On Market Power And Cartel Detection: The South African Flour Cartel

Liberty Mncube

Studies in Economics and Econometrics, 2013, vol. 37, issue 3, 41-60

Abstract: For several different reasons, competition authorities are expected to identify the source of market power, which may not be the result of anti-competitive conduct. Empirical techniques could help to gauge the degree of market power, and firm conduct. We ask the question, do observed prices and quantities in the flour industry reflect switching from collusive to non-collusive behavior and test for this empirically using the monthly time series data from September 2003 to December 2008. Within the framework of a structural model of equilibrium pricing, we specify a simultaneous equation switching regression model in which the parameters of the demand and cost functions are estimated. Our estimated conduct parameters suggest that the level of market power exercised by the flour millers is quite low in both periods. The perfect collusion hypothesis is rejected by the data. In addition, the estimated level of the conduct parameter diverges from those implied the models of competition and therefore we cannot define precisely the firm behaviour.

Date: 2013
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/10800379.2013.12097259 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:rseexx:v:37:y:2013:i:3:p:41-60

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/rsee20

DOI: 10.1080/10800379.2013.12097259

Access Statistics for this article

Studies in Economics and Econometrics is currently edited by Willem Bester

More articles in Studies in Economics and Econometrics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().