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9/ Thank you to everyone who provided useful comments when I presented this paper seventeen times!

Here is a link to the paper:

www.sephorahmangin.info/current_rese...

I would love to hear your thoughts or questions, so please don’t hesitate to reach out!

8/ It is worth highlighting that the paper uses a very surprising and useful equivalence between mixed Poisson distributions and “invariant” search technologies that was recently discovered by Cai, Gautier, and Wolthoff (2025).

7/ I thank the co-editor Chad Jones and three anonymous referees for extremely insightful suggestions that greatly improved the paper and yielded new results, applications, and proofs. I also thank Louis Becker for his valuable contribution to an earlier version of the paper.

6/ For example, suppose the number of firms in a consumer’s choice set is a random variable that is negative binomial.

Suppose consumers draw utility shocks from a uniform distribution.

Greater consumer heterogeneity increases the average markup.

5/ The paper generalizes a nice result about extreme value outcomes in Gabaix, Laibson, Li, Li, Resnick and de Vries (2016) by incorporating heterogeneity across agents.

For example, the paper delivers a generalization of a result on markups in Gabaix et al.

4/ How do these new EVDs arise?

For example, suppose the number of options an agent gets is a random variable that is negative binomial.

Suppose options are drawn from a Pareto distribution.

The EVD takes this general form. 👇

3/ The paper presents a new class of extreme value distributions (EVDs) that generalizes the three standard EVDs (Fréchet, Gumbel, Weibull) by incorporating heterogeneity across agents.

Here is an example of a new family of EVDs. 👇

2/ My forthcoming Econometrica paper answers this general question.

The paper provides a toolkit that I hope is useful for both macroeconomists and microeconomists alike.

Potential applications include growth, productivity, trade, markups, auctions, networks, IO.

Congratulations!