Guanglei Shi.  Application of Grey Forecast Management Based on Translog Function in Government Development of Low-Carbon Economy.  Dynamic Systems and Applications 29 (2020) No. 3, 958-978

https://doi.org/10.46719/dsa202029344

ABSTRACT.
With the rapid development of the world economy, some developing countries only pay attention to the growth rate of GDP, but ignore the importance of sustainable development. The extensive economy, which relies on a lot of energy to drive economic growth, can no longer meet the development requirements of low-carbon economy. Fundamentally changing this mode of economic growth, optimizing the energy structure will become an effective key path. This paper starts with the current situation of the government’s development of low-carbon economy, and analyzes the factors affecting the low-carbon economy. In order to develop low-carbon economy, reduce haze pollution, reduce greenhouse gas emissions, the energy conservation and emission reduction work of logistics industry is imminent. Analyze the current situation of logistics energy efficiency and structure, use qualitative and quantitative research methods to measure the impact of these indicators on low-carbon economy, then predict the total energy demand and supply under different scenarios, and formulate the best scenario to optimize the energy structure. Finally, the government put forward the grey prediction management scheme for the development of low-carbon economy.

Keywords: translog function, low carbon economy, grey prediction