Skill Gap, Mismatch, and the Dynamics of Italian Companies’ Productivity

20  May 2019    11:30 am CEST

Lunchtime Seminar with Dario Guarascio, National Institute for Public Policies Analysis


wiiw, Rahlgasse 3, 1060 Vienna, library (2nd floor)


The presentation is based on a paper co-authored with Lucrezia Fanti and Matteo Tubiana.

Is there a relationship between companies’ knowledge-base characteristics and their performance in terms of productivity dynamics? A large part of the public and academic debate seems to support this assumption, pointing to the lack of a rich, updated and appropriate knowledge-base as one of the primary causes of firms weaknesses in terms of productivity and, more general, performance. From an empirical standpoint, measuring companies’ knowledge-base characteristics is, however, not an easy task. And this is even more the case when it comes to measuring the degree of skill gap and/or skill mismatch at the firm level. The main reason behind such empirical difficulties concerns the lack of sound micro-level information on firms’ workforce characteristics (at a high degree of disaggregation); upskilling and reskilling needs; competences (again at an adequate detail level) entering into companies organizational structure via new hirings.

This work overcomes most of the empirical limitations faced by previous studies focusing on skills and firms performance. The analysis is based on a unique longitudinal firm-level database integrating information on companies skill needs, labour productivity, and new hirings at the 4–digit occupational categories. Information on new hirings is further qualified in terms of workers’ relative skills, knowledge and abilities. As a first step we analyse Italian companies’ productivity dynamics against the skill gaps they face (discriminating such gaps by clustering skills in homogeneous groups). Secondly, we test whether facing a skill mismatch has an impact on productivity. The analysis is carried out using a two-step Heckman-type procedure by controlling, among other things, for firms’ innovative activities. In this way we are able to partly circumvent potential endogeneity biases related to unobserved technology related companies’ characteristics that may be behind the presence of skill gaps and/or skill mismatch, identifying in a finer way the very relationship between the evolution of the knowledge base and firms’ performance. Preliminary results highlight a negative impact of skill mismatch on productivity dynamics. The paper also provides a large set of additional tests aimed at investigating the role of skill gap and mismatch differentiating firms by industry and prevalent type of innovation activity.

Sandwiches will be served.

Paper and Powerpoint presentation, as far as available, are posted on this page after the seminar.

Keywords: Skill mismatch, labour productivity, firm-level heterogeneity, innovation

JEL classification: J21, J24