Research on effects of ecological restoration and afforestation and their links to land conservation and regional development have received global attention. The Chinese government has successively invested a substantial amount of funds in the Grain for Green Program (GGP) since the mid-1990s. The economic effects of the GGP on macroeconomic growth could be attributed to an increase in agricultural production and off-farm employment and follow-up industry development. Few studies have focused on economic effects of the GGP at the national level using long-term series of panel data in 31 provinces and cities across the country. This study analyzed the regional differentiation and temporal-spatial changes in the GGP and investigated economic impacts of the GGP at different scales. Results showed that the scale of the GGP varied significantly in the eastern, central and western regions and regional changes were characterized by temporal differentiation from 2000 to 2016. The GGP had a slightly negative impact on China’s economic growth, which presented an overall U-shape, changed with an increase in economic growth. Significant regional heterogeneities in economic growth and impacts of the GGP were observed in the eastern, central and western regions. In the current situation in China, the technical progress, adjustment of industrial structure and focus on human capital to promote the development of follow-up industries and farmers’ labor skills have demonstrated the role for improving economic growth and optimizing the GGP arrangement. It is crucial to achieve a synergy between ecosystem conservation and regional economic in China.
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The authors acknowledge financial support from the National Natural Science Foundation of China (41 871 203).
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Liu, J., Wang, J., Li, Z. et al. Exploring impacts of the Grain for Green program on Chinese economic growth. Environ Dev Sustain (2020). https://doi.org/10.1007/s10668-020-00810-1
- Grain for Green program (GGP)
- Economic growth
- Regional differences
- Panel quantile regression
- Effective implementation