A model of collusion formation and measurement in the open ascending bid auctions in the agricultural markets

Dipankar Das

Journal of Economic Studies, 2023, vol. 50, issue 8, 1748-1774

Abstract: Purpose - This paper gives a model of collusion formation and a method of measuring the degree of it among the traders/bidders in the agricultural commodity markets in India. The important assumption is that the bidding is repetitive with a set of common bidders. The theory has been derived based on the behavior of the wholesale market of agricultural commodities in India. The paper is based on full information in the collusion formation. The paper first derives the theoretical structure of the bidders' behavior and thereafter derives a measure of collusion formation with the help of real-life data. Design/methodology/approach - The paper used the standard theory of optimization and the theory of auction and probability statistics. Findings - This is a complete information model of cartel formation. The bidding is repetitive and continues forever in discrete time. Hence bidders behavior is observable. Using the proposed method, if the APMC measures for each market and publishes on a periodic basis, say weekly basis, then it will be easier to break the collusion in the market where relative collision is present. For example, if a farmer has three options to sell in three different markets, then the published data would help them to select the market where the degree of collusion is relatively lower. Moreover, the undesirable loss can be avoided based on the right choice of market. As a result, transaction costs will be optima. Originality/value - The paper first derives the theoretical structure of the bidders' behavior and thereafter derives a measure of collusion formation with the help of real-life data.

Keywords: Auctions/bidding; Game theory; Collusion; Agriculture (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eme:jespps:jes-07-2022-0381

DOI: 10.1108/JES-07-2022-0381

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