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Optimizing Incentive Policy of Energy-Efficiency Retrofit in Public Buildings: A Principal-Agent Model

Author

Listed:
  • Xin Liang

    (School of International and Public Affairs, Shanghai Jiao Tong University, Shanghai 200240, China)

  • Geoffrey Qiping Shen

    (Department of Building and Real Estate, Hong Kong Polytechnic University, Hong Kong, China)

  • Li Guo

    (School of Economics and Management Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100037, China)

Abstract

The building sector consumes most energy in the world, especially public buildings, which normally have high energy-use intensity. This phenomenon indicates that the energy-efficiency retrofit (EER) for public buildings is essential for energy saving. Incentive policies have been emphasized by governments in recent years, but their effectiveness has not been sufficient. A major reason is agency problems in EER and that the government and building owners have asymmetric information. Furthermore, most policies apply identical standard to existing buildings of different types, resulting in resistance from owners and tenants. To mitigate this issue, this study proposes a principal–agent model to optimize incentive policy in EER. The proposed model defines two pairs of principal–agent relations (i.e., the government-owner and owner-tenant) and models their behaviors under different scenarios as per principal–agent theory. The results indicate the optimal incentive policies for different scenarios. In addition, critical factors of policy making, such as cost, risk, uncertainty, and benefit distribution are discussed. This study has implications for policy that will benefit policy makers, particularly in promoting EER by mitigating the agency problem found for the different scenarios.

Suggested Citation

  • Xin Liang & Geoffrey Qiping Shen & Li Guo, 2019. "Optimizing Incentive Policy of Energy-Efficiency Retrofit in Public Buildings: A Principal-Agent Model," Sustainability, MDPI, vol. 11(12), pages 1-19, June.
  • Handle: RePEc:gam:jsusta:v:11:y:2019:i:12:p:3442-:d:242151
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    References listed on IDEAS

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