Abstract
The purpose of this study is to analyze technical efficiency, technology gaps and productivity of the manufacturing industries introducing the meta-frontier model in Korea and China for 2000–2004. We compare technical efficiency ignoring pollution with environmental technical efficiency considering pollution in order to estimate the influence of environmental factors on the competitiveness of manufacturing industries in the two countries. While the technical efficiencies of the Chinese manufacturing industries are higher on average than those of Korea in the two cases (ignoring and considering the pollution), the productivities of the Korean manufacturing industries are higher on average than those of China in both cases. This suggests that the China has a difficulty in reducing pollutants and increasing desirable outputs simultaneously. That is, Korean manufacturing is seemingly closer to sustainable growth than Chinese manufacturing.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
The Financial Times reported that China will emerge as the world’s largest manufacturing country in 2025 year and will outpace the US as a result. This is caused by the ratio of production to the world’s manufacturing industries increased from 15% in 2008 to 34.7% in 2025 according to the research of Global Insight which is an economic consultant, located in Washington (http://www.ft.com/cms).
- 2.
The production function ignoring pollution is defined as F(x) = {(x, y): x can produce y}.
- 3.
According to Fare, Grosskopf, and Pasurka (1986), we assume that the pollution set exhibits weak disposability and the output set exhibits strong disposability. The weak disposability of the pollution can be expressed as (y, b) ∈ F(x) and (βy, βb) ∈ F(x) if 0 ≤ β ≤ 1. This indicates that a producer should reduce pollution emission and desirable output simultaneously. On the other hand, the strong disposability, producing desirable output while reducing pollution emission freely, can be expressed as (y, b)∈F(x) and (y′, b)∈F(x) if ∀y′ ≤ y.
- 4.
The existing studies mainly suppose a certain scale, however, we do not consider the difference accompanied by the different economy scales because the focus of this study is not an economy scale but comparing the technical efficiency and productivity of the manufacturing industries in the two countries.
- 5.
SOx can indicate other air pollutants partially but it cannot reflect levels of water and soil pollutants. However, as China includes only the emission amounts of SOx in the statistical data of pollutants, we use only one pollutant, SOx. Pollutants that are particularly difficult to treat may require additional cost for disposal. But as most of pollutants are usually processed in the same manner, pollutant treatment cost does not vary, regardless of inclusion in pollutant types. That is, pollution control facilities must be operated to treat at least one pollutant with the whole process of pollution treatment regardless of the types of pollutants (Kang and Yoon 2008).
- 6.
Investment in fixed assets from Chinese Statistical Yearbook was used.
- 7.
Industrialization started in China since 1978 and the new investment was available from the early 1980s. However, we estimated the amount of new investment by extending the terms up to the middle of the 1960s and adopting the average growth rate of the new investment in the 1980s in order to bring them roughly into line with Korea. China has invested mainly in the manufacturing industries, especially in the light industry since its reform and openness. So the new investment in the most of the light industry is zero or near zero before 1978. The estimation formula by the perpetual inventory method is as follows:
$$ {\hbox{K}}\left( {1} \right) = {{{{\hbox{I}}\left( {{1}} \right)}} \left/ {{\left( {{{\delta + g}}} \right)}} \right.} $$where K(1) is capital stock in the first term, I(1) is new investment in the first term, δ is the depreciation rate, and g is the annual growth rate of new investment in the five initial years. Therefore, continuous capital stocks are calculated by the following formula:
$$ {\hbox{K}}\left( {1} \right) = \left( {{1} - {{\delta }}} \right){\hbox{K}}\left( {{\hbox{t}} - {1}} \right) + {\hbox{I}}\left( {\hbox{t}} \right),{\hbox{ t}} = {2},{ } \ldots { },{\hbox{T}} $$The same depreciation rate was applied to consistently analyze the capital stocks of two countries.
- 8.
In order to compare evenly, it is necessary to unify the statistical data of input, output, and pollution. In China, the statistical data of input and output are classified into 16 sectors and that of pollution is presented with 32 sectors. On the contrary, the manufacturing industries are classified into 23 sectors in Korea, with slight difference in each item. Therefore, perfect unification is impossible. Hence, the statistical data of pollution in China is integrated into 16 sectors as they are unified into input and output.
- 9.
The Chinese government has been interested in international environmental protection since the Earth Summit in 1992. The Chinese government started to conduct the maintenance and revision of the environmental laws and regulations after the year 2000, even though the Chinese government promoted the environmental laws and regulations gradually after the middle of 1990s.
References
Battese, G. E., & Rao, D. S. P. (2002). Technology gap, efficiency, and a stochastic meta-frontier function. International Journal of Business and Economics, 1(2), 87–93.
Chen, K. H., Huang, Y. J., & Yang, C. H. (2009). Analysis of regional productivity growth in China: A generalized meta-frontier MPI approach. China Economic Review, 20(4), 777–792.
Färe, R., Grosskopf, S., Norris, M., & Zhang, Z. (1994). Productivity growth, technical progress, and efficiency change in industrialized countries. The American Economic Review, 84(1), 66–83.
Jemaa, M. M. B., & Dhif, M. A. (2005). Agricultural productivity and technological gap between MENA region and some European countries: A meta-frontier approach. Economic Research Forum, 1–20.
Kang, S.-M., & Yoon, S.-M. (2008). Environmentally-adjusted productivity growth and growth accounting analysis in Korean and Chinese manufacturing. The Northeast Asia Economic Association of Korea, 20(3), 155–191.
Lee, M.-H., Choi, M.-C., Lim, J.-C., & Jang, J.-Y. (2008). Comparison of technical efficiency, shadow prices of capital and SO2 in Korean-Chinese manufacturing industries. Kukje Kyungje Youngu, 14(1), 29–47.
O’Donnell, C. J., Battese, G. E., & Rao, D. S. P. (2004). A meta-frontier production function for estimation of technical efficiencies and technology gaps for firms operating under different technologies. Journal of Productivity Analysis, 21(1), 91–103.
Rungsuriyawiboon, S., & Wang, X. (2007). Recent evidence on agricultural efficiency and China: A meta frontier approach (IAMO discussion paper 104). Leibniz: Leibniz Institute of Agricultural Development in Central and Eastern Europe (IAMO).
Young, A. (1995). The tyranny of numbers: Confronting the statistical realities of the East Asian growth. Quarterly Journal of Economics, 110(3), 641–680.
Acknowledgements
This work was supported by the National Research Foundation of Korea Grant funded by the Korean Government (NRF-2010-330-B00087).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer Science+Business Media Dordrecht
About this chapter
Cite this chapter
Kang, SM., Kim, MH. (2012). Analysis of Technical Efficiency and Productivity Using Meta-frontier-Manufacturing Industries in Korea and China. In: Vazquez-Brust, D., Sarkis, J. (eds) Green Growth: Managing the Transition to a Sustainable Economy. Greening of Industry Networks Studies, vol 1. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-4417-2_5
Download citation
DOI: https://doi.org/10.1007/978-94-007-4417-2_5
Published:
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-007-4416-5
Online ISBN: 978-94-007-4417-2
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)