Next up, we have Jeff Yusof presenting joint work with Ricardo Perez-Truglia on Billionaire Superstar: Public Image and Demand for Taxation. They use an experiment where they used luxury queues -- pictures of their luxury homes -- in an informational experiment. Again, drawing links...

and in my paper with Ricardo Perez-Truglia we study people's attitudes toward taxing billionaires.

www.nber.org/papers/w32712

[14/14]

together with @acohn.bsky.social, Michel Maréchal, and @rfisman.bsky.social, we explore whose preferences are most predictive of actual redistribution…

nber.org/papers/w31974

[13/14]

In general, my work explores how people perceive inequality, how this shapes their preferences for redistribution, and their support for welfare policies.

In other projects…

[12/14]

Main take-away: Our results suggest that the conventional dichotomy of effort versus luck falls short of explaining redistributive preferences when market forces beyond individual control create inequality.

Link to paper: bit.ly/40y8XGM

[11/14]

But how do fairness preferences influence people’s support for real-world welfare policies?

We find that our experimental measures of fairness preferences are a strong predictor of support for welfare policies (controlling for SES and political affiliation).

[10/14]

Does the market luck effect generalize to real-world market settings?

In a complementary vignette study based on real-world scenarios, we again find that individuals perceive inequalities as fairer when caused by external market shocks rather than by brute luck.

[9/14]

Do we see similar patterns across different cultural contexts?

We ran additional experiments in France and China (N=3,500).

The order of implemented inequality is consistent across all countries (bl<ml<ef), but the magnitude of the market luck effect varies.

[8/14]

Additional treatments and analysis of open-ended answers show that:

– Mere presence of the buyer alone cannot explain the market luck effect.
– Workers’ deservingness increases when they generate a profit for the buyer.

[7/14]

We find a substantial market luck effect:

Spectators implement 50% more inequality (Gini coef) in the market luck treatment than in the brute luck treatment—about half of the effort treatment effect.

This difference mirrors the inequality gap between Denmark and the U.S.!

[6/14]

To benchmark our main treatment effect, we also implement an *effort* treatment:

Here, effort levels are no longer fixed; instead, relative performance on the task determines which worker receives the high income.

[5/14]

In our control treatment, there are no buyers, and income is determined by a coin flip - *brute luck *.

Key points:
1. In both treatments, which worker receives the high income is entirely random.
2. All workers provide the same level of effort.

[4/14]

How do people perceive these inequalities? How do they redistribute earnings between workers?

Our main outcome variable is the redistributive choices of nearly 2,000 subjects from the general U.S. population, who act as third-party spectators.

[3/14]

In this paper, co-authored with Simona Sartor, we design an experiment that creates income inequality between workers with different skills.

By randomly matching workers with buyers who require specific skills, we generate income inequalities driven by *market luck*.

[2/14]

🚨Job Market Paper Alert 🚨

A significant part of inequality stems from market forces beyond individual control - what we call *market luck*.

In meritocratic societies, this raises a key question: Do people perceive these inequalities as fair? [1/14]

Thanks so much for posting our paper, Stephanie!