Nonlinear pricing in multidimensional context: An empirical analysis of energy consumption

Xintong Han, Zimin Liu, Tong Wang*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

Modern business practices frequently employ a blend of pricing strategies to segment markets effectively. As a result, consumers may encounter pricing schedules that are nonlinear and multidimensional. This paper presents a structural approach for estimating multidimensional nonlinear pricing models involving multiple decision variables in an energy market. Using a unique, rich panel dataset of Chinese household electricity consumption, we structurally estimate consumer preferences under the influence of an Increasing Block Price (IBP) and a Time-of-Use(ToU) system. Our structural approach allows us to distinguish and evaluate household-level price elasticities of demand, presenting a novel explanation for consumers’ feedback on marginal price changes. Through model-based simulations, we demonstrate that a 1% increase in price corresponds to a 0.7% reduction in total electricity demand. However, our analysis indicates that practical opportunities for optimization within multi-dimensional pricing systems are limited.Our findings offer distinct insights into the complex interplay between intricate pricing structures and energy consumption behavior, thereby providing valuable guidance for policymakers and regulators.
Original languageEnglish
Article number103034
Pages (from-to)1-21
Number of pages21
JournalInternational Journal of Industrial Organization
Early online date21 Nov 2023
Publication statusPublished - Dec 2023

Keywords / Materials (for Non-textual outputs)

  • energy policies
  • multidimensional non-linear pricing
  • structural estimation


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