I’m on the Job Market! 🚨 Ever wondered how does uncertainty about sources of inequality affects redistribution? In my jmp, Excuses and Redistribution, I explore how people use excuses to distort beliefs about merit and luck, justifying self-serving behavior. 🧵(1/7)

In the fourth installment of our null results blog series, Manasi Deshpande and @RDizonRoss share how their initial null finding on the impact of informing parents of their child’s potential loss of SSI benefits informed their follow-up study:

📢 #MUES research seminar Tomorrow, Ahumada Bea (@beaahumada_) from @PittEcon will present a study exploring how, when income inequality is perceived to arise from both effort and luck, excuses can influence acceptance of inequality. Join us ⏩ https://t.co/u5IjDPsGRR

I would love to hear your thoughts and connect with others working on similar topics! 🤝#EconTwitter #EconJobMarket

My research uses behavioral insights to inform public policy, aiming to reduce inequality by addressing differences in opportunities and exploring mechanisms like redistribution, fairness, and hiring practices. I explore how institutions can promote fairness and mobility.

🎯 Future projects: Handicaps in the Labor Market: Initial ability differences often grow due to unequal opportunities. Using theory and experiments, I study if handicap tournaments (like in sports) can close ability gaps and reduce long-term inequality.

🤔 “Silly” Interview Questions and Gender Bias in Hiring (w/@disml_scientist & @NeerajaEcon): We study how "irrelevant" questions (like ice-breakers) affect hiring decisions and whether they justify gender biases.

Timing mirrors real-world policies (e.g., taxes, student loan forgiveness) and results could inform better policy design!

🌟 Preferences over the Timing of Fairness Policies (w/ @disml_scientist) We study how the timing of redistribution and related info impacts preferences. Spectators decide redistribution for workers who either know or don’t know about it before performing a task.

Do you want to know more about my research agenda? My work explores fairness, inequality, and redistribution preferences using experimental and behavioral methods. In this thread, I talk about my ongoing and future projects!🧵

Read more here: https://t.co/do2rERbsRb

Why does this matter? Economic implications: These behaviors can perpetuate inequality. Social implications: Fosters polarization - people believe that those who are poor have themselves to blame, but those who are rich are due to luck. (6/7)

Belief distortions aren’t the only story. I find evidence that people choose fairness views (egalitarian, meritocratic, or libertarian) that best align with their self-interest. (5/7)

Results: Under No Information, participants believe their partners’ success is due to luck, justifying keeping more earnings for themselves. Redistribution is lower, and inequality increases. (4/7)

Key treatments: No Information: Only know how much $ each of them made. Partial Information: Effort distribution is shown, reducing uncertainty. (3/7)

In a lab experiment: Participants perform a real-effort task where the piece rate (high or low) is randomly determined. Then, they redistribute earnings between themselves and a partner under different information conditions. (2/7)

Thanks for sharing my JMP, @jeffrlin. I hope to have a new version to share soon 😀

📄💬 | Bea Ahumada (@beaahumada_ ), académica de University of Pittsburg (@PittEcon ), presentará: "Excuses and Redistribution" 📆 Miércoles 01 de julio 12:30 PM 📍 Sala 401, Beauchef 851, Piso 4

Santiago post lluvia.

A field experiment among US university students shows that incentives for sleep increase both sleep and academic performance and can be a cost-effective intervention, from Osea Giuntella, Silvia Saccardo, and Sally Sadoff https://t.co/OLIcgW8DLM