Nonlinear panel data estimation via quantile regressions

2016/03/19 by Manuel Arellano, Stéphane Bonhomme · 3 citations
Mathematics · Economics, Econometrics and Finance · #Statistical Methods and Inference #Spatial and Panel Data Analysis #Monetary Policy and Economic Impact

paper · doi:10.1111/ectj.12062

openalex publication_date 2016/03/19 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/23

Abstract

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.

Citations

• On deconvolution with repeated measurements
• Quantile regression for longitudinal data
• On the Convergence Properties of the EM Algorithm
• Estimation of distributions, moments and quantiles in deconvolution problems
• Counterfactual decomposition of changes in wage distributions using quantile regression
• CAViaR
• Assessing the Equalizing Force of Mobility Using Short Panels: France, 1990-2000
• Regression Quantiles

Cited by

• Causal models for longitudinal and panel data: a survey
• A practitioner’s guide to panel data quantile regression
• Stéphane Bonhomme [wikipedia]

Related

• Quantile Regression for General Spatial Panel Data Models with Fixed Effects
• Panel Data Quantile Regression for Treatment Effect Models
• Bootstrap inference for panel data quantile regression
• On the Unbiased Asymptotic Normality of Quantile Regression with Fixed Effects
• Minimum Distance Estimation of Quantile Panel Data Models