Forestry Resource Efficiency, Total Factor Productivity Change, and Regional Technological Heterogeneity in China

被引:7
|
作者
Shah, Wasi Ul Hassan [1 ]
Hao, Gang [2 ]
Yan, Hong [1 ]
Shen, Jintao [1 ]
Yasmeen, Rizwana [3 ]
机构
[1] Zhejiang Shuren Univ, Sch Management, Hangzhou 310015, Peoples R China
[2] City Univ Hong Kong, Dept Management Sci, Hong Kong, Peoples R China
[3] Panzhihua Univ, Sch Econ & Management, Panzhihua 617000, Peoples R China
来源
FORESTS | 2024年 / 15卷 / 01期
关键词
forest resource efficiency; regional heterogeneity; total factor productivity growth; DEA; SLACKS-BASED MEASURE; ECONOMIC-DEVELOPMENT; MANAGEMENT; OUTPUT;
D O I
10.3390/f15010152
中图分类号
S7 [林业];
学科分类号
0829 ; 0907 ;
摘要
The efficient and sustainable management of forestry resources is crucial in ensuring economic and societal sustainability. The Chinese government has invested significantly in regulations, afforestation, and technology to enhance the forest resource efficiency, reduce technological disparities, and boost productivity growth. However, the success level of this undertaking is unclear and worth exploring. To this end, this study applied DEA-SBM, meta-frontier analysis, and the Malmquist productivity index to gauge the forest resource efficiency (FRE), regional technology heterogeneity (TGR), and total factor productivity growth (MI) in 31 Chinese provinces for a study period of 2001-2020. Results revealed that the average FRE was 0.5430, with potential growth of 45.70%, to enhance the efficiency level in forestry resource utilization. Anhui, Tibet, Fujian, Shanghai, and Hainan were found to be the top performers in forestry utilization during the study period. The southern forest region was ranked highest, with the highest TGR of 0.915, indicating advanced production technologies. The average MI score was 0.9644, signifying a 3.56% decline in forestry resource productivity. This deterioration is primarily attributed to technological change (TC), which decreased by 5.2%, while efficiency change (EC) witnessed 1.74% growth over the study period. The Southern Chinese forest region, indicating an average 3.06% increase in total factor productivity, ranked highest in all four regions. Guangxi, Tianjin, Shandong, Chongqing, and Jiangxi were the top performers, with prominent growth in MI. Finally, the Kruskal-Wallis test found a significant statistical difference among all four regions for FRE and TGR.
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页数:23
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