UNIVERSITE LIBRE DE BRUXELLES
Faculté des Sciences Sociales, Politiques et Economiques
Année académique 2006-2007
Wage Inequalities in Europe: Influence of Gender and Family Status
A series of empirical essays
Thèse présentée en vue de l’obtention du grade de Docteure en Sciences Economiques par
Salimata SISSOKO
Sous la direction du Prof. Robert Plasman
Members of the Jury
Thesis director: Prof. Robert Plasman (Université Libre de Bruxelles)
Restricted jury: Prof. Nabanita Datta Gupta (Danish National Institute of Social Research)
Prof. Catherine Dehon (Université Libre de Bruxelles) Prof. Maria Jepsen (Université Libre de Bruxelles)
Prof. François Rycx (Université Libre de Bruxelles)
I
Remerciements
Je tiens à exprimer toute ma reconnaissance à Robert Plasman, mon directeur de thèse, pour m'avoir proposé ce sujet de recherche, son soutien et ses jugements très pertinents sur mon manuscrit, tant sur le fond que sur la forme tout au long de ma thèse. Je tiens à témoigner ma reconnaissance à, par ordre alphabétique, Nabanita Datta Gupta, Catherine Dehon, Maria Jepsen et François Rycx, pour m’avoir fait l'honneur d'accepter de faire partie de mon jury de thèse.
Je remercie tous les chercheurs, académiques et membres du personnel du Dulbéa pour leur amitié et leur aide pendant ces quelques années de thèse. Mes remerciements vont également au Dulbéa en tant que centre de recherche dans lequel il a été mis à ma disposition d’excellentes conditions logistiques et financières.
Mes plus chaleureux remerciements vont à mes amis les plus chers, qui se reconnaîtront ici, pour les discussions entourant les travaux de cette thèse et pour leur soutien moral qu’ils m’auront fourni tout au long de la réalisation de ces travaux.
Je termine par un grand remerciement à mes parents et à mes sœurs auxquels je dédie
cette thèse.
II
III
Table of Contents
Introduction... 1
Chapter I: The Gender Wage Gap in an International Perspective ... 19
1.1 Introduction ... 19
1.2 The Data... 24
1.3 The wage structure and the gender wage gap... 27
1.4 Methodology... 30
1.4.1 Oaxaca and Binder (1973) decomposition... 30
1.4.2 Taking the wage structure into account, the Juhn-Murphy-Pierce (1991) decomposition... 32
1.4.3 Application of Oaxaca-Blinder’s decomposition method to cross-national comparisons of the gender pay gap ... 33
1.4.4 Taking occupational segregation into account: the Brown, Moon and Zoloth (1980) decomposition... 34
1.5 Results... 36
1.5.1 The effect of human-capital characteristics ... 36
1.5.2 The wage structure... 38
1.5.3 Occupational segregation ... 45
1.6 Conclusions ... 49
Appendix I. ... 53
Chapter II: Does unobserved heterogeneity matter? A Panel-data Analysis of the Gender Pay Gap ... 58
2.1 Introduction ... 58
2.2 Data and Descriptive statistics ... 62
2.3 An overview of the gender wage gap in Europe ... 65
2.4 Estimation Method ... 67
2.4.1 Wage Equations ... 67
2.4.2 Cross-section and Panel-data Decompositions ... 70
2.5 Results... 73
2.5.1 The wage equations ... 73
2.5.2 Cross-section decomposition over time... 75
2.5.3 The effects of accounting for individual heterogeneity on the adjusted gender pay gap... 79
2.6 Conclusion ... 83
Appendix II.1: Descriptive statistics ... 85
Appendix II.2: Wage equations ... 87
Chapter III: The Wage Effect for Mothers of Young Children in the Household.
Mean and quantile regressions applied to ten EU-Member states... 90
IV
3.1 Introduction ... 91
3.2 Theoretical background ... 94
3.3 Empirical background... 98
3.4 Methodology... 102
3.4.1 Introduction to quantile regression ... 102
3.4.2 The methodology used in the first stage of this analysis ... 105
3.4.3 The methodology used in the second stage of this analysis ... 108
3.4.4 Correcting for selection bias... 111
3.5 Data and sample selection ... 113
3.6 Descriptive statistics ... 115
3.7 Results... 123
3.7.1 Correcting for self-selection... 123
3.7.2 Human capital, occupational and sectoral segregation and the wage penalty/bonus for young mothers ... 124
3.7.3 Human capital, occupational and sectoral segregation and the wage penalty/bonus for old mothers ... 127
3.7.4 The family pay gap and family policies... 129
3.7.5 The wage penalty/bonus along the wage distribution ... 134
3.7.6 A Young mothers... 136
3.7.7 B Old mothers ... 142
3.8 Conclusion ... 143
Appendix III. ... 147
Chapter IV: Is There a Lone Motherhood Wage Penalty in Europe? ... 155
4.1 Introduction ... 155
4.2 (Lone) Motherhood in Europe... 161
4.3 Data ... 163
4.4 Methodology... 166
4.5 Results... 167
4.5.1 Lone motherhood wage penalty and differential selection in employment... 167
4.5.2 Elements of the welfare generosity and childcare provisions that can explain the lone mother pay differentials... 172
4.5.3 Effect of young children on the lone motherhood pay gap... 173
4.5.4 Lone motherhood wage penalty and unobserved heterogeneity ... 176
4.5.5 Quantile analysis of the wage gap associated with lone motherhood... 179
4.6 Conclusion ... 184
Appendix IV. ... 187
Conclusion ... 192
References... 202
V
Liste of Tables
Table 1: Provision of childcare in Europe in 2003... 14
Table 2: Maternity and paternity leave duration and payment (2003)... 18
Table 3: Average hourly gender wage gap, 1995... 27
Table 4: Wage setting systems, 1994 ... 29
Table 5: Oaxaca decomposition in Europe ... 37
Table 6: Cross-country differential decomposition (Juhn, Murphy and Pierce), Belgium as reference country ... 40
Table 7: Cross-countries differential decomposition (Oaxaca), Belgium as reference country ... 43
Table 8: Distribution by Occupation ... 46
Table 9: Gender segregation indexes by 1-Digit Occupation... 47
Table 10: Brown, Moon and Zoloth decomposition ... 48
Table 11: Average gender wage gap in European countries, 1994 and 2001... 64
Table 12: Cross-section decomposition, Oaxaca (1973), 1994 and 2001... 77
Table 13: Panel-data decomposition, Oaxaca (1973), 1994 and 2001... 79
Table 14: Adjusted gender pay differentials, gender coefficients (std. error in parentheses) ... 81
Table 15: Reduction of the adjusted gender pay gap and gender differences in education and experience ... 83
Table 16:Descriptive statistics for mothers (young and old) and non-mothers... 116
Table 17: The wage effect of the presence of young children for young mothers... 124
Table 18: The wage effect of the presence of old children for old mothers ... 128
Table 19: Scores of the raw family pay gap of young mothers and the three measures of family policy... 131
Table 20: Estimates of the family policies indexes on the family pay gap... 133
Table 21: Effect of the share of mothers in high/low paid occupations on glass ceiling/sticky floors... 139
Table 22: Estimates of wage dispersion on the family pay gap ... 141
VI
Table 23: Employment rates of lone and partnered mothers... 169
Table 24: Raw pay gap by family status with/without correction for sample selection bias, GLM
1... 171
Table 25: Estimates of the family policies indexes on the family pay gap... 173
Table 26: Lone motherhood pay gaps of mothers who have and have no child under 6 in their household ... 175
Table 27: GLM and fixed-effect estimation of the lone motherhood pay gap ... 177
Table 28: Raw Pay Gap by family Status ... 181
Table 29: Lone motherhood pay gap with the restricted model ... 181
Table 30: Lone motherhood pay gap with the full model... 182
Liste of Figures
Figure 1: Gender pay differentials in Europe, 1998... 2
1
Introduction
The achievement of gender pay equality has become a central topic on the policy agendas of many countries under the directive of the European Union. Before this, labour economists had taken a deep interest in the estimated gender pay gap and the identification of the elements that shape this wage differential between men and women.
As a result of this interest, substantial literature exists on the issue.
For many years, all Member States have complied with the EC obligation under Article
119 of the Treaty of Rome (now Article 114 EC) that establishes the principle of equal
pay for equal work. Since then this principle has been developed by a number of EU
Directives that extend the concept of equal pay for work of equal value, guarantee the
right to equal treatment in the workplace (that is, access to employment, vocational
training, promotion and working conditions), and provide equal treatment of women and
men with respect to both statutory social security and occupational social security (Rice,
1999). In addition, since 1999 tackling the gender pay gap has been part of the European
Employment Strategy. In 2003 Member States were encouraged to produce quantitative
and qualitative targets in this respect “in order to achieve by 2010 a substantial reduction
in the gender pay gap in each Member State through a multi-faceted approach
addressing the underlying factors of the gender pay gap including sector and
occupational segregation, education and training, job classifications and pay systems,
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awareness raising and transparency” (Plantenga and Remery, 2006). Nevertheless, we continue to observe pay differentials between work of equal value without significant evidence of improvement.
What do we mean by gender pay gap? And what are its scale and variation across European countries?
Most commonly, the gender pay gap refers to the difference between the mean gross hourly earnings of male and female employees, expressed as a percentage of men’s mean gross hourly earnings.
Figure 1: Gender pay differentials in Europe, 1998
Note: sample of employees working more than 15 hours per week in the private and public sector.
Source: Eurostat, European Community Household Panel, 1998
0 10 20 30 40 50 60 70 80 90 100
PT BE IT DK FR EL ES UE DE IRL NL AT UK
3
Figure 1 shows that, on average, mean gross hourly earnings for female employees are just 83.8% of male employees’ earnings in Europe, resulting in a gender pay gap in hourly earnings of 16.2%. Only in three Member States – Italy, Belgium and Portugal - are the average hourly earnings higher than 90% of those of male employees.
The reasons for the existence of a gender pay gap are complex, being influenced by factors in the domestic, social and employment arenas. However, the most common cited causes in the literature are related to the human capital theory, the wage structure, domestic responsibilities (home and childcare responsibilities), the level of equality legislation and its limited effectiveness or discrimination.
It is widely agreed that there exist differences in the acquired abilities of men and women. These abilities are proxied by the acquisition of educational and vocational qualifications and labour market experience. Nowadays, in most countries, women have higher educational qualifications than men, though not in the most valued fields of study as technology, engineering or science
1. The differences in educational attainment and field of education are diminishing among younger generations, as a result of the opening up of higher education and delayed childbirth among women. However, private and family responsibilities, and the greater propensity of women to work part-time, lead to women not acquiring skills and experience at the same rate as men. Therefore, their stock of accumulated work experience is, on average, lower than that of male employees.
1 Eurostat, NewCronos.
4
Besides these differences in human capital, several studies have shown that a part of the pay gap can be attributed to the segregation of employment by gender. One component is the confinement of women in a restricted number of jobs at lower levels of the occupational hierarchy. To a certain extent, inter-occupational wage differentials reflect differences in human capital. However, they also reflect heterogeneous preferences for particular types of work or field of study. They can also be accounted for by the societal pressures or by the glass ceiling that hinders women from reaching the highest positions even when they have the capabilities to do so (discrimination in appointments and promotions procedures and other employment practices). Another component of occupational segregation is the undervaluation of women’s work in female-dominated occupations. Some studies have shown that both men and women earn less if they work in female-dominated jobs, all else being equal. There are different possible explanations why female-dominated jobs could offer lower wages. Some suggest that ‘female’ skills are under-valued in the labour market because of the association with domestic production. The “crowding” model suggests that the labelling of “men’s” and “women’s”
jobs leads women to be crowded into female-dominated occupations or excluded from male-dominated occupations (or both). This causes the wage offered in the crowded occupations to decrease because of the labour surplus generated, even if both types of employment require the same level of qualifications.
In addition to differences in individual and job characteristics, the gender pay gap may
also be related to the overall structure of wages. It is well known now, that concentrated
5
wages and the introduction of the minimum wage potentially improves the earnings of women especially those who are less qualified. Blau and Kahn (1992 and 1996) have found a positive correlation between the size of the gender pay gap and the degree of wage dispersion. This is not surprising since we know that women are over-represented at the bottom end of the wage distribution. Therefore in a concentrated wage structure, the penalty attached to holding a relative low paid position is not as great so the gender pay differential tends to be narrower. The wage structure is influenced by the bargaining system. Countries with centralised wage bargaining present fewer wage inequalities than other countries. The reasons are first that centralised systems reduce inter industry and inter firm wage variations. In this way, these systems are more likely to reduce such disparities, ceteris paribus. Secondly, given that women’s wage distribution is below that of men, centralised systems, which increase minimum wages irrespective of gender, also produce fewer disparities. Finally, the impact of specific gender policies, which aim at increasing the women’s wage, may be more efficient in centralised systems. When analysing the relationship between wage bargaining systems and the gender wage gap, one has also to take into account the extent of the bargaining system. In fact, even a centralised system would have fewer effects if it covered only a small number of workers. Usual indicators of the extent of the bargaining system are the degree of unionisation, the collective bargaining coverage, level of centralisation and coordination.
In many countries, mandatory and voluntary extension mechanisms extend the results of
collective agreements between unions and employers to non-unionised workers and
firms. The formal coverage of the collective bargaining system in most EU Member
States has remained high over the past decade. The UK is the main exception where by
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2000 the coverage has fallen to 42 per cent (Rubery et al., 2002). Over the past decade the trend in most Member States has been towards more decentralisation of pay, fragmentation of wage determination and reduction of the relative value of the minimum wage. These current trends tend to increase the gender pay gap.
In the first chapter of this thesis, we investigate the impact of human capital and wage structure on the gender pay in a panel of European countries using a newly available and appropriate database for cross-country comparisons and a comparable methodology for each country.
Our first question is : What role do certain individual characteristics and choices of
working men and women play in shaping the cross-country differences in the gender pay
gap? What is the exact size of the gender pay gap using the “more appropriate” database
available for our purpose? Giving that there are mainly only two harmonized data-sets for
comparing gender pay gap throughout Europe: the European Community Household
Panel (ECHP) and the European Structure of Earning Survey (ESES). Each database
having its shortages: the main weakness of the ECHP is the lack of perfect reliability of
the data in general and of wages in particular. However the main advantage of this
database is the panel-data dimension and the information on both households and
individuals. The data of the ESES is, on the contrary, of a very high standard but it only
covers the private sector and has a cross-sectional dimension. Furthermore only few
countries are currently available : Denmark, Belgium, Spain, Ireland and Italy.
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We use the European Structure of Earning Survey (ESES) to analyse international differences in gender pay gaps in the private sector based on a sample of five European economies: Belgium, Denmark, Ireland, Italy and Spain. Using different methods, we examine how wage structures, differences in the distribution of measured characteristics and occupational segregation contribute to and explain the pattern of international differences. Furthermore, we take account of the fact that indirect discrimination may influence female occupational distributions. We find these latter factors to have a significant impact on gender wage differentials. However, the magnitude of their effect varies across countries.
The answer to this first question considers the gender pay gap of five European countries at a specific moment in time, the year 1995, and assesses the role of a certain observed heterogeneity in productive characteristics between men and women, brings us to our second question. The human capital model, we estimate don’t take into account the questions of application and effort intensity. So indicators of abilities only act as an imperfect proxy for productivity – which is what we really want to measure.
In the second chapter, we analyse the persistence of the gender pay differentials over
time in Europe and better test the productivity hypothesis by taking into account
unobserved heterogeneity.
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Our second question is : What is the evolution of the pay differential between men and women over a period of time in Europe? And what is the impact of unobserved heterogeneity?
The researcher here provides evidence on the effects of unobserved individual heterogeneity on estimated gender pay differentials. Using the European Community Household Panel (ECHP), we present a cross-country comparison of the evolution of unadjusted and adjusted gender pay gaps using both cross-section and panel-data estimation techniques. The analysed countries differ greatly with respect to labour market legislation, bargaining practices structure of earnings and female employment rates. On adjusting for unobserved heterogeneity, we find a narrowed male-female pay differential, as well as significantly different rates of return on individual characteristics. In particularly, the adjusted wage differential decreases by 7 per cent in Belgium, 14 per cent in Ireland, between 20-30 per cent Germany, Italy, the Netherlands and Spain and of 41 per cent and 54 per cent in the UK and in Denmark respectively.
In the third chapter, we investigate causes of the gender pay gap beyond the gender differences in observed and unobserved productive characteristics or simply the sex.
Explanations of the gender pay gap may be the penalty women face for having children.
Obviously, the motherhood wage penalty is relevant to larger issues of gender inequality given that most women are mothers and that childrearing remains a women’s affair.
Thus, any penalty associated with motherhood but not with fatherhood affects many
9
women and as such contributes to gender inequalities as the gender pay gap.
Furthermore, the motherhood wage effect may be different along the wage distribution as women with different earnings may not be equal in recognising opportunities to reconcile their mother’s and earner’s role. This brings us to our third question.
Our third question is : What is the wage effect for mothers of young children in the household? And does it vary along the wage distribution of women?
This chapter provides more insight into the effect of the presence of young children on
women’s wages. We use individual data from the ECHP (1996-2001) and both a
generalised linear model (GLM) and quantile regression (QR) techniques to estimate the
wage penalty/bonus associated with the presence of children under the age of sixteen for
mothers in ten EU Member States. We also correct for potential selection bias using the
Heckman (1979) correction term in the GLM (at the mean) and a selectivity correction
term in the quantile regressions. To distinguish between mothers according to their age at
the time of their first birth, wage estimations are carried out, separately, for mothers who
had their first child before the age of 25 (‘young mothers’) and mothers who had their
first child after the age of 25 (‘old mothers’). Our results suggest that on average young
mothers earn less than non-mothers while old mothers obtain a gross wage bonus in all
countries. These wage differentials are mainly due to differences in human capital,
occupational segregation and, to a lesser extent, sectoral segregation between mothers
and non-mothers. This overall impact of labour market segregation, suggests a
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“crowding” explanation of the family pay gap – pay differential between mothers and non-mothers. Nevertheless, the fact that we still find significant family pay gaps in some countries after we control for all variables of our model suggests that we cannot reject the
“taste-based” explanation of the family gap in these countries. Our analysis of the impact of family policies on the family pay gap across countries has shown that parental leave and childcare policies tend to decrease the pay differential between non-mothers and mothers. Cash and tax benefits, on the contrary, tend to widen this pay differential.
Sample selection also affects the level of the mother pay gap at the mean and throughout the wage distribution in most countries. Furthermore, we find that in most countries inter- quantile differences in pay between mothers and non-mothers are mainly due to differences in human-capital. Differences in their occupational and sectoral segregation further shape these wage differentials along the wage distribution in the UK, Germany and Portugal in our sample of young mothers and in Spain in the sample of old mothers.
In the fourth chapter, we analyse the combined effect of motherhood and the family status on women’s wage.
Our fourth question is : Is there a lone motherhood pay gap in Europe? And does it vary along the wage distribution of mothers?
Substantial research has been devoted to the analysis of poverty and income gaps
between households of different types. The effects of family status on wages have been
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studied to a lesser extent. In this chapter, we present a selectivity corrected quantile regression model for the lone motherhood pay gap – the differential in hourly wage between lone mothers and those with partners. We used harmonized data from the European Community Household Panel and present results for a panel of European countries. We found evidence of lone motherhood penalties and bonuses. In our analysis, most countries presented higher wage disparities at the top of the wage distribution rather than at the bottom or at the mean. Our results suggest that cross-country differences in the lone motherhood pay gap are mainly due to differences in observed and unobserved characteristics between partnered mothers and lone mothers, differences in sample selection and presence of young children in the household. We also investigated other explanations for these differences such as the availability and level of childcare arrangements, the provision of gender-balanced leave and the level of child benefits and tax incentives. As expected, we have found significant positive relationship between the pay gap between lone and partnered mothers and the childcare, take-up and cash and tax benefits policies. Therefore improving these family policies would reduce the raw pay gap observed.
All along the thesis, we refer to level of equality legislation and its limited effectiveness
as a potential cause of the continuing gender pay. In particular, equal treatment
legislation which provides the guarantee that an individual will be considered for a job
on an equal basis, even for a job that is traditionally regarded as a male or female role in
order to support and underpin decisions to invest in training or education relevant to the
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chosen career. The equal pay policy ensures a fair return on investments in education
and training and provides for appropriate incentives for the development of skills in jobs
traditionally undertaken by women. Equal pay policy refers to the equal pay legislation
and anti-discrimination laws. The effects of equal treatment and equal pay policies have
had an obvious positive impact on the gender pay gap. However their efficiency depends
on the quality of the measures, their application and, more particularly, on an
organisation's failure to comply with it. Chicha (2006) notes in particular that
organisations seem reluctant to abide by this legislation on account of the salary and
benefits increase that would ensue, and because of perceived potentially negative effects
on their competitive position in the marketplace. Moreover, organisations fear that
compliance with the law may result in a major transformation of the workplace, such as
changes in the present occupational classification system or in pay scales, thus leading to
internal disputes and jeopardizing social peace. Blau and Kahn (1996) also highlight the
fact that, given the importance of occupational and sector segregation, the equal pay
policy, aiming at equal pay for equal work within the same occupation and sector, can
only produce poor results. In contrast, measures enhancing equal opportunities and equal
pay for work of equal value, independent of the occupation, are more likely to succeed. In
addition, the former type of policies asks for shifts in women’s occupational structure,
which may take a long time to implement before any impact is seen on pay. The latter
aspires to increase pay in female-dominated occupations and may have a more significant
effect on wages.
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Another important addendum refers to equal opportunities policy. There is wide recognition in Europe of the importance of social policy in assisting women to reconcile professional, family and private life. Given that gender differences in employment patterns are determinant factors in the gender pay gap, it is important to enable women to have an uninterrupted career. In this respect, policies targeted towards increasing childcare facilities are important. The literature on family policy suggests that improvements in childcare possibilities strengthen a mother's participation and commitment to the labour market. This can be explained by the fact that, on the one hand, the more suitable the childcare provision (availability, accessibility, quality, cost and so forth), the less women will have to adjust their time allocation in favour of the home when children enter the picture (Blau and Ferber, 1992). On the other hand, childcare conditions seem to have a bigger influence on the women’s budget constraints than on their preference to stay at home (Connelly, 1992; Michalopoulos, Robins and Garfinkel, 1992). Therefore, the more costly childcare arrangements are, the lower the mothers disposable income and thus also their labour supply. Reconciliation of work and family has featured much more prominently on the European social agenda over the last decade.
Historically there have been wide-ranging differences across the Member States in both
the nature and the extent of intervention in the area of family policy, however we can
observe certain commonalities. Policy variations should not be surprising, given that
these policies were initiated at different times, they expand at various rates, and the
catalysts for their enactment and growth are diverse (Gornick, 2006). At the Barcelona
summit in 2002, targets were set with regards to childcare. Member States should provide
by 2010 to at least 90 per cent of children from the ages of 3 years until the mandatory
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school age and at least 33 per cent care for children under 3 years of age. Very few countries provide widely available, affordable childcare. Of those that do, childcare is considered as a social right and heavily subsidised places are offered. Four Nordic countries have framed childcare as a social right (Denmark, Finland, Iceland and Sweden): when the child reaches a certain age, parents have a guarantee of a childcare place. Table 1 shows that only five European countries (EU-15) have met the Barcelona target of 33 per cent childcare for children under three.
Table 1: Provision of childcare in Europe in 2003
Childcare coverage 0-3 years
Daily opening hours 0-3
1Childcare coverage 3-compulsory
Public expenditure on
formal day care as % of
GDP
Belgium (Flanders) 81% 100%
Belgium (French) 33% 8
98% 0.1%
Denmark 56% 10 to 12 93% 1.7%
Germany 7% 9 89% 0.4%
Greece 7% n.a. 60% 0.4%
Spain 10% n.a. 98% 0.1%
France 43% 8 to 10 100% 0.7%
Ireland n.a. n.a. n.a. 0.2%
Italy 6% 8 93% n.a.
Luxembourg 14% 8 80% n.a.
Netherlands 35% 8 100% 0.2%
Austria 9% 8 82% 0.4%
Portugal 19% 4 to 11 75% 0.2%
Finland 21% 8 to 10 70% 1.2%
Sweden 41% 8 90% 1.3%
United Kingdom n.a. 5 n.a. n.a.
Source: Plantenga et Remery (2005), Eurostat – 1 Hélène Pévrier (2004), figures of 2000.
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This coverage rate is particularly notable in Denmark and in the Flemish part of Belgium.
France, Sweden, The Netherlands and the French part of Belgium also score rather favourably. Several countries score fairly low; their coverage rate not reaching 10 per cent. In the countries where available and affordable childcare places are limited, it can be a significant barrier for labour market participation especially for low-income families.
The Barcelona target of 90 per cent is reached or almost reached in 8 countries: Belgium, Denmark, Germany, Spain, France, Italy, The Netherlands and Sweden. Plantenga and Remery (2005) note that a relative low coverage rate does not necessarily mean shortages in supply of childcare facilities but may indicate alternative ways of looking after children such as parental leave provision.
Besides childcare, family leave facilities are another important part of reconciliation
policy. EU legislation has set minimum levels of provision in respect of maternity and
parental leave, but in many countries, national provision predates EU requirements and is
significantly more generous. The EU maternity leave Directive (1992) entitles all women
to a statutory entitlement of 14 weeks continuous paid leave and the right to return to the
same or equivalent job. Since June 1996, a EU directive has ensured that a minimum
standard is guaranteed within the Member States regarding parental leave. This provides
for up to three months of unpaid leave on the grounds of the birth or adoption of a child
for each parent, and the right of an individual to return to the same, or an equivalent job,
following their leave (Rice, 1999). The Family leave legislation settles the entitlement but
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also provides the right not to be discriminated against on grounds of maternity and the right to return to the same or equivalent job.
The effect in terms of the gender pay gap is more complicated though. On the one hand, the availability of well-organised provisions to facilitate motherhood, offering high replacement incomes may raise the relative earnings of women by simplifying their return to employment and increase their incentive to invest in job-specific training after childbearing (Trzcinski, 1991). On the other hand, it is recognised that the availability of long leave entitlements may limit female participation rates and damage future career and on-the-job training opportunities, which in turn will decrease their earning capacity in the long run. Yet, Rice (1999) notes that if parental leave is an entitlement of the family, rather than the individual, and the levels of benefits paid are relatively low, these arrangements tend to institutionalise an interrupted employment pattern for married women and reinforce their role as secondary wage earners. Arrangements for childcare leave, be it maternity and/or parental leave, risk jeopardising women’s long-term employment prospects if they are not supported by extensive provision of affordable childcare. The effects of long-term parental leave rights have mixed consequences for gender equality mainly because they are taken overwhelmingly by women.
There is a broad range of differing national regulations on maternity, paternity and family
leave within countries regarding replacement rates, duration and entitlements. Maternity
leave is common and, in nearly all countries, mothers are granted a substantial degree of
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economic security during some or all of the first year after childbirth. Furthermore, the benefits that can be claimed by parents (maternity and family leave combined) vary substantially, with the approximate duration of full-time pay ranging from as little as just over one month to nearly a year. In addition, the length of the effective leave that can be claimed (maternity and parental, paid and unpaid) also varies extensively, from less than a year to nearly four years. Finally, most countries allow for some flexibility in the take- up of leave, i.e., parents may take their leave until their children turn three, five, or even eight; and several allow parents to combine pro-rated leave with part-time employment (Gornick, 2002). Table 2 compares the length of the leave period with the level of wage entitlement for maternity and paternity leave. All Member States excluding Germany offer a longer leave than that set forward by the EC. In particular, Denmark and Sweden offer 18 weeks of maternity leave (at about two-thirds pay). The continental countries, overall, offer about three to five months of maternity leave, also on almost full pay. The two English-speaking countries – Ireland and the UK – offer paid maternity, but no paid paternity, leave. And as far as the British maternity leave is concerned provisions are limited when compared with a cross-national perspective. The Southern European countries offer longer and fully entitled leave. De Henau et al. (2006) note particularly that leave policy is maybe the only dimension of family policy where these countries appear somewhat effective as regards their commitment to the female labour market.
Very few countries offer real opportunities for fathers to take up paternity leave. In these
countries, the leave varies between five days in Portugal (fully compensated) and
eighteen working days in Finland (fully compensated). In most countries, the low level of
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compensation discourages fathers from taking either part or all of their leave allowance.
In Denmark, only 58 per cent of those eligible took paternity leave in 2003. In France, Finland and Sweden, where the system is more financially rewarding, 68 per cent, 68 per cent and 75 per cent respectively took leave in 2002, while in Belgium virtually all eligible fathers exercised their right in 2005 (De Henau et al., 2006).
Table 2: Maternity and paternity leave duration and payment (2003)
AT 0 IT 21.7 DE 100% FI 18 EL 100%
FI 0 DK 18 EL 100% FR 14 ES 100%
IT 0 IE 18 ES 100% BE 10 FR 100%
NL 0 SE 18 FR 100% DK 10 LU 100%
UK 0 UK 18 LU 100% SE 10 NL 100%
DK 21 FI 17.5 NL 100% PT 5 PT 100%
DE 84 PT 17.1 AT 100% ES 2 FI 100%
ES 180 EL 17 PT 100% LU 2 BE 87%
BE 183 ES 16 IT 80% NL 2 SE 80%
LU 183 FR 16 SE 80% EL 1 DK 51%
PT 183 LU 16 BE 77% DE 0 DE 0%
SE 183 NL 16 IE 70% IE 0 IE 0%
EL 200 AT 16 FI 66% IT 0 IT 0%
IE 273 BE 15 DK 62% AT 0 AT 0%
FR 304 DE 14 UK 49% UK 0 UK 0%
Paternity leave period (working
days) Maternity leave
period (weeks) Qualification
period (days)
Average replacement rate
(%) Average
replacement rate (%)
Note: BE stands for Belgium, DK for Denmark, DE for Germany, EL for Greece, ES for Spain, FR for France, IE for Ireland, IT for Italy, LU for Luxembourg, NL for the Netherlands, AT for Austria, PT for Portugal, FI for Finland, SE for Sweden, UK for the United Kingdom. These country codes are used in the whole document.
In the UK, all female employees are entitled to eighteen weeks but those women who have been employed for one year by the same employer are entitled to twenty-nine weeks compensated at 90 per cent of their earnings for six weeks and at a flat-rate for a further twelve weeks (Moss and Deven 1999).
Key to read the table: in Belgium, in 2003, maternity leave lasted for fifteen weeks during which wages are replaced at 77 per cent on average; there is a ten-day paternity leave paid at 87 per cent of the father’s wage.
Source: De Henau et al. (2006)
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Chapter I: The Gender Wage Gap in an International Perspective
1.1 Introduction
Abundant literature exists on the causes of gender wage differences. The main (quantitative) analytical approaches to the gender pay gap seek to account for the contribution made by human-capital variables, the shape of the wage distribution and the degree of occupational segregation.
The first explanations date from the early 70s and are based on both Mincer and Polachek’s (1974) human-capital theory and on Becker’s (1971) discrimination theory.
According to Mincer and Polachek (1974), gender wage gaps are due to endowment differences in individual characteristics. Women invest less in human-capital because, firstly, they anticipate career breaks they will take throughout their working life.
Secondly, women take into account the fact that, because of their family responsibilities,
their professional career could be shorter than that of men. Becker (1971) argues that
economic agents belonging to a specific group can have discriminatory preferences
against members of another group. If hiring a person of a discriminated group implies an
additional psychological cost for the employer, then the employer will probably want to
20
be compensated for this added burden and will offer a lower wage to these workers.
Therefore, the discriminated group will have to accept a wage lower than that of other groups of employees.
The Oaxaca-Blinder (1973) decomposition technique emerges from a combination of both of the above theories. The gender wage gap is, indeed, decomposed into two effects:
on the one hand, the effect of differences in characteristics between men and women, and on the other hand, the effect of discrimination against women on the labour market.
Oaxaca (1973) shows, using US wage data, that personnel characteristics (such as education, experience, number of children, occupation, sector, part-time work, marital status, region, and so on.) explain 42 per cent of the gender pay gap of whites and 44 per cent of that of blacks. Contemporary applications of Oaxaca-Blinder techniques are numerous (see Asplund et al., 1993; Langford, 1995; Le Grand, 1991; Plasman et al., 2002a; Beblo et al., 2003). They all find that a significant part of the pay gap would remain even if male and female workers had similar characteristics. Generally speaking, the variables with the most explanatory power are sector, occupation and (potential) experience. Additionally, Oaxaca (1973) notes that the controls for occupation can
“eliminate some of the effects of occupational barriers as sources of discrimination. As a result, we are likely to underestimate the effects of discrimination”.
The recent literature on gender disparities has revealed some new facts. This literature
considers an important factor: the wage structure. The wage structure may be
characterised by various elements, the collective bargaining structure is one of the most
21
important elements. Some authors such as Blau and Kahn (1996) have shown that centralised bargaining enhances gender wage gap reduction. The main reason is that such centralisation tends to reduce the wage differences between sectors and firms. In addition, centralised bargaining has a tendency to fix a minimum wage for all workers. As women are, on average, at the lower end of the wage ladder than men are, these systems, by reducing wage dispersion, also reduce the gender wage gap.
Juhn, Murphy and Pierce (1991, 1993) have proposed an innovative model for wage decomposition that control for the wage structure. This model measures the evolution of the return to workers’ (un)observed individual characteristics. According to these authors, the increasing wage inequalities in the USA can be explained by the growth in the return to (un)observed individual characteristics. As women are generally less qualified and less numerous in high paid sectors, they are pushed to the bottom of the wage distribution.
Applying the same methodology, Blau and Kahn (1992) have analysed the factors that
explain cross-national differences in gender pay differentials. They show that country
differences in wage structure are important in explaining international differences in the
gender pay gap. US women present favourable productivity-related characteristics
compared to women in other countries. Paradoxically, the level of wage inequality
widens the gender pay gap in the US compared to all other countries analysed. Datta
Gupta, Oaxaca and Smith (2001) use the technique of Juhn et al. (1991, 1993) to compare
trends in the gender wage gap between the U.S. and Denmark over the period from 1985
to 1995. They find that the stagnation of the Danish gap is due to unfavourable wage
structure, selection bias and a ranking effect while these factors are more favourable for
22 US women.
Female occupational segregation further influences wage differentials between genders.
Bergmann (1989) tried to explain differences in employment structure based on the discrimination theory, According to this author, when women are rejected in certain male occupations, they move towards typically female ones. This trend causes the wage offered in these occupations to decrease because of the labour surplus generated, even if both types of employment require the same level of qualifications. The theory of occupational choices states that women are inclined to move towards these kinds of jobs.
An analysis in terms of indirect discrimination identifies whether offering lower wages to women who are working in low qualified female occupations is fair or whether it is the result of entry barriers in the best-paid and qualified occupations, thus causing discrimination.
Brown et al. (1980) have developed a method of decomposition of the gender wage
differential that isolates the part of the gap which is due to differences in occupational
segregation between women and men. Using a model of occupational attainment, Brown
et al., simulate the female distribution in case of non-discrimination: the case where
female occupational attainment structure is the same as men’s. Their findings show that
the concentration of women in low pay occupations is not just a matter of levels of
human-capital. Further, Kidd and Shannon (1996) apply the same methodology and find
that when the occupation is treated as exogenous, the ‘explained’ part of the gender pay
gap increases with the level of occupational aggregation while this latter factor has little
23
effect on the pay gap when occupation is treated as endogenous.
Thus as noted above, the current literature has already presented many results on the size and the structure of the gender pay gap in different countries. This chapter comes within the scope of this literature and makes an original contribution to this topic by ascertaining how much of the differences in gender pay gaps across a sample of European countries can be explained by human-capital variables, the shape of the wage distribution and the degree of occupational segregation based on unique micro-databases that allow cross- country comparisons of results. The data used are the 1995 European Structure of Earnings Surveys, which were available for Belgium, Denmark, Spain, Italy and Ireland within the framework of the project Pay Inequalities and Economic Performance (PIEP) financed by the European Commission. In fact, very few studies on international comparisons of the gender pay gap are based on comparable databases that allow both the application of the most suitable econometric techniques and the extraction of reliable cross-country comparisons
2. In line with the literature, our findings indicate that there are significant differences in the extent as well as in the structure of the gender pay gap across EU member countries.
The remainder of this chapter is structured as follows. The next section describes the sample used in the analysis, and subsequent sections present the theoretical effects of
2 Studies of Plasman et al. (2007), Gannon et al. (forthcoming) and Simón and Russell (2004) have also used the ESES within the framework of the PIEP project to analyse the gender wage gap.
24
wage structure upon the gender wage gap, the estimation techniques and the results.
Finally, the last section presents the conclusions.
1.2 The Data
This study is based on a newly available comparative economic data, the 1995 European Structure of Earnings Surveys (ESES). For many member countries, the database is held at Eurostat in Luxembourg. The Pay Inequalities and Economic Performance (PIEP) project has given us the opportunity to have secure remote access to the micro-data. The PIEP project investigates the relationship between pay stratification and business and employment performance in Europe at the micro level. It is conducted by a multidisciplinary team of academic researchers with support from the European Commission and in close collaboration with Eurostat and the national statistical institutes.
The micro-data of ESES offers distinct advantages compared with other sources that have been available in the past. It uses a common methodology and set of statistical definitions across countries. And it contains a wide range of information, provided by the management of firms, on the individual characteristics of employees (such as sectors, level of wage bargaining, size of the establishment, and so on) and of the establishments in which they work (such as level of education, age, occupation, tenure, sex, and so on).
The analysis covers all the five partner countries of the PIEP project : Belgium, Denmark,
Ireland, Italy and Spain. The surveys are conducted on large representative samples for
25
each country
3. It covers establishments in the private sector employing at least ten workers and with economic activities falling within C to K
4of the Nace Rev. 1 nomenclature.
The dependent variable of the wage equations is the logarithm of hourly wage
5. As far as control variables are concerned, we have chosen to restrict the model as much as possible to a ‘human-capital model’. We have therefore excluded variables such as region, sector, occupation, bargaining regime, and so on. Moreover, we chose not to account for occupation and sector since the literature shows that treating the occupation as exogenous can underestimate the effect of discrimination (Oaxaca, 1973) and have endogenised occupational attainment instead. The independent variables are the number of study years, prior potential experience (in level and squared)
6, tenure in the firm (in level and
3 Size of the different data-sets: Belgian sample: 145,112 individuals, Danish sample: 619,505 individuals, Irish sample: 39,105 individuals, Italian sample: 96,267 individuals and Spanish sample: 177,141 individuals.
4 Mining and quarrying (C), Manufacturing (D), Electricity, gas and water supply (E), Construction (F), Wholesale and retail trade; repair of motor vehicles, motorcycles and personal and household goods (G), Hotels and restaurants (H), Transport, storage and communication (I), Financial intermediation (J), Real estate, renting and business activities (K).
5 It includes overtime paid and bonuses for shift work, night work and weekend work. Pay for holidays, 13th month, arrears, advances, travelling expenses, and so forth are excluded.
6 Potential prior experience is computed as follows: age-years of schooling-start age of schooling.
26
squared), the number of paid hours
7, contract types, firm size and dummy variables for workers without tenure and for overtime. The independent variables of the model of occupational attainment are the number of years of schooling, potential experience and tenure both in level and squared.
Table 3 shows for example that in Belgium the average gross hourly wage was 602.57 Belgian francs for men and at 482.52 Belgian francs for women in 1995. Belgian men thus earn 24.9 per cent more on average than their female counterparts or, said differently, women earn on average 19.9 per cent less than men. The lowest gender pay gap was observed in Denmark at 22.8 per cent and the highest, in Ireland at 51.8 per cent.
These gender differentials are quite important. One explanation is that the ESES survey (1995) is only carried out in the private sector. Other studies (see Rice, 1999) have shown that the public sector employs many highly skilled women and records fewer wage differentials than the private sector. Not taking this wide sector into account certainly affects our results, in the sense of overestimating the wage differentials. Moreover, these descriptive statistics use the female average wage as the reference. This method contrasts
7 We control for the number individual working hours in our wage equations since the literature shows that variation in gross hourly wages may arise from differences in hours worked. Nevertheless, this inclusion may produce a potential endogeneity bias because labour supply decision may depend upon the potential market wage rate. A way to solve this problem would be to use instrumental variables representing the expected working hours of each employee. Unfortunately find appropriate instruments is not an easy task and quite beyond the scope of this chapter so we chose not to account for this potential bias .
27
with most studies in the literature that take the male average wage as the reference and thus tend then to underestimate gender pay differentials.
Table 3: Average hourly gender wage gap, 1995
Average
salary
Male Female Gap1 Belgium 602.57 482.52 24.9%
Denmark 154.30 125.64 22.8%
Spain 1519.48 1087.20 39.8%
Ireland 10.58 6.97 51.8%
Italy 19.94 15.14 31.7%
Note: Formula in national currency: =
( w
m w
f) / w
fwithw
m, the average male wage andw
f , the average female wage Source: ESES 1995, own calculations.
1.3 The wage structure and the gender wage gap
Blau and Kahn (1992 and 1996) have shown that the overall wage structure has an impact
on the gender wage gap. These authors have found a positive correlation between the
level of wage inequality in a country and the size of the gender pay gap. This finding is
not surprising since we know that women are over-represented at the bottom of the wage
distribution. A narrower distribution will then reduce wage disparities between men and
women.
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The wage structure is influenced by the bargaining system. Corporatist countries present smaller wage inequalities than do other countries. There are several reasons for this phenomenon. First, centralised systems reduce variations between sectors and firms and thus are more likely to decrease such disparities, ceteris paribus. Secondly, given that women’s wage distribution is below that of men, centralised systems, which increase minimum wages irrespective of gender, also produce fewer disparities. Finally, the impact of specific gender policies, which aim at increasing women’s wage, could be more efficient in centralised systems.
When analysing the relationship between wage bargaining systems and the gender wage gap, one has to take into account the extent of the bargaining system. In fact, even a centralised system would have fewer effects if only a small number of workers are covered. Table 4 gives some indicators of the extent of bargaining system in each country studied here.
In many countries, mandatory and voluntary extension mechanisms extend the results of collective agreements between unions and employers to non-unionised workers. This is the case in Belgium, Italy and Spain where the extension mechanisms explain the high level of collective bargaining coverage in these countries. The highest level is recorded in Belgium (90%) and the lowest in Ireland (66%).
According to the ranking of Table 4, Denmark can be considered as the most centralised
country of the five. This is due to its centralised procedure of bargains and its high degree
of coordination of wage bargaining. Belgium comes next. Although Italy ranks low in
terms of degree of centralisation, this country benefits from a high level of coordination.
29
In Spain, coordination is average and the State does not interfere in the private sector wage bargaining since it is a somewhat decentralised country. Ireland seems to be the most decentralised and non-coordinated country of our sample
8.
Table 4: Wage setting systems, 1994
Union densitya
Collective bargaining coveragea
Degree of centralisationc
Coordination of wage bargainingb
Degree of coordinationc
bState interference in private-sector wage bargaining
Belgium 54% 90% 10
State-imposed
(SI) 2 SI: Unilateral
regulation
Denmark 76% 69% 14
State-sponsored
(SS) 3 SS: conciliation
Spain 19% 78% 7 Intra-
associational 2 Non-interference
Ireland 46.2% 66% 6
State-sponsored
(SS) 1
SS: Tripartism without authoritative implementation Italy
39% 82% 5
State-sponsored
(SS) 2.5
SS: Tripartism without authoritative implementation
Note: The index of centralization ranges from 1 (decentralization) to 15 (centralization) and that of coordination from 1 (non-coordination) to 5 (coordination).
Sources: a data for 1994, b data for 1994-1996, c data for 1991-1993, Traxler et al. (2001); cNickell and Layard (1999).
It will be shown later in this study that the size of the gender wage gap follows this ranking. We will also confirm that the gender wage gap is influenced by the level of wage inequality in a country.
8 Gannon et al. 2004 note that since the advance of the social partnership and a return to centralised wage bargaining from 1987 it is difficult to measure the level of corporatism in Ireland. However, before that point it would certainly have been reasonable to see Ireland as ranking relatively low on a corporatism index.
