Women's Employment - United Nations Research Institute for Social ...

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Women’s employment in the textile manufacturing sectors of Bangladesh and Morocco from the male wage function, and the constant from the male wage function, into the equation estimating the female wage. 10 The coefficients in the final equation show the relative weight of each personal or work-related characteristic in determining the average wage differential. 11 Table 7: Average differential between men’s and women’s wages, using different estimation methods Method Estimate Absolute differential Male wage in Dh 1896 Female wage in Dh 1496 Gross differential -21.12 % Estimated wages from log wage function Male wage in Dh 1519 Female wage in Dh 1163 Gross differential - 23.42 % Estimated differential with theoretical reference wage - 41.20 % Source: Belghazi, 1995a:18; 1995b:26. 2. Results of analysis of wage functions and estimation of gender discrimination in wages Table 7 gives the estimates of wage discrimination using three different methods. The first is simply a comparison of the absolute wage gap between men and women using ENPAU data. The second is the estimation based on log linear earnings functions; and the third is the estimate based on the difference between observed female wages and the theoretical male reference wage. The main implication from this table is that the observed level of discrimination from direct comparisons of male and female wage estimates is lower than the level of discrimination comparing actual female wages with a reference theoretical male wage, controlling for the impact of personal and workforce characteristics by gender. This relates to the earlier observation that the urban female labour force is generally more educated than its male counterpart; so that observed wage differences understate the true extent of discrimination. Sectoral analysis of wage discrimination (see Table 8) shows that it is highly variable, with the highest levels of discrimination occurring 48
Wage discrimination by gender in Morocco’s urban labour force in domestic service, banking and insurance and “other” manufacturing industries (not textiles and clothing), while the lowest levels are recorded for collective services (education and health) and trade as well as textile and garment manufacturing. Interestingly, the most female intensive sectors (textile and garment) appear to have relatively low levels of discrimination. However, this may be because wages are depressed in the sector overall and men in the sector are paid lower wages than they would be in other sectors. On the other hand, as seen above, there is a positive relationship between the rate of female employment in manufacturing sectors and the rate of increase in real wages, which may indicate that employers are recognizing the importance of retaining skilled female workers (Joekes, 1995a). Table 8: Wage discrimination by sector Sector of activity Percentage discrimination Administration - 29.18 Agric., forestry and fisheries -37.08 Textile, clothing, leather -21.06 Other manuf. industries -46.68 Trade -8.46 Hotels and catering -38.69 Banking and insurance -56.90 Domestic service -63.61 Collective services (education and health) -3.35 Total -41.20 Source: Adapted from Belghazi, 1995a:19; 1995b:27. VII. Contribution of different factors in explaining wage levels (male and female) and differentials 12 Three different approaches were used in estimating the overall level and determinants of the gender gap or discrimination in wages. In the first linear multiple regression, a dummy variable for gender was used, which gave a value for the wage differential of Dh 273.52. In other words, men were found to have an advantage of 11.47 per cent over the average total wage, while women have a disadvantage of -3.42 per cent. This, it could be argued, shows the “pure” effect of gender separate from its interaction with various household and work related characteristics (see below). 13 49
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Women’s Employment in the Textile
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This United Nations Research Instit
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Acknowledgements Many people have b
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notwithstanding the inertia of the
Page 11 and 12: Carol Miller is a policy analyst on
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Page 15 and 16: Introduction 1 Introduction 1 Shahr
Page 17 and 18: Introduction Table 1: Basic indicat
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Page 37 and 38: Introduction IV. The case studies T
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Page 47 and 48: Introduction Household Power Relati
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Gender and employment in Moroccan t
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Gender and employment in Moroccan t
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Gender dimensions of labour migrati
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Table 1: Total number of male and f
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Becoming a garment worker 5Becoming
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Becoming a garment worker garment w
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Becoming a garment worker Table 1:
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Becoming a garment worker being. Th
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Becoming a garment worker they firs
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Becoming a garment worker V. Conclu
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Becoming a garment worker is a job
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Becoming a garment worker Endnotes
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Becoming a garment worker Cole P. D
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Women’s employment in the textile
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258 Women’s employment in the tex
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260 Annex Table 2:Level of wages an
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