Collusive compensation schemes aided by algorithms

Simon Martin and Wolfgang Schmal

No 375, DICE Discussion Papers from Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE)

Abstract: Sophisticated collusive compensation schemes such as assigning future market shares or direct transfers are frequently observed in detected cartels. We show formally why these schemes are useful for dampening deviation incentives when colluding firms are temporary asymmetric. The relative attractiveness of each of these schemes is shaped by firms' ability to predict future market conditions, possibly aided by algorithms. Prices and profits are inverse u-shaped in prediction ability. Assigning future market shares is optimal when prediction ability is intermediate, and otherwise direct transfers are optimal. Competition authority's limited resources should be utilized to respond to these changing market conditions.

Keywords: algorithmic collusion; market forecasting; prediction ability; firm asymmetry; compensation schemes (search for similar items in EconPapers)
JEL-codes: D21 L41 L51 (search for similar items in EconPapers)
Date: 2021
New Economics Papers: this item is included in nep-bec, nep-com, nep-ind and nep-reg
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Working Paper: Collusive Compensation Schemes Aided by Algorithms (2021)
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:dicedp:375

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