Educational presorting as a cause of occupational segregation

This article concentrates on the measurement of both occupational and educational segre gation between the men and women of the Dutch labour force. The majority of studies which have been conducted in this area are rather one-sided, concentrating on occupational segregation alone. However, occupational segregation can be split into three components. The first component concerns presorting as a consequence of the different educational choices made by boys and girls. The second component concerns postsorting (given their educational status), as a result of the differing occupational choices and opportunities for promotion between men and women during their careers. If men and women with the same educational background are directed towards different occupations, then postsorting may add to the occupational segregation which was already induced by the earlier educational segregation. This kind of postsorting increases the gap between occupational and educational segregation. The third component, which we refer to as reintegration is also a kind of postsorting, narrowing the gap between occupational and educational segregation. This occurs when men with a ''male type'' of education and women with a ''female type'' of education come together in one occupation. Given that educational segregation of the labour force is fixed in the short term, reintegration is the only effective, but probably difficult affirmative action program to reduce occupational segregation in the short term. More usual programs are ineffective and can even be counterproductive. After using the Duncan and Duncan segregation index we construct new segregation indices which measure the relative importance of pre- and postsorting in the occupational segregation more accurately. A more detailed insight into these three components is relevant when choosing the policy instruments needed to achieve equal employment opportunities for men and women.education, training and the labour market;

Computers, Skills and Wages

Computer use is mainly associated with skilled, high-wage workers. Furthermore, the introduction of computers leads to upgrading of skill requirements. This suggests that the computer requires certain skills to take full advantage of its possibilities. Empirical findings, however, suggest that the effects of computers on the labor market are complicated and difficult to trace. This paper offers a simple model and new empirical evidence from Britain showing how computers change the labor market. The model shows that wages are an important determinant of computer use and that neither computer skills nor complementary skills seem to be needed to explain skill upgrading. The empirical results are consistent with the model because they indicate that computer use is explained by wages rather than by skills and that wages are not related to computer skills. Keywords: Wage Differentials by Skill; Computer Use and Skill. JEL Classification: J30; J31.education, training and the labour market;

How computerizaton changes the UK Labour Market: The Facts viewed from a new Perspective

The digitisation of the world as a result of the introduction of computers, chips, and ICT, has undoubtedly been the most important technological development of the past few decades. The fact that more and more workers use computers has led to the conclusion that computer skills are becoming a key to social success. The aim of this paper is to contribute to the discussion of the effects of computerization on work. Our main conclusions are that the fear of a digital split in society appears unjustified. Although computers initially find their way primarily to the higher educated, practically all workers eventually end up working with computers. Absence of computer skills probably plays no role during this process of computerization. This does not mean, however, that there is no need for policies to optimise the economic potential of computers and ICT in general. Firstly, a properly developed infrastructure may be of importance for a rapid diffusion of the possibilities offered by ICT. This applies not only to the physical networks, but also to the availability of software and information. In addition, it may be expected that the educational requirements for workers will increase across the board and there will be changes in the knowledge and skills that people need to have. These are not primarily computer skills, but concern a much wider shift in the importance of various skills. Adjusting adequately to these changes requires reliable data. What is being measured and how the measurements are taken, will need to change considerably.education, training and the labour market;

What happens when agent T gets a computer?

During the last decade a great many authors have shown that computers have a large impact on skill demand, production processes, and the organization and intensity of work. Analyses have indicated that the rates of change of these variables have been the largest in the more computer-intensive sectors. Empirical findings, however, suggest that the effects of computers on the labor market are complicated and difficult to trace. This paper offers a simple model to explain how computers have changed the labor market. The model demonstrates that wage differentials between computer users and other workers are consistent with the observation that computers are first introduced in high-wage jobs because of cost efficiency. It also shows that neither computer skills nor complementary skills are needed to explain skill upgrading, changes in product characteristics, and the organization and intensity of work. Finally, it is shown that these findings shed a different light on the way computers have changed the labor market and on the changes to be expected following the further diffusion of computers.education, training and the labour market;

The Occupational Structure of Further and Higher Education in Ireland and the Netherlands

Although most types of education give access to a range of occupations, the educational background determines to a large extent the labour market possibilities of a worker. However, since educational systems vary widely between different countries, there is a question about the specific role of each type of education in a country and the influence of the structure of the educational system as a whole on the relationship between education and the labour market. In this paper a comparison of the occupational structure of further and higher education in Ireland and the Netherlands is made. This comparison is based on a common occupational classification, which provides the possibility of measuring the extent of the occupational domains of types of education and the overlap in occupational domain of different types of education within each country and between both countries. The extent of the occupational domain and the similarities within a country provide information about aspects of the occupational structure of higher education in both countries, while the similarities between types of education in both countries make it possible to determine in a simple way the mutual position of types of education in the two countries. It is shown in the paper that since the Irish education system is more generally oriented than the Dutch system, Ireland has a broader occupational domain for similar types of further and higher education, on average, than the Netherlands. In addition the occupational domains for academics and technicians in Ireland have more overlap between different fields of study than in the Netherlands. Furthermore, despite the fact that the fraction of higher educated people in the Netherlands considerably exceeds the fraction in Ireland – which might result in some qualifications inflation – some types of education in Ireland, such as engineering and agricultural science, at higher levels seem to be closer to the Dutch intermediate vocational level than to the higher level.education, training and the labour market;

Mobiliteit op de Nederlandse arbeidsmarkt

De Nederlandse arbeidsmarkt wordt vaak beschreven aan de hand van standcijfers zoals de werkloosheid op een bepaald moment of de werkgelegenheid per sector, beroep of opleidingstype. Achter deze standcijfers gaan echter veelal grote stromen schuil die niet in de standcijfers tot uitdrukking komen. Zo zal ook als de werkloosheid in twee opeenvolgende jaren qua omvang vergelijkbaar is, een aanzienlijk deel van de werklozen in het eerste jaar inmiddels werk hebben gevonden, of de arbeidsmarkt hebben verlaten, terwijl gedurende dat jaar er een nieuwe groep werklozen is bijgekomen. De laatste jaren is er voor de analyse van arbeidsmarktprocessen steeds meer interesse gekomen in deze arbeidsmarktmobiliteit. Met name het werk van Blanchard en Diamond (1989) heeft de interesse in deze stroomcijfers vergroot. Er is echter relatief weinig informatie over stromen op de Nederlandse arbeidsmarkt. De dataverzameling is nog niet aangepast aan deze verschoven belangstelling van zowel onderzoekers als beleidsmakers. Dit hangt mede samen met het feit dat het verzamelen van stroomgegevens aanzienlijk gecompliceerder te zijn dan het verzamelen van standcijfers. In deze notitie wordt daarom een overzicht gegeven van de stroomcijfers die thans beschikbaar zijn over de Nederlandse arbeidsmarkt. Dit overzicht heeft een drietal doelstellingen. Ten eerste beoogt het voor zover bekend een indicatie te geven van de omvang van enkele relevante arbeidsmarktstromen in Nederland. Ten tweede wordt hiermee duidelijk op welke punten er wel en op welke punten er nog geen stroomcijfers beschikbaar zijn, zodat de blinde vlekken in de dataverzameling getraceerd kunnen worden. Ten derde beoogt deze notitie in te gaan op de mogelijke problemen bij het verzamelen van stroomcijfers.education, training and the labour market;