Radical Restorative Remedies for Digital Markets

Abstract

Much evidence from recent antitrust cases casts doubt 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. However, the remedies fall short of outright economic regulation in that they aim to restore the competitive process, not to impose a competitive outcome. 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.