Welcome to visit ACADEMIC MONTHLY,Today is

Volume 51 Issue 2
May 2019
Article Contents

Citation: Jiechang XIA, Yu XIAO and Shilin LI. Re-measurement and Influence Factors of Total Factor Productivity in China’s Service Industry[J]. Academic Monthly, 2019, 51(2): 34-43. shu

Re-measurement and Influence Factors of Total Factor Productivity in China’s Service Industry

  • This paper uses the semi-parametric OP method (Olley and Pakes, 1996) to measure the total factor productivity of the service industry in China from 2007 to 2016. The study found that in the sub-sectors of the service industry, the degree of technological progress of seven industries, including real estate and finance, is higher than that of public management and social organizations, as well as health, social security and social welfare industries intuitively. In the sub-regions, the degree of technological progress of Beijing, Shanghai, Zhejiang, Guangdong and other places is significantly higher than that of the central and western provinces and cities. From the perspective of growth trends, there are different increases and decreases between different industries within the service industry. However, since 2007, the total factor productivity of China’s service industry has shown a significant increase. Although some industries have shortcomings in technological progress, these gaps are shrinking significantly in terms of development trends.Among the four major economic regions, in addition to the downward trend in the western region, the total factor productivity of the service industry in the eastern, central and northeastern regions of China has increased significantly. From the perspective of influencing factors, the level of service industry development, urbanization rate, trade dependence and birth rate are all important variables to promote the growth of total factor productivity in the service industry.
  • 加载中

Figures(1) / Tables(5)

Article Metrics

Article views: 3409 Times PDF downloads: 27 Times Cited by: 0 Times

Metrics
  • PDF Downloads(27)
  • Abstract views(3409)
  • HTML views(283)
  • Latest
  • Most Read
  • Most Cited
          通讯作者: 陈斌, bchen63@163.com
          • 1. 

            沈阳化工大学材料科学与工程学院 沈阳 110142

          1. 本站搜索
          2. 百度学术搜索
          3. 万方数据库搜索
          4. CNKI搜索

          Re-measurement and Influence Factors of Total Factor Productivity in China’s Service Industry

          • 1. National Academy of Economic Strategy, Chinese Academy of Social Sciences, Beijing, 100028
          • 2. Graduate School of Chinese Academy of Social Sciences, Beijing, 102488
          • 3. Institute for Global Private Equity, Tsinghua University

          Abstract: This paper uses the semi-parametric OP method (Olley and Pakes, 1996) to measure the total factor productivity of the service industry in China from 2007 to 2016. The study found that in the sub-sectors of the service industry, the degree of technological progress of seven industries, including real estate and finance, is higher than that of public management and social organizations, as well as health, social security and social welfare industries intuitively. In the sub-regions, the degree of technological progress of Beijing, Shanghai, Zhejiang, Guangdong and other places is significantly higher than that of the central and western provinces and cities. From the perspective of growth trends, there are different increases and decreases between different industries within the service industry. However, since 2007, the total factor productivity of China’s service industry has shown a significant increase. Although some industries have shortcomings in technological progress, these gaps are shrinking significantly in terms of development trends.Among the four major economic regions, in addition to the downward trend in the western region, the total factor productivity of the service industry in the eastern, central and northeastern regions of China has increased significantly. From the perspective of influencing factors, the level of service industry development, urbanization rate, trade dependence and birth rate are all important variables to promote the growth of total factor productivity in the service industry.

            HTML

          Figure (1)  Table (5)

          目录

          /

          DownLoad:  Full-Size Img  PowerPoint
          Return