Economics competition for high school and middle school students in Italy

Yesterday,  Tito Boeri, David Card and I attended the  award ceremony of the EconoMia and EcoQuiz competitions for high school and middle school students in Italy.

 At the Intesa Sanpaolo skyscraper, the award ceremony of the EconoMia and EcoQuiz competitions, as part of the International Festival of Economics. 

Here we are with the high school students whose essays received awards. 

 

 

Susan Athey on biggish data and machine learning

 Susan Athey is interviewd in JAMA:

How an Economist’s Application of Machine Learning to Target Nudges Applies to Precision Medicine   by Roy Perlis and Virginia Hunt  JAMA. Published online May 16, 2025. doi:10.1001/jama.2025.4497 

"A recent study by economist Susan Athey, PhD, and her colleagues may shed light on how best to target treatments using machine learning. The investigation, published in the Journal of Econometrics, focused on the effectiveness of text and email reminders, or nudges, sent to students about renewing their federal financial aid. The researchers compared causal targeting, which was based on estimates of which treatments would produce the highest effects, and predictive targeting, which was based on both low and high predicted probability of financial aid renewal.

"In the end, the study found hybrid models of the 2 methods proved most effective. However, the result that may be most surprising to Athey was that targeting students at the highest risk of nonrenewal was actually less effective.

...

"Dr Athey:When I first started working on this, I was like, “Oh, there’s going to be a gold mine. I’m going to go back and reanalyze all of these experiments that have already been run, and we’re going to be doing new scientific discoveries every day.” It didn’t quite work out that way. We had some big successes, but there has been a lot of lack of success.

What are the cases where this doesn’t work? Machine learning is using the data to learn about these treatment effects. You have to do a lot of sample splitting. There’s always a cost to using the data to discover the model. You can do it without sample splitting, but then you have to adjust your P values. There’s no free lunch. If you have a very small dataset, you probably know what the most important factors are. You might be better off prespecifying those and just doing your subgroup analysis. If [there are] hundreds of observations, it’s just unlikely. These techniques are too data hungry to work.

Generally, you need thousands of people in the experiment. Then more than that, the statistical power needed to get treatment effect heterogeneity is large. And even treatment effect heterogeneity is easier—trying to get differential targeting is another thing. Imagine you have 3 drugs. It’s hard enough to say that something works relative to nothing. If you’re trying to say that one drug works better than another drug where both work, that’s hard. Usually you need really large, expensive trials to do that.

Then you add on top of that that I want to say, “This drug is better for these people, and this other drug is better for these other people.” You need 10 times as much data as you would for the basic “is there a treatment effect at all?” Now, of course, sometimes there’s a genetic thing: this drug literally doesn’t work or it has this terrible side effect for some people. That will pop out of the data.

For more subtle effects, you do need larger studies. That’s really been the main impediment. And as an economist, it’s like, why are all these things just barely powered? Why are there so many clinical studies with a t-statistic of 2? Of course, people did the power calculations, and they had some data already when they planned the experiments. If you have more data, maybe you add another treatment arm or something else. You don’t actually overpower an experiment. In my own research, I’ve ended up running my own experiments that are designed to get heterogeneity. I’ve also had a lot of luck when there’s very big administrative datasets, and there’s a really good natural experiment. Then you have lots of data. But former clinical trials are selected to not be good because the researcher themself didn’t overpower their own experiment. That’s why this isn’t so useful.

But nonetheless, that’s not to say it’s not out there. Like in any discovery, if it’s going to save lives and money, it’s worth doing. It’s just that there’s not a whole bunch of low-hanging fruit. There’s no dollars lying on the sidewalk."

Nicole Immorlica celebrated (and interviewed) in a Microsoft Resarch podcast

 Here's a podcast with Nicole Immorlica, in which she talks about her research origins (including a course and a poem), what computer science brings to economics, and the role of theory in the age of generative AI.

Ideas: Economics and computation with Nicole Immorlica 

December 5, 2024 | Gretchen Huizinga and Nicole Immorlica

When research manager Nicole Immorlica discovered she could use math to make the world a better place for people, she was all in. She discusses working in computer science theory and economics, including studying the impact of algorithms and AI on markets.

 

Behind every emerging technology is a great idea propelling it forward. In the Microsoft Research Podcast series Ideas, members of the research community at Microsoft discuss the beliefs that animate their research, the experiences and thinkers that inform it, and the positive human impact it targets.

In this episode, host Gretchen Huizinga talks with Senior Principal Research Manager Nicole Immorlica. As Immorlica describes it, when she and others decided to take a computational approach to pushing the boundaries of economic theory, there weren’t many computer scientists doing research in economics. Since then, contributions such as applying approximation algorithms to the classic economic challenge of pricing and work on the stable marriage problem have earned Immorlica numerous honors, including the 2023 Test of Time Award from the ACM Special Interest Group on Economics and Computation and selection as a 2023 Association for Computing Machinery (ACM) Fellow. Immorlica traces the journey back to a graduate market design course and a realization that captivated her: she could use her love of math to help improve the world through systems that empower individuals to make the best decisions possible for themselves.

---

Learn more:

• Impact of Decentralized Learning on Player Utilities in Stackelberg Games 
  Publication, June 2024 
• The Disparate Effects of Strategic Manipulation
  Publication, January 2019 
• Marriage, honesty, and stability
  Publication, January 2005
• AI, Cognition, and the Economy (AICE)
  Project homepage

 

Feedback (from Trump campaign) on open letter by economists

 I get asked to sign many letters, and  while I'm generally reluctant to venture beyond my own specific areas of expertise into areas in which others are more expert, I recently signed one circulated by Joe Stiglitz, aimed to respond to some egregious campaign disinformation. 

Sixteen Nobel Prize-winning economists warn a second Trump term would ‘reignite' inflation By Rebecca Picciotto,CNBC   https://www.nbcnewyork.com/news/business/money-report/sixteen-nobel-prize-winning-economists-warn-a-second-trump-term-would-reignite-inflation/5538998/

The letter got this reaction from the campaign in question:

"The American people don't need worthless out of touch Nobel peace prize winners to tell them which president put more money in their pockets," Trump campaign spokesperson Karoline Leavitt said in a statement to CNBC." (emphasis added)

I'll listen for that line in tomorrow night's debate.

Update: here's a link that contains the whole letter   https://www.cbsnews.com/news/trump-economy-nobel-prize-winners-letter-inflation-warning/ 

It begins this way:

"We the undersigned are deeply concerned about the risks of a second Trump administration for the U.S. economy. 

"Among the most important determinants of economic success are the rule of law and economic and political certainty. For a country like the U.S., which is embedded in deep relationships with other countries, conforming to international norms and having normal and stable relationships with other countries is also an imperative. Donald Trump and the vagaries of his actions and policies threaten this stability and the U.S.'s standing in the world. "

Call for papers: 4th ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO '24)

 Nick Arnosti sends along the following call for papers (with a deadline on Wednesday):

We are excited to announce the Call for Participation for the 4th ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO '24). The conference will be held from October 29-31, 2024 in San Luis Potosí, Mexico.

EAAMO '24 will bring together academics and practitioners from diverse disciplines and sectors. The conference will highlight work along the research-to-practice pipeline aimed at improving access to opportunity for historically underserved and disadvantaged communities, as well as mitigating harms concerning inequitable and unsafe outcomes. In particular, we seek contributions from different fields that offer insights into the intersectional design and impacts of algorithms, optimization, and mechanism design with a grounding in the social sciences and humanistic studies.

Submissions can include research, survey, and position papers as well as problem- and practice-driven submissions by academics and practitioners from any disciplines or sectors alike. 

Important Dates:

Paper Submission Deadline: 17 April 2024, AoE

Submission Notification: 18 July 2024

Paper Submission Page: https://eaamo24.hotcrp.com/u/0/

Event Dates: 29 October - 31 October 2024

The conference will offer opportunities to engage with leading experts, share innovative research and practices, and network with peers. We look forward to your participation, and we encourage you to disseminate the Call for Papers to any interested colleagues.

 For any further inquiries about the conference, please contact the Program Chairs at pc24@eaamo.org.

 Sincerely,

EAAMO '24 Organizers 

 Program Chairs: 

Nick Arnosti, University of Minnesota
Caterina Calsamiglia, IPEG

Salvador Ruiz-Correa, IPIYCT

John P. Dickerson, Arthur & University of Maryland

SITE 2024 Conference: Call For Papers for Summer 2024

 Now is the time to be thinking of submitting papers for the summer sessions at Stanford. (Some deadlines are in April.)

Here's the call for papers:

SITE 2024 Conference: Call For Papers

Stanford Economics is proud to host its annual Stanford Institute for Theoretical Economics (SITE) Conference from July 1 to September 11 2024. SITE sponsors sessions that encompass both economic theory and empirical work and cover a broad range of topics. It brings together established and emerging scholars to present leading-edge economic research, to educate, and to collaborate.

These sessions are scheduled:

1. Gender  Monday, July 1, 2024, 8:00am - Tuesday, July 2, 2024, 5:00pm
2. Empirical Implementation of Theoretical Models of Strategic Interaction and Dynamic Behavior  Thursday, July 11, 2024, 8:00am - Friday, July 12, 2024, 5:00pm
3. Trade and Finance  Thursday, July 25, 2024, 8:00am - Friday, July 26, 2024, 5:00pm
4. Fiscal Sustainability  Thursday, August 1, 2024, 8:00am - Friday, August 2, 2024, 5:00pm
5. Dynamic Games, Contracts, and Markets  Monday, August 5, 2024, 8:00am - Wednesday, August 7, 2024, 5:00pm
6. The Micro and Macro of Labor Markets  Tuesday, August 6, 2024, 8:00am - Wednesday, August 7, 2024, 5:00pm
7. Political Economic Theory  Thursday, August 8, 2024, 8:00am - Friday, August 9, 2024, 5:00pm
8. Market Design  Thursday, August 8, 2024, 8:00am - Friday, August 9, 2024, 5:00pm
9. Market Failures and Public Policy  Wednesday, August 14, 2024, 8:00am - Thursday, August 15, 2024, 5:00pm
10. Empirical Market Design  Thursday, August 15, 2024, 8:00am - Friday, August 16, 2024, 5:00pm
11. Climate Finance and Banking  Monday, August 19, 2024, 8:00am - Tuesday, August 20, 2024, 8:00am
12. Frontiers of Macroeconomic Research Wednesday, August 21, 2024, 8:00am - Friday, August 23, 2024, 5:00pm
13. Experimental Economics  Thursday, August 22, 2024, 8:00am - Friday, August 23, 2024, 5:00pm
14. Psychology and Economics Monday, August 26, 2024, 8:00am - Tuesday, August 27, 2024, 9:00pm
15. The Labor Market Experience of Vulnerable Populations of Workers  Monday, August 26, 2024, 8:00am - 5:00pm
16. Housing and Urban Economics  Wednesday, August 28, 2024, 8:00am - Friday, August 30, 2024, 5:00pm
17. The Macroeconomics of Uncertainty and Volatility  Wednesday, September 4, 2024, 8:00am - Friday, September 6, 2024, 5:00pm
18. New Research in Asset Pricing  Wednesday, September 4, 2024, 8:00am - Friday, September 6, 2024, 5:00pm
19. The Economics of Transparency  Thursday, September 5, 2024, 8:00am - Friday, September 6, 2024, 5:00pm
20. Financial Regulation  Monday, September 9, 2024, 8:00am - Wednesday, September 11, 2024, 5:00pm