A Cross-section Analysis of the Fairness-of-pay Perception of UK Employers
AbstractThis paper aims to contribute to the understanding of individuals' fairness perceptions by using cross-section data from the British Social Attitudes Survey to estimate what seem to be the first fairness perceptions-of-pay equations in the literature. The results suggest that, consistent with the existence of discrimination in the labour market, non-white workers perceive their pay as disadvantageously unfair. In contrast, a rather interesting finding is that women's fairness-of-pay perceptions are higher than that of men. The findings suggest that tackling pay alone will not eliminate feelings of underpayment. There is also evidence that with age, workers feel less fairly paid.
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Bibliographic InfoPaper provided by Royal Economic Society in its series Royal Economic Society Annual Conference 2003 with number 162.
Date of creation: 04 Jun 2003
Date of revision:
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fairness perception; pay;
Find related papers by JEL classification:
- C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
- C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
- C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
- J28 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Safety; Job Satisfaction; Related Public Policy
- J71 - Labor and Demographic Economics - - Labor Discrimination - - - Hiring and Firing
- Z13 - Other Special Topics - - Cultural Economics - - - Economic Sociology; Economic Anthropology; Social and Economic Stratification
This paper has been announced in the following NEP Reports:
- NEP-ALL-2003-06-16 (All new papers)
- NEP-CBE-2003-06-16 (Cognitive & Behavioural Economics)
- NEP-LAB-2003-06-16 (Labour Economics)
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