Automation and Irish towns: who's most at risk?

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dc.contributor.author Crowley, Frank
dc.contributor.author Doran, Justin
dc.date.accessioned 2019-03-21T12:16:15Z
dc.date.available 2019-03-21T12:16:15Z
dc.date.issued 2019
dc.identifier.citation Crowley, F. and Doran, J. (2019) 'Automation and Irish towns: who's most at risk?'. Available at: https://www.ucc.ie/en/media/projectsandcentres/srerc/SRERCWP2019-1_upload.pdf (Accessed: 21 March 2019) en
dc.identifier.startpage 1 en
dc.identifier.endpage 30 en
dc.identifier.uri http://hdl.handle.net/10468/7653
dc.description.abstract Future automation and artificial intelligence technologies are expected to have a major impact on the labour market. Despite the growing literature in the area of automation and the risk it poses to employment, there is very little analysis which considers the sub-national geographical implications of automation risk. This paper makes a number of significant contributions to the existing nascent field of regional differences in the spatial distribution of the job risk of automation. Firstly, we deploy the automation risk methodology developed by Frey and Osborne (2017) at a national level using occupational and sector data and apply a novel regionalisation disaggregation method to identify the proportion of jobs at risk of automation across the 200 towns of Ireland, which have a population of 1,500 or more using data from the 2016 census. This provides imputed values of automation risk across Irish towns. Secondly, we employ an economic geography framework to examine what types of local place characteristics are most likely to be associated with high risk towns while also considering whether the automation risk of towns has a spatial pattern across the Irish urban landscape. We find that the automation risk of towns is mainly explained by population differences, education levels, age demographics, the proportion of creative occupations in the town, town size and differences in the types of industries across towns. The impact of automation in Ireland is going to be felt far and wide, with two out of every five jobs at high risk of automation. The analysis found that many at high risk towns have at low risk nearby towns and many at low risk towns have at high risk neighbours. The analysis also found that there are also some concentrations of at lower risk towns and separately, concentrations of at higher risk towns. Our results suggest that the pattern of job risk from automation across Ireland demands policy that is not one size fits all, rather a localised, place-based, bottom up approach to policy intervention. en
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.publisher Spatial and Regional Economics Research Centre, University College Cork en
dc.relation.uri https://www.ucc.ie/en/media/projectsandcentres/srerc/SRERCWP2019-1_upload.pdf
dc.rights © 2019, the Authors. All rights reserved. en
dc.subject Automation en
dc.subject Artificial intelligence en
dc.subject Labour market en
dc.subject Regional en
dc.subject Disaggregation en
dc.subject Economic geography en
dc.title Automation and Irish towns: who's most at risk? en
dc.type Article (non peer-reviewed) en
dc.internal.authorcontactother Justin Doran, Economics, University College Cork, Cork, Ireland. +353-21-490-3000 Email: justin.doran@ucc.ie en
dc.internal.availability Full text available en
dc.date.updated 2019-03-21T12:05:37Z
dc.description.version Published Version en
dc.internal.rssid 478334194
dc.description.status Not peer reviewed en
dc.internal.copyrightchecked Yes en
dc.internal.licenseacceptance Yes en
dc.internal.IRISemailaddress justin.doran@ucc.ie en
dc.internal.IRISemailaddress frank.crowley@ucc.ie en
dc.identifier.articleid SRERCWP2019-1


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