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  • Studies on wage discrimination assume that independent observers are able to distinguish a priori which workers are suffering from discrimination. However, this may not be a good assumption when anti-discrimination laws mean that severe penalties can be imposed on discriminatory employers or when unobserved heterogeneity is significant. We develop a wage discrimination model in which workers are not classified a priori. It can be thought of as a generalization of the standard empirical framework, whereas the Oaxaca--Blinder model can be thought of as an extreme case. We propose a finite mixture model to explicitly model unobserved heterogeneity in individual characteristics and estimate the probabilities of being a discriminated or a non-discriminated worker. We illustrate this proposal by estimating wage discrimination in Germany and the UK. (xsd:string)
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  • (SILC) (xsd:string)
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  • EU-SILC-Bibliography (xsd:string)
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  • 2020 (xsd:gyear)
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  • 2020 (xsd:gyear)
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  • 10.1108/S1049-258520200000028008 ()
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  • 187 (xsd:string)
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  • english (xsd:string)
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  • The Measurement of Wage Discrimination with Imperfect Information: A Finite Mixture Approach (xsd:string)
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?:reference
?:sourceCollection
  • Inequality, Redistribution and Mobility (xsd:string)
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  • Bibsonomy (xsd:string)
  • In Inequality, Redistribution and Mobility, edited by Rodríguez, Juan Gabriel and Bishop, John A., 28, 187-204, Emerald Publishing Limited, 2020 (xsd:string)
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  • European Union Statistics on Income and Living Conditions (EU-SILC) (xsd:string)
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  • 2020 (xsd:string)
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  • SILC (xsd:string)
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  • 204 (xsd:string)
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  • 28 (xsd:string)