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Article type: Research Article
Authors: Ritchie, Felixa; * | Veliziotis, Michailb | Drew, Hilarya | Whittard, Damiana
Affiliations: [a] Bristol Business School, University of the West of England, Bristol, UK | [b] Southampton Business School, University of Southampton, Southampton, UK
Correspondence: [*] Corresponding author: Felix Ritchie, Bristol Centre for Economics and Finance, Bristol Business School, University of the West of England, Coldharbour Lane Bristol BS16 1QY UK. Tel.: +44 117 32 81319; E-mail: felix.ritchie@uwe.ac.uk.
Abstract: Identifying genuine underpayment of minimum wages is not straightforward. Some well-known statistical issues affect the measurement of compliance rates, but factors such as processing or behavioural influences amongst respondents can also have an impact. We study the quantitative measurement of non-compliance with the minimum wage, using UK apprentices (who have particularly high non-compliance rates) as a case study. We show that understanding the institutional and behavioural context can be invaluable, as can triangulation of different sources. While the binary nature of compliance makes such problems easier to identify and evaluate, this analysis holds wider lessons for the understanding of the characteristics of large and complex datasets.
Keywords: Minimum wage, non-compliance, measurement error, data qualityJEL codes: C18, C55, C81, C83, J31, J38
DOI: 10.3233/JEM-180448
Journal: Journal of Economic and Social Measurement, vol. 42, no. 3-4, pp. 249-270, 2017
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