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arXiv · 2605.22820

Integrable Elasticity via Neural Demand Potentials

Carlos Heredia·Daniel Roncel
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Abstract

We propose the Integrable Context-Dependent Demand Network (ICDN), a demand-first neural model for multiproduct retail demand. The model learns log-demand as a smooth, context-conditioned function of log-prices, allowing elasticities to be derived exactly from the learned demand surface. On the Dominick's beer dataset, ICDN improves out-of-sample generalization over a directed log-log benchmark and yields more stable, economically plausible elasticity estimates, especially for weakly identified cross-price effects.

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Carlos Heredia, Daniel Roncel. 2026-05-21. Integrable Elasticity via Neural Demand Potentials. https://arxiv.org/abs/2605.22820

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