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Both academia and policymakers express a strong belief in higher average education levels exerting a narrowing impact on wage inequality in general and gender wage gaps in particular. The purpose of this paper is to scrutinize whether or not this effect extends to R&D- and export-intensive branches such as the technology industry.

In exploring the impact of individual and job-related background factors and, especially, of job-task evaluation schemes on the size and change in gender wage gaps in the technology industry, the paper applies an elaborated decomposition method based on unconditional quantile regression techniques.

While changes in standard human capital endowments can explain little, if anything, of the growth in real wages or the widening of wage dispersion among the Finnish technology industry's white-collar workers, a new job-task evaluation scheme introduced in 2002 seems to have succeeded, at least in part, to make the wage-setting process more transparent by re-allocating especially the technology industry's female white-collar workers in a way that better reflects their skills, efforts and responsibilities.

One crucial implication of this finding is that improving the standard human capital of women closer to that of men will not suffice to narrow the gender wage gap in the advanced parts of the economy and, hence, not also the overall gender wage gap. The reason is obvious: concomitant with rising average education levels, other skill aspects have received increasing attention in working life. Consequently, a conscious combination of formal and informal competencies as laid down in well-designed job-task evaluation schemes may, in many instances, offer a more powerful path for tackling the gender wage gap.

While the existing evidence on the impact of performance-related pay on gender wage gaps is still scarce but growing the authors know of no empirical studies analyzing the gender pay-gap effect of job-task evaluation systems.

The objective of this paper is to analyse the role of adverse working conditions in the determination of individual wages and job satisfaction in the Finnish labour market.

The paper uses estimation of econometric models for wages and job satisfaction scores by using the Quality of Work Life Survey of Statistics Finland.

The paper finds that adverse working conditions have a very minor role in the determination of individual wages. In contrast, adverse working conditions substantially decrease the level of job satisfaction and the perception of fairness of pay at the workplace. This evidence speaks against the existence of compensating wage differentials, but is consistent with the view that the Finnish labour market functions in a non‐competitive fashion.

Provides useful information for improvement of working conditions.

Very few papers have analysed the data sets that include, besides wages and job satisfaction scores, detailed information on several different aspects of self‐reported working conditions at the workplace, not just conditions typical of some occupations or industries.