Simulating Endogenous Global Automation

Seth Benzell (), Laurence Kotlikoff, Guillermo LaGarda and Victor Yifan Ye

No 29220, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: This paper develops a 17-region, 3-skill group, overlapping generations, computable general equilibrium model to evaluate the global consequences of automation. Automation, modeled as capital- and high-skill biased technological change, is endogenous with regions adopting new technologies when profitable. Our approach captures and quantifies key macro implications of a range of foundational models of automation. In our baseline scenario, automation has a moderate effect on regional outputs and a small effect on world interest rates. However, it has a major impact on inequality, both wage inequality within regions and per capita GDP inequality across regions. We examine two policy responses to technological change -- mandating use of the advanced technology and providing universal basic income to share gains from automation. The former policy can raise a region's output, but at a welfare cost. The latter policy can transform automation into a win-win for all generations in a region.

JEL-codes: E1 E23 F43 O31 O33 O4 O41 (search for similar items in EconPapers)
Date: 2021-09
New Economics Papers: this item is included in nep-dge, nep-isf, nep-mac and nep-tid
Note: DAE DEV ITI PR
References: Add references at CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.nber.org/papers/w29220.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nbr:nberwo:29220

Ordering information: This working paper can be ordered from
http://www.nber.org/papers/w29220

Access Statistics for this paper

More papers in NBER Working Papers from National Bureau of Economic Research, Inc National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.. Contact information at EDIRC.
Bibliographic data for series maintained by ().