Corruption and Collusion in Procurement Tenders
Ariane Lambert-Mogiliansky () and
Konstantin Sonin ()
No w0036, Working Papers from Center for Economic and Financial Research (CEFIR)
There is a mounting body of evidence that collusive agreements between bidders in large multiple-object procurement tenders are often supported by a corrupt administrator. In a first-price multiple-object auction, if the auctioneer has some legal discretion to allow bidders to readjust their offers prior to the official opening, he also has incentives to extract bribes from agents in exchange for abusing this discretion. In particular, corrupt agent’s incentives to receive bribes are closely linked with that of creating a ’bidding ring’ as the agent’s discretionary power gains value when firms collude. Thus, corruption generates focal equilibria where bidders fully refrain from competing with each other. Additional flexibility of the auction format such as the possibility to submit package bids, which is often considered to be efficiency-enhancing in theoretical literature, increases the risk of collusion in the presence of corruption. Such problems are more likely to arise in tenders, where participating firms are not too close competitors.
Keywords: auctions; corruption; collusion (search for similar items in EconPapers)
JEL-codes: D44 H57 K42 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-cis, nep-eec and nep-tra
References: Add references at CitEc
Citations: View citations in EconPapers (5) Track citations by RSS feed
Downloads: (external link)
Journal Article: Collusive Market Sharing and Corruption in Procurement (2006)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:cfr:cefirw:w0036
Access Statistics for this paper
More papers in Working Papers from Center for Economic and Financial Research (CEFIR) Contact information at EDIRC.
Bibliographic data for series maintained by Julia Babich ().