4.7 Article

Evaluation of Forestry Ecological Efficiency: A Spatiotemporal Empirical Study Based on China's Provinces

Journal

FORESTS
Volume 12, Issue 2, Pages -

Publisher

MDPI
DOI: 10.3390/f12020142

Keywords

forestry ecological efficiency; spatial distribution; super-efficiency SBM; spatiotemporal difference; influencing factors

Categories

Funding

  1. National Natural Science Foundation of China [71473195, 71773091]
  2. Special Fund for Scientific Research of Forestry Commonwealth Industry [201504424]

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In this study, the non-expected super-efficiency SBM model was used to measure the forestry ecological efficiency of 31 provinces in China, and the spatial and temporal evolution of FEE was analyzed. Results showed regional differences in the total factor productivity change of China's forestry, with high-tech industries exhibiting obvious positive spatial correlation characteristics in 2018. Environmental regulation was identified as a significant factor affecting forestry ecological efficiency in China.
Forests play a very important role in carbon dioxide emissions and climate change, and the development of China's forestry is of great significance to our citizens. However, it is an arduous task for us to improve forestry output at a high and good level while taking environmental factors into account. In this paper, the non-expected super-efficiency SBM (slacks-based measure) model was used to measure the forestry ecological efficiency (FEE) of 31 provinces in China from 2004 to 2018, and the spatial and temporal evolution of FEE in different regions of China was analysed by using spatial econometric method. Tobit regression and random forest algorithm were selected to analyze the influence on FEE. The results showed that, firstly, the average annual increase of the national total factor productivity change of China's forestry was 1.2%, and that the average annual increase of the national total factor productivity change in the eastern region was lower than that in the central and western regions. Secondly, the distribution of China's FEE of the northeast and the south was higher, and FEE of China's middle regions was relatively lower in 2004, but then the FEE in Northeast China has decreased, and the FEE has increased gradually from north to south in 2018. The agglomeration of high-tech industries in most regions of China had obvious positive spatial correlation characteristics in 2018. Thirdly, there was a negative correlation between forestry fixed assets investment and FEE, environmental regulation was an important factor affecting the ecological efficiency of forestry in China, and the level of economic development and industrial structure also had a certain impact on FEE.

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