Loughborough University
Browse
Collusive Price Rigidity.pdf (374.88 kB)

Collusive price rigidity under price-matching punishments

Download (374.88 kB)
conference contribution
posted on 2015-02-25, 09:44 authored by Luke GarrodLuke Garrod
By analysing an infinitely repeated game where unit costs alternate stochastically between low and high states and where firms follow a price-matching punishment strategy, we demonstrate that the best collusive prices are rigid over time when the two cost levels are sufficiently close. This provides game theoretic support for the results of the kinked demand curve. In contrast to the kinked demand curve, it also generates predictions regarding the level and the determinants of the best collusive price, which in turn has implications for the corresponding collusive profits. The relationships between such price rigidity and the expected duration of a high-cost phase, the degree of product differentiation, and the number of firms in the market are also investigated.

Funding

The support of the Economic and Social Research Council (UK) is gratefully acknowledged.

History

School

  • Business and Economics

Department

  • Economics

Published in

European Association of Research in Industrial Economics

Pages

1 - 31 (31)

Citation

GARROD, L., 2011. Collusive price rigidity under price-matching punishments. 38th EARIE Annual Conference, European Association of Research in Industrial Economics, Stockholm, Sweden, 1st-3rd September 2011, 31pp.

Version

  • AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Publication date

2011

Notes

This is a conference paper.

Publisher version

Language

  • en

Location

Stockholm, Sweden

Usage metrics

    Loughborough Publications

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC