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

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 accou...

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Main Authors: Shuai Chen, Shunbo Yao
Format: Article
Language:English
Published: MDPI AG 2021-01-01
Series:Forests
Subjects:
Online Access:https://www.mdpi.com/1999-4907/12/2/142
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spelling doaj-aa30de0f1eae46dda363fedb9c9a74f92021-01-27T00:06:10ZengMDPI AGForests1999-49072021-01-011214214210.3390/f12020142Evaluation of Forestry Ecological Efficiency: A Spatiotemporal Empirical Study Based on China’s ProvincesShuai Chen0Shunbo Yao1Center of Resource Economy and Environmental Management Research, College of Economics and Management, Northwest A & F University, Xianyang, Shaanxi 712100, ChinaCenter of Resource Economy and Environmental Management Research, College of Economics and Management, Northwest A & F University, Xianyang, Shaanxi 712100, ChinaForests 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.https://www.mdpi.com/1999-4907/12/2/142forestry ecological efficiencyspatial distributionsuper-efficiency SBMspatiotemporal differenceinfluencing factors
collection DOAJ
language English
format Article
sources DOAJ
author Shuai Chen
Shunbo Yao
spellingShingle Shuai Chen
Shunbo Yao
Evaluation of Forestry Ecological Efficiency: A Spatiotemporal Empirical Study Based on China’s Provinces
Forests
forestry ecological efficiency
spatial distribution
super-efficiency SBM
spatiotemporal difference
influencing factors
author_facet Shuai Chen
Shunbo Yao
author_sort Shuai Chen
title Evaluation of Forestry Ecological Efficiency: A Spatiotemporal Empirical Study Based on China’s Provinces
title_short Evaluation of Forestry Ecological Efficiency: A Spatiotemporal Empirical Study Based on China’s Provinces
title_full Evaluation of Forestry Ecological Efficiency: A Spatiotemporal Empirical Study Based on China’s Provinces
title_fullStr Evaluation of Forestry Ecological Efficiency: A Spatiotemporal Empirical Study Based on China’s Provinces
title_full_unstemmed Evaluation of Forestry Ecological Efficiency: A Spatiotemporal Empirical Study Based on China’s Provinces
title_sort evaluation of forestry ecological efficiency: a spatiotemporal empirical study based on china’s provinces
publisher MDPI AG
series Forests
issn 1999-4907
publishDate 2021-01-01
description 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.
topic forestry ecological efficiency
spatial distribution
super-efficiency SBM
spatiotemporal difference
influencing factors
url https://www.mdpi.com/1999-4907/12/2/142
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