期刊
ECONOMETRICS JOURNAL
卷 19, 期 3, 页码 C61-C94出版社
OXFORD UNIV PRESS
DOI: 10.1111/ectj.12062
关键词
Dynamic models; Expectation-maximization; Non-separable heterogeneity; Panel data; Quantile regression
类别
资金
- European Research Council (ERC) [263107]
- ESRC [ES/M010147/1] Funding Source: UKRI
- Economic and Social Research Council [ES/M010147/1] Funding Source: researchfish
- European Research Council (ERC) [263107] Funding Source: European Research Council (ERC)
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.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据