IDEAS home Printed from https://ideas.repec.org/a/rjr/romjef/vy2022i3p128-143.html
   My bibliography  Save this article

What Makes the Level of Particulate Matter Emissions Worse in Korea?

Author

Listed:
  • Eunmo YANG

    (Department of Economics, Sungkyunkwan University, Seoul, Republic of Korea.)

  • Hojoong BAE

    (Korean Women’s Development Institute, Seoul, Republic of Korea.)

  • Doojin RYU

    (Department of Economics, Sungkyunkwan University, Seoul, Republic of Korea.)

Abstract

This study empirically examines the effects of economic activities on air pollution, especially particulate matter 2.5 (PM2.5) and particulate matter 10 (PM10). Using monthly regional panel data, we explain which socioeconomic activities worsen air pollution levels. Our results show that some economic activities, such as manufacturing of chemical products and chemicals, and diesel consumption increase both PM10 and PM2.5 emission levels. As diesel consumption increases, PM10 emission level increases according to the GLS (generalized least squares) estimations. In addition, as the manufacturing of coke, briquettes, and petroleum products increases, the PM2.5 emission level increases. As the manufacturing of chemical products and chemicals increases, both PM10 and PM2.5 emission levels increase in neighboring regions using SDM(b). Diesel consumption has also a positive effect on the increase in the PM2.5 emission level in neighboring regions using SDM(a). As the number of precipitation days increases, both PM10 and PM2.5 emission levels decrease according to the GLS estimates, SDM(b). We forecast that both PM10 and PM2.5 levels will continue to rise if people continue to engage in certain socioeconomic activities, such as chemicals, coke, briquettes, petroleum products manufacturing, and diesel consumption. However, serious levels of pollution may not necessarily arise in the future, as using new and renewable energy lowers the levels of both PM10 and PM2.5 according to the SDM(a) and (b). These findings help to explain future air quality level forecasts using monthly regional data with spatial dependence.

Suggested Citation

  • Eunmo YANG & Hojoong BAE & Doojin RYU, 2022. "What Makes the Level of Particulate Matter Emissions Worse in Korea?," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 128-143, October.
  • Handle: RePEc:rjr:romjef:v::y:2022:i:3:p:128-143
    as

    Download full text from publisher

    File URL: https://www.ipe.ro/rjef/rjef3_2022/rjef3_2022p128-143.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. M. Hashem Pesaran, 2015. "Testing Weak Cross-Sectional Dependence in Large Panels," Econometric Reviews, Taylor & Francis Journals, vol. 34(6-10), pages 1089-1117, December.
    2. repec:bla:obuest:v:61:y:1999:i:0:p:631-52 is not listed on IDEAS
    3. Pesaran, M. Hashem & Vanessa Smith, L. & Yamagata, Takashi, 2013. "Panel unit root tests in the presence of a multifactor error structure," Journal of Econometrics, Elsevier, vol. 175(2), pages 94-115.
    4. Pesaran, M. Hashem & Smith, Ron, 1995. "Estimating long-run relationships from dynamic heterogeneous panels," Journal of Econometrics, Elsevier, vol. 68(1), pages 79-113, July.
    5. M. Hashem Pesaran, 2007. "A simple panel unit root test in the presence of cross-section dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(2), pages 265-312.
    6. Peter C. B. Phillips & Donggyu Sul, 2007. "Transition Modeling and Econometric Convergence Tests," Econometrica, Econometric Society, vol. 75(6), pages 1771-1855, November.
    7. G. S. Maddala & Shaowen Wu, 1999. "A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(S1), pages 631-652, November.
    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. Cheng, Rui & Frijns, Bart & Kim, Hyeongjun & Ryu, Doojin, 2024. "Effects of option incentive compensation on corporate innovation: The case of China," Economic Systems, Elsevier, vol. 48(1).

    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. Bakry, Walid & Nghiem, Xuan-Hoa & Farouk, Sherine & Vo, Xuan Vinh, 2023. "Does it hurt or help? Revisiting the effects of ICT on economic growth and energy consumption: A nonlinear panel ARDL approach," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 597-617.
    2. Škare, Marinko & Porada-Rochoń, Małgorzata, 2023. "Are we making progress on decarbonization? A panel heterogeneous study of the long-run relationship in selected economies," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
    3. Mariam Camarero & Sergi Moliner & Cecilio Tamarit, 2022. "Which are the long-run determinants of US outward FDI? Evidence using large long-memory panels," Working Papers 2022.08, International Network for Economic Research - INFER.
    4. Sudeshna Ghosh, 2022. "Effects of tourism on carbon dioxide emissions, a panel causality analysis with new data sets," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(3), pages 3884-3906, March.
    5. Chakraborty, Saptorshee Kanto & Mazzanti, Massimiliano, 2020. "Energy intensity and green energy innovation: Checking heterogeneous country effects in the OECD," Structural Change and Economic Dynamics, Elsevier, vol. 52(C), pages 328-343.
    6. Eibinger, Tobias & Deixelberger, Beate & Manner, Hans, 2024. "Panel data in environmental economics: Econometric issues and applications to IPAT models," Journal of Environmental Economics and Management, Elsevier, vol. 125(C).
    7. Jibril, Halima & Chaudhuri, Kausik & Mohaddes, Kamiar, 2020. "Asymmetric oil prices and trade imbalances: Does the source of the oil shock matter?," Energy Policy, Elsevier, vol. 137(C).
    8. Cem Ertur & Antonio Musolesi, 2017. "Weak and Strong Cross‐Sectional Dependence: A Panel Data Analysis of International Technology Diffusion," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(3), pages 477-503, April.
    9. Chakraborty, Saptorshee Kanto & Mazzanti, Massimiliano, 2021. "Renewable electricity and economic growth relationship in the long run: Panel data econometric evidence from the OECD," Structural Change and Economic Dynamics, Elsevier, vol. 59(C), pages 330-341.
    10. Marcus Box & Karl Gratzer & Xiang Lin, 2023. "Self-employment, corruption, and property rights: a comparative analysis of European and CEE economies," SN Business & Economics, Springer, vol. 3(1), pages 1-29, January.
    11. Mounir Dahmani & Mohamed Mabrouki & Adel Ben Youssef, 2022. "The Information and Communication Technologies-Economic Growth Nexus in Tunisia - A Cross-Section Dynamic Panel Approach," Montenegrin Journal of Economics, Economic Laboratory for Transition Research (ELIT), vol. 18(2), pages 161-174.
    12. Khan, Zeeshan & Haouas, Ilham & Trinh, Hai Hong & Badeeb, Ramez Abubakr & Zhang, Changyong, 2023. "Financial inclusion and energy poverty nexus in the era of globalization: Role of composite risk index and energy investment in emerging economies," Renewable Energy, Elsevier, vol. 204(C), pages 382-399.
    13. Baráth, Lajos & Fertő, Imre, 2020. "Accounting for TFP Growth in Global Agriculture - a Common-Factor- Approach-Based TFP Estimation," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 12(4), December.
    14. Cem Ertur & Antonio Musolesi, 2014. "Dépendance individuelle forte et faible : une analyse en données de panel de la diffusion internationale de la technologie," Working Papers halshs-01015208, HAL.
    15. Elisabet Rodriguez Llorian & Janelle Mann, 2022. "Exploring the technology–healthcare expenditure nexus: a panel error correction approach," Empirical Economics, Springer, vol. 62(6), pages 3061-3086, June.
    16. Trofimov, Ivan D., 2020. "Is There a J-Curve Effect in the Services Trade in Canada? A Panel Data Analysis," MPRA Paper 106704, University Library of Munich, Germany.
    17. Schneider, Nicolas & Strielkowski, Wadim, 2023. "Modelling the unit root properties of electricity data—A general note on time-domain applications," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 618(C).
    18. Masako Ikegami & Zijian Wang, 2024. "Does energy technology R&D save energy in OECD countries?," Economic Change and Restructuring, Springer, vol. 57(2), pages 1-22, April.
    19. Ibrahim D. Raheem & Aviral K. Tiwari & Daniel Balsalobre-lorente, 2019. "The Role of ICT and Financial Development on CO2 Emissions and Economic Growth," Working Papers of the African Governance and Development Institute. 19/058, African Governance and Development Institute..
    20. Acikgoz, Senay & Ben Ali, Mohamed Sami, 2019. "Where does economic growth in the Middle Eastern and North African countries come from?," The Quarterly Review of Economics and Finance, Elsevier, vol. 73(C), pages 172-183.

    More about this item

    Keywords

    air pollution forecasting; emerging economy; particulate matter emission; spatial dependence; sustainable development;
    All these keywords.

    JEL classification:

    • Q53 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • Q58 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Government Policy

    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:rjr:romjef:v::y:2022:i:3:p:128-143. 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: Corina Saman (email available below). General contact details of provider: https://edirc.repec.org/data/ipacaro.html .

    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.