Attrition Bias in Panel Data: A Sheep in Wolf's Clothing? A Case Study Based on the MABEL Survey

Terence Cheng () and Pravin Trivedi

Health, Econometrics and Data Group (HEDG) Working Papers from HEDG, c/o Department of Economics, University of York

Abstract: 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. Descriptive evidence show 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. Estimates from a number of different econometric models indicate that attrition does not have a significant impact on the estimation of physician earnings. We discuss how the top-up samples in MABEL survey can be used to address the problem of panel attrition.

Keywords: Attrition; MABEL longitudinal survey; Medical doctors; Earnings (search for similar items in EconPapers)
JEL-codes: C23 I11 J31 (search for similar items in EconPapers)
Date: 2014-01
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Citations: View citations in EconPapers (2)

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Related works:
Journal Article: Attrition Bias in Panel Data: A Sheep in Wolf's Clothing? A Case Study Based on the Mabel Survey (2015)
Working Paper: Attrition Bias in Panel Data: A Sheep in Wolf’s Clothing? A Case Study Based on the MABEL Survey (2014)
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Persistent link: https://EconPapers.repec.org/RePEc:yor:hectdg:14/04

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