| 面板数据的可加分位回归模型研究与应用 |
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| 引用本文： | 罗幼喜,张敏,田茂再. 面板数据的可加分位回归模型研究与应用[J]. 统计研究, 2020, 37(2): 105-118. DOI: 10.19343/j.cnki.11-1302/c.2020.02.009 |
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| 作者姓名： | 罗幼喜 张敏 田茂再 |
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| 作者单位： | 湖北工业大学理学院;中国人民大学统计学院 |
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| 基金项目： | 国家社会科学基金项目“高维复杂面板数据的双惩罚分位回归建模方法研究”(17BJY210)。 |
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| 摘 要： | 本文在贝叶斯分析的框架下讨论了面板数据的可加模型分位回归建模方法。首先通过低秩薄板惩罚样条展开和个体效应虚拟变量的引进将非参数模型转换为参数模型，然后在假定随机误差项服从非对称Laplace分布的基础上建立了贝叶斯分层分位回归模型。通过对非对称Laplace分布的分解，论文给出了所有待估参数的条件后验分布，并构造了待估参数的 Gibbs抽样估计算法。计算机模拟仿真结果显示，新提出的方法相比于传统的可加模型均值回归方法在估计稳健性上明显占优。最后以消费支出面板数据为例研究了我国农村居民收入结构对消费支出的影响，发现对于农村居民来说，无论是高、中、低消费群体，工资性收入与经营净收入的增加对其消费支出的正向刺激作用更为明显。进一步，相比于高消费农村居民人群，低消费农村居民人群随着收入的增加消费支出上升速度较为缓慢。
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| 关 键 词： | 可加模型 惩罚样条 非参数分位回归 马尔科夫蒙特卡罗算法 |
The Research and Application of Additive Quantile Regression Models for Panel Data |
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| Luo Youxi,Zhang Min,Tian Maozai. The Research and Application of Additive Quantile Regression Models for Panel Data[J]. Statistical Research, 2020, 37(2): 105-118. DOI: 10.19343/j.cnki.11-1302/c.2020.02.009 |
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| Authors: | Luo Youxi Zhang Min Tian Maozai |
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| Abstract: | In the paper,additive quantile regression models for panel data is discussed in the framework of Bayesian analysis.By using penalty spline of low rank thin plate and introducing dummy variables,the nonparametric models are transformed into parametric ones.Then,under the assumption that random error is subject to asymmetric Laplace distribution,a Bayesian hierarchical quantile regression model is established.At the same time,the conditional posterior distribution of all unknown parameters are introduced and a Gibbs sampling algorithm is also proposed to estimate them.The computer simulation results show that the proposed method is more robust than the classical additive mean regression methods.Finally,taking the consumer expenditure panel data as an example,the new method is demonstrated to study the impact of the income structure of our rural residents on consumption expenditure.Some useful new conclusions have been obtained from the model.The empirical results show that for rural residents,whether its consumption is high,medium or low,the positive stimulus effect of wage income and household business income on consumer expenditure is more obvious.Furthermore,compared with high consumption rural residents,the growth rate of consumption expenditure for low consumption rural residents is slower with the increase of income. |
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| Keywords: | Additive Model Penalty Spline Nonparametric Quantile Regression Markov Chain Monte Carlo Algorithm |
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