@techreport{49c7eaee8a88459f9e694d69c17a3dbe,
title = "A Principled Approach to Assessing Missing-Wage Induced Selection Bias",
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.",
keywords = "wage, labour supply, selection, missing at random, multiple imputation",
author = "Duo Qin and \{Van Huellen\}, Sophie and Raghda Elshafie and Yimeng Liu and Thanos Moraitis",
year = "2019",
month = jan,
day = "1",
language = "English",
series = "Working Paper Series",
publisher = "SOAS University of London",
number = "216",
address = "United Kingdom",
type = "WorkingPaper",
institution = "SOAS University of London",
}