  This paper provides a method to construct simultaneous confidence bands for
quantile functions and quantile effects in nonlinear network and panel models
with unobserved two-way effects, strictly exogenous covariates, and possibly
discrete outcome variables. The method is based upon projection of simultaneous
confidence bands for distribution functions constructed from fixed effects
distribution regression estimators. These fixed effects estimators are debiased
to deal with the incidental parameter problem. Under asymptotic sequences where
both dimensions of the data set grow at the same rate, the confidence bands for
the quantile functions and effects have correct joint coverage in large
samples. An empirical application to gravity models of trade illustrates the
applicability of the methods to network data.
