2018/01/15 by Jiaying Gu, Stanislav Volgushev, Gu, Jiaying +1 · 3 citations
Economics, Econometrics and Finance · Mathematics · #Advanced Statistical Methods and Models #Asymptotic distribution #Demography #Econometrics #Econometrics (econ.EM) #Economics #Estimation #Estimator #FOS: Computer and information sciences #FOS: Economics and business #Mathematics #Methodology (stat.ME) #Panel data #Population #Quantile #Quantile regression #Regression analysis #Statistical Methods and Bayesian Inference #Statistical Methods and Inference #Statistics #econ.EM #stat.ME
paper · pdf · doi:10.48550/arxiv.1801.05041
published in arXiv (Cornell University) (Cornell University)
openalex publication_date 2018/01/15 · arxiv created 2018/08/05 · arxiv updated 2018/08/07 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/06
This paper introduces estimation methods for grouped latent heterogeneity in panel data quantile regression. We assume that the observed individuals come from a heterogeneous population with a finite number of types. The number of types and group membership is not assumed to be known in advance and is estimated by means of a convex optimization problem. We provide conditions under which group membership is estimated consistently and establish asymptotic normality of the resulting estimators. Simulations show that the method works well in finite samples when T is reasonably large. To illustrate the proposed methodology we study the effects of the adoption of Right-to-Carry concealed weapon laws on violent crime rates using panel data of 51 U.S. states from 1977 - 2010.