Mauricio Romero

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Full paper here: doi.org/10.1086/739022
Also, keep an eye out for a follow-up project with Eric Edmonds, Martina Jakob, and Carla Coccia (in partnership with @poverty-action.bsky.social), testing mentoring and information to prevent dropout in Guatemala.

To sum up: a gov’t-led, ultra low-cost program (USD 2–3/student) reduced dropout at the critical 6th→7th grade transition by 1.2pp (~3%). Effects faded after 2 yrs, highlighting both the promise of these types of intervention to prevent dropout & the need for follow-up support.

Indeed, in 2019, the Ministry rolled out the guide nationwide; cohort differences vanished thereafter, consistent with this.

Despite fadeout, ENTRE is very cost-effective: ~0.64 years of schooling gained per USD 100, far above CCTs/scholarships (0.01–0.17). It has a ~27% IRR and a cost–benefit ratio of 7–17. At <$3/student, ENTRE is affordable within the national education budget.

ENTRE was designed for scale: led by Guatemala’s Ministry of Education using existing staff, costing only USD 2–3 per student. This gov’t ownership reduced the risk of ‘fade out’ often seen when NGO pilots expand.
(See "experiment at scale" by @karthik-econ.bsky.social Paul Niehaus)

Qualitative data revealed 3 takeaways: (1) ENTRE signaled dropout prevention as a gov’t priority, motivating teachers; (2) the guide gave concrete tools & legitimacy to act; (3) deep barriers (e.g., poverty, social norms, scarce scholarships) remained, limiting long-run impact.

Admin data let us see longer-term: ENTRE boosted 6th→7th grade transition in 2019, but by 2020–22 gains vanished. Many later dropped out, likely due to a lack of follow-up support in secondary (and other structural factors)

We use admin data to track student enrollment for several years. What do we find? Dropout decreases by ~1.2 pp from a 34% base (≈−3.3%). Effects similar across arms; lists and nudges add ~0 beyond training+guide.

These 4,000 schools were randomly split:
• 1,000 got training + guide
• 1,000 got training + guide + risk list
• 1,000 got training + guide + risk list + nudges
• 1,000 were controls.
Schools were spread nationwide, making this one of the largest dropout-prevention RCTs.

We evaluated ENTRE in 4,000 Guatemalan schools (from 6,080 eligible, ~44% of all 6th graders). Eligibility required enough secondary school supply, excluded the smallest primaries, and only included schools with some predicted at-risk students.

Finally, some principals received 5 monthly nudges (via the ministry’s portal) to keep dropout top of mind.

Some schools also received a list of 6th-graders at highest risk of dropping out, predicted using sex, age, GPA, grade repetition & school history. The model identified 82% of future dropouts (See doi.org/10.1080/0964... for more details on the predictive model)

The core of ENTRE is a half-day training + a practical guide for principals & 6th-grade teachers. The guide offered simple, low-cost strategies: motivate students, help with scholarship information, provide remedial support, engage families, and ease enrollment logistics.

In 2017, Guatemala’s gov’t & World Bank launched ENTRE, a low-cost early warning system to cut dropout in the 6th→7th transition. It trains principals/teachers, flags at-risk students, and uses behavioral nudges to address knowledge gaps, data deficiencies, and prioritization issues

Guatemala’s dropout crisis is rooted in deep structural problems: >50% live in poverty, 6th globally in malnutrition, and secondary schools are scarce & urban-biased. While fixing these takes time, we test a low-cost, scalable intervention to reduce dropout now.

For context: Globally, primary enrollment is near universal, but secondary is not; many drop out in the transition. In Guatemala, 1 in 3 students leave school, moving from 6th→7th grade. Because most schools offer only primary or secondary, switching schools raises dropout risk.

Officially forthcoming at @jlaborecon.bsky.social, our new paper with Melissa Adelman, Francisco Haimovich, and Emmanuel Vazquez on the results from a large experiment with 4,000 schools on how to reduce dropout between primary and secondary schools in Guatemala. Short 🧵below #EconSky

Note that our colleagues in the Business School are also hiring. It’s a fantastic, young department pushing frontier research with strong links to the Econ Department. Great people+ great energy: econjobmarket.org/positions/11...
#econsky #econjobmarket

I have such data for mexico... Not sure if you want it for the US or just generally speaking

We (Econ at ITAM) are hiring:econjobmarket.org/positions/11841
Pay is competitive with the US (in absolute terms), working language is English, virtually no service work, spend ~80% of your time in research, and you get to live in one of the coolest cities in the world.
#econsky

Home Petter Berg

This is part of a larger agenda studying ECE in India.Expect more soon 🙂

+check out @petterberg.bsky.social, he is on the market and is fantastic;he was the driving force behind this paper: sites.google.com/view/petterb...

His JMP focuses on the long-run effects of outsourced schools in Sweden.

Our themes relate to other great work:

RCTs: See work by Ganimian @karthik-econ.bsky.social and Walters on improving AWCs; by @joshtdean.bsky.social @seema.bsky.social on vouchers for private preschool

Facts: See ASER Centre Early Years and main ASER Reports

Our results provide a unified view of public vs private effects from preschool to the end of primary edu (+ links to inequality).

Substantively, it supports the recent focus on improving ECE systems in India.

New: understanding edu *markets* at this stage is important.

Villages with better public pre/primary schools also have better private sectors ➡️ unequal access to quality education across villages.

Why?

Maybe public sector quality induces better performance from the private sector (as Tahir, Bau,Das @nkarachiwalla.bsky.social and Khwaja find in Pakistan)?

Result 3: Private preschools outperform public ones in nearly ALL villages.

In primary schooling, this is more variable across geographies.

(Doing this correctly needs Bayesian shrinkage; details in paper)

Result 2: Richer kids are far more likely to attend private schools (+35pp in preschool, +39pp in primary). This explains ~60% of the SES test score gap at preschool ages (but none in primary, since private schools show no value-added there).

Result 1: Average value-added in private preschools larger than public AWCs by 0.74σ in math & 0.59σ in Tamil.

By contrast, private primary schools have NO positive value-added over government schools in these subjects (we did not test English)

Sample: Household-based panel data on ~19k students (age 3-10) across 215 villages. All children tested one-to-one. Age-appropriate tests linked on a common scale using IRT (using overlaps across ages). Items align with national goals for foundational skills.

Context: Tamil Nadu, nearly all kids 4-5y enroll in *some* preschool

Public: Mostly anganwadi centres. Free to attend, only 1 worker + 1 helper. In TN, ~38 mins/day on cognitive tasks.

Private: Nursery/KG, often linked to primary sch. Fee-charging, focus on early learning.