dc.contributor.author | GAL, Michal | |
dc.contributor.author | PETIT, Nicolas | |
dc.date.accessioned | 2021-02-08T11:57:23Z | |
dc.date.available | 2021-02-08T11:57:23Z | |
dc.date.issued | 2021 | |
dc.identifier.citation | Berkeley technology law journal, 2021, Vol. 36, No. 2, pp. 617-674 | en |
dc.identifier.issn | 1086-3818 | |
dc.identifier.uri | https://hdl.handle.net/1814/69817 | |
dc.description.abstract | Much evidence from recent antitrust cases casts doubts on the ability of conventional remedies to restore competition in digital markets. This paper considers three untested remedies for antitrust enforcement in digital markets: mandatory sharing of algorithmic learning; subsidization of competitors; and temporary shutdowns. All three remedies are radical from several perspectives. First, they go beyond halting specific anticompetitive conduct by actively seeking to restore structural conditions favoring competition. Second, they entail government interference with freedom of enterprise and property rights to a substantially higher degree than the market-driven process which normally governs antitrust remedy design. Third, all three remedies create complex tradeoffs, in that they could lead either to competitive benefits (e.g., the entry of new firms) or to harms (e.g., consumer losses in cases of platform shutdowns, or anticompetitive coordination in cases of algorithmic sharing). All three thus require careful balancing before implementation. | en |
dc.format.mimetype | application/pdf | en |
dc.language.iso | en | en |
dc.publisher | Berkeley Law Admissions Office | en |
dc.relation.ispartof | Berkeley technology law journal | en |
dc.title | Radical restorative remedies for digital markets | en |
dc.type | Article | en |
dc.identifier.doi | 10.15779/Z38HQ3S02R | |
dc.identifier.volume | 36 | en |
dc.identifier.startpage | 617 | |
dc.identifier.endpage | 674 | |
dc.identifier.issue | 2 | |