I'm on the #EconJobMarket! I study how policies and childhood environments shape outcomes of low-income & vulnerable kids.
In my JMP, I study the effects of allowing youth who would have aged out of foster care at 18 to stay until 21—offering support their peers not in foster care get from parents.
In case you missed our paper last week or are short on time - we have a quick writeup of it on the Community College Research Center blog: ccrc.tc.columbia.edu/easyblog/new...
Ultimately, we think these findings make a strong case for increased research & policy attention to understand which aspects of the transition may be most amenable to policy intervention. Lots more detail in the paper, hope you’ll give it a read! 10/10
Our descriptive evidence is consistent w/ intuitive conclusion: low-SES grads appear disadvantaged in the first job transition, regardless of the broader economic context, and this has consequences for earnings gaps years later. 9/
Horizontal bar chart showing how controlling for first job characteristics reduces earnings gaps between low- and high-socioeconomic status college graduates five years after graduation. Three horizontal bars extend leftward from zero, representing negative dollar amounts. The top gray bar shows an initial gap of $4,948 for observably similar graduates. The middle gray bar shows the gap reduced to $2,251 after controlling for first job salary, with a horizontal bracket and whiskers indicating a 55% reduction. The bottom blue bar shows the gap further reduced to $1,716 after controlling for all first job features, with a second horizontal bracket indicating a 65% reduction from the middle bar. Title states 'The Role of First Job Transitions in Explaining Earnings Gaps for Similar Low- vs. High-SES Grads, Five Years After Graduation.' Subtitle indicates data is from traditionally aged BA graduates from 2010-17 from a large urban public university system. X-axis shows dollar amounts from -$5,000 to $0.
Overall, we find that diffs in first job transitions can explain *nearly two-thirds* of the year 5 residual earnings gap between high- and low-SES graduates (i.e., the gap that remains after controlling for other observable differences at graduation, including major, GPA, test scores, etc.) 8/
Interestingly, the SES gap in the first firm’s *average* pay is substantially bigger than the SES gap in grads’ own starting salaries (even in percentage terms). In other words, low-SES grads start out at firms where they may have less “room to grow” 7/
Descriptively, low SES-grads are less likely to have already started working with their first post-college employer prior to graduation (34% vs. 40%), have lower starting salaries ($38K vs $43K) and work at lower-paying firms ($53K average vs $64K average) than high-SES grads 6/
To describe first job transitions, we look at time to first job, starting salary, industry, industry-major match, firm size and average pay (and a few other things too) - these are all predictive of earnings at year five 5/
We don’t examine these constraints directly, but begin by documenting large SES gaps in post-college earnings: even after controlling for a ton of other info on students’ background and grades, high-SES grads earn almost $5,000 (8%) more than similar low-SES grads five years post-grad 4/
But what if some groups have persistently rockier transitions to the labor market, even in boom times? E.g. what if low-SES students struggle more to land a good first job, not b/c of their school, major, or grades, but b/c informational, financial, or structural constraints get in the way? 3/
Context: While earnings bump for BAs remains strong, unemployment for recent grads has risen faster than other groups since 2022. Rigorous research shows economic conditions at graduation have long-run impacts, in part b/c it affects quality of grads’ first jobs 2/ www.newyorkfed.org/research/col...
🧵 New working paper! In joint work w/ @jscottclayton.bsky.social, Veronica Minaya, & Joshua Thomas, we use admin data from a large public univ system to examine earnings gaps for high- vs low-SES college grads 5 years out & the role of first jobs in explaining the gaps. 1/ www.nber.org/papers/w34366
Whoa, White House withdraws Trump’s controversial nominee to lead BLS after ousting predecessor over jobs data
www.cnn.com/2025/09/30/p...
How about this? drive.google.com/file/d/1QdMA...
Unarchiver was able to get it to extract for me.
Blast! I may have it on an old external hard drive - I can check later tonight
Does the file at this link work for you? web.archive.org/web/20210213...
one amazing feature here is simply loading the entire dataset would probably freeze your laptop!
instead you can run this regression quickly and not worry about memory problems, thanks to the magic of duckdb and dbreg
Anyone know if anyone is doing any formal benchmarking of LLM performance on Stata tasks? www.statalist.org/forums/forum...
Certainly not arguing the status quo (where all sorts of award letter shenanigans can and do occur) is optimal, but just as a matter of calculation, how would you calculate the value of IDR, PSLF, borrower protections such as hardship forbearances, in school deferments, closed school discharge, etc.
Thanks for all you do for this package!
Vis method for decomposition now merged to main, feedback welcome!
Also could it handle “negative” contributions (variables that increase the coefficient) in a way that is visually intuitive?
This looks great!! Think it would scale well to many covariates?
Man, when @dieworkwear.bsky.social weighs in on EJ Antoni's outfits, it may shake the earth.
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...
