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Indirect Economic Impact Incurred by Haze Pollution: An Econometric and Input–Output Joint Model

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  • Jibo Chen

    (School of Mathematics and Statistics, Nanjing University of Information Science & Technology, Nanjing 210044, China)

  • Keyao Chen

    (National Climate Center, China Meteorological Administration, Beijing 100081, China)

  • Guizhi Wang

    (School of Mathematics and Statistics, Nanjing University of Information Science & Technology, Nanjing 210044, China)

  • Rongrong Chen

    (School of Mathematics and Statistics, Nanjing University of Information Science & Technology, Nanjing 210044, China)

  • Xiaodong Liu

    (School of Computing, Edinburgh Napier University, Edinburgh EH10 5DT, UK)

  • Guo Wei

    (Department of Mathematics and Computer Science, University of North Carolina at Pembroke, Pembroke, NC 28372, USA)

Abstract

Econometrics and input–output models have been presented to construct a joint model (i.e., an EC + IO model) in the paper, which is characterized by incorporating the uncertainty of the real economy with the detailed departmental classification structure, as well as adding recovery period variables in the joint model to make the model dynamic. By designing and implementing a static model, it is estimated that the indirect economic loss for the transportation sector caused by representative haze pollution of Beijing in 2013 was 23.7 million yuan. The industrial-related indirect losses due to the direct economic losses incurred by haze pollution reached 102 million yuan. With the constructed dynamic model, the cumulative economic losses for the industrial sectors have been calculated for the recovery periods of different durations. The results show that: (1) the longer the period that an industrial department returns to normal output after haze pollution has impacted, the greater the cumulative economic loss will be; (2) when the recovery period is one year, the cumulative economic loss value computed by the dynamic EC + IO model is much smaller than the loss value obtained by the static EC + IO model; (3) the recovery curves of industrial sectors show that the recovery rate at the early stage is fast, while it is slow afterwards. Therefore, the governance work after the occurrence of haze pollution should be launched as soon as possible. This study provides a theoretical basis for evaluating the indirect economic losses of haze pollution and demonstrates the value of popularization and application.

Suggested Citation

  • Jibo Chen & Keyao Chen & Guizhi Wang & Rongrong Chen & Xiaodong Liu & Guo Wei, 2019. "Indirect Economic Impact Incurred by Haze Pollution: An Econometric and Input–Output Joint Model," IJERPH, MDPI, vol. 16(13), pages 1-14, July.
  • Handle: RePEc:gam:jijerp:v:16:y:2019:i:13:p:2328-:d:244866
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    References listed on IDEAS

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    3. Guizhi Wang & Rongrong Chen & Jibo Chen, 2017. "Direct and indirect economic loss assessment of typhoon disasters based on EC and IO joint model," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 87(3), pages 1751-1764, July.
    4. Fan Yang & Ling Ding & Cai Liu & Lizheng Xu & Stephen Nicholas & Jian Wang, 2018. "Haze Attitudes and the Willingness to Pay for Haze Improvement: Evidence from Four Cities in Shandong Province, China," IJERPH, MDPI, vol. 15(10), pages 1-15, October.
    5. Jibo Chen & Keyao Chen & Guizhi Wang & Lingyan Wu & Xiaodong Liu & Guo Wei, 2019. "PM 2.5 Pollution and Inhibitory Effects on Industry Development: A Bidirectional Correlation Effect Mechanism," IJERPH, MDPI, vol. 16(7), pages 1-21, March.
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    Cited by:

    1. Dianyuan Ma & Hui Sun & Xuechao Xia & Yan Zhao, 2022. "The Impact of Government and Public Dual-Subject Environmental Concerns on Urban Haze Pollution: An Empirical Research on 279 Cities in China," Sustainability, MDPI, vol. 14(16), pages 1-21, August.

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