Governmental incentives (e.g. production subsidy, R&D subsidy, and tax benefit) could spur the research and development (R&D) of energy storage enterprises (ESEs), thereby reducing the cost of energy storage. However, long-term high-intensity incentives may increase fiscal burden and disrupt the sustainability of incentive policies. We develop a compound real option model to identify and compare the influence mechanisms and consequences of individual or combined incentives on ESEs' R&D decisions, and further explore the effects of different incentives on fiscal burden. The main conclusions are as follows. (1) Production subsidy and R&D subsidy can promote early start of R&D, while tax benefit does the opposite. R&D subsidy leads to longer duration of R&D and faster cost reduction than other incentives. (2) With increasing incentive intensity, R&D subsidy enables faster cost reduction and more investment revenue than production subsidy and tax benefit, thereby increasing ESE's total taxes and reducing governmental fiscal burden. (3) Incentive combinations bring longer duration of R&D and more social welfare, but increase fiscal burden and fail to spur early start of R&D. There are also differences in the effects of these incentive combinations. (4) Simulations of dynamic changes in incentives for China and the United States reveal that China's approach yields longer duration of R&D and faster cost reduction, but with bigger fiscal burden. We finally discuss how governments select reasonable incentive policies and combinations according to regional endowments.

Publication:

ENERGY ECONOMICS

http://dx.doi.org/10.1016/j.eneco.2026.109226

Author:

Haowei Jin

School of Management, Xi’an Jiaotong University, Xi’an, 710049, China

Ju-e Guo

School of Management, Xi’an Jiaotong University, Xi’an, 710049, China

Yanzhao Li

School of Management, Xi’an Jiaotong University, Xi’an, 710049, China

Corresponding author

E-mail address: yzli0806@xjtu.edu.cn

Shouyang Wang

Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100190, China