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  • 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. (xsd:string)
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  • https://dspace.cuni.cz/bitstream/handle/20.500.11956/120638/130291480.pdf?sequence=1. (PIAAC) (xsd:string)
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  • The risks of job automation in the regions of the Czech Republic (xsd:string)
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