IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i12p9404-d1168923.html
   My bibliography  Save this article

The Non-Linear Relationship between Air Pollution, Labor Insurance and Productivity: Multivariate Adaptive Regression Splines Approach

Author

Listed:
  • Syamsiyatul Muzayyanah

    (Department of Business Administration, Chaoyang University of Technology, Taichung 413310, Taiwan)

  • Cheng-Yih Hong

    (Faculty of Finance, Chaoyang University of Technology, Taichung 413310, Taiwan)

  • Rishan Adha

    (Department of Statistics, National Chengchi University, Taipei 11605, Taiwan
    Graduate Institute of Applied Physics, National Chengchi University, Taipei 11605, Taiwan
    Faculty of Social and Political Science, Muhammadiyah University of Mataram, Mataram 83115, Indonesia)

  • Su-Fen Yang

    (Department of Statistics, National Chengchi University, Taipei 11605, Taiwan)

Abstract

This study explores the non-linear relationship between air pollution, socio-economic factors, labor insurance, and labor productivity in the industrial sector in Taiwan. Using machine learning, specifically multivariate adaptive regression splines (MARS), provides an alternative approach to examining the impact of air pollution on labor productivity, apart from the traditional linear relationships and parametric methods employed in previous studies. Examining this topic is imperative for advancing the knowledge on the effects of air pollution on labor productivity and its association with labor insurance, employing a machine learning framework. The results reveal that air pollution, particularly PM 10 , has a negative impact on labor productivity. Lowering the PM 10 level below 36.2 μg/m 3 leads to an increase in marginal labor productivity. Additionally, the study identifies labor insurance as a significant factor in improving productivity, with a 9% increase in the total number of labor insurance holders resulting in a substantial 42.9% increase in productivity. Notably, a link between air pollution and insurance is observed, indicating that lower air pollution levels tend to be associated with higher labor insurance coverage. This research holds valuable implications for policymakers, businesses, and industries as it offers insights into improving labor productivity and promoting sustainable economic development.

Suggested Citation

  • Syamsiyatul Muzayyanah & Cheng-Yih Hong & Rishan Adha & Su-Fen Yang, 2023. "The Non-Linear Relationship between Air Pollution, Labor Insurance and Productivity: Multivariate Adaptive Regression Splines Approach," Sustainability, MDPI, vol. 15(12), pages 1-20, June.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:12:p:9404-:d:1168923
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/12/9404/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/12/9404/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Elena Grinza & François Rycx, 2020. "The Impact of Sickness Absenteeism on Firm Productivity: New Evidence from Belgian Matched Employer–Employee Panel Data," Industrial Relations: A Journal of Economy and Society, Wiley Blackwell, vol. 59(1), pages 150-194, January.
    2. Rita Yi Man Li & Yi Lut Li & M. James C. Crabbe & Otilia Manta & Muhammad Shoaib, 2021. "The Impact of Sustainability Awareness and Moral Values on Environmental Laws," Sustainability, MDPI, vol. 13(11), pages 1-26, May.
    3. Naoki Aizawa & Hanming Fang, 2020. "Equilibrium Labor Market Search and Health Insurance Reform," Journal of Political Economy, University of Chicago Press, vol. 128(11), pages 4258-4336.
    4. Jiaxiu He & Haoming Liu & Alberto Salvo, 2019. "Severe Air Pollution and Labor Productivity: Evidence from Industrial Towns in China," American Economic Journal: Applied Economics, American Economic Association, vol. 11(1), pages 173-201, January.
    5. Yuo-Hsien Shiau & Su-Fen Yang & Rishan Adha & Syamsiyatul Muzayyanah, 2022. "Modeling Industrial Energy Demand in Relation to Subsector Manufacturing Output and Climate Change: Artificial Neural Network Insights," Sustainability, MDPI, vol. 14(5), pages 1-18, March.
    6. Peyman Yariyan & Saeid Janizadeh & Tran Phong & Huu Duy Nguyen & Romulus Costache & Hiep Le & Binh Thai Pham & Biswajeet Pradhan & John P. Tiefenbacher, 2020. "Improvement of Best First Decision Trees Using Bagging and Dagging Ensembles for Flood Probability Mapping," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(9), pages 3037-3053, July.
    7. Snezhana Gocheva-Ilieva & Atanas Ivanov & Maya Stoimenova-Minova, 2022. "Prediction of Daily Mean PM 10 Concentrations Using Random Forest, CART Ensemble and Bagging Stacked by MARS," Sustainability, MDPI, vol. 14(2), pages 1-26, January.
    8. Dizioli, Allan & Pinheiro, Roberto, 2016. "Health insurance as a productive factor," Labour Economics, Elsevier, vol. 40(C), pages 1-24.
    9. Tom Chang & Joshua Graff Zivin & Tal Gross & Matthew Neidell, 2016. "Particulate Pollution and the Productivity of Pear Packers," American Economic Journal: Economic Policy, American Economic Association, vol. 8(3), pages 141-169, August.
    10. Konrad Bogner & Florian Pappenberger & Massimiliano Zappa, 2019. "Machine Learning Techniques for Predicting the Energy Consumption/Production and Its Uncertainties Driven by Meteorological Observations and Forecasts," Sustainability, MDPI, vol. 11(12), pages 1-22, June.
    11. Cyprian Amutabi & Anthony Wambugu, 2020. "Determinants of labor productivity among SMEs and large‐sized private service firms in Kenya," African Development Review, African Development Bank, vol. 32(4), pages 591-604, December.
    12. Rishan Adha & Cheng-Yih Hong, 2021. "How Large the Direct Rebound Effect for Residential Electricity Consumption When the Artificial Neural Network Takes on the Role? A Taiwan Case Study of Household Electricity Consumption," International Journal of Energy Economics and Policy, Econjournals, vol. 11(3), pages 354-364.
    13. Mohammed Alamoudi & Osman Taylan & Behrooz Keshtegar & Mona Abusurrah & Mohammed Balubaid, 2022. "Modeling Sulphur Dioxide (SO 2 ) Quality Levels of Jeddah City Using Machine Learning Approaches with Meteorological and Chemical Factors," Sustainability, MDPI, vol. 14(23), pages 1-21, December.
    14. Joshua Graff Zivin & Matthew Neidell, 2012. "The Impact of Pollution on Worker Productivity," American Economic Review, American Economic Association, vol. 102(7), pages 3652-3673, December.
    15. Pami Dua & Niti Khandelwal Garg, 2019. "Determinants of labour productivity: Comparison between developing and developed countries of Asia‐Pacific," Pacific Economic Review, Wiley Blackwell, vol. 24(5), pages 686-704, December.
    Full references (including those not matched with items on IDEAS)

    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. repec:ags:aaea22:335436 is not listed on IDEAS
    2. Lin, Jiada & Wan, Haiyuan & Yu, Yangcheng, 2024. "What you breathe makes you poor: The effect of air pollution on income," China Economic Review, Elsevier, vol. 83(C).
    3. Colmer, Jonathan & Lin, Dajun & Liu, Siying & Shimshack, Jay, 2021. "Why are pollution damages lower in developed countries? Insights from high-Income, high-particulate matter Hong Kong," Journal of Health Economics, Elsevier, vol. 79(C).
    4. Timothy J. Halliday & Rachel Inafuku & Lester Lusher & Aureo de Paula, 2022. "VOG: Using Volcanic Eruptions to Estimate the Impact of Air Pollution on Student Learning Outcomes," Working Papers 202203, University of Hawaii at Manoa, Department of Economics.
    5. Liu, Haoming & Salvo, Alberto, 2017. "Severe Air Pollution and School Absences: Longitudinal Data on Expatriates in North China," IZA Discussion Papers 11134, Institute of Labor Economics (IZA).
    6. Zhang, Xin & Zhang, Xiaobo & Chen, Xi, 2017. "Happiness in the air: How does a dirty sky affect mental health and subjective well-being?," Journal of Environmental Economics and Management, Elsevier, vol. 85(C), pages 81-94.
    7. Aloys Prinz & David J. Richter, 2021. "Feinstaubbelastung und Lebenserwartung in Deutschland," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 15(3), pages 237-272, December.
    8. Felix Bracht & Dennis Verhoeven, 2021. "Air pollution and innovation," CEP Discussion Papers dp1817, Centre for Economic Performance, LSE.
    9. Picchio, Matteo & van Ours, Jan C., 2024. "The impact of high temperatures on performance in work-related activities," Labour Economics, Elsevier, vol. 87(C).
    10. Jindong Wu & Jiantao Weng & Bing Xia & Yujie Zhao & Qiuji Song, 2021. "The Synergistic Effect of PM 2.5 and CO 2 Concentrations on Occupant Satisfaction and Work Productivity in a Meeting Room," IJERPH, MDPI, vol. 18(8), pages 1-21, April.
    11. de Oliveira, Guilherme & Lima, Gilberto Tadeu, 2022. "Economic growth as a double-edged sword: The pollution-adjusted Kaldor-Verdoorn effect," Ecological Economics, Elsevier, vol. 199(C).
    12. Aragón, Fernando M. & Miranda, Juan Jose & Oliva, Paulina, 2017. "Particulate matter and labor supply: The role of caregiving and non-linearities," Journal of Environmental Economics and Management, Elsevier, vol. 86(C), pages 295-309.
    13. Diane Alexander & Hannes Schwandt, 2022. "The Impact of Car Pollution on Infant and Child Health: Evidence from Emissions Cheating," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 89(6), pages 2872-2910.
    14. Michelle Marcus, 2021. "Pollution at schools and children's aerobic capacity," Health Economics, John Wiley & Sons, Ltd., vol. 30(12), pages 3016-3031, December.
    15. Zhonghua Huang & Xuejun Du, 2022. "Does air pollution affect investor cognition and land valuation? Evidence from the Chinese land market," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 50(2), pages 593-613, June.
    16. Agarwal, Sumit & Wang, Long & Yang, Yang, 2021. "Impact of transboundary air pollution on service quality and consumer satisfaction," Journal of Economic Behavior & Organization, Elsevier, vol. 192(C), pages 357-380.
    17. Benjamin A. Jones, 2020. "Labor Market Impacts of Deforestation Caused by Invasive Species Spread," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 77(1), pages 159-190, September.
    18. Bridget Hoffmann & Juan Pablo Rud, 2022. "Exposure or Income? The Unequal Effects of Pollution on Daily Labor Supply," Working Papers 109, Red Nacional de Investigadores en Economía (RedNIE).
    19. Felix Holub & Laura Hospido & Ulrich J. Wagner, 2020. "Urban air pollution and sick leaves: evidence from social security data," Working Papers 2041, Banco de España.
    20. Yao, Yao & Li, Xue & Smyth, Russell & Zhang, Lin, 2022. "Air pollution and political trust in local government: Evidence from China," Journal of Environmental Economics and Management, Elsevier, vol. 115(C).
    21. Yu SHEN & Wenkai SUN, 2023. "Information and avoidance behaviour: The effect of air pollution disclosure on labour supply in China," International Labour Review, International Labour Organization, vol. 162(4), pages 665-686, December.

    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:gam:jsusta:v:15:y:2023:i:12:p:9404-:d:1168923. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.