Salience and (Non-)Buyer's Remorse: Optimal Nonlinear Pricing with Cognitively Constrained Consumers

Aaron L. Bodoh-Creed, Brent R. Hickman, John List, Ian Muir and Gregory K. Sun

No 35003, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: Nonlinear pricing theory predicts that firms can extract surplus by inducing heterogeneous consumers to self-sort across price contract offers that are ex-post optimal for them. We study subscription pricing when the frictionless sorting assumption fails. Using large-scale subscription experiments conducted by Lyft, we document systematic deviations from optimal self-selection: many high-demand consumers decline subscriptions that would have saved them money, while some subscribers fail to break even. We develop a structural model of intensive-margin demand in which consumers may exhibit salience failures, forecast errors about future demand, or impulsivity. We show that subscription uptake can be recast as one-sided noncompliance in a binary-instrument framework, allowing us to leverage LATE methods to identify counterfactual outcome distributions and a novel “uptake function” linking baseline outcomes to compliance behavior. Combining experimental price variation with this identification strategy, we recover utility primitives, demand heterogeneity, and behavioral parameters. Salience failures and forecast errors play quantitatively important roles. Counterfactual analyses show that optimal subscription pricing generates substantial gains relative to linear pricing, but these gains are highly sensitive to consumer deviations from ex-post optimal choice. Implementing nonlinear pricing therefore requires not only optimal contract design for consumer screening, but also coordinated efforts to mitigate behavioral frictions.

JEL-codes: C14 C51 C93 D04 L4 (search for similar items in EconPapers)
Date: 2026-03
New Economics Papers: this item is included in nep-com, nep-exp and nep-upt
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Working Paper: Salience and (Non-)Buyer's Remorse: Optimal Nonlinear Pricing with Cognitively Constrained Consumers (2026)
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