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Optimal path for sustainable development under the dual constraints based on endogenous growth algorithm

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Abstract

Constructing an economic growth model comprising dual resource and environmental constraints by introducing both environmental quality and non-renewable resources as endogenous factors also introducing the production and utility functions. This was used to systematically analyze the endogenous mechanism through factors such as non-renewable resource consumption, environmental pollution externalities, the accumulation of physical capital, human capital development, and endogenous technological advancement could influence long-term economic growth. The basic conclusion of the model suggests that under both resource and environmental constraints, it is investment in both human capital and research & innovation that is the main driving and determining factor for long-term sustainable economic growth. The optimal development strategy of economic sustainability can be achieved through supporting human capital accumulation and technological innovation activities, promoting the advancement of clean production technologies, and formulating stringent environmental standards, as well as strengthening the society’s awareness of the environment and sustainable development.

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Acknowledgements

The authors would like to thank the referees and the editor for their valuable comments and suggestions. This work was supported in part by National Natural Science Foundation of China (Grant No. 71371111), Young and Middle-Aged Scientists Research Awards Fund of Shandong Province (Grant No. BS2013SF019), Postdoctoral Science Foundation of China (Grant No. 2014M551937), Key Project of National Statistical Science Research of China (Grant No. 2010LB27; 2010LB21), Research and Innovation Teams of Shandong University of Science and Technology (2015TDJH103).

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Correspondence to Shijian Wu.

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Wu, S., Zhang, R. Optimal path for sustainable development under the dual constraints based on endogenous growth algorithm. Cluster Comput 20, 2981–2991 (2017). https://doi.org/10.1007/s10586-017-0947-8

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