Interprovincial Migration and the Stringency of Energy Policy in China

Abstract

Interprovincial migration flows involve substantial relocation of people and productive activity, with implications for regional energy use and greenhouse gas emissions. In China, these flows are not explicitly considered when setting energy and environmental targets for provinces, and their potential impact on the effectiveness of policy alternatives is ignored. We analyze how migration affects outcomes under energy intensity targets and energy caps. While both policies are part of the nation’s Twelfth Five Year Plan (2011–2015) and imposed at the provincial level, only the intensity targets are binding at present. We estimate a migration model, integrate it into a general equilibrium model that resolves each province in China, and simulate the effect of migration on energy use and economic activity. We find that although both types of policies are affected by uncertain migration flows, energy intensity targets (energy use indexed to economic output) are more robust than absolute caps. They are also more cost-effective, placing less burden on the relatively clean in-migration provinces. Our findings also underscore the value of moving from provincial targets to an integrated national emissions trading system, given that the choice of abatement strategies will adjust endogenously to labor relocation.The authors thank Eni S.p.A., ICF International, Shell International Limited, and the French Development Agency (AFD), founding sponsors of the China Energy and Climate Project. We also gratefully acknowledge the support of the Energy Information Administration at the U.S. Department of Energy. We are also thankful for support provided by the Ministry of Science and Technology of China, the National Development and Reform Commission, and Rio Tinto China. We further gratefully acknowledge the financial suppo rt for this work provided by the MIT Joint Program on the Science and Policy of Global Change through a consortium of industrial sponsors and Federal grants. This work is also supported by the DOE Integrated Assessment Grant (DE-FG02-94ER61937)