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Analysis of environmental efficiency variations: A nutrient balance approach

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  • Hoang, Viet-Ngu
  • Nguyen, Trung Thanh

Abstract

Recent literature has argued that environmental efficiency (EE), which is built on the materials balance (MB) principle, is more suitable than other EE measures in situations where the law of mass conversation regulates production processes. In addition, the MB-based EE method is particularly useful in analysing possible trade-offs between cost and environmental performance. Identifying determinants of MB-based EE can provide useful information to decision makers but there are very few empirical investigations into this issue. This article proposes the use of data envelopment analysis and stochastic frontier analysis techniques to analyse variation in MB-based EE. Specifically, the article develops a stochastic nutrient frontier and nutrient inefficiency model to analyse determinants of MB-based EE. The empirical study applies both techniques to investigate MB-based EE of 96 rice farms in South Korea. The size of land, fertiliser consumption intensity, cost allocative efficiency, and the share of owned land out of total land are found to be correlated with MB-based EE. The results confirm the presence of a trade-off between MB-based EE and cost allocative efficiency and this finding, favouring policy interventions to help farms simultaneously achieve cost efficiency and MP-based EE.

Suggested Citation

  • Hoang, Viet-Ngu & Nguyen, Trung Thanh, 2013. "Analysis of environmental efficiency variations: A nutrient balance approach," Ecological Economics, Elsevier, vol. 86(C), pages 37-46.
  • Handle: RePEc:eee:ecolec:v:86:y:2013:i:c:p:37-46
    DOI: 10.1016/j.ecolecon.2012.10.014
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    References listed on IDEAS

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    Cited by:

    1. Sueyoshi, Toshiyuki & Yuan, Yan & Goto, Mika, 2017. "A literature study for DEA applied to energy and environment," Energy Economics, Elsevier, vol. 62(C), pages 104-124.
    2. Yanni Yu & Yongrok Choi, 2015. "Measuring Environmental Performance Under Regional Heterogeneity in China: A Metafrontier Efficiency Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 46(3), pages 375-388, October.
    3. Saem Lee & Trung Thanh Nguyen & Patrick Poppenborg & Hio-Jung Shin & Thomas Koellner, 2016. "Conventional, Partially Converted and Environmentally Friendly Farming in South Korea: Profitability and Factors Affecting Farmers’ Choice," Sustainability, MDPI, Open Access Journal, vol. 8(8), pages 1-18, July.
    4. repec:spr:annopr:v:255:y:2017:i:1:d:10.1007_s10479-015-1933-2 is not listed on IDEAS
    5. 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.
    6. Aldanondo-Ochoa, Ana M. & Casasnovas-Oliva, Valero L. & Almansa-Sáez, M. Carmen, 2017. "Cross-constrained Measuring the Cost-environment Efficiency in Material Balance Based Frontier Models," Ecological Economics, Elsevier, vol. 142(C), pages 46-55.
    7. Jean-Lionel Payeur-Poirier & Trung Thanh Nguyen, 2017. "The Inclusion of Forest Hydrological Services in the Sustainable Development Strategy of South Korea," Sustainability, MDPI, Open Access Journal, vol. 9(8), pages 1-16, August.
    8. K Hervé Dakpo & Philippe Jeanneaux & Laure Latruffe, 2014. "Inclusion of undesirable outputs in production technology modeling:The case of greenhouse gas emissions in French meat sheep farming," Working Papers SMART - LERECO 14-08, INRA UMR SMART-LERECO.
    9. Gregg, Daniel & Rolfe, John, 2016. "The value of environment across efficiency quantiles: A conditional regression quantiles analysis of rangelands beef production in north Eastern Australia," Ecological Economics, Elsevier, vol. 128(C), pages 44-54.
    10. Aldanondo, Ana M. & Casasnovas, Valero L. & Almansa, M. Carmen, 2016. "Cost-constrained measures of environmental efficiency: a material balance approach," MPRA Paper 72490, University Library of Munich, Germany.
    11. Zhang, Ning & Wang, Bing & Chen, Zhongfei, 2016. "Carbon emissions reductions and technology gaps in the world's factory, 1990–2012," Energy Policy, Elsevier, vol. 91(C), pages 28-37.
    12. Ilkwon Kim & Quang Bao Le & Soo Jin Park & John Tenhunen & Thomas Koellner, 2014. "Driving Forces in Archetypical Land-Use Changes in a Mountainous Watershed in East Asia," Land, MDPI, Open Access Journal, vol. 3(3), pages 1-24, August.
    13. Wettemann, Patrick, 2015. "Die Entwicklung der Produktivität von Marktfruchtbetrieben unter Berücksichtigung von Treibhausgasemissionen," 55th Annual Conference, Giessen, Germany, September 23-25, 2015 209213, German Association of Agricultural Economists (GEWISOLA).
    14. Hampf, Benjamin, 2015. "Estimating the materials balance condition: A stochastic frontier approach," Darmstadt Discussion Papers in Economics 226, Darmstadt University of Technology, Department of Law and Economics.
    15. Huang, Wei & Bruemmer, Bernhard & Huntsinger, Lynn, 2016. "Incorporating measures of grassland productivity into efficiency estimates for livestock grazing on the Qinghai-Tibetan Plateau in China," Ecological Economics, Elsevier, vol. 122(C), pages 1-11.
    16. Alfons Oude Lansink & Alan Wall, 2014. "Frontier models for evaluating environmental efficiency: an overview," Economics and Business Letters, Oviedo University Press, vol. 3(1), pages 43-50.
    17. Yu, Yantuan & Huang, Jianhuan & Zhang, Ning, 2019. "Modeling the eco-efficiency of Chinese prefecture-level cities with regional heterogeneities: A comparative perspective," Ecological Modelling, Elsevier, vol. 402(C), pages 1-17.
    18. Hampf, Benjamin & Rødseth, Kenneth Løvold, 2019. "Environmental efficiency measurement with heterogeneous input quality: A nonparametric analysis of U.S. power plants," Energy Economics, Elsevier, vol. 81(C), pages 610-625.

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