A Principled Approach to Assessing Missing-Wage Induced Selection Bias

Duo Qin, Sophie Van Huellen, Raghda Elshafie, Yimeng Liu, Thanos Moraitis

Research output: Working paper

Abstract

Multiple imputation (MI) techniques are applied to simulate missing wage rates of nonworking wives under the missing-at-random (MAR) condition. The assumed selection effect of the labour force participation decision is framed as deviations of the imputed wage rates from MAR. By varying the deviations, we assess the severity of subsequent selection bias in standard human capital models through sensitivity analyses (SA). Our experiments show that the bias remains largely insignificant. While similar findings are possibly attainable through the Heckman procedure, SA under the MI approach provides a more structured and principled approach to assessing selection bias.
Original languageEnglish
Place of PublicationLondon
PublisherSOAS University of London
Number of pages29
Publication statusPublished - 1 Jan 2019

Publication series

NameWorking Paper Series
PublisherSOAS University of London
No.216

Keywords

  • wage
  • labour supply
  • selection
  • missing at random
  • multiple imputation

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