CJ Libassi

It has been the honor of my life to serve as Commissioner of BLS alongside the many dedicated civil servants tasked with measuring a vast and dynamic economy. It is vital and important work and I thank them for their service to this nation.

AEA Statement on Dismissal of BLS Comm.

"The independence of the federal statistical agencies is essential to the proper functioning of a modern economy. Accurate, timely, and impartial statistics are the foundation upon which households, businesses, and policymakers make critical decisions."

Thanks for maintaining it! Was very grateful to see that it was part of pyfixest.

I think these look great! Very logical way to put things together. The challenge in my mind is how to handle many vars? One thing I have toyed with for this is trying to plot the top N vars decomposition results. Something like this toy example I just had Claude code whip up on simulated data.

Lexington, KY

Excited to announce the call for papers for the inaugural MidSouth Education Policy Workshop, October 16-17, in Lexington, KY!

Send us your abstracts on all things econ of ed & ed policy by 8/27. Grad students & early career folks especially welcome!

Info & link to submit here: bit.ly/44TdiGf

ICYMI last week - take a peek at our new report to better understand the earnings prospects of the professional school programs Congress just (nearly) uniformly & dramatically changed liquidity provision for: pseocoalition.org/wp-content/u...

@jdmatsudaira.bsky.social and @clibassi.bsky.social explain what new graduate loan limits will mean, not only for borrowers in medical school but across the graduate education landscape. Check out this thread/follow @peerresearch.bsky.social for more!

House/Senate are set to eliminate Grad PLUS, and put in place loan limits that would dramatically restrict graduate borrowing. Media coverage emphasizes impact this may have on very expensive programs like Medicine and Dentistry, but @peerresearch.bsky.social finds impact will be much(!) broader 1/

Truly thank you. Finding these emojis was the most exciting part of this.

Much more in the report, from tracing earnings trajectories across programs to how earnings paths interact with IDR. We hope you will take a read! Many thanks to the folks who volunteered to give comments on drafts, helping improve the report tons. Find it here:: pseocoalition.org/wp-content/u...

Chart showing earnings ranges for professional programs 5 and 10 years after graduation. Horizontal bars display interquartile ranges with median lines. Programs from lowest to highest 10-year median earnings: Rehabilitation/Therapeutic Professions, Veterinary Medicine, Optometry, Law/JD, Pharmacy, Dentistry, and Medicine/MD. Medicine shows dramatically higher earnings than other programs, with 10-year median above $300k and upper range extending to over $500k. Most other programs cluster between roughly $100k-$150k for 10-year median earnings

On top of tracking debt-to-earnings over a longer period, we look at different parts of the distribution of earnings. Here for example is the interquartile range of earnings for all of the students in the PSEO data, which captures a recurring fact in the report: things are just different in medicine

Maybe the biggest headline is just how much higher earnings for these professional programs is than the (quite large!) debt levels reported by ED. Remember that this is over just the first 10 years following graduation, and we still see ratios of total earnings to total debt near or exceeding 10x.

Scatter plot comparing median program debt (x-axis, $50k-$300k) vs 10-year cumulative earnings (y-axis, $0.5M-$2M) for professional programs. Medicine MD programs (pink squares) cluster in upper right with high debt ($150k-$250k) and high earnings ($1.4M-$1.8M). Law programs (blue circles) cluster in the bottom left corner with lower debt and lower earnings, though some elite programs show medicine-level earnings and somewhat higher debt than other law schools. Veterinary Medicine (green diamonds), Dentistry (plus signs) and Pharmacy (X marks) are distributed across middle ranges of earnings, but across wide ranges of the distribution of debt, with almost all pharmacy programs having lower debt than almost all dentistry programs. Physical therapy and veterinary programs have law-like earnings (between half a million and a million over 10 years), and while PT has law-like debt as well, veterinary debt is generally much higher and closer to medical school.

New at @pseocoalition.bsky.social, @julia-turner.bsky.social & I have a new report on grad school debt & earnings over the medium term. For some key professional fields (🩺⚖️🦷💊🐾), we show the varied patterns both within & across areas of study, looking at the first decade of earnings after graduation

Absolute banger of a review by @economeager.bsky.social in the JEL of "We Are Not Able to Live in the Sky: The Seductive Promise of Microfinance" by Mara Kardas-Nelson www.aeaweb.org/articles?id=...

Particularly enjoyed this concluding paragraph:

I feel like if there were one job you’d like more than economist it would be generating puns at super human pace for monthly paying subscribers

The @peerresearch.bsky.social newsletter has had lots of good stuff on things in the bill and I imagine will have something on the latest changes soon

AI assisted search-based research actually works now For the past two and a half years the feature I’ve most wanted from LLMs is the ability to take on search-based research tasks on my behalf. We saw the …

More on what is possible in the new search tools here: simonwillison.net/2025/Apr/21/...

The sort of many-source synthesis you are looking for would probably be a better fit for the o3 with deep research turned on or Gemini 2.5 + deep research

While not specialized for that task, I often have the new o3 or o4-mini flavors of chat gpt w/ web search option turned on search official docs for me and make user guides or answer specific questions - I usually start by pointing it to URLs where the docs are, but it can also find them on their own

not a standard battery or a free-for-all, but a literal secret third thing

you are both right & I certainly don't want to add to the list of steps in the publication process (making an exception of course for forcing everyone to report AMIP stats...). does seem like it would be nice tho for there to be a toolbox for detecting these things in a more systematic way

For sure - though I’m not sure that’s dispositive of the fact that there shouldn’t be a standard battery.

Truly the only compliment I want out of academia-sky, many thanks.

That seems too hard a problem given the wide variety of types of results people present in papers, but is there some better way to consistently formally test for simulated data? Again, not sure it makes sense, but it seems like the intuition of “this should have been caught” might imply some tests

At the risk of being overly literal about this whole endeavor of ours, one thing I’m sort of curious about is whether one could formalize the intuition of “too perfect” as a statistical test. Something like “too many of your effects are same signed & significant across all tests”

The journal Research in Higher Education is seeking manuscripts using data from the National Center for Education Statistics for a special issue. Please read the full call for papers here and circulate to your networks! #RIHE link.springer.com/collections/...

Chicago Pope, notorious for asking tough questions in seminars.

The Prime Minister faced yet another setback this week as the ongoing scandal over two-way fixed effects produced two more estimators for Canadians to learn. ‘You’re telling me these regressions produced negative weights and the Liberals knew nothing?!” the Conservative Party leader tweeted Sunday

Screenshot of an email from Alex Smith on April 23, 2025, announcing an update to the Integrated Postsecondary Education Data System (IPEDS) data on the College Scorecard website. The update includes more recent data values from a new collection year, a new metric called "SCORECARD_SECTOR" to classify institutions by dominant award and ownership, and updated data derived from Federal Student Aid sources for various metrics like Operating Status Flag and Cohort Default Rate.

The Pope didn't die without performing one last miracle.

Much of the voter participation gap by gender may be explained by the fact that women are more educated than men and that more educated citizens vote more often.

New work by Cameron Arnzen and @cohodes.bsky.social.

edworkingpapers.com/ai25-1152

Access to Full-Day Kindergarten Grows While most kindergarten-aged children do attend some type of kindergarten, their experience depends on where they live. This wide variation means children are getting uneven starts to their formal edu...

I bet @chloergibbs.bsky.social has this - I think she collected it ~comprehensively in her most recent paper on the topic. Also New America usually keeps tabs on this sort of thing and may point to some good resources in their posts on the topic: newamerica.org/education-po...