TY - JOUR
T1 - Nonlinear pricing in multidimensional context
T2 - An empirical analysis of energy consumption
AU - Han, Xintong
AU - Liu, Zimin
AU - Wang, Tong
N1 - Funding Information:
Acknowledgments: We express our gratitude to Christian Belzil, Ben Handel, Jorgen Hansen, Michael D. Grubb, Richard Langford, Yao Luo, Thierry Magnac, Robert Ritz, and Bing Ye in addition to seminar and conference attendees at CIREQ, Concordia University, the 9th Annual International Industrial Organization Conference (IIOC), the University of Edinburgh, the University of East Anglia, the Shanghai University of Finance and Economics (SHUFE), and Zhejiang University for their insightful feedback. This research has been financially supported by the National Natural Science Foundation of China (NSFC, Nos. 72192801, 71173236, 71603218) and the UEBS First Grant Venture Fund. Our sincere appreciation goes to the State Grid Corporation of China for providing the data. It is important to note that the opinions expressed in this paper are solely those of the authors and do not reflect the views of the State Grid Corporation of China. The authors accept responsibility for any remaining errors.
Funding Information:
Acknowledgments: We express our gratitude to Christian Belzil, Ben Handel, Jorgen Hansen, Michael D. Grubb, Richard Langford, Yao Luo, Thierry Magnac, Robert Ritz, and Bing Ye in addition to seminar and conference attendees at CIREQ, Concordia University, the 9th Annual International Industrial Organization Conference (IIOC), the University of Edinburgh, the University of East Anglia, the Shanghai University of Finance and Economics (SHUFE), and Zhejiang University for their insightful feedback. This research has been financially supported by the National Natural Science Foundation of China (NSFC, Nos. 72192801 , 71173236 , 71603218 ) and the UEBS First Grant Venture Fund . Our sincere appreciation goes to the State Grid Corporation of China for providing the data. It is important to note that the opinions expressed in this paper are solely those of the authors and do not reflect the views of the State Grid Corporation of China. The authors accept responsibility for any remaining errors.
PY - 2023/12
Y1 - 2023/12
N2 - 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.
AB - 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.
KW - energy policies
KW - multidimensional non-linear pricing
KW - structural estimation
U2 - 10.1016/j.ijindorg.2023.103034
DO - 10.1016/j.ijindorg.2023.103034
M3 - Article
SN - 0167-7187
VL - 91
SP - 1
EP - 21
JO - International Journal of Industrial Organization
JF - International Journal of Industrial Organization
M1 - 103034
ER -