Michela Tincani

@michelatincani.bsky.social

Associate Professor at UCL Economics. Research on college access, information frictions, peer effects. Affiliations: IFS, CEPR, LEAP, CESifo, HCEO. From Lake Maggiore to London via Philly. https://sites.google.com/site/mtincani

It's been 2 years (+ 1 month) since I left academia. In case anyone is wondering, I have zero regrets. Indeed, I'm living my best life and am so happy I made the leap. If you're considering leaving too, here are some thoughts on how to explore your options/find a job you'll love...

This was a fun conversation with Maddy Breen. I spoke about how my life experiences have shaped my research interests, and why access to information is so important for true equality of opportunities. Thank you @uclpolicylab.bsky.social for the opportunity!

UCL Policy Lab@uclpolicylab.bsky.social · 12mo ago

Dr Michela Tincani (@michelatincani.bsky.social) explores the unseen power of early decision-making in higher education. www.ucl.ac.uk/policy-lab/n...

I've been working on a new tool, Refine, to make scholars more productive. If you're interested in being among the very first to try the beta, please read on. Refine leverages the best current AI models to draw your attention to potential errors and clarity issues in research paper drafts. 1/

I'm very excited for #EEA25! We had 1900 submissions and look set for a fabulous time in Bordeaux. A HUGE thanks to the leads and graders who allowed us to get the programme together. See you in Bordeaux!

EEA@eeanews.bsky.social · last yr.

As the scientific programme of #EEA25 is released, let us thank our scientific committee for putting together everything. Thanks to you all: eea2025.org/eea-scientif... Full scientific programme: eea2025.org/full-programme

New results from our study of the long-term impacts of affirmative action in college admissions (with Michela Carlana, Sara Chiuri and Enrico Miglino), using Chile’s PACE program. How far down the academic achievement distribution can you go while still benefitting the students you target?

Yue Li@nkliyue.bsky.social · last yr.

📢Michela Tincani (UCL), with Michela Carlana and Enrico Miglino, presents “How Far Can Inclusion Go? The Long-term Impacts of Preferential College Admissions” (1/7) @stoneeconucl.bsky.social @michelatincani.bsky.social

Preparing a lecture on subjective expectations for the Econometric Society summer school in Dynamic Structural Econometrics, and I found a Wolpin paper from 1985 (!) on the use of expectation data to estimate choice models.

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Great talk by @dynarski.bsky.social on the effects of guaranteeing tuition fee coverage for disadvantaged students to attend a selective college. Results: faster BA completion and more selective college degrees. The program likely pays for itself through improved job market prospects 👏

Kotaro Fujisaki@kotarofujisaki.bsky.social · last yr.

Susan Dynarski (Harvard University) presents “Experimental Evidence on the Effects of College Quality on Educational Outcomes”, examining how a scholarship program closes college quality gaps between low- and high-income students. (1/5)

I am deeply saddened by the news of Ghazala’s untimely passing. Her work has been a great inspiration for my work for years, and in April this year I had the pleasures of finally meeting her in person. I was struck by her powerfully graceful demeanour and kindness. My heart goes out to her family.

It's the time of year when economics-trained faculty can be nominated to become NBER affiliates. If you primarily work on the economics of education and would like me to nominate you, send me an e-mail. Though budget constraints prevent all nominees from being chosen, it's worth trying!

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I'm not an R person, but I totally agree with this point: we're doing students a disservice by teaching them stata. Even worse if you're teaching at a public university: using public money to create consumers for a private company.

Josh Merfeld@merfeld.bsky.social · 2y ago

We should care about students’ career outcomes. Teaching them R will be MUCH more helpful than Stata. Not only is R more highly valued, it also makes learning things like Python much easier.