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Can Regional Eco-Efficiency Forecast the Changes in Local Public Health: Evidence Based on Statistical Learning in China

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  • Xianning Wang

    (School of Economics and Management, Chongqing Normal University, Chongqing 401331, China
    Big Data Marketing Research and Applications Center, Chongqing Normal University, Chongqing 401331, China
    Regional Economics Applications Laboratory (REAL), University of Illinois Urbana-Champaign, Champaign, IL 61801, USA)

  • Zhengang Ma

    (College of Life Sciences, Chongqing Normal University, Chongqing 401331, China)

  • Jiusheng Chen

    (School of Economics and Management, Chongqing Normal University, Chongqing 401331, China)

  • Jingrong Dong

    (School of Economics and Management, Chongqing Normal University, Chongqing 401331, China)

Abstract

Regional eco-efficiency affects local public health through intermediaries such as economic and environmental impacts. Considering multiple factors, the implicit and uncertain relationship with regional characteristics, and the limited data availability, this paper investigated the forecasting of changes in local public health—including the number of visits to hospitals (VTH), outpatients with emergency treatment (OWET), number of inpatients (NI), number of health examinations (NOHE), and patients discharged (PD)—using calculated regional eco-efficiency with the Least Square-Support Vector Machine-Forecasting Model and acquired empirical evidence, utilizing the province-level data in China. Results: (1) regional eco-efficiency is a good predictor in both a single and multi-factor situation; (2) the prediction accuracy for five dimensions of the changes in local public health was relatively high, and the volatility was lower and more stable throughout the whole forecasting period; and (3) regional heterogeneity, denoted by three economic and demographic factors and three medical supply and technical level factors, improved the forecasting performance. The findings are meaningful for provincial-level decision-makers in China in order for them to know the current status or trends of medical needs, optimize the allocation of medical resources in advance, and enable ample time to tackle urgent emergencies, and, finally, the findings can serve to evaluate the social effects of improving regional eco-efficiency via local enterprises or individuals and adopting sustainable development strategies.

Suggested Citation

  • Xianning Wang & Zhengang Ma & Jiusheng Chen & Jingrong Dong, 2023. "Can Regional Eco-Efficiency Forecast the Changes in Local Public Health: Evidence Based on Statistical Learning in China," IJERPH, MDPI, vol. 20(2), pages 1-19, January.
    • Handle: RePEc:gam:jijerp:v:20:y:2023:i:2:p:1381-:d:1033192
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    as
    1. Woon, Kok Sin & Lo, Irene M.C., 2016. "An integrated life cycle costing and human health impact analysis of municipal solid waste management options in Hong Kong using modified eco-efficiency indicator," Resources, Conservation & Recycling, Elsevier, vol. 107(C), pages 104-114.
    2. Alexander Cimprich & Jair Santillán‐Saldivar & Cassandra L. Thiel & Guido Sonnemann & Steven B. Young, 2019. "Potential for industrial ecology to support healthcare sustainability: Scoping review of a fragmented literature and conceptual framework for future research," Journal of Industrial Ecology, Yale University, vol. 23(6), pages 1344-1352, December.
    3. Nikolaos Vlastakis & George Dotsis & Raphael Markellos, 2008. "Nonlinear modelling of European football scores using support vector machines," Applied Economics, Taylor & Francis Journals, vol. 40(1), pages 111-118.
    4. Kondilis, E. & Giannakopoulos, S. & Gavana, M. & Ierodiakonou, I. & Waitzkin, H. & Benos, A., 2013. "Economic crisis, restrictive policies, and the population's health and health care: The greek case," American Journal of Public Health, American Public Health Association, vol. 103(6), pages 973-980.
    5. Ranis, Gustav & Stewart, Frances & Ramirez, Alejandro, 2000. "Economic Growth and Human Development," World Development, Elsevier, vol. 28(2), pages 197-219, February.
    6. Chakraborty, Shankha, 2004. "Endogenous lifetime and economic growth," Journal of Economic Theory, Elsevier, vol. 116(1), pages 119-137, May.
    7. J. Paul Brooks, 2011. "Support Vector Machines with the Ramp Loss and the Hard Margin Loss," Operations Research, INFORMS, vol. 59(2), pages 467-479, April.
    8. Stefano Cucurachi & Samuel Schiess & Andreas Froemelt & Stefanie Hellweg, 2019. "Noise footprint from personal land‐based mobility," Journal of Industrial Ecology, Yale University, vol. 23(5), pages 1028-1038, October.
    9. Ke Wang & Jiayu Wang & Klaus Hubacek & Zhifu Mi & Yi‐Ming Wei, 2020. "A cost–benefit analysis of the environmental taxation policy in China: A frontier analysis‐based environmentally extended input–output optimization method," Journal of Industrial Ecology, Yale University, vol. 24(3), pages 564-576, June.
    10. Giok Ling Ooi, 2007. "Urbanization in Southeast Asia: Assessing Policy Process and Progress toward Sustainability," Journal of Industrial Ecology, Yale University, vol. 11(2), pages 31-42, April.
    11. Johannesson, Magnus & Jonsson, Bengt, 1991. "Economic evaluation in health care: Is there a role for cost-benefit analysis?," Health Policy, Elsevier, vol. 17(1), pages 1-23, February.
    12. Dinah A. Koehler & Deborah H. Bennett & Gregory A. Norris & John D. Spengler, 2005. "Rethinking Environmental Performance from a Public Health Perspective: A Comparative Industry Analysis," Journal of Industrial Ecology, Yale University, vol. 9(3), pages 143-167, July.
    13. Zifeng Liang & Manli Zhang & Qingduo Mao & Bingxin Yu & Ben Ma, 2018. "Improvement of Eco-Efficiency in China: A Comparison of Mandatory and Hybrid Environmental Policy Instruments," IJERPH, MDPI, vol. 15(7), pages 1-20, July.
    14. Li, Ying & Chiu, Yung-ho & Lu, Liang Chun, 2018. "Energy and AQI performance of 31 cities in China," Energy Policy, Elsevier, vol. 122(C), pages 194-202.
    15. Monia Niero & Michael Z. Hauschild & Simon B. Hoffmeyer & Stig I. Olsen, 2017. "Combining Eco-Efficiency and Eco-Effectiveness for Continuous Loop Beverage Packaging Systems: Lessons from the Carlsberg Circular Community," Journal of Industrial Ecology, Yale University, vol. 21(3), pages 742-753, June.
    16. Simou, Effie & Koutsogeorgou, Eleni, 2014. "Effects of the economic crisis on health and healthcare in Greece in the literature from 2009 to 2013: A systematic review," Health Policy, Elsevier, vol. 115(2), pages 111-119.
    17. Tay, Francis E. H. & Cao, Lijuan, 2001. "Application of support vector machines in financial time series forecasting," Omega, Elsevier, vol. 29(4), pages 309-317, August.
    18. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    19. Du, Juan & Liang, Liang & Zhu, Joe, 2010. "A slacks-based measure of super-efficiency in data envelopment analysis: A comment," European Journal of Operational Research, Elsevier, vol. 204(3), pages 694-697, August.
    20. Hui Hu & Qian Jin & Philip Kavan, 2014. "A Study of Heavy Metal Pollution in China: Current Status, Pollution-Control Policies and Countermeasures," Sustainability, MDPI, vol. 6(9), pages 1-19, September.
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