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Measuring skill mismatches and qualification mismatches. Current trends, challenges and opportunities. |
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| Session Organisers |
Mr Stephan Bischof (Leibniz Institute for Educational Trajectories, Bamberg (Germany)) Dr James Patrick Allen (Research Centre for Education and the Labour Market, Maastricht University (Netherlands)) |
| Time | Thursday 20 July, 16:00 - 17:30 |
| Room | U6-01e |
Skill or qualification mismatches are widespread phenomena affecting considerable parts of the working population across different regions, countries and economies. This issue is further strengthened by current trends such as digitalisation, technological innovation, globalisation or educational expansion and resulting shifts in labour markets and changing occupational demands. The matching process between individuals and jobs is particularly challenging in times of multiple crises and challenges, for example, due to educational and economic consequences of the COVID-19 pandemic, shortage of skilled workers or structural shifts in labour supply and demand due to migration flows or climate change.
Understanding the causes and consequences of skill or qualification mismatches and addressing the resulting challenges need valid and adequate measurement of mismatches between individuals and jobs. Policymakers, training organizations, companies or social partners need accurate information on mismatches to developing strategic policies to handle mismatches, such as changes in education and training systems, to counteract future skill deficits, or to provide the employability of individuals. However, skill or qualification mismatch incidences highly vary depending on the measurement approach, illustrating the relevance of using adequate measurement methods.
The paper session aims to address current trends, challenges and opportunities to measuring skill mismatches and qualification mismatches. The session is thus intended to give researchers dealing theoretically or empirically with measurement methods of skill mismatches or qualification mismatches (e.g. educational mismatch, field of education mismatch) the opportunity to present and discuss their research, methods and challenges in mismatch measurement. For example, subjective and objective mismatch measurement methods as well as multidimensional or skill-specific measurement methods could be presented and discussed. Furthermore, current developments and future opportunities for mismatch measurement, such as the use of online surveys or the relevance of mismatches in specific fields and skill domains, can be presented and discussed.
Keywords: Skill mismatch, Qualification mismatch, Educational mismatch, Field of education mismatch
Ms Santiago-Vela Ana (Federal Institute for Vocational Education and Training) - Presenting Author
Dr Wehner Caroline (Federal Institute for Vocational Education and Training)
Mismatch in the labour market refers to a misalignment between the supply of education or skills (i.e., the worker’s education or skills) and the demand of education or skills (i.e., the job’s education or skill requirements) and it involves both educational and skill mismatches. While overeducation (overskilling) means that the education (skills) are not fully utilized for adequate job positions at the labour market, undereducation (underskilling) relates to a lack of education (skills). Mismatch is typically considered as undesirable for workers, as most studies have focused on overeducation or overskilling and on their negative consequences with regard to wages and job satisfaction. However, undereducation or underskilling might even be profitable for workers because this situation represents a career enhancement without sufficient human capital investments. Thus, when human capital investments are not the only determinant of a worker’s career, what other factors are important? In this paper, we focus on having an internal locus of control (ILOC) as a predictor for mismatch in the labour market. We take different measures of mismatch: (1) subjective educational mismatch, (2) objective educational mismatch, and (3) skill mismatch. Moreover, we specifically look at gender differences. Our results suggest that ILOC helps workers in avoiding overeducation or overskilling, while it helps to enhance the workers’ careers by undereducation or underskilling.
We contribute to the mismatch literature. First, the few studies that analyse relationship between ILOC and mismatch in the labour market focus only on overeducation, but neglect both undereducation and other measures of mismatch in the labour market. Recent literature suggests that using subjective and objective approaches for the analysis of education and skills mismatch is particularly insightful. Second, since there is no study analysing gender differences in relationship between ILOC and mismatch, our study provides further important insights in gender inequalities in the labour market.
Dr Vlasta Zucha (Institute for Advanced Studies (IHS)) - Presenting Author
Ms Judith Engleder (Institute for Advanced Studies (IHS))
In contrast to the objective approach, subjective mismatch measurement methods can take individual occupational circumstances into account (cf. Mayerl 2017, Hall 2021). However, they don’t capture whether mismatch is seen by the employee as an accepted or an undesirable condition. This distinction is crucial because, for example, overqualification is not necessarily negative for individuals and for employers. Employees can still feel a high degree of satisfaction when the job matches their interests and values, and this is the reason why productivity and morale at work still can be assured (cf. Erdogan et al. 2011).
Including the factor of job satisfaction, the undesired mismatch can be separated from the accepted mismatch. Taking the example of a graduate study of the Universities of Applied Sciences in Lower Austria (Zucha et al. 2021), 38% of the graduates surveyed show a mismatch between their employment and their level of education and/or their field of study. At the same time, however, much less than half of these graduates are dissatisfied with their occupation (14%; vgl. ibid.).
An in-depth analysis of higher education graduates with undesired mismatch is provided to evaluate the specification of mismatch by the degree of satisfaction. This analysis includes the specific aspects of job satisfaction (e.g., with job tasks or income) as well as other closed and open response format questions, e.g., income, field of study, satisfaction with the study program. Are there systematic differences between the graduates with undesired or accepted mismatch? What are the characteristics of the graduates in undesired mismatching jobs? What adjustments need to be made – either at individual or institutional level – to support the initiation of matching employment? The results of the analysis are presented and their implications for further developing the measurement of qualification mismatch are discussed.
Mr Fabian Trennt (German Centre for Higher Education Research and Science Studies (DZHW)) - Presenting Author
Dr Johann Carstensen (German Centre for Higher Education Research and Science Studies (DZHW))
Dr Nancy Kracke (German Centre for Higher Education Research and Science Studies (DZHW))
Dr Frauke Peter (German Centre for Higher Education Research and Science Studies (DZHW))
Up to 30 percent of all first-year students in Germany leave higher education (HE) without a degree (Heublein, Richter, & Schmelzer, 2020). Public and scientific discourse deem this as bad investment (Berlingieri & Bolz, 2020; Heigle & Pfeiffer, 2020; Klein, Mishra, & Müller, 2021). At least implicitly, this view assumes that HE experience without a degree does not add to skills to be used on the labour market. Whether this is actually true is at best evaluated against skills (mis)match. However, as most indicators of (mis)match rely on formal qualification levels, tackling the question of (mis)match for the policy relevant group of HE dropouts is not straightforward. To address this issue, we focus on HE dropouts with a vocational degree and compare them to vocational degree holders without HE experience concerning similarity between trained and actual occupation. This way, we aim to reveal the skill ((mis)match) effect of HE dropout. To determine the similarity of occupational skills between trained and actual occupation, we use an index applied by Kracke, Reichelt, and Vicari (2018). Using starting cohort 6 of the National Educational Panel Study (NEPS), our analysis shows that HE experience without graduating adds to skills that pay off on the labour market. We see that dropouts, compared to individuals with a vocational degree without HE experience, more often hold occupations dissimilar from those they were trained for in vocational education. Compared to common approaches, we are able to detect (mis)match of skills that are not formally certified. Therefore, our results expand beyond the topic of HE dropout making this approach a fruitful starting point for evaluating skills (mis)match of a broad range of informal learning.