IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v160y2020ics0040162520310489.html
   My bibliography  Save this article

Does China's carbon regulatory policy improve total factor carbon efficiency? A fixed-effect panel stochastic frontier analysis

Author

Listed:
  • Tan, Xiujie
  • Choi, Yongrok
  • Wang, Banban
  • Huang, Xiaoqi

Abstract

In China, climate policy has been strengthened by the mandated carbon intensity reduction target, which is a simple measurement of carbon efficiency under the single-factor framework. Is this carbon regulation during the 12th Five-Year Plan (FYP) actually effective for total factor carbon efficiency (TFCE) in China? To answer this research question, we estimate the TFCE and its policy and economic drivers using the fixed-effect stochastic frontier approach. The main results are as follows. First, the TFCE shows time and sector heterogeneity ranging from 0.235 to 0.996. Moreover, the changing pattern implies a positive relationship between TFCE and the 12th FYP. Second, the implementation of carbon regulations during the 12th FYP not only helped meet the carbon intensity reduction target, but also assisted in effectively improving TFCE. Third, carbon regulations have positively enhanced the role of energy prices in TFCE promotion and alleviated the negative role of exports. The results have significant policy implications for the carbon regulations in China's forthcoming 14th FYP. It is necessary to introduce market-oriented tools aside from the existing command-and-control policies.

Suggested Citation

  • Tan, Xiujie & Choi, Yongrok & Wang, Banban & Huang, Xiaoqi, 2020. "Does China's carbon regulatory policy improve total factor carbon efficiency? A fixed-effect panel stochastic frontier analysis," Technological Forecasting and Social Change, Elsevier, vol. 160(C).
    • Handle: RePEc:eee:tefoso:v:160:y:2020:i:c:s0040162520310489
    DOI: 10.1016/j.techfore.2020.120222
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162520310489
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techfore.2020.120222?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Adeyemi, Olutomi I. & Hunt, Lester C., 2014. "Accounting for asymmetric price responses and underlying energy demand trends in OECD industrial energy demand," Energy Economics, Elsevier, vol. 45(C), pages 435-444.
    2. Filippini, Massimo & Hunt, Lester C., 2015. "Measurement of energy efficiency based on economic foundations," Energy Economics, Elsevier, vol. 52(S1), pages 5-16.
    3. Clò, Stefano & Ferraris, Matteo & Florio, Massimo, 2017. "Ownership and environmental regulation: Evidence from the European electricity industry," Energy Economics, Elsevier, vol. 61(C), pages 298-312.
    4. Marius Ley, Tobias Stucki, and Martin Woerter, 2016. "The Impact of Energy Prices on Green Innovation," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    5. Zhang, Lulu & Xiong, Lichun & Cheng, Baodong & Yu, Chang, 2018. "How does foreign trade influence China’s carbon productivity? Based on panel spatial lag model analysis," Structural Change and Economic Dynamics, Elsevier, vol. 47(C), pages 171-179.
    6. Long, Ruyin & Shao, Tianxiang & Chen, Hong, 2016. "Spatial econometric analysis of China’s province-level industrial carbon productivity and its influencing factors," Applied Energy, Elsevier, vol. 166(C), pages 210-219.
    7. Wang, Hung-Jen & Ho, Chia-Wen, 2010. "Estimating fixed-effect panel stochastic frontier models by model transformation," Journal of Econometrics, Elsevier, vol. 157(2), pages 286-296, August.
    8. Sun, J. W., 2005. "The decrease of CO2 emission intensity is decarbonization at national and global levels," Energy Policy, Elsevier, vol. 33(8), pages 975-978, May.
    9. Yu, Shiwei & Wei, Yi-Ming & Guo, Haixiang & Ding, Liping, 2014. "Carbon emission coefficient measurement of the coal-to-power energy chain in China," Applied Energy, Elsevier, vol. 114(C), pages 290-300.
    10. Lin, Boqiang & Xu, Mengmeng, 2018. "Regional differences on CO2 emission efficiency in metallurgical industry of China," Energy Policy, Elsevier, vol. 120(C), pages 302-311.
    11. Zhou, P. & Ang, B.W. & Han, J.Y., 2010. "Total factor carbon emission performance: A Malmquist index analysis," Energy Economics, Elsevier, vol. 32(1), pages 194-201, January.
    12. Lu, Yingying & Liu, Yu & Zhou, Meifang, 2017. "Rebound effect of improved energy efficiency for different energy types: A general equilibrium analysis for China," Energy Economics, Elsevier, vol. 62(C), pages 248-256.
    13. Yao, Xin & Guo, Chengwen & Shao, Shuai & Jiang, Zhujun, 2016. "Total-factor CO2 emission performance of China’s provincial industrial sector: A meta-frontier non-radial Malmquist index approach," Applied Energy, Elsevier, vol. 184(C), pages 1142-1153.
    14. Belotti, Federico & Ilardi, Giuseppe, 2018. "Consistent inference in fixed-effects stochastic frontier models," Journal of Econometrics, Elsevier, vol. 202(2), pages 161-177.
    15. Luken, Ralph & Van Rompaey, Frank & Zigová, Katari­na, 2008. "The determinants of EST adoption by manufacturing plants in developing countries," Ecological Economics, Elsevier, vol. 66(1), pages 141-152, May.
    16. Brian R. Copeland & M. Scott Taylor, 1994. "North-South Trade and the Environment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 109(3), pages 755-787.
    17. Yang, Xue & Su, Bin, 2019. "Impacts of international export on global and regional carbon intensity," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    18. Antonietti, Roberto & Fontini, Fulvio, 2019. "Does energy price affect energy efficiency? Cross-country panel evidence," Energy Policy, Elsevier, vol. 129(C), pages 896-906.
    19. Wang, Guofeng & Deng, Xiangzheng & Wang, Jingyu & Zhang, Fan & Liang, Shiqi, 2019. "Carbon emission efficiency in China: A spatial panel data analysis," China Economic Review, Elsevier, vol. 56(C), pages 1-1.
    20. Yang, Zhenbing & Fan, Meiting & Shao, Shuai & Yang, Lili, 2017. "Does carbon intensity constraint policy improve industrial green production performance in China? A quasi-DID analysis," Energy Economics, Elsevier, vol. 68(C), pages 271-282.
    21. Chen, Yi-Yi & Schmidt, Peter & Wang, Hung-Jen, 2014. "Consistent estimation of the fixed effects stochastic frontier model," Journal of Econometrics, Elsevier, vol. 181(2), pages 65-76.
    22. Dong, Feng & Li, Xiaohui & Long, Ruyin & Liu, Xiaoyan, 2013. "Regional carbon emission performance in China according to a stochastic frontier model," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 525-530.
    23. Pethig, Rudiger, 1976. "Pollution, welfare, and environmental policy in the theory of Comparative Advantage," Journal of Environmental Economics and Management, Elsevier, vol. 2(3), pages 160-169, February.
    24. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    25. Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, vol. 126(2), pages 269-303, June.
    26. Fan, Ying & Liu, Lan-Cui & Wu, Gang & Tsai, Hsien-Tang & Wei, Yi-Ming, 2007. "Changes in carbon intensity in China: Empirical findings from 1980-2003," Ecological Economics, Elsevier, vol. 62(3-4), pages 683-691, May.
    27. Chen, Shiyi & Golley, Jane, 2014. "‘Green’ productivity growth in China's industrial economy," Energy Economics, Elsevier, vol. 44(C), pages 89-98.
    28. Greening, Lorna A. & Ting, Mike & Davis, William B., 1999. "Decomposition of aggregate carbon intensity for freight: trends from 10 OECD countries for the period 1971-1993," Energy Economics, Elsevier, vol. 21(4), pages 331-361, August.
    29. Zhang, Ning & Zhou, P. & Choi, Yongrok, 2013. "Energy efficiency, CO2 emission performance and technology gaps in fossil fuel electricity generation in Korea: A meta-frontier non-radial directional distance functionanalysis," Energy Policy, Elsevier, vol. 56(C), pages 653-662.
    30. Shuai Shao, Zhenbing Yang, Lili Yang, and Shuang Ma, 2019. "Can China's Energy Intensity Constraint Policy Promote Total Factor Energy Efficiency? Evidence from the Industrial Sector," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    31. Lin, Boqiang & Du, Kerui, 2015. "Modeling the dynamics of carbon emission performance in China: A parametric Malmquist index approach," Energy Economics, Elsevier, vol. 49(C), pages 550-557.
    32. McGuire, Martin C., 1982. "Regulation, factor rewards, and international trade," Journal of Public Economics, Elsevier, vol. 17(3), pages 335-354, April.
    33. Cheng, Zhonghua & Li, Lianshui & Liu, Jun & Zhang, Huiming, 2018. "Total-factor carbon emission efficiency of China's provincial industrial sector and its dynamic evolution," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 330-339.
    34. Zhang, Ning & Kong, Fanbin & Choi, Yongrok & Zhou, P., 2014. "The effect of size-control policy on unified energy and carbon efficiency for Chinese fossil fuel power plants," Energy Policy, Elsevier, vol. 70(C), pages 193-200.
    35. Sun, Chuanwang & Li, Zhi & Ma, Tiemeng & He, Runyong, 2019. "Carbon efficiency and international specialization position: Evidence from global value chain position index of manufacture," Energy Policy, Elsevier, vol. 128(C), pages 235-242.
    36. Herrala, Risto & Goel, Rajeev K., 2012. "Global CO2 efficiency: Country-wise estimates using a stochastic cost frontier," Energy Policy, Elsevier, vol. 45(C), pages 762-770.
    37. Zhang, Ning & Choi, Yongrok, 2013. "Total-factor carbon emission performance of fossil fuel power plants in China: A metafrontier non-radial Malmquist index analysis," Energy Economics, Elsevier, vol. 40(C), pages 549-559.
    38. Du, Kerui & Li, Jianglong, 2019. "Towards a green world: How do green technology innovations affect total-factor carbon productivity," Energy Policy, Elsevier, vol. 131(C), pages 240-250.
    39. Wang, Q.W. & Zhou, P. & Shen, N. & Wang, S.S., 2013. "Measuring carbon dioxide emission performance in Chinese provinces: A parametric approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 324-330.
    40. Zhu, Zhi-Shuang & Liao, Hua & Cao, Huai-Shu & Wang, Lu & Wei, Yi-Ming & Yan, Jinyue, 2014. "The differences of carbon intensity reduction rate across 89 countries in recent three decades," Applied Energy, Elsevier, vol. 113(C), pages 808-815.
    41. Zhou, P. & Ang, B.W. & Wang, H., 2012. "Energy and CO2 emission performance in electricity generation: A non-radial directional distance function approach," European Journal of Operational Research, Elsevier, vol. 221(3), pages 625-635.
    42. Du, Minzhe & Wang, Bing & Zhang, Ning, 2018. "National research funding and energy efficiency: Evidence from the National Science Foundation of China," Energy Policy, Elsevier, vol. 120(C), pages 335-346.
    43. Wang, Qunwei & Su, Bin & Zhou, Peng & Chiu, Ching-Ren, 2016. "Measuring total-factor CO2 emission performance and technology gaps using a non-radial directional distance function: A modified approach," Energy Economics, Elsevier, vol. 56(C), pages 475-482.
    44. Kim, Jihyo & Heo, Eunnyeong, 2013. "Asymmetric substitutability between energy and capital: Evidence from the manufacturing sectors in 10 OECD countries," Energy Economics, Elsevier, vol. 40(C), pages 81-89.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xu, Mengmeng & Tan, Ruipeng & He, Xinju, 2022. "How does economic agglomeration affect energy efficiency in China?: Evidence from endogenous stochastic frontier approach," Energy Economics, Elsevier, vol. 108(C).
    2. Du, Minzhe & Wu, Fenger & Ye, Danfeng & Zhao, Yating & Liao, Liping, 2023. "Exploring the effects of energy quota trading policy on carbon emission efficiency: Quasi-experimental evidence from China," Energy Economics, Elsevier, vol. 124(C).
    3. Minyoung Yang & Jinsoo Kim, 2022. "A Critical Review of the Definition and Estimation of Carbon Efficiency," Sustainability, MDPI, vol. 14(16), pages 1-18, August.
    4. Xiangyu Hua & Haiping Lv & Xiangrong Jin, 2021. "Research on High-Quality Development Efficiency and Total Factor Productivity of Regional Economies in China," Sustainability, MDPI, vol. 13(15), pages 1-22, July.
    5. Zhou, Sheng & Xu, Zhiwei, 2022. "Energy efficiency assessment of RCEP member states: A three-stage slack based measurement DEA with undesirable outputs," Energy, Elsevier, vol. 253(C).
    6. Bin Xu, 2022. "How to Efficiently Reduce the Carbon Intensity of the Heavy Industry in China? Using Quantile Regression Approach," IJERPH, MDPI, vol. 19(19), pages 1-24, October.
    7. Li-Ming Xue & Zhi-Xue Zheng & Shuo Meng & Mingjun Li & Huaqing Li & Ji-Ming Chen, 2022. "Carbon emission efficiency and spatio-temporal dynamic evolution of the cities in Beijing-Tianjin-Hebei Region, China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(6), pages 7640-7664, June.
    8. Li, Xin & Li, Zheng & Su, Chi-Wei & Umar, Muhammad & Shao, Xuefeng, 2022. "Exploring the asymmetric impact of economic policy uncertainty on China's carbon emissions trading market price: Do different types of uncertainty matter?," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
    9. Ren, Yi-Shuai & Boubaker, Sabri & Liu, Pei-Zhi & Weber, Olaf, 2023. "How does carbon regulatory policy affect debt financing costs? Empirical evidence from China," The Quarterly Review of Economics and Finance, Elsevier, vol. 90(C), pages 77-90.
    10. Zhang, Qi & Gu, Baihe & Zhang, Haiying & Ji, Qiang, 2023. "Emission reduction mode of China's provincial transportation sector: Based on “Energy+” carbon efficiency evaluation," Energy Policy, Elsevier, vol. 177(C).
    11. Ma, Rufei & Deng, Liqian & Ji, Qiang & Zhai, Pengxiang, 2022. "Environmental regulations, clean energy access, and household energy poverty: Evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    12. Juanjuan Tian & Xiaoqian Song & Jinsuo Zhang, 2022. "Spatial-Temporal Pattern and Driving Factors of Carbon Efficiency in China: Evidence from Panel Data of Urban Governance," Energies, MDPI, vol. 15(7), pages 1-24, March.
    13. Shan Miao & Yandi Tuo & Xi Zhang & Xiang Hou, 2023. "Green Fiscal Policy and ESG Performance: Evidence from the Energy-Saving and Emission-Reduction Policy in China," Energies, MDPI, vol. 16(9), pages 1-19, April.
    14. Bresciani, Stefano & Puertas, Rosa & Ferraris, Alberto & Santoro, Gabriele, 2021. "Innovation, environmental sustainability and economic development: DEA-Bootstrap and multilevel analysis to compare two regions," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
    15. Zhou, Tao & Huang, Xuhui & Zhang, Ning, 2023. "The effect of innovation pilot on carbon total factor productivity: Quasi-experimental evidence from China," Energy Economics, Elsevier, vol. 125(C).
    16. Honma, Satoshi & Ushifusa, Yoshiaki & Okamura, Soyoka & Vandercamme, Lilu, 2023. "Measuring carbon emissions performance of Japan's metal industry: Energy inputs, agglomeration, and the potential for green recovery reduction," Resources Policy, Elsevier, vol. 82(C).
    17. Wang, Jianda & Dong, Kangyin & Sha, Yezhou & Yan, Cheng, 2022. "Envisaging the carbon emissions efficiency of digitalization: The case of the internet economy for China," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    18. Tao Ge & Jinye Li & Cang Wang, 2023. "Econometric analysis of the impact of innovative city pilots on CO2 emissions in China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(9), pages 9359-9386, September.
    19. Mingjuan Ma & Shuifa Ke & Qiang Li & Yaqi Wu, 2023. "Towards Carbon Neutrality: A Comprehensive Analysis on Total Factor Carbon Productivity of the Yellow River Basin, China," Sustainability, MDPI, vol. 15(8), pages 1-23, April.
    20. Romero-Jordán, Desiderio & del Río, Pablo, 2022. "Analysing the drivers of the efficiency of households in electricity consumption," Energy Policy, Elsevier, vol. 164(C).
    21. Liu, Fangmei & Li, Li & Ye, Bin & Qin, Quande, 2023. "A novel stochastic semi-parametric frontier-based three-stage DEA window model to evaluate China's industrial green economic efficiency," Energy Economics, Elsevier, vol. 119(C).
    22. Peng, Hua-Rong & Tan, Xiujie & Managi, Shunsuke & Taghizadeh-Hesary, Farhad, 2022. "Club convergence in energy efficiency of Belt and Road Initiative countries: The role of China’s outward foreign direct investment," Energy Policy, Elsevier, vol. 168(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Minyoung Yang & Jinsoo Kim, 2022. "A Critical Review of the Definition and Estimation of Carbon Efficiency," Sustainability, MDPI, vol. 14(16), pages 1-18, August.
    2. Xian’En Wang & Shimeng Wang & Xipan Wang & Wenbo Li & Junnian Song & Haiyan Duan & Shuo Wang, 2019. "The Assessment of Carbon Performance under the Region-Sector Perspective based on the Nonparametric Estimation: A Case Study of the Northern Province in China," Sustainability, MDPI, vol. 11(21), pages 1-23, October.
    3. Cheng, Zhonghua & Li, Lianshui & Liu, Jun & Zhang, Huiming, 2018. "Total-factor carbon emission efficiency of China's provincial industrial sector and its dynamic evolution," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 330-339.
    4. Kuang, Yunming & Lin, Boqiang, 2022. "Natural gas resource utilization, environmental policy and green economic development: Empirical evidence from China," Resources Policy, Elsevier, vol. 79(C).
    5. Lin, Boqiang & Sai, Rockson, 2022. "Towards low carbon economy: Performance of electricity generation and emission reduction potential in Africa," Energy, Elsevier, vol. 251(C).
    6. Wang, Qunwei & Su, Bin & Zhou, Peng & Chiu, Ching-Ren, 2016. "Measuring total-factor CO2 emission performance and technology gaps using a non-radial directional distance function: A modified approach," Energy Economics, Elsevier, vol. 56(C), pages 475-482.
    7. Lin, Boqiang & Xu, Mengmeng, 2018. "Regional differences on CO2 emission efficiency in metallurgical industry of China," Energy Policy, Elsevier, vol. 120(C), pages 302-311.
    8. Wang, Qunwei & Su, Bin & Sun, Jiasen & Zhou, Peng & Zhou, Dequn, 2015. "Measurement and decomposition of energy-saving and emissions reduction performance in Chinese cities," Applied Energy, Elsevier, vol. 151(C), pages 85-92.
    9. Lin, Boqiang & Du, Kerui, 2015. "Modeling the dynamics of carbon emission performance in China: A parametric Malmquist index approach," Energy Economics, Elsevier, vol. 49(C), pages 550-557.
    10. Yao, Xin & Guo, Chengwen & Shao, Shuai & Jiang, Zhujun, 2016. "Total-factor CO2 emission performance of China’s provincial industrial sector: A meta-frontier non-radial Malmquist index approach," Applied Energy, Elsevier, vol. 184(C), pages 1142-1153.
    11. Wang, Qunwei & Chiu, Yung-Ho & Chiu, Ching-Ren, 2017. "Non-radial metafrontier approach to identify carbon emission performance and intensity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 664-672.
    12. Jiao Wang & Zhenliang Liao & Hui Sun, 2023. "Analysis of Carbon Emission Efficiency in the Yellow River Basin in China: Spatiotemporal Differences and Influencing Factors," Sustainability, MDPI, vol. 15(10), pages 1-19, May.
    13. Juanjuan Tian & Xiaoqian Song & Jinsuo Zhang, 2022. "Spatial-Temporal Pattern and Driving Factors of Carbon Efficiency in China: Evidence from Panel Data of Urban Governance," Energies, MDPI, vol. 15(7), pages 1-24, March.
    14. Xiao, Huijuan & Wang, Daoping & Qi, Yu & Shao, Shuai & Zhou, Ya & Shan, Yuli, 2021. "The governance-production nexus of eco-efficiency in Chinese resource-based cities: A two-stage network DEA approach," Energy Economics, Elsevier, vol. 101(C).
    15. Du, Minzhe & Wang, Bing & Zhang, Ning, 2018. "National research funding and energy efficiency: Evidence from the National Science Foundation of China," Energy Policy, Elsevier, vol. 120(C), pages 335-346.
    16. Lin, Boqiang & Sai, Rockson, 2021. "A multi factor Malmquist CO2emission performance indices: Evidence from Sub Saharan African public thermal power plants," Energy, Elsevier, vol. 223(C).
    17. Lin, Boqiang & Du, Kerui, 2015. "Energy and CO2 emissions performance in China's regional economies: Do market-oriented reforms matter?," Energy Policy, Elsevier, vol. 78(C), pages 113-124.
    18. Lv, Yulan & Chen, Wei & Cheng, Jianquan, 2020. "Effects of urbanization on energy efficiency in China: New evidence from short run and long run efficiency models," Energy Policy, Elsevier, vol. 147(C).
    19. Cheng, Zhonghua & Liu, Jun & Li, Lianshui & Gu, Xinbei, 2020. "Research on meta-frontier total-factor energy efficiency and its spatial convergence in Chinese provinces," Energy Economics, Elsevier, vol. 86(C).
    20. Du, Kerui & Li, Jianglong, 2019. "Towards a green world: How do green technology innovations affect total-factor carbon productivity," Energy Policy, Elsevier, vol. 131(C), pages 240-250.

    More about this item

    Keywords

    Carbon efficiency; Industrial sub-sectors; Fixed-effect panel stochastic frontier analysis; Total factor carbon efficiency;
    All these keywords.

    JEL classification:

    • Q56 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:tefoso:v:160:y:2020:i:c:s0040162520310489. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.