This indicator describes the risk of job automation in regional labour markets (indexed with respect to the ESPON countries' average)
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| Spatial Extent | Nomenclature | ||
|---|---|---|---|
| name | version | level | |
| EU28+4 | NUTS | 2013 | 2 |
The computation of the regional average risk of automation and the regional share of jobs at high risk is based on the following steps:
1. for ESPON countries where PIIAC exists, the individual probability of automation was directly estimated, based on the estimations obtained for Canada by Nedelkoska and Quintini (2018) ;
2. next, the weighted average probability of automation by NUTS-2 region, by region and occupation (ISCO 1-digit), by region and sector (NACE Rev.2.2. 1-digit) was computed as well as the share of jobs at high risk of automation by region, by region and occupation and by region and sector
3. for ESPON countries not participating to PIIAC, estimation of average probability of automation by NUTS2 region and the regional share of jobs at high risk of automation have been obtained as out-of-the-sample estimates obtained from an econometric regression analysis on PIIAC NUTS-2 regions in ESPON. This methodology allows to highlight the statistically significant relationship between the risk of automation and both the degree of penetration of ICTs and the local behaviour in using such technologies for the countries that have PIIAC data. This methodology enables to identify the importance (i.e the weight) of each variable to the risk of automation. These weights will be multiplied times their variables for the non PIIAC countries, obtaining their risk of automation at NUTS-2 level. The specific variables used in this regression analysis have been sourced from EUROSTAT and include:
• the regional share of population having access to broadband connection,
• the regional share of population using e-banking services,
• the regional share of population purchasing holidays online,
• the regional share of population registering online purchases in the last 3 months,
• the regional share of people using internet daily.
For additional details see the project scientific report.
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