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ATTRITION BIAS IN PANEL DATA: A SHEEP IN WOLF'S CLOTHING? A CASE STUDY BASED ON THE MABEL SURVEY

机译:面板数据中的偏差:狼在穿衣服上的羊?基于maBEL调查的案例研究

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摘要

This paper investigates the nature and consequences of sample attrition in a unique longitudinal survey of medical doctors. We describe the patterns of non-response and examine if attrition affects the econometric analysis of medical labour market outcomes using the estimation of physician earnings equations as a case study. We compare the econometric gestimates obtained from a number of different modelling strategies, which are as follows: balanced versus unbalanced samples; an attrition model for panel data based on the classic sample selection model; and a recently developed copula-based selection model. Descriptive evidence shows that doctors who work longer hours, have lower years of experience, are overseas trained and have changed their work location are more likely to drop out. Our analysis suggests that the impact of attrition on inference about the earnings of general practitioners is small. For specialists, there appears to be some evidence for an economically significant bias. Finally, we discuss how the top-up samples in the Medicine in Australia: Balancing Employment and Life survey can be used to address the problem of panel attrition.
机译:本文在一次独特的医生纵向调查中研究了样本损耗的性质和后果。我们以医生收入方程的估计为例,描述了无应答的模式,并研究了人员流失是否会影响对医疗劳动力市场结果的计量经济分析。我们比较了从许多不同的建模策略中获得的计量经济学汇总,这些策略如下:平衡样本与非平衡样本;基于经典样本选择模型的面板数据损耗模型;以及最近开发的基于copula的选择模型。描述性证据表明,工作时间更长,经验较少,受过海外培训并且改变工作地点的医生更容易辍学。我们的分析表明,减员对全科医生收入的推断影响很小。对于专家而言,似乎有一些证据表明存在重大的经济偏见。最后,我们讨论了如何在《澳大利亚医学:平衡就业和生活》调查中充值的样本可用于解决小组成员流失的问题。

著录项

  • 作者

    Cheng, TC; Trivedi, PK;

  • 作者单位
  • 年度 2015
  • 总页数
  • 原文格式 PDF
  • 正文语种 English
  • 中图分类

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