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Peter Bergman

@peterbergman.bsky.social

Associate Prof. of Economics @utaustin. Director http://learningcollider.org. @NBERpubs affiliate. Co-Chair @mit @jpal edtech. Schmidt Futures Innovation Fellow. www.peter-bergman.com.

329 Posts4890 Follower877 Folgt
Petra Moser@pmoser.bsky.social · 6d ago

⚠️ IMPORTANT NOTICE: Hi, someone is impersonating me on Bluesky using a fake account. Please be aware: If you receive a message or follow from an account that looks like mine but has a slightly different handle, please do not engage with it. Thanks, and sorry for the inconvenience!

Jed Kolko@jedkolko.bsky.social · last wk.

The 2025 American Community Survey should have come out today. But it has been delayed because of unusual political encroachment at Census. ACS drives business and policy decisions, especially in local communities, and is the primary input to Census’s immigration estimates.

Joshua Goodman@joshua-goodman.com · 3w ago

🚨New working paper alert!🚨 Private tutoring chains like Kumon and Sylvan have grown rapidly. Who uses them? Do they improve kids' skills? BU econ PhD student Samuel Nitkin and I provide answers in: "Kumon Up: Private Tutoring Centers and Student Achievement" www.nber.org/papers/w35671 1/?

Private tutoring chains like Kumon and Sylvan have expanded rapidly in recent decades. Combining data on business locations, household spending, and district test scores, we study who uses these centers and how they affect academic skills. Nearly half of tutoring users are from the top income decile, with Asian and White households five and two times as likely to purchase tutoring as Black and Hispanic households. A staggered differences-in-differences design shows the opening of a district's first chain center raises district-wide math and reading scores by 0.02-0.03 standard deviations, at a much lower cost than public spending typically producing similar gains. Math effects are largest for White and Asian students, so that center entry widens racial achievement gaps, though less so in more racially integrated districts. These private investments help their users, deepen educational inequality, and shape outcomes by which state accountability systems and families judge schools.
Sarah Cohodes@cohodes.bsky.social · 2mo ago

Guys I’m having a week. Tomorrow come see me present “The effects of charter schools on economic mobility” at the Labor/Ed NBER SI session at 3:50pm ET. (In-person only)

Jennifer Doleac@jenniferdoleac.bsky.social · 2mo ago

If you'll be on the econ job market this fall with a paper related to crime, the criminal justice system, or people with criminal records, and would like to present it in the ViCE seminar, email me! (My address is on my website.)

@davidaldridgedc.bsky.social · 3mo ago

In a league of killers, Jalen Brunson is one of the best winners of his generation. He won two chips at Villanova in three years, and he's made the New York Knicks into NBA champions. At 6-foot-1-ish. He's a great, GREAT basketball player.

Peter Bergman@peterbergman.bsky.social · 3mo ago

New NBER working paper. We meta-analyze 82 RCTs of low-cost parent programs in 20+ countries. We use data on unwritten RCTs from funder records, RCT registries, author queries, etc. to estimate a model that adjusts for publication bias and characterizes the effect distribution for unwritten studies.

NBER working paper. Paper title: Characterizing the File Drawer: Evidence from a Meta-Analysis of Parent-Interventions Around the World Abstract: We conduct a meta-analysis of 82 randomized controlled trials across more than 20 countries to estimate the effects of low-cost, remote parental engagement interventions delivered through text messages, phone calls, and apps. We estimate a joint likelihood function that incorporates both written studies and unwritten studies identified through trial registries, funder records, research labs, evidence clearinghouses, and other sources. By also recording sample sizes for unwritten studies, the model estimates the distribution of standard errors, identifies write-up probabilities conditional on significance, and characterizes the file drawer by estimating effect distributions for written \textit{and} unwritten studies. Bias-corrected effects are 0.05 SD for test scores, 0.07 SD for grades, 0.05 SD for attendance, and 0.03 SD for enrollment. In the best-identified domain, test scores, statistically insignificant results are still written up at high rates. We also find that larger studies tend to estimate smaller latent effects, which could indicate that true effects are correlated with study precision, violating a common meta-analysis assumption. In smaller-sample domains, our approach helps identify selection probabilities by anchoring the absolute write-up rates. Finally, we estimate the value of additional RCTs to inform adoption decisions. Any single study estimate is unlikely to dissuade adoption because parent interventions have high marginal value of public funds. Instead, future research is most valuable when it can explain heterogeneity across settings.
Caitlin Myers@caitlinmyers.bsky.social · 4mo ago

Wow, I didn't expect our paper on iPhones and fertility to generate this much buzz—thanks for all the feedback! Rather than scattershot replies, here's a compilation of thoughts and new robustness checks. 🧵1/15