Part-Time Work and the Pay-Gap
While job growth in the European Union from 1991 to 1996 was almost entirely due to an increase in part-time employment, which even compensated for the decrease in full-time employment, this trend has changed with the economic upswing. Since 1997 created employment also includes full-time jobs, and in 1999, for the first time since 1990, the percentage of newly created full-time employment was higher than for part-time employment. The contribution of part-time contra full-time employment to the change in employment from 1994 to 1999 varies strongly across the European Union.
Description
In Austria, Belgium and Germany part-time accounted for the entire employment growth; in Sweden part-time decreased ; and in France and the Netherlands part-time accounted for almost all the growth. The factors governing part-time employment and the attitude of social partners towards part-time employment are bound to have a profound effect on the quality of part-time jobs that are created. There is a difference depending on whether part-time jobs are created in order to help women integrate into the labour market, as has happened in The Netherlands and is currently being promoted in Germany, or whether they are developed to reduce unemployment via work sharing where women are largely present on the labour market in full-time employment as in France.
It could also be argued that for The Netherlands and Germany policies creating good quality low-cost childcare might be a better solution to create incentives for women to enter the labour market.
Nevertheless, it should not be forgotten that women working part-time are heterogeneous in their characteristics and attitudes. Part-time employment for a woman working in a supermarket three hours a day cannot be compared to part-time employment for a woman working in the financial sector who takes Wednesday afternoons off to care for her children.
However, whatever the reason for working part-time or for governments to encourage the creation of part-time jobs, the related costs are high, e.g. lower wage, lower probability of training, less likelihood of promotion, confinement to certain sectors (Meulders et al. 1994, Evans et al. 2001). Just how high some of these costs are and what creates them was the topic of my PhD thesis. Four indicators were investigated. The first three used the ECHP and examined the wage gap between full-time and part-time workers, the probability of being a low paid worker, the level of job satisfaction . Data for Belgium, Denmark and France were used. The last indicator was, via an institutional analysis, to establish the degree to which social security systems influence the number of hours worked.
The current project is meant to elaborate on the work I did on the first indicator namely the wage gap between part-time and full-time workers using the SES data for 1995 and 1999. The first step will be to reproduce for Belgium the econometric estimations I did in my PhD thesis in order to evaluate the robustness of the two data sources. Once the methodology is put in place these estimations will also be conducted for 5 other EU member states using the same data source (Italy, Britain, Denmark, Spain, Ireland).
These estimations will try to answer questions like:
Is there a pay-gap? What causes the pay gap (sectorial and occupational segregation; difference in human capital; discrimination)? Is there a difference in the causes between the countries and if yes why?
Can the different developments and involvement of social partners in the creation of part-time employment in the three countries give a hint as to the impact of the different developments on the quality of part-time employment.
What are the policy implications and how does it fit with the part-time directive?
A second part of the study will concentrate on the impact of rent-sharing on the PT/FT pay gap. In a recent article (Ryxc and Tojerow 2002), the authors find that for Belgium, rent sharing accounts for almost one-third of the gender gap. This last research question will use a unique combination of two large-scale data sets for Belgium, where we have information on firm profit for each individual. The same exercise will be extended to the before mentioned five countries, although using slightly less sophisticated matched data, as the profit will come from a more aggregated data base (NACE 3).
This project has several original elements to it: firstly very few people have access to these data sets (only 4 universities), secondly the rent-sharing theory has never been conducted on the part-time/full-time nexus in a comparative manner, the econometrics which will be applied will be on the very forefront of the state-of-the-art.
The results will be submitted for peer-review at international conferences and international reviews. The results will also be transformed into a more user-friendly style for ETUI use.
This project will be done in collaboration with François Rycx from DULBEA who has access to the data.
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