China’s Energy Efficiency: Re-estimation Incorporating
Human Capital and the Analysis of Its Distribution
Dynamics
Lingdi Zhao
Feng Jian
Economics School of
Ocean University of China
Singapore, June 21, 2017
China’s Energy Efficiency: Re-estimation Incorporating Human
Capital and the Analysis of Its Distribution Dynamics
1
2
3.1
3
4
5
• Introduction
• Methodology
• Data and Variables
• Results and Discussions
• Conclusions
1. Introduction
Background
• Energy conservation
• Carbon emission
Literature
review
• DEA, first proposed by Charnes et al. (1978)
• Joint-activity total-factor DEA – a appropriate way to
evaluate the relative efficiency of energy(Hu and Wang,
2006)
• Considered with undesirable outputs during the production
progress（e.gCO2),when evaluating energy efficiency. (Wu
et al.,2012 Choi et al.,2012)
• Non-radial and non-oriented SBM, proposed by Cooper et
al.(2007)
Theories of
human
capital
• Put forward by Schultz (1961) and Becker (1962)
• An important production factor to promote GDP(Caballé and
Santos 1993; Benhabib and Spiegel 1994)
• Effect technology development—a key factor for energy
efficiency improvement(Voigt 2014; Zhao et al. 2014)
• Laborers with higher level human capital absorb new
technology more quickly(Gangaharan 2006; Blackman and
Kildegaard 2010; Manderson and Kneller 2012)
3.1
2. Methodology
SBM-Undesirable output model
1. Production technology:
2. Weak disposability and null-jointness hypothesis
3.1
3. Production possibility set
2. Methodology
4. Linear programming solution
3.1
3. Variables
Input variables
SBM-Undesirable
1.Capital stock
（K）
Total Factor
2.Energy
Energy Efficiency
（E）
3.Human capital stock/
Number of employees
（L）
Output variables
1.Desirable output:
GDP（G）
2.Undesirable output:
CO2(C)
4. Results and discussions
Table1. MEPI (human capital stock as labor input)
4. Results and discussions
Table 2.TEPI (the number of employees as labor input)
4. Results and discussions
Fig. 1 Comparison of performance indicators with MEPI and TEPI
4. Results and discussions
4. Results and discussions
5. Conclusion
1. Difference between the evaluation results
of MEPI and TEPI
2.Distribution dynamics of energy efficiency
with MEPI
3. Further study with other DEA models
References
Acemoglu, D., Zilibotti, F. (2001). Productivity Differences. The Quarterly Journal of Economics, 116(2), 563-606.
Ai, H., Deng, Z., Yang, X. (2015). The effect estimation and channel testing of the technological progress on China’s regional
environmental performance. Ecological Indicators, 51, 67-78.
Barro, R. J., Lee, J. W. (1996). International measures of schooling years and schooling quality. American Economic Review, 86(2), 218223.
Bartel, A. P, Lichtenberg, F. R. (1987). The Comparative Advantage of Educated Workers in Implementing New Technology. The Review
of Economics and Statistics, 69(1), 1-11.
Becker, G. S. (1962). Investment in human capital: A theoretical analysis. The Journal of Political Economy, 70(5), 9-49.
Benhabib J., Spiegel M. M. (1994). The role of human capital in economic development evidence from aggregate cross-country data.
Journal of Monetary Economics, 34(2), 143-173.
Blackman, A., Kildegaard, A. (2010). Clean technological change in developing-country industrial clusters: Mexican leather tanning.
Environmental Economics and Policy Studies, 12(3), 115-132.
BP, (2014) Statistical Review of World Energy 2014.
http://www.bp.com/content/dam/bp/pdf/Energy-economics/statistical-review-2014/BP-Statistical-Review-of-World-Energy-2014-Chinainsights.pdf.
Bronzini, R., Piselli, P. (2009). Determinants of long-run regional productivity with geographical spillovers: the role of R&D, human
capital and public infrastructure. Regional Science and Urban Economics, 39(2), 187-199.
Caballé, J., Santos, M. S. (1993). On endogenous growth with physical and human capital. Journal of Political Economy, 101(6), 10421067.
Caselli, F., Coleman, W. J. (2002). The US technology frontier. American Economic Review, 92(2), 148-152.
Charnes, A., Cooper W. W., Rhodes E. (1978). Measuring the efficiency of decision making units. European Journal of Operational
Research, 2(6), 429-444.
Chen, J., Song, M., Xu, L. (2015). Evaluation of environmental efficiency in China using data envelopment analysis. Ecological
Indicators, 52, 577-583.
Chen, S. (2015). The evaluation indicator of ecological development transition in China's regional economy. Ecological Indicators, 51,
42-52.
Chen, S., Golley, J. (2014). ‘Green’ productivity growth in China's industrial economy. Energy Economics, 44, 89-98.
Choi, Y., Zhang, N., Zhou, P. (2012). Efficiency and abatement costs of energy-related CO2 emissions in China: a slacks-based efficiency
measure. Applied Energy, 98, 198-208.
Chung, Y. H., Färe, R., Grosskopf, S. (1997). Productivity and undesirable outputs: a directional distance function approach. Journal of
Environmental Management, 51(3), 229-240.
References
Colantonio, E., Marianacci, R., Mattoscio, N. (2010). On human capital and economic development: some results for Africa. ProcediaSocial and Behavioral Sciences, 9, 266-272.
Cole, M. A., Elliott, R. J. R., Shimamoto, K. (2005). Industrial characteristics, environmental regulations and air pollution: an analysis of
the UK manufacturing sector. Journal of Environmental Economics and Management, 50(1), 121-143.
Cole, M. A., Elliott, R. J. R., Wu, S. (2008). Industrial activity and the environment in China: an industry-level analysis. China Economic
Review, 19(3), 393-408.
Cooper, W. W., Seiford, L. M., Tone, K. (2007). Data envelopment analysis: a comprehensive text with models, applications, references
and DEA-solver software, 2nd ed. Boston: Kluwer Academic Publishers.
Dagum, C., Slottje, D. J. (2000). A new method to estimate the level and distribution of household human capital with application.
Structural Change and Economic Dynamics, 11(1), 67-94.
Doménech, R. (2006). Human capital in growth regressions: how much difference does data quality make? Journal of the European
Economic Association, 4(1), 1-36.
Fleisher, B., Li, H., Zhao, M. Q. (2010). Human capital, economic growth, and regional inequality in China. Journal of Development
Economics, 92(2), 215-231.
Fukuyama, H., Weber, W. L. (2009). A directional slacks-based measure of technical inefficiency. Socio-Economic Planning Sciences,
43(4), 274-287.
Färe, R. (1989). Multilateral Productivity Comparisons When Some Outputs Are Undesirable: A Nonparametric Approach. The Review of
Economics and Statistics, 71(1), 90-98.
Färe, R., Grosskopf, S., Pasurka, C. A. (2007). Pollution abatement activities and traditional productivity. Ecological Economics, 62(3),
673-682.
Førsund, F. R. (2009). Good Modelling of Bad Outputs: Pollution and Multiple-Output Production. International Review of Environmental
and Resource Economics, 3(1), 1-38.
Gangadharan, L. (2006). Environmental compliance by firms in the manufacturing sector in Mexico. Ecological Economics, 59(4), 477486.
Honma, S., Hu, J. L. (2008). Total-factor energy efficiency of regions in Japan. Energy Policy, 36(2), 821-833.
Hu, J. L., Wang, S. C. (2006). Total-factor energy efficiency of regions in China. Energy policy, 34(17), 3206-3217.
Jorgenson, D., Fraumeni, B. M. (1989). The accumulation of human and nonhuman capital, 1948-84, in Lipsey, R. E., Tice, H. S. (Eds.),
The measurement of saving, investment, and wealth (pp. 227-286). Chicago: University of Chicago Press.
Kalemli-Ozcan, S., Ryder, H. E., Weil, D. N. (2000). Mortality decline, human capital investment, and economic growth. Journal of
Development Economics, 62(1), 1-23.
Kendrick, J. W. (1976). The formation and stocks of total capital. New York: Columbia University Press.
Lan, J., Kakinaka, M., Huang, X. (2012). Foreign direct investment, human capital and environmental pollution in China. Environmental
and Resource Economics, 51(2), 255-275.
References
Lan, J., Munro, A. (2013). Environmental compliance and human capital: Evidence from Chinese industrial firms. Resource and
Energy Economics, 35(4), 534-557.
Lucas, R. E. (1988). On the mechanics of economic development. Journal of Monetary Economics, 22(1), 3-42.
Mandal, S. K. (2010). Do undesirable output and environmental regulation matter in energy efficiency analysis? Evidence from
Indian cement industry. Energy Policy, 38(10), 6076-6083.
Manderson, E., Kneller, R. (2012). Environmental regulations, outward FDI and heterogeneous firms: are countries used as
pollution havens? Environmental and Resource Economics, 51(3), 317-352.
Nelson, R. R., Phelps, E. S. (1966). Investment in humans, technological diffusion, and economic growth. American Economic
Review, 56(1/2), 69-75.
Pan, X., Liu, Q., Peng, X. (2015). Spatial club convergence of regional energy efficiency in China. Ecological Indicators, 51, 2530.
Rao, X., Wu J., Zhang, Z., Y., & Liu, B. (2012). Energy efficiency and energy saving potential in China: an analysis based on
slacks-based measure model. Computers & Industrial Engineering, 63(3), 578-584.
Romer, P. M. (1986). Increasing returns and long-run growth. Journal of Political Economy, 94 (5), 1002-1037.
Romer, P. M. (1990). Endogenous technological change. Journal of Political Economy, 98(5), S71-S102.
Scheel, H. (2001). Undesirable outputs in efficiency valuations. European Journal of Operational Research, 132(2), 400-410.
Schultz, T. W. (1961). Investment in human capital. American economic review, 51(1), 1-17.
Seiford, L. M., Zhu, J. (2002). Modeling undesirable factors in efficiency evaluation. European Journal of Operational Research,
142(1), 16-20.
Shan, H. J. (2008). Reestimating the capital stock of China: 1952–2006. The Journal of Quantitative & Technical Economics, 10,
17-31(in Chinese).
Shi, G. M., Bi, J., Wang, J. N. (2010). Chinese regional industrial energy efficiency evaluation based on a DEA model of fixing
non-energy inputs. Energy Policy, 38(10), 6172-6179.
Silverman, B. W. (1986). Density estimation for statistics and data analysis. London: Chapman and Hall.
Song, M., Guan, Y. (2014). The environmental efficiency of Wanjiang demonstration area: A Bayesian estimation approach.
Ecological Indicators, 36, 59-67.
Stern, D. I. (2012). Modeling international trends in energy efficiency. Energy Economics, 34(6), 2200-2208.
The National People's Congress (NPC) (2011). The Twelfth Five-Year Plan for National Economic and Social Development of
the People's Republic of China, Beijing, March 2011. http://www.npc.gov.cn/wxzl/gongbao/2011-08/16/content_1665636.htm (in
Chinese).
Tone, K. (2001). A slacks-based measure of efficiency in data envelopment analysis. European Journal of Operational Research,
130(3), 498-509.
References
Tone, K. (2001). A slacks-based measure of efficiency in data envelopment analysis. European Journal of Operational
Research, 130(3), 498-509.
Uzawa, H. (1965). Optimum technical change in an aggregative model of economic growth. International Economic Review,
6(1), 18-31.
Voigt, S., De Cian, E., Schymura, M., Elena V. (2014). Energy intensity developments in 40 major economies: Structural change
or technology improvement? Energy Economics, 41, 47-62.
Wang, Y., Yao, Y. (2003). Sources of China's economic growth 1952–1999: incorporating human capital accumulation. China
Economic Review, 14(1), 32-52.
Wei, Y. M., Liao, H., Fan, Y. (2007). An empirical analysis of energy efficiency in China's iron and steel sector. Energy, 32(12),
2262-2270.
Wu, F., Fan, L. W., Zhou, P., Zhou D. Q. (2012). Industrial energy efficiency with CO2 emissions in China: A nonparametric
analysis. Energy Policy, 49, 164-172.
Wu, A. H., Cao Y. Y., Liu B. (2014). Energy efficiency evaluation for regions in China: an application of DEA and Malmquist
indices. Energy Efficiency, 7, 429-439.
Yang L., Ouyang H., Fang K., et al. (2015). Evaluation of regional environmental efficiencies in China based on super-efficiencyDEA. Ecological Indicators, 51, 13-19.
Zhang, C., Liu, H., Bressers, H. T. A., et al. (2011). Productivity growth and environmental regulations-accounting for
undesirable outputs: Analysis of China's thirty provincial regions using the Malmquist–Luenberger index. Ecological Economics,
70(12), 2369-2379.
Zhang, N., Choi, Y. (2013). Environmental energy efficiency of China's regional economies: A non-oriented slacks-based
measure analysis. Social Science Journal, 50(2), 225-234.
Zhang, N., Kong, F., Yu, Y. (2015). Measuring ecological total-factor energy efficiency incorporating regional heterogeneities in
China. Ecological Indicators, 51, 165-172.
Zhao, X., Yang, R., Ma, Q. (2014). China's total factor energy efficiency of provincial industrial sectors. Energy, 65, 52-61.
Zhou, P., Ang, B. W. (2008). Linear programming models for measuring economy-wide energy efficiency performance. Energy
Policy, 36(8), 2911-2916.