Revenue Effects of Pricing Rule Changes in Cement Auctions of the Iran Mercantile Exchange

Nazer, Gayaneh; Mehrara, Mohsen; Rahmati, Mohammad Hossein

doi:10.22059/jte.2026.409348.1009066

Revenue Effects of Pricing Rule Changes in Cement Auctions of the Iran Mercantile Exchange

Document Type : Research Paper

Authors

Gayaneh Nazer ¹

Mohsen Mehrara ¹

Mohammad Hossein Rahmati ²

¹ Department of Theoretical Economics, Faculty of Economics, University of Tehran, Tehran, Iran.

² Department of Economics, Faculty of Management and Economics, Sharif University of Technology, Tehran, Iran.

10.22059/jte.2026.409348.1009066

Abstract

In economics, auctions are among the most important methods for resource allocation. If designed appropriately, they can achieve the mechanism designer’s objectives, such as efficiency in the price discovery process or revenue maximization. Currently, the Iran Mercantile Exchange (IME) is one of the country’s most significant commodity trading platforms, utilizing auction mechanisms to allocate goods among buyers. Recently, a simultaneous auction method (a type of sealed-bid auction) has been proposed for the cement sector to replace the open auction. Despite the alteration in the auction framework, its pricing rule remains unchanged and continues to follow a discriminatory pricing rule. The objective of this study is to investigate whether a uniform or a discriminatory pricing rule yields higher revenues for sellers. To examine the effects of changing the auction method, this study employs an agent-based model along with auction data from October 2024. The results indicate that as the demand-to-supply ratio increases, or as competition intensifies within the auction, the revenue generated from the uniform price auction surpasses that of the discriminatory price auction.

Keywords

Agent Based Model

Auction

Discriminatory Auction

Uniform Price Auction

Subjects

دستورالعمل معاملات کالا و اوراق بهادار مبتنی بر کالا در بورس کالای ایران، مصوب 05/07/1389 شورای عالی بورس و اوراق بهادار (1405).

Commodity and Commodity-Backed Securities Trading Regulations of the Iran Mercantile Exchange. (2010). [in Persian]. Retrieved from https://cmr.seo.ir/ShowRules?Id=10268&VersionId=61454&search=%D9%85%D8%B9%D8%A7%D9%85%D9%84%D8%A7%D8%AA%20%DA%A9%D8%A7%D9%84%D8%A7.

Alberizzi, A., Di Barba, P., & Ziel, F. (2025). Agent based modeling for intraday electricity markets. OPSEARCH, 62(1), 178-197. Retrieved from https://link.springer.com/article/10.1007/s12597-024-00805-w.

Anatolitis, V., & Welisch, M. (2017). Putting renewable energy auctions into action–An agent-based model of onshore wind power auctions in Germany. Energy Policy, 110, 394-402. Retrieved from https://www.sciencedirect.com/science/article/abs/pii/S0301421517305189.

Backus, M., Blake, T., Masterov, D. V., & Tadelis, S. (2015). Is sniping a problem for online auction markets? Proceedings of the 24th International Conference on World Wide Web (88-96). Retrieved from http://www.nber.org/papers/w20942.pdf.

Bresky, M. (2008). Properties of Equilibrium Strategies in Multiple-Unit, Uniform-Price Auctions. CERGE-EI Working Paper Series, (354). Retrieved from https://www.cerge-ei.cz/pdf/wp/Wp354.pdf.

Èihák, M. (2008). The 2007 Nobel prize in economics: Mechanism design theory. Czech Journal of Economics and Finance, 58(01-02), 82-89. Retrieved from http://journal.fsv.cuni.cz/storage/1107_str_82_89.-_cihak.pdf.

Hailu, A., Rolfe, J., Windle, J., & Greiner, R. (2010). Auction design and performance: an agent-based simulation with endogenous participation. International Conference on Agents and Artificial Intelligence (214-226). Berlin: Springer. Retrieved from https://link.springer.com/chapter/10.1007/978-3-642-19890-8_16.

Hailu, A., & Thoyer, S. (2010). What format for multi-unit multiple-bid auctions? Agent-based simulation of auction performance and nonlinear bidding behaviour. Computational Economics, 35(3), 189-209. Retrieved from https://link.springer.com/article/10.1007/s10614-010-9199-x.

Hortaçsu, A., & Kastl, J. (2012). Valuing dealers' informational advantage: A study of Canadian treasury auctions. Econometrica, 80(6), 2511-2542. Retrieved from https://onlinelibrary.wiley.com/doi/10.3982/ECTA8365.

Hubbard, T. P., & Paarsch, H. J. (2015). Auctions. Cambridge, MA: The MIT Press. Retrieved from https://mitpress.mit.edu/9780262334730/auctions/.

Kim, S. Y., & Kim, S. (2025). Spectrum Auction Policy Design for International Mobile Telecommunications in South Korea: Application of Agent-Based Simulation. Applied Sciences, 15(4), 1769. Retrieved from https://www.mdpi.com/2076-3417/15/4/1769.

Kuśmierczyk, P. (2010). Economic efficiency as one of the main objectives of auction design. Ekonomia, 9(136), 73-82. Retrieved from https://dbc.wroc.pl/Content/119709/Kusmierczyk_Economic_efficiency_as_one.pdf.

Lu, Y., Gupta, A., Ketter, W., & Van Heck, E. (2019). Dynamic decision making in sequential business-to-business auctions: A structural econometric approach. Management Science, 65(8), 3853-3876. Retrieved from https://pubsonline.informs.org/doi/10.1287/mnsc.2018.3118.

MacKinnon, J. G., & White, H. (1985). Some heteroskedasticity-consistent covariance matrix estimators with improved finite sample properties. Journal of Econometrics, 29(3), 305-325. Retrieved from https://www.sciencedirect.com/science/article/abs/pii/0304407685901587.

Roth, A. E., & Ockenfels, A. (2002). Last-minute bidding and the rules for ending second-price auctions: Evidence from eBay and Amazon auctions on the Internet. American Economic Review, 92(4), 1093-1103. Retrieved from https://www.aeaweb.org/articles?id=10.1257/00028280260344632.

Santos, E. C., Storm, H., & Rasch, S. (2021). The cost-effectiveness of conservation auctions in the presence of asset specificity: An agent-based model. Land Use Policy, 102, 104907. Retrieved from https://www.sciencedirect.com/science/article/abs/pii/S026483771931258X.

Tesfatsion, L. (2003). Agent-based computational economics. ISU Economics Working Paper, 1, Retrieved from https://dr.lib.iastate.edu/server/api/core/bitstreams/65190bba-c64d-410d-8a59-062d35d28662/content.

Zeithammer, R. (2006). Forward-looking bidding in online auctions. Journal of Marketing Research, 43(3), 462-476. Retrieved from https://journals.sagepub.com/doi/10.1509/jmkr.43.3.462.