Working Paper

Network and panel quantile effects via distribution regression

Authors

Martin Weidner, Ivan Fernandez-Val, Victor Chernozhukov

Published Date

12 December 2018

Type

Working Paper (CWP70/18)

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 bias corrected 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.


Latest version

Network and Panel Quantile Effects Via Distribution Regression
Martin Weidner, Ivan Fernandez-Val, Victor Chernozhukov
CWP27/20

Previous version

Network and panel quantile effects via distribution regression
Martin Weidner, Ivan Fernandez-Val, Victor Chernozhukov
CWP21/18