Wholesale Price Prediction: The Role of Information and Transparency

David Brown, Andrew Eckert and Douglas Silveira

No 2025-08, Working Papers from University of Alberta, Department of Economics

Abstract: The extent of real-time information disclosure in electricity markets has been a longstanding debate. Regulators have the difficult task of striking a careful balance between transparency to improve market outcomes under uncertainty while limiting the potential for coordinated action. We consider the case of Alberta’s electricity market where, until 2017, firms observed anonymized price-quantity offers in the wholesale market in near-real-time. We empirically evaluate the role that this information played in improving firms’ abilities to forecast wholesale prices, a key argument raised by stakeholders for this information to be published. While we find that this information improved firms’ abilities to forecast wholesale prices under certain market conditions, we present evidence to suggest that the economic significance of this improvement is minimal. We point to other types of near-real-time information that could help improve expectations of future market outcomes and provide suggestions on information disclosure policies that aim to strike a balance on motivating efficient outcomes, while reducing the risk of coordination.

Keywords: Machine Learning; Electricity; Price Forecasting; Competition Policy (search for similar items in EconPapers)
JEL-codes: D43 L13 L50 L94 Q40 (search for similar items in EconPapers)
Pages: 53
Date: 2025-10-26
New Economics Papers: this item is included in nep-com, nep-for, nep-ind and nep-reg
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https://sites.ualberta.ca/~econwps/2025/wp2025-08.pdf

Related works:
Journal Article: Wholesale price prediction: The role of information and transparency (2026)
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Persistent link: https://EconPapers.repec.org/RePEc:ris:albaec:021762

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