of a statistics lemma beyond my measure theory paygrade. Question: how many samples from LLMs do I need in practice to be 95% confident the proof is correct? Do different LLMs help ensure that there is no correlation between these draws?
PLEASE RT :)
Submit to the annual Network Science and Economics Conference, the largest US event for network theory and empirical research in and adjacent to economics
Deadline Jan 30 (soon!)
Conference Apr 11-13 at Stanford
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.
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....