Search results

In this chapter we review the economic literature on the various causes of skills obsolescence and the ways in which skills obsolescence has been modelled or estimated. Most of the literature focuses on skills obsolescence due to atrophy and worker displacements. Skills obsolescence may, however, also be due to the wear of skills, technological and organizational developments, shifts in the structure of employment and organizational forgetting. In the second part of the chapter, we discuss measures for skills obsolescence. Skills obsolescence measures are related to both the cause of skills obsolescence and the way in which it manifests itself.

In our analyses, using data on Dutch tertiary education graduates, we use a direct measure for skills obsolescence based on workers' self-assessment. On average, almost a third of the skills obtained in tertiary education were obsolete seven years later. Skills obsolescence is strongly related to rapid changes in work domain, and to shortcomings in tertiary education. Obsolescence occurs as much in generic as in specific fields of study. It is only weakly related to current skill shortages, and not at all to the prospects for further skill acquisition, wages and investments in additional training.

This paper addresses the long run consequences of skills mismatches generated by innovation for those workers who are not involved in the process of innovation. Skills mismatches are interpreted as indicators of skills obsolescence. We impose the need of specific skills for successful implementation of new technologies in final production. While the work-force has to be compensated by the cost of implementing new technologies the compensation is limited by the productivity of the new design. If the cost of acquiring skills is high relative to the compensation then growth slows down irrespective of the amount of resources devoted to R&D.

The paper analyses skills obsolescence during transition to the market economy, using individual wage data from Hungary, 1986–1999. The link between workers' age composition and firms' productivity is also examined using firm-level information. Transition started with the collapse of demand for unskilled labor and the concomitant improvement in the relative position of skilled workers. At later stages of the transition, when technological change gained impetus, general appreciation of skilled labor stopped. Since 1992 the market value of skills acquired under communism has been falling. Consistent with the wage data, the productivity estimates suggest the devaluation of skills acquired under communism.

This paper examines the impact on the experience-earnings profile of a worker's ageing and of the human capital depreciation due to the obsolescence of schooling in Switzerland. To disentangle the vintage effect from the age effect, we follow the methodological idea proposed by Neuman and Weiss (1995). The results show that vintage effects are relatively pronounced in Swiss manufacturing: there is greater depreciation in the return on experience for better educated workers in both low and high-tech industries, but this depreciation is significantly higher for high-tech workers.

Technological progress renders various skills obsolete, however, the rate of skill obsolescence will vary according to the worker's human capital investments. Workers heavily invested in general skills, such as education, will not suffer high rates of obsolescence, while less-educated workers who invest more in “technology-specific” skills will suffer more when the technology is changed. Consistent with this framework, this chapter demonstrates that increasing randomness is the primary source of inequality growth within uneducated workers, whereas inequality growth within educated workers is determined more by predictable factors. Furthermore, this chapter shows that increasing randomness generates a “precautionary” demand for education.

This paper examines the computer use of older workers from the perspective that the availability of skills is not the only factor relevant for the decision to invest in computers. Using British data, we show that computer use does not depend on age when taking into account wage costs and the tasks to be performed. Older workers embody less computer skills than younger workers, but the relative lack of computer skills does not negatively affect the wages of older workers. Hence, the analysis does not find support for the concern about older workers not being able to cope with computers.