arXiv subjects

Myungkou Shin

Publications and source records attributed to Myungkou Shin.

3 recordsLinked to original sources

arXiv2026

Identification of Heterogeneous Peer Effects

We develop a model of peer effects where each peer has a separate effect depending on their rank in the distribution of peers' outcomes. Our model admits a unique equilibrium, and model parameters can be identified using peers' exogenous characteristics. To obtain a more parsimonious model of peer effects, we introduce a tractable specification based on quantile-dependent peer effect coefficients, and develop a specification test. Applying the model to several student outcomes in the Add Health data, we uncover heterogeneous and often non-monotonic spillovers that cannot be captured by existing models. Our results have direct implications for counterfactual analysis, suggesting that a student's influence in a network depends not only on network structure, but also on that student's position in the outcome distribution of their peers.

econ.EM↗

arXiv2025

Distributional Treatment Effect with Latent Rank Invariance

Treatment effect heterogeneity is of a great concern when evaluating policy impact: "is the treatment Pareto-improving?", "what is the proportion of people who are better off under the treatment?", etc. However, even in the simple case of a binary random treatment, existing analysis has been mostly limited to an average treatment effect or a quantile treatment effect, due to the fundamental limitation that we cannot simultaneously observe both treated potential outcome and untreated potential outcome for a given unit. This paper assumes a conditional independence assumption that the two potential outcomes are independent of each other given a scalar latent variable. With a specific example of strictly increasing conditional expectation, I label the latent variable as 'latent rank' and motivate the identifying assumption as 'latent rank invariance.' In implementation, I assume a finite support on the latent variable and propose an estimation strategy based on a nonnegative matrix factorization. A limiting distribution is derived for the distributional treatment effect estimator, using Neyman orthogonality.

econ.EM↗

arXiv2024

Finitely Heterogeneous Treatment Effect in Event-study

A key assumption of the differences-in-differences designs is that the average evolution of untreated potential outcomes is the same across different treatment cohorts: a parallel trends assumption. In this paper, we relax the parallel trend assumption by assuming a latent type variable and developing a type-specific parallel trend assumption. With a finite support assumption on the latent type variable and long pretreatment time periods, we show that an extremum classifier consistently estimates the type assignment. Based on the classification result, we propose a type-specific diff-in-diff estimator for type-specific ATT. By estimating the type-specific ATT, we study heterogeneity in treatment effect, in addition to heterogeneity in baseline outcomes.

econ.EM↗