Relative demand for highly skilled workers and use of different ICT technologies

ABSTRACT

This study investigates the relationship between several indicators of ICT usage and digitalization and the relative demand for highly skilled workers. The data are based on two-digit industry-level information on seven European countries for the period 2001–2010. For manufacturing industries, static fixed-effects models show that the share of employees with internet broadband access, the diffusion of mobile internet access and the use of enterprise resource planning (ERP) systems and automatic data exchange combined with electronic invoicing are all significantly and positively related to skill intensity in the industries observed. For service industries, only mobile internet usage intensity is significant. Specifically for manufacturing, a 10-point increase in the percentage of firms using ERP systems is associated with an increase in the share of highly skilled workers by 0.4 percentage points. These estimates indicate that the increase in ERP system usage during the period studied accounted for 30% of the increase in the share of workers with a tertiary degree across manufacturing industries and countries. The results are robust with respect to the estimation method and the potential endogeneity of ICT.

KEYWORDS:

• Skill intensity
• broadband-enabled employees
• enterprise resource planning systems
• skill-biased technological change

JEL CLASSIFICATION:

• O33
• J23
• J24

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 For a review of the relationship between innovation and employment, see Vivarelli (2013, 2014).

2 Product innovation can cause disruption and fierce competition within the same industry or across related industries, such that the employment gains in an industry could come at the cost of employment losses in industries producing substitute goods and services.

3 Bartel and Lichtenberg (1987) argue that highly educated workers have a comparative advantage with respect to learning and implementing new technologies and that they tend to adopt innovations sooner than workers with less education.

4 Previous studies have only distinguished between two types of skills, making it impossible to investigate polarization.

5 See Chennells and Van Reenen (2002) for the derivation of the skills share equation from the translog cost function.

6 Given the small number of time periods, the large number of cross-section units and the fact that the key variables of interest are measured as shares, the so-called spurious regression problem can be ignored.

7 The Micro Moments database includes micro-aggregated firm-level information for Austria, Denmark, Finland, France, Germany, Ireland, Italy, the Netherlands, Norway, Sweden, Slovenia and the UK.

8 Source: Eurostat, Community Survey on ICT Usage and E-Commerce in Enterprises.

Additional information

Funding

This work was supported by the Institute for Prospective Technological Studies, Joint Research Centre (JRC-IPTS), European Commission. The first author is also grateful to the Austrian National Bank research grant (JF 16524) for financial support. Data have been made available through collaboration with the Eurostat Esslait project (grant number 50721.2013). We would like to thank Tyler Schaffner for excellent proof-reading.