Dissertationen zum Thema „Gender differentials“

The first chapter is devoted to the analysis of the interaction between inter-industry wage differentials and the gender wage gap in six European countries, i.e. Belgium, Denmark, Ireland, Italy, Spain, and the U.K. To do so, we have relied on a unique harmonised matched employer-employee data set, the 1995 European Structure of Earnings Survey. As far as we know, this paper is the first to analyse with recent techniques, on a comparable basis, and from a European perspective: i) inter-industry wage differentials by gender, ii) gender wage gaps by industry, and iii) the contribution of industry effects to the overall gender wage gap. It is also one of the few, besides Kahn (1998), to analyse for both sexes the relationship between collective bargaining characteristics and the dispersion of industry wage differentials.

Empirical findings show that, in all countries and for both sexes, wage differentials exist between workers employed in different sectors, even when controlling for working conditions, individual and firm characteristics. We also find that the hierarchy of sectors in terms of wages is quite similar for male and female workers and across countries. Yet, the apparent similarity between male and female industry wage differentials is challenged by standard statistical tests. Indeed, simple t-tests show that between 43 and 71% of the industry wage disparities are significantly different for women and men. Moreover, Chow tests indicate that sectoral wage differentials are significantly different as a group for both sexes in all countries. Regarding the dispersion of the industry wage differentials, we find that results vary for men and women, although not systematically nor substantially. Yet, the dispersion of industry wage differentials fluctuates considerably across countries. It is quite large in Ireland, Italy and the U.K. and relatively moderate in Belgium, Denmark and Spain. For both sexes, results point to the existence of a negative and significant relationship between the degree of centralisation of collective bargaining and the dispersion of industry wage differentials.

Furthermore, independently of the country considered, results show that more than 80% of the gender wage gaps within industries are statistically significant. The average industry gender wage gap ranges between -.18 in the U.K. and -.11 in Belgium. This means that on average women have an inter-industry wage differential of between 18 and 11% below that for men. Yet, correlation coefficients between the industry gender wage gaps across countries are relatively small and often statistically insignificant. This finding suggests that industries with the highest and the lowest gender wage gaps vary substantially across Europe.

Finally, results indicate that the overall gender wage gap, measured as the difference between the mean log wages of male and female workers, fluctuates between .18 in Denmark and .39 in the U.K. In all countries a significant (at the .01 level) part of this gap can be explained by the segregation of women in lower paying industries. Yet, the relative contribution of this factor to the gender wage gap varies substantially among European countries. It is close to zero in Belgium and Denmark, between 7 and 8% in Ireland, Spain and the U.K. and around 16% in Italy. Differences in industry wage premia for male and female workers significantly (at the .05 level) affect the gender wage gap in Denmark and Ireland only. In these countries, gender differences in industry wage differentials account for respectively 14 and 20% of the gender wage gap. To sum up, findings show that combined industry effects explain around 29% of the gender wage gap in Ireland, respectively 14 and 16% in Denmark and Italy, around 7% in the U.K. and almost nothing in Belgium and Spain.

In conclusion, our results emphasize that the magnitude of the gender wage gap as well as its causes vary substantially among the European countries. This suggests that no single policy instrument will be sufficient to tackle gender pay inequalities in Europe. Our findings indicate that policies need to be tailored to the very specific context of the labour market in each country.

The second chapter examines investigates how rent sharing interacts with the gender wage gap in the Belgian private sector. Empirical findings show that individual gross hourly wages are significantly and positively related to firm profits-per-employee even when controlling for group effects in the residuals, individual and firm characteristics, industry wage differentials and endogeneity of profits. Our instrumented wage-profit elasticity is of the magnitude 0.06 and it is not significantly different for men and women. Of the overall gender wage gap (on average women earn 23.7% less than men), results show that around 14% can be explained by the fact that on average women are employed in firms where profits-per-employee are lower. Thus, findings suggest that a substantial part of the gender wage gap is attributable to the segregation of women is less profitable firms.

The third and final chapter contributes to the understanding of inter-industry wage differentials in Belgium, taking advantage of access to a unique matched employer-employee data set covering the period 1995-2002. Findings show the existence of large and persistent wage differentials among workers with the same observed characteristics and working conditions, employed in different sectors. The unobserved ability hypothesis may not be rejected on the basis of Martins’ (2004) methodology. However, its contribution to the observed industry wage differentials appears to be limited. Further results show that ceteris paribus workers earn significantly higher wages when employed in more profitable firms. The instrumented wage-profit elasticity stands at 0.063. This rent-sharing phenomenon accounts for a large fraction of the industry wage differentials. We find indeed that the magnitude, dispersion and significance of industry wage differentials decreases sharply when controlling for profits.

Doctorat en Sciences économiques et de gestion
info:eu-repo/semantics/nonPublished

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.

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.

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.

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 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 “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 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.

Doctorat en Sciences économiques et de gestion
info:eu-repo/semantics/nonPublished