Forthcoming in the JEL: "The Economics of Age at School Entry: Insights from Evidence and Methods" by Mariagrazia Cavallo, Elizabeth Dhuey, Luca Fumarco, Levi Halewyck, and Simon ter Meulen.
@lfumarco
Asst Prof, @econmuni.bsky.social; @iza.org, GLO, @j-pal.bsky.social. Before @tulaneu.bsky.social, and @statec-luxembourg.bsky.social. Studies (mostly) on discrimination w/ RCTs and age at school entry. https://sites.google.com/site/lucafumarco
Forthcoming in the JEL: "The Economics of Age at School Entry: Insights from Evidence and Methods" by Mariagrazia Cavallo, Elizabeth Dhuey, Luca Fumarco, Levi Halewyck, and Simon ter Meulen.
#econsky
Working paper versions (online appendixes included) are available via, e.g., IZA, GLO, and EdWorkingPapers.
What ASE finding surprised you most? And where should future work focus β relative-age mechanisms? Long-run health? Family spillovers? Would love to hear. 9/9
For policymakers: ASE effects are real, multidimensional, and often long-lasting. And, we suspect, researchers are still just scratching the surface. 8/9
For researchers: the paper maps the literature and flags where conceptual and identification clarity can still improve. Appendixes cover 50+ paper summaries, school cutoff dates worldwide, and list 250+ readings. 7/9
Relative age is the most underappreciated component. Its effects are especially sticky in:
πΉ Behavioral assessments
πΉ ADHD diagnoses
πΉ Special education placement
Why? As a possible answer, schools benchmark kids against classmates β not against developmental norms. 6/9
A central insight: most ASE estimates are composite effects. Even clean RDD designs with grade-level outcomes bundle multiple components mechanically.
Knowing the exact source of variation is essential for results interpretation. 5/9
Methods matter β a lot. We walk through 2SLS, RDD, DiD, and reduced-form approaches, and clarify what each design actually identifies (and what it doesn't).
Cross-jurisdiction variation matters too β tracking systems, diagnostic rules, dropout policies β is often underused and underappreciated. 4/9
We propose a clean conceptual framework. ASE has four distinct components:
β Starting-age (maturity at entry)
β Age-at-outcome (how old you are when measured)
β Relative-age (your rank within the class)
β Time-in-school (cumulative exposure)
And they have an impact through various channels. 3/9
Being slightly older/younger when you start school matters. Age at school entry (ASE) shapes:
π Educational attainment
πΌ Earnings & employment
π§ Mental & physical health
π₯ Social relationships
βοΈ Crime
π Family formation
Economists largely ignored this topic for decades. Not anymore. 2/9
π¨Forthcoming paper, @aeajournals.bsky.social π¨#econsky
A thread π§΅ on "The Economics of Age at School Entry: Insights from Evidence and Methods". Humbled to work w/ @mariagraziacavallo.bsky.social, @bdhuey.bsky.social, Levi Halewyck & Simon ter Meulen 1/9
many thanks!
it is a survey of the literature on age at school entry. in some days, we ll post the usual thread w more details
yep, that's it (and bookmarklet is the word i should ve used instead of app, sorry)
you cannot install it on edge, or?
Grazie Alfredo!
Many thanks!
Aaah! Waking up in the morning to an acceptance decision from the Journal of Economic Literature...it feels great!
pitty altmetric app works only on a couple of browsers. great feature though
www.nature.com/articles/s41...
yet again, a good reason for using this platform?
it's great: it reads like a 80s song title, econ vibes though
how was the murder rate in the years before covid-19?
Fig. 4. Regression results of heckles for female speakers and male interrupters. Note: The points show marginal effects from the triple-interaction model in Eq. (2), estimated relative to the first Bundestag period and displayed with 95% confidence intervals. Panel (a) reports the estimate for , capturing the effect of having a female speaker; Panel (b) presents the estimate for , representing the effect of a male MP as the potential interrupter; and Panel (c) shows the interaction between male interrupters and female speakers, measured by . Full regression results are provided in Appendix Table A1.
Title Decoding discourse: Gendered heckling in German Bundestag debates (1949β2021) Author Teresa Hailer-RΓΆthel Abstract This paper investigates the gendered dynamics of parliamentary interruptions in the German Bundestag across 19 legislative periods (1949β2021). Motivated by anecdotal and journalistic reports of sexist heckling, the study examines whether female politicians face more frequent interruptions and, if so, under which conditions. Using a newly constructed dyadic dataset that links over 200,000 interruptions to individual speeches, the analysis explores how gender, ideology, and institutional position shape patterns of adversarial behavior. The findings reveal that in earlier decades, female MPs were not primarily interrupted by men, while since the late 1980s such a gendered pattern has become observable. In addition, heckling of female MPs often originates from opposing ideological camps or parliamentary blocs. These results nuance existing theories of gender bias in political discourse by highlighting how ideological conflict and inter-gender competition shape communicative power in parliamentary settings.
Interesting paper on the gendered heckling the German Bundestag www.sciencedirect.com/science/arti...
hey #econsky, here is another cool AI: paperreview.ai from Stanford ML group. This is an AI reviewer, it (apparently) works well with econ papers! It is free, you just enter an API key, and then paperreview will email you a report within minutes.
hey #econsky, check this out: seminar-dry-run.vercel.app from @plausiblyexog.bsky.social. Very cool way to train for seminars: AI listens to your presentation, asks you questions, and then provides you with feedback!
I see some optimist in "new stable equilibrium"
Mediation analyses indicate that part of this effect operates through educational pathways: older students are less likely to experience delays and more likely to have student jobs. These factors explain someβbut not allβof the relative age advantage.
Being almost one year older within a cohort increases the probability of employment one year after graduation by 3.5 p.p., and raises the likelihood of obtaining a permanent (+5.1 p.p.) or fullβtime (+6.5 p.p.) contract.
Using rich Flemish survey data and a 2SLS strategy, we study whether being older than oneβs classmates due to school entry rules affects the transition from school to work.
π¨new pub!π¨
link.springer.com/article/10.1...
W/ S. Baert, L. Halewyck, E. Moens, A. Vandromme
We show that small differences in age at school entry can meaningfully shape early career outcomes. A short overview π