The impact of overeducated and undereducated workers on establishment-level productivity

Abstract

Purpose – Many contributions to the educational mismatch literature address the productivity effects of both excess and deficit educational attainments for workers at the individual level. Due to the limited transferability of their results to establishment-level performance, especially when allowing for the possibility of spillover effects from mismatched workers to their well-matched colleagues, from an employer’s point of view, it is highly important to know the net effect of educationally mismatched employees on productivity at the establishment level. The paper aims to discuss these issues. Design/methodology/approach – This paper analyses the impact of overeducated and undereducated workers among an establishment’s workforce on its productivity, providing first representative evidence for Germany. Using linked employer-employee data from Germany, the author estimates dynamic panel production functions using a system GMM estimator. Findings – The author finds that undereducated workers among an establishment’s workforce impair its (establishment-level) productivity, implying that an establishment’s HR management should avoid the recruitment of undereducated workers, at least if they follow a short-term personnel policy. The effect for overeducated employees is also negative, albeit small and insignificant. Originality/value – The consideration of the phenomena of over and undereducation from the employer’s point of view provides further insight into the consequences of educational mismatch.

Over‐, Required, and Undereducation: Consequences on the Bottom Lines of Firms

“…Employing workers with credentials below prevailing requirements appears to hamper productivity, whereas the effect of overeducation is not clear‐cut (Grunau, ; Kampelmann and Rycx, ; Quintini, ). Regarding direct measures of wage and labour cost effects, most existing studies such as the meta‐analyses from Groot and Maassen van den Brink () and Leuven and Oosterbeek () are consistent in that they suggest that the wage returns to educational credentials beyond the required level in a given job are in general positive, whereas the estimated positive returns to overeducation turn out to be lower with IV compared with OLS estimations (Leuven and Oosterbeek ()).…”

“…Building on the literature regarding educational mismatch (Baert and Verhaest, ; Hartog, ; Mavromaras and McGuinness, ; Sanchez‐Sanchez and McGuinness, ; Sellami et al ., ; Verhaest and Omey, , ; Verhaest and Van der Velden, ), in which direct measures of productivity are still rare (Grunau, ; Kampelmann and Rycx, ; Mahy et al ., ) and direct measures of gaps between labour productivity and wage costs (i.e. profits) have so far not been estimated, our paper shows that up‐ and downward deviations from the required education in a job do not have the same consequences: all models suggest that the extent of undereducation is in general harmful for firm profits, whereas higher levels of required and overeducation generate positive economic rents of roughly the same magnitude.…”

“… There is still very little direct evidence on whether overeducation is beneficial or detrimental for firm productivity (Grunau, ; Quintini, ). However, results of Kampelmann and Rycx () for the Belgian private sector suggest that the net effect is significant and positive.…”

Disruptive Technologies for Labor Market Information System Implementation Enhancement in the UAE: A Conceptual Perspective

“…It is necessary to mitigate the skills and educational mismatch problem in the UAE as it can lead to employee productivity issues, wage dissatisfaction, and other unfavorable labor market outcomes [32][33][34]. Besides, another fact that the COVID-19 pandemic has further deepened this problem in UAE and other countries across the globe.…”

Retraining for the unemployed and the quality of the job match

“…Finally, because the standard derivative-based standard errors have been shown to be inconsistent after nearest neighbour matching and because bootstrapping is unreliable if it is performed with a fixed number of comparison observations (Abadie and Imbens 2008), we apply the adjusted estimation of standard errors proposed by Abadie and Imbens (2006, 2011, 2016.…”