We study nonparametric regression in a setting where N(N-1) dyadic outcomes are observed for N randomly sampled units. Outcomes across dyads sharing a unit in common may be dependent (i.e., our dataset exhibits dyadic dependence). We present two sets of results. First, we calculate lower bounds...

We propose a generalization of the linear quantile regression model to accommodate possibilities afforded by panel data. Specifically, we extend the correlated random coefficients representation of linear quantile regression (e.g., Koenker, 2005; Section 2.6). We show that panel data allows the...

We propose a generalization of the linear quantile regression model to accommodate possibilities afforded by panel data. Specifically, we extend the correlated random coefficients representation of linear quantile regression (e.g., Koenker, 2005; Section 2.6). We show that panel data allows the...