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

• Published in: Health economics Vol. 24; no. 9; pp. 1101 - 1117
• Main Authors: Cheng, Terence C., Trivedi, Pravin K.
• Format: Journal Article
• Language: English
• Published: England Blackwell Publishing Ltd 01.09.2015; Wiley Periodicals Inc
• Subjects: Attrition; Australia; Bias; Case studies; copula; Data Interpretation, Statistical; earnings; Econometrics; Economics, Medical - statistics & numerical data; Female; General Practitioners - economics; General Practitioners - statistics & numerical data; Health economics; Humans; I11; Income - statistics & numerical data; J31; JEL C23; Labor market; Longitudinal Studies; Male; medical doctors; Medicine - statistics & numerical data; Models, Econometric; Physicians; Research Subjects - statistics & numerical data; Studies; Surveys and Questionnaires; Australia; medical doctors; earnings; attrition; copula; I11; J31; JEL C23
• ISSN: 1057-9230; 1099-1050; 1099-1050
• DOI: 10.1002/hec.3206

Summary 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. Copyright © 2015 John Wiley & Sons, Ltd.