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Research on the Temporal and Spatial Distribution and Influencing Factors of Forestry Output Efficiency in China

Author

Listed:
  • Yu Lin

    (School of Economics and Management, Beijing Forestry University, Beijing 100083, China)

  • Wenhui Chen

    (School of Economics and Management, Beijing Forestry University, Beijing 100083, China)

  • Junchang Liu

    (School of Economics and Management, Beijing Forestry University, Beijing 100083, China)

Abstract

Forestry output efficiency is key to forestry development. China is now promoting the development of forestry, and thus the research on forestry output efficiency is of practical significance. Through the data envelopment analysis (DEA)-Malmquist index, spatial autocorrelation model, and fixed effect model of panel data, in this study, we analyzed the forestry output efficiency of China with indicators, such as the fixed asset input, employed personnel, total output value, and timber output, and drew the following conclusions. In the time series, the forestry total-factor productivity (TFP) in China saw a rapid increase, which is attributed to the technological progress change (TC), whereas the efficiency change (EC) imposed negative influences upon the forestry TFP. In the spatial distribution, there was a difference in the increase in the forestry output efficiency among the eastern, central, and western regions of China, with the eastern region having the fastest growth and the central region having the slowest growth. According to the spatial autocorrelation, there was spatial aggregation (high–high (HH) and low–low (LL)) with a significant positive correlation. Through the optimized fixed effect regression model, the fixed asset input, employed personnel, total output value, and timber output all had significant influences on the comprehensive technical efficiency of the forestry output, wherein the input indicators had negative influences, and the output indicators had positive influences.

Suggested Citation

  • Yu Lin & Wenhui Chen & Junchang Liu, 2021. "Research on the Temporal and Spatial Distribution and Influencing Factors of Forestry Output Efficiency in China," Sustainability, MDPI, vol. 13(9), pages 1-17, April.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:9:p:4687-:d:541475
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    References listed on IDEAS

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    1. Vítor João Pereira Domingues Martinho & António José Dinis Ferreira, 2020. "Forest Resources Management and Sustainability: The Specific Case of European Union Countries," Sustainability, MDPI, vol. 13(1), pages 1-21, December.
    2. Xiaohui Yu & Sai Ma & Kang Cheng & Grigorios L. Kyriakopoulos, 2020. "An Evaluation System for Sustainable Urban Space Development Based in Green Urbanism Principles—A Case Study Based on the Qin-Ba Mountain Area in China," Sustainability, MDPI, vol. 12(14), pages 1-22, July.
    3. Chia-Nan Wang & Han-Sung Lin & Hsien-Pin Hsu & Van-Tinh Le & Tsung-Fu Lin, 2016. "Applying Data Envelopment Analysis and Grey Model for the Productivity Evaluation of Vietnamese Agroforestry Industry," Sustainability, MDPI, vol. 8(11), pages 1-15, November.
    4. Guitang Liao & Peng He & Xuesong Gao & Liangji Deng & Hui Zhang & Nana Feng & Wei Zhou & Ouping Deng, 2019. "The Production–Living–Ecological Land Classification System and Its Characteristics in the Hilly Area of Sichuan Province, Southwest China Based on Identification of the Main Functions," Sustainability, MDPI, vol. 11(6), pages 1-16, March.
    5. Paula Simões & M. Lucília Carvalho & Sandra Aleixo & Sérgio Gomes & Isabel Natário, 2017. "A Spatial Econometric Analysis of the Calls to the Portuguese National Health Line," Econometrics, MDPI, vol. 5(2), pages 1-23, June.
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    Cited by:

    1. Zhang, Qianxi & Li, Fei, 2022. "Correlation between land use spatial and functional transition: a case study of Shaanxi Province, China," Land Use Policy, Elsevier, vol. 119(C).

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