How does the Chinese land restriction policy influence green total factor productivity? Evidence from the Chinese cities
Authors:
- Ping HuaPHPing Hua
- Miao LiuMLMiao Liu
- Yibo ChenYCYibo Chen
Preprint
Abstract
The ample and inexpensive land supply since 1986 has contributed to the strong development of high-energy-consuming and high-polluting industries in China, becoming the world's biggest CO2 emitter. To reorient this urban polluting industrialization towards a sustainable development, China decided in 2014 to restrict the land supply to new industrial construction in the city centers of more than 5 million populations, limiting thus the new industrial firms from setting up there. Is this restriction good for harmonizing environment and long-term sustainable development?The theoretical arguments suggest several channels through which the land restriction policy influences green total factor productivity (GTFP). They are verified by a difference-in-differences (DID) method using panel data over the 1999-2017 period for 14 cities affected by the policy as the experimental group and the remaining cities including all prefecture-level ones as the control group. The obtained results show that the land restriction policy has improved the urban GTFP via 1) improving allocation efficiency of land transfer 2) increasing land price and transforming industrial structure in favor of tertiary industry, which exert themselves positive impacts on GTFP, and 3) decreasing newly built enterprises, investment, patents for inventions, or technological innovation, which influence themselves negatively GTFP. They show moreover that the effects of the land policy are heterogeneous and stronger in eastern cities, municipalities directly under the Central Government and resource-based cities. Consequently, a selective land policy in favor of green industry is thus necessary to avoid the risk of urban deindustrialization and to promote the sustainable industrial development of the urban economy in the process of low-carbon transition.Keywords
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