Peer effect analysis with latent processes

Vincent Starck

Papers from arXiv.org

Abstract: I study peer effects that arise from irreversible decisions in the absence of a standard social equilibrium. I model a latent sequence of decisions in continuous time and obtain a closed-form expression for the likelihood, which allows to estimate proposed causal estimands. The method avoids regression on conditional expectations or linear-in-means regression -- and thus reflection-type problems (Manski, 1993) or simultaneity issues -- by modeling the (unobserved) realized direction of causality, whose probability is identified. Under a parsimonious parametric specification, I introduce a peer effect parameter meant to capture the causal influence of first-movers on their peers. Various forms of peer effect heterogeneity can be accommodated. Parameters are shown to be consistently estimated by maximum likelihood methods and lend themselves to standard inference.

Date: 2025-11
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