Chernozhukov, V;
Fernandez-Val, I;
Weidner, M;
(2021)
Network and Panel Quantile Effects Via Distribution Regression.
Journal of Econometrics
10.1016/j.jeconom.2020.08.009.
(In press).
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Abstract
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.
| Type: | Article |
|---|---|
| Title: | Network and Panel Quantile Effects Via Distribution Regression |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.jeconom.2020.08.009 |
| Publisher version: | https://doi.org/10.1016/j.jeconom.2020.08.009 |
| Language: | English |
| Additional information: | This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
| Keywords: | Quantile effects, Counterfactual distributions, Fixed effects, Incidental parameter problem, Long panels |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL SLASH UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS > Dept of Economics |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10109973 |
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