From Micro to Macro in an Equilibrium Diffusion Model

Working Paper
Published on 1 January 2023

Two previous versions of this paper were published in October 2020 and July 2022 respectively.


We quantify the benefits of better firm-to-firm matching in an aggregate diffusion model and use it to interpret empirical moments from interventions that do so at a smaller scale. We build a model in which individuals reap profitable knowledge from others in the economy, then study the implications when meeting technology makes it easier to meet high-knowledge agents. We estimate the model using recent empirical evaluations of smallscale programs that create new learning opportunities among firm managers. The equilibrium gains from better meetings are primarily disciplined by empirical moments other than the average treatment effect. Extrapolating from it therefore generates large quantitative bias. However, for a broad class of diffusion models and interventions, these additional moments can be estimated with a simple linear regression from experimental data, thus providing practical information on the potential at-scale gains that can be useful for policy decisions.


Wyatt Brooks

Arizona State University

Kevin Donovan

Yale University

Terence R. Johnson

University of Virginia