Gender employment discrimination: Greece and the United Kingdom

Livanos, Ilias; Yalkın, Çağrı; Núñez, Imanol

doi:10.1108/01437720911004443

Cited by 17 publications

(16 citation statements)

References 26 publications

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“…The results mirror the findings of previous studies of the determinants of labour market participation in the Greek labour market (Kanellopoulos and Mavromaras, 2002;Livanos et al, 2009). …”

Section: Wage Decompositionssupporting

confidence: 88%

Educational segregation and the gender wage gap in Greece

Livanos

Pouliakas

2012

Journal of Economic Studies

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PurposeTo investigate the extent to which differences in the subject of degree studied by male and female university graduates contributes to the gender pay gap in Greece, an EU country with historically large gender discrepancies in earnings and occupational segregation. In addition, to explore the reasons underlying the distinct educational choices of men and women, with particular emphasis on the role of wage uncertainty. Design/methodology/approachUsing micro-data from the Greek Labour Force Survey (LFS), Oaxaca-Blinder decompositions are employed to detect the extent to which gender differences in the type of degree studied can explain the male-female pay gap. "Risk-augmented earnings functions" are also used to examine the differential wage premiums offered to men and women in Greece in response to the uncertainty associated with different fields of study. FindingsIt is found that the subjects in which women are relatively over-represented (e.g. Education, Humanities) are also those with the lowest wage returns. Gender differences in the type of degree studied can therefore explain an additional 8.4% of the male-female pay gap in Greece. A potential reason for distinct gender educational choices is that women opt for less uncertain educations that consequently command lower wage premiums in the job market. Practical ImplicationsThe findings suggest that the promotion of gender equality in Greece should pay closer attention to removing informal barriers to entry for women in educational fields traditionally chosen by men (e.g. more effective careers advice, work-experience placements, matching of young girls with professional "mentors").

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Section: Wage Decompositionssupporting

confidence: 88%

Educational segregation and the gender wage gap in Greece

Livanos

Pouliakas

2012

Journal of Economic Studies

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“…40. Livanos et al (2009) provide some evidence that discrimination contributes to lower employment rates of women relative to men's. Figure A1.…”

Section: Growth Enhancing Policy Reforms That Have An Uncertain Impacmentioning

confidence: 98%

Less Income Inequality and More Growth – Are They Compatible? Part 2. The Distribution of Labour Income

Koske

Fournier

Wanner

2012

OECD Economics Department Working Papers

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Less income inequality and more growth-Are they compatible? Part 2. The distribution of labour income This paper explores the role of macroeconomic factors and structural policies in shaping the distribution of labour income. Technological change and globalisation play at least some role in driving inequality patterns, but structural policy can also have an important influence on inequality outcomes, in particular through education and labour market policies. Drawing on empirical analysis of the links between structural policies and the distribution of labour income, the paper looks at potential policy tradeoffs and complementarities with respect to the two policy objectives of lowering income inequality and raising economic growth. It concludes that many policies yield a double dividend in the sense that they contribute to achieving both goals simultaneously. This relates in particular to policies that facilitate the accumulation of human capital, that make educational achievement less dependent on personal and social circumstances, that reduce labour market dualism and that promote the labour market integration of immigrants and women.

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“…In fact, one can find many papers in the literature focusing on unemployment differentials, especially in the case of analysing, for example, racial gaps. See, among others, Sundstrom (1997 and, Blackaby et al (1997 and, Leslie et al (1998), Azmat et al (2006) or Livanos et al (2009). 13 As it is well-known, apart from exogenous and linearly independent covariates and a correct specification, consistency in logit models requires that the error term follows a logistic distribution.…”

Section: Methodsmentioning

confidence: 99%