Computational Statistics

, Volume 29, Issue 6, pp 1543–1570 | Cite as

Dynamic activity analysis model-based win-win development forecasting under environment regulations in China

  • Shiyi ChenEmail author
  • Wolfgang K. Härdle
Original Paper


Porter hypothesis states that environmental regulation may lead to win-win opportunities, that is, improve the productivity and reduce the undesirable output simultaneously. Based on directional distance function, this paper proposes a novel dynamic activity analysis model to forecast the possibilities of win-win development in Chinese industry between 2011 and 2050. The consistent bootstrap estimation procedures are also developed for statistical inference of the point forecasts. The evidence reveals that the appropriate energy-saving and emission-abating regulation will significantly result in both the net growth of potential output and the increasing growth of total factor productivity for most industrial sectors in a statistical sense. This favors Porter hypothesis.


Dynamic activity analysis model Win win development  Environmental regulations China industry 



The work is sponsored by Deutsche Forschungsgemeinschaft through SFB 649 “Economic Risk”. The supports from National Natural Science Foundation (71173048), National Social Science Foundation (12AZD047), Ministry of Education (11JJD790007), Shanghai Leading Talent Project and Fudan Zhuo-Shi Talent Plan are also acknowledged.


  1. Ambec S, Barla P (2002) A theoretical foundation of the Porter hypothesis. Econ Lett 75(3):355–360zbMATHCrossRefGoogle Scholar
  2. Beaumont NJ, Tinch R (2004) Abatement cost curves: a viable management tool for enabling the achievement of win-win waste reduction strategies? J Environ Manag 71(3):207–215CrossRefGoogle Scholar
  3. Boyd GA, McClelland JD (1999) The impact of environmental constraints on productivity improvement in integrated paper plants. J Environ Econ Manag 38:121–142zbMATHCrossRefGoogle Scholar
  4. Boyd GA, Tolley G, Pang J (2002) Plant level productivity, efficiency, and environmental performance of the container glass industry. Environ Resour Econ 23:29–43CrossRefGoogle Scholar
  5. Cerin P (2006) Bringing economic opportunity into line with environmental influence: a discussion on the Coase theorem and the Porter and van der Linde hypothesis. Ecol Econ 56(2):209–225CrossRefGoogle Scholar
  6. Chambers R, Chung YH, Färe R (1996) Benefit and distance function. J Econ Theory 70:407–419zbMATHCrossRefGoogle Scholar
  7. Chen S (2011) The abatement of carbon intensity in China: factor decomposition and policy implications. World Econ 34(7):1148–1167CrossRefGoogle Scholar
  8. Chen S (2013) Energy, environment and economic transformation in China. Routledge Taylor & Francis Group, LondonGoogle Scholar
  9. Chen S, Golley J (2014) ‘Green’ productivity growth in China’s industrial economy. Energy Econ 44:89–98Google Scholar
  10. Chen S, Jefferson GH, Zhang J (2011) Structural change, productivity growth and industrial transformation in China. China Econ Rev 22(1):133–150CrossRefGoogle Scholar
  11. Chen W, Gao P, He J (2004) Impacts of future carbon reductions on the Chinese GDP growth. J Tsinghua Univ (Sci Technol) 44(6):744–747Google Scholar
  12. Chenery HB, Robinson S, Syrquin M (1986) Industrialization and growth: a comparative study. Oxford University Press, New YorkGoogle Scholar
  13. Chung YH, Färe R, Grosskopf S (1997) Productivity and undesirable outputs: a directional distance function approach. J Environ Manag 51:229–240CrossRefGoogle Scholar
  14. Daraio C, Simar L (2007) Advanced robust and nonparametric methods in efficiency analysis: methodology and applications. Springer, BerlinGoogle Scholar
  15. Efron B (1979) Bootstrap methods: another look at the jackknife. Ann Stat 7:1–26zbMATHMathSciNetCrossRefGoogle Scholar
  16. Färe R, Grosskopf S, Lovell K, Pasurka C (1989) Multilateral productivity comparisons when some outputs are undesirable: a nonparametric approach. Rev Econ Stat 71:90–98CrossRefGoogle Scholar
  17. Färe R, Grosskopf S, Pasurka CA Jr (2001) Accounting for air pollution emissions in measures of state manufacturing productivity growth. J Reg Sci 41(3):381–409CrossRefGoogle Scholar
  18. Faucheux S, Nicolaï I (1998) Environmental technological change and governance in sustainable development policy. Ecol Econ 27:243–256CrossRefGoogle Scholar
  19. Feichtinger G, Hartl RF, Kort PM, Veliov VM (2005) Environmental policy, the porter hypothesis and the composition of capital. J Environ Econ Manag 50(2):434–446zbMATHCrossRefGoogle Scholar
  20. Greaker M (2006) Spillovers in the development of new pollution abatement technology: a new look at the Porter-hypothesis. J Environ Econ Manag 52(1):411–420zbMATHCrossRefGoogle Scholar
  21. Groom B, Grosjean P, Kontoleon A, Swanson T, Zhang S (2010) Relaxing rural constraints: a ‘win-win’ policy for poverty and environment in China? Oxford Econ Pap 62(1):132–156CrossRefGoogle Scholar
  22. Hall P, Härdle W, Simar L (1995) Iterated bootstrap with application to frontier models. J Product Anal 6(1):63–76CrossRefGoogle Scholar
  23. Härdle W (1990) Applied nonparametric regression. Cambridge University Press, CambridgezbMATHCrossRefGoogle Scholar
  24. Jaffe A, Peterson S, Portney P, Stavins R (1995) Environmental regulation and the competitiveness of US manufacturing: what does the evidence tell us? J Econ Lit 33(1):132–163Google Scholar
  25. Jeon BM, Sickles RC (2004) The role of environmental factors in growth accounting. J Appl Econ 19(5):567–591CrossRefGoogle Scholar
  26. Karvonen M (2001) Natural versus manufactured capital: win-lose or win-win? A case study of the Finnish pulp and paper industry. Ecol Econ 37(1):71–85CrossRefGoogle Scholar
  27. Kuosmanen T, Bijsterbosch N, Dellink R (2009) Environmental cost-benefit analysis of alternative timing strategies in greenhouse gas abatement. Ecol Econ 68(6):1633–1642CrossRefGoogle Scholar
  28. Lee CF, Lin SJ, Lewis C, Chang YF (2007) Effects of carbon taxes on different industries by fuzzy goal programming: a case study of the petrochemical-related industries, Taiwan. Energy Policy 35(8):4051–4058CrossRefGoogle Scholar
  29. Lovell CAK (1993) Production frontiers and productive efficiency. In: Fried H, Lovell CAK, Schmidt SS (eds) The measurement of productive efficiency: techniques and applications. Oxford University Press, Oxford, pp 3–67Google Scholar
  30. Mohr RD (2002) Technical change, external economies, and the Porter hypothesis. J Environ Econ Manag 43(1):158–168zbMATHCrossRefGoogle Scholar
  31. Murty MN, Kumar S (2003) Win-win opportunities and environmental regulation: testing of porter hypothesis for Indian manufacturing industries. J Environ Manag 67(2):139–144CrossRefGoogle Scholar
  32. Palmer K, Oates WE, Portney PR (1995) Tightening environmental standards: the benefit-cost or the no-cost paradigm. J Econ Perspect 9(4):97–118CrossRefGoogle Scholar
  33. Porter ME (1991) America’s Green strategy. Sci Am 264(4):168CrossRefGoogle Scholar
  34. Porter ME, van der Linde C (1995) Toward a new conception of the environment: competitiveness relationship. J Econ Perspect 9(4):97–118CrossRefGoogle Scholar
  35. Reddy BS, Assenza GB (2009) The great climate debate. Energy Policy 37(8):2997–3008CrossRefGoogle Scholar
  36. Roughgarden T, Schneider SH (1999) Climate change policy: quantifying uncertainties for damages and optimal carbon taxes. Energy Policy 27(7):415–429CrossRefGoogle Scholar
  37. Schaltegger S, Synnestvedt T (2002) The link between green and economic success: environmental management as the crucial trigger between environmental and economic performance. J Environ Manag 65(4):339–346Google Scholar
  38. Sickles RC, Streitwieser ML (1998) An analysis of technology, productivity, and regulatory distortion in the interstate natural gas transmission industry: 1977–1985. J Appl Econ 13(4):377–395CrossRefGoogle Scholar
  39. Silverman BW (1978) Choosing the window width when estimating a density. Biometrika 65:1–11zbMATHMathSciNetCrossRefGoogle Scholar
  40. Silverman BW (1986) Density estimation for statistics and data analysis. Chapman and Hall, LondonzbMATHCrossRefGoogle Scholar
  41. Simar L, Wilson PW (1998) Sensitivity analysis of efficiency scores: how to bootstrap in nonparametric frontier models. Manag Sci 44:49–61zbMATHCrossRefGoogle Scholar
  42. Simar L, Wilson PW (1999) Estimating and bootstrapping Malmquist indices. Eur J Oper Res 115:459–471zbMATHCrossRefGoogle Scholar
  43. Xepapadeas A, De Zeeuw A (1999) Environmental policy and competitiveness: the Porter hypothesis and the composition of Capital. J Environ Econ Manag 37(2):165–182zbMATHCrossRefGoogle Scholar
  44. Zhang N, Choi Y (2013) Total-factor carbon emission performance of fossil fuel power plants in China: a metafrontier non-radial Malmquist index analysis. Energy Econ 40:549–559CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.China Center for Economic Studies, School of EconomicsFudan UniversityShanghaiChina
  2. 2.Center for Applied Statistics and EconomicsHumboldt-Universität zu BerlinBerlinGermany
  3. 3.Lee Kong Chian School of BusinessSingapore Management UniversitySingaporeSingapore

Personalised recommendations