Open AccessNonlinear panel data estimation via quantile regressions
Author(s) -
Arellano Manuel,
Bonhomme Stéphane
Publication year - 2016
Publication title -
the econometrics journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.861
H-Index - 36
eISSN - 1368-423X
pISSN - 1368-4221
DOI - 10.1111/ectj.12062
Subject(s) - quantile regression , quantile , autoregressive model , covariate , estimator , econometrics , computer science , estimation , statistics , mathematics , economics , management
Summary We introduce a class of quantile regression estimators for short panels. Our framework covers static and dynamic autoregressive models, models with general predetermined regressors and models with multiple individual effects. We use quantile regression as a flexible tool to model the relationships between outcomes, covariates and heterogeneity. We develop an iterative simulation‐based approach for estimation, which exploits the computational simplicity of ordinary quantile regression in each iteration step. Finally, an application to measure the effect of smoking during pregnancy on birthweight completes the paper.