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</script>Stochastic frontier analysis of productive efficiency in China's Forestry Industry
Abstract Forest resources are vital to the development of green economics. Given the booming development of China's forestry industry and its ambitious reforestation efforts in the developing world, this paper is the first to use the output distance function to synthetically consider the economic and ecological outputs of China's forestry industry, and discuss its productive efficiency with a stochastic frontier model. Control and environmental variables are incorporated to capture heterogeneity in China's forestry industry, which helps us get an unbiased estimation. The empirical results show that there was no obvious efficiency disparity among China's economic regions except Northeastern China, and the state-owned forestry structure has a significantly negative effect on productive efficiency in China's forestry industry. Moreover, provinces with poor productive performance in the forestry industry such as Inner-Mongolia, Heilongjiang, and Hebei have been identified and their individual characteristics regarding productive efficiency have also been analyzed. The findings in this paper have targeted and practical implications for the development of China's forest green economy.
- Anhui University of Finance and Economics China (People's Republic of)
- Nanjing Audit University China (People's Republic of)
- Southwestern University of Finance and Economics China (People's Republic of)
- Southwestern University of Finance and Economics China (People's Republic of)
- Nanjing Audit University China (People's Republic of)
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).25 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
