Work detail

The Risks of Job Automation in the Regions of the Czech Republic

Author: Bc. Jan Suchánek
Year: 2020 - summer
Leaders: Mgr. Jan Mareš, Ph.D.
Consultants:
Work type: Bachelors
Language: English
Pages: 54
Awards and prizes:
Link: https://is.cuni.cz/webapps/zzp/detail/214053/
Abstract: This thesis estimates the risk of job automation in the regions of the Czech
Republic on second level of Nomenclature of Territorial Units for Statistics (NUTS 2). We base our methodology on occupation-based approach
and then proceed to implement task-based approach and use weighted Generalized Linear Model. We evaluate data from 1st Round of 1st Cycle of
collection in The Survey of Adult Skills (PIAAC). After acquiring predictions for the Czech Republic, we further analyzed them in order to estimate relationship between them and 20 macro-level indicators, which we
suspected of being linked to automatibility and robotisation. For that, we
used individual OLS regression of predictions on these indicators and also
computed Pearson correlation coefficient between share of high risk of automatibility jobs and these indicators. Then we proceeded to discuss results
and derived policy suggestions for government and policy makers in order to
minimize the threat automation and robotization poses. We conclude that
NUTS 2 regions highly threatened by automation or robotization are Central Moravian, Northwestern and Moravian-Silesian region. We also derived
that government and policy makers ought to focus in their policies to lower
future long term employment losses by improving quality of educational institutions, implementing requalification programmes for workers at high risk
of automation or adjusting taxes and investments so that economy performs
as good as possible.

Partners

Deloitte
Česká Spořitelna

Sponsors

CRIF
McKinsey
Patria Finance
EY