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A penalized spline estimator for fixed effects panel data models

机译:固定效果面板数据模型的惩罚样条估计器

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摘要

Estimating nonlinear effects of continuous covariates by penalized splines is well established for regressions with cross-sectional data as well as for panel data regressions with random effects. Penalized splines are particularly advantageous since they enable both the estimation of unknown nonlinear covariate effects and inferential statements about these effects. The latter are based, for example, on simultaneous confidence bands that provide a simultaneous uncertainty assessment for the whole estimated functions. In this paper, we consider fixed effects panel data models instead of random effects specifications and develop a first-difference approach for the inclusion of penalized splines in this case. We take the resulting dependence structure into account and adapt the construction of simultaneous confidence bands accordingly. In addition, the penalized spline estimates as well as the confidence bands are also made available for derivatives of the estimated effects which are of considerable interest in many application areas. As an empirical illustration, we analyze the dynamics of life satisfaction over the life span based on data from the German Socio-Economic Panel (SOEP). An open source software implementation of our methods is available in the R package pamfe.
机译:对于带有横截面数据的回归以及具有随机效应的面板数据回归,已经很好地建立了通过罚样条估计连续协变量的非线性效应的方法。惩罚样条曲线是特别有利的,因为它们既可以估计未知的非线性协变量效应,又可以对这些效应进行推论。后者例如基于同时置信带,该置信带为整个估计函数提供了同时不确定性评估。在本文中,我们考虑固定效果面板数据模型,而不是随机效果规范,并针对这种情况下的点线样条线的包含方法开发出一阶差分方法。我们考虑了所得的依存关系结构,并相应地调整了同时置信带的构造。此外,还可以将惩罚样条估计以及置信带用于估计效果的导数,这在许多应用领域中引起了极大的兴趣。作为经验例证,我们根据德国社会经济专家组(SOEP)的数据分析了整个寿命期内生活满意度的变化。 R包pamfe中提供了我们方法的开源软件实现。

著录项

  • 作者

    Pufctz Peter; Kneib Thomas;

  • 作者单位
  • 年度 2016
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
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