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Collusion under imperfect monitoring with asymmetric firms

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journal contribution
posted on 2017-01-10, 12:00 authored by Luke GarrodLuke Garrod, Matthew Olczak
We explore the effects of asymmetries in capacity constraints on collusion where market demand is uncertain and where firms must monitor the agreement through their privately observed sales and prices. In this private monitoring setting, we show that all firms can infer when at least one firm's sales are below some firm-specific \trigger level". This public information ensures that firms can detect deviations perfectly if fluctuations in market demand are sufficiently small. Otherwise, there can be collusion under imperfect public monitoring where punishment phases occur on the equilibrium path. We find that symmetry facilitates collusion. Yet, we also show that if the fluctuations in market demand are sufficiently large, then the optimal collusive prices of symmetric capacity distributions are actually lower on average than the competitive prices of asymmetric capacity distributions. We draw conclusions for merger policy.

History

School

  • Business and Economics

Department

  • Economics

Published in

The Journal of Industrial Economics

Volume

65

Issue

3

Pages

654-682

Citation

GARROD, L. and OLCZAK, M., 2017. Collusion under imperfect monitoring with asymmetric firms. The Journal of Industrial Economics, 65(3), pp. 654-682.

Publisher

© The Editorial Board of The Journal of Industrial Economics and John Wiley

Version

  • AM (Accepted Manuscript)

Publisher statement

This is the peer reviewed version of the following article: GARROD, L. and OLCZAK, M., 2017. Collusion under imperfect monitoring with asymmetric firms. The Journal of Industrial Economics, 65(3), pp. 654-682, which has been published in final form at https://doi.org/10.1111/joie.12145. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.

Acceptance date

2016-12-21

Publication date

2017-10-23

Copyright date

2017

ISSN

0022-1821

eISSN

1467-6451

Language

  • en

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