IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i19p8620-d1758169.html

Threshold Effects of PM 2.5 on Pension Contributions: A Fuzzy Regression Discontinuity Design and Machine Learning Approach

Author

Listed:
  • Bingxia Wang

    (Institute of Mathematical Sciences, Faculty of Science, Universiti Malaya, Kuala Lumper 50603, Malaysia
    Department of Finance and Commerce, Chongqing Jianzhu College, Chongqing 400072, China)

  • Zailan Siri

    (Institute of Mathematical Sciences, Faculty of Science, Universiti Malaya, Kuala Lumper 50603, Malaysia)

  • Mohd Azmi Haron

    (Institute of Mathematical Sciences, Faculty of Science, Universiti Malaya, Kuala Lumper 50603, Malaysia)

Abstract

Air pollution risk significantly impacts social and economic systems. Given the critical role of the pension system in socioeconomic stability, it is crucial to explore the impact of air pollution on pension contributions. Utilizing panel data from eight Chinese provinces between 2014 and 2024, this study quantifies the impact of Particulate Matter (PM 2.5 ) on pension contributions and explores its nonlinear and lagged effects through a fuzzy regression discontinuity design (FRDD) coupled with double machine learning (DML) techniques. Through the application of the FRDD, we found that pension contributions are significantly reduced when the PM 2.5 concentration exceeds the standard annual threshold of 35 µ g / m 3 , and the effects differ between the Urban Employees Basic Pension Insurance (UEBPI) and the Urban and Rural Residents’ Pension Scheme (URRPS). Further, the DML approach validated these findings and suggested that a complex hysteresis response mechanism exists in relation to air pollution. Additionally, it indicated that when PM 2.5 concentrations do not exceed the threshold, this similarly has a negative effect on pension contributions. These findings emphasize the need for policymakers and pension fund managers to integrate environmental considerations into pension sustainability strategies to increase resilience to ongoing environmental risks.

Suggested Citation

  • Bingxia Wang & Zailan Siri & Mohd Azmi Haron, 2025. "Threshold Effects of PM 2.5 on Pension Contributions: A Fuzzy Regression Discontinuity Design and Machine Learning Approach," Sustainability, MDPI, vol. 17(19), pages 1-27, September.
  • Handle: RePEc:gam:jsusta:v:17:y:2025:i:19:p:8620-:d:1758169
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/19/8620/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/17/19/8620/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Koichiro Ito & Shuang Zhang, 2020. "Willingness to Pay for Clean Air: Evidence from Air Purifier Markets in China," Journal of Political Economy, University of Chicago Press, vol. 128(5), pages 1627-1672.
    2. Giovanis, Eleftherios & Ozdamar, Oznur, 2018. "Health status, mental health and air quality: evidence from pensioners in Europe," MPRA Paper 86483, University Library of Munich, Germany.
    3. Li, Lixing & Liu, Kevin Zhengcheng & Nie, Zhuo & Xi, Tianyang, 2021. "Evading by any means? VAT enforcement and payroll tax evasion in China," Journal of Economic Behavior & Organization, Elsevier, vol. 185(C), pages 770-784.
    4. Robert Novy‐Marx & Joshua Rauh, 2011. "Public Pension Promises: How Big Are They and What Are They Worth?," Journal of Finance, American Finance Association, vol. 66(4), pages 1211-1249, August.
    5. Tom Chang & Joshua S. Graff Zivin & Tal Gross & Matthew J. Neidell, 2019. "Corrigendum: Particulate Pollution and the Productivity of Pear Packers," American Economic Journal: Economic Policy, American Economic Association, vol. 11(3), pages 454-456, August.
    6. Imbens, Guido W. & Lemieux, Thomas, 2008. "Regression discontinuity designs: A guide to practice," Journal of Econometrics, Elsevier, vol. 142(2), pages 615-635, February.
    7. Stefan Wager & Susan Athey, 2018. "Estimation and Inference of Heterogeneous Treatment Effects using Random Forests," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(523), pages 1228-1242, July.
    8. McCrary, Justin, 2008. "Manipulation of the running variable in the regression discontinuity design: A density test," Journal of Econometrics, Elsevier, vol. 142(2), pages 698-714, February.
    9. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey & James Robins, 2018. "Double/debiased machine learning for treatment and structural parameters," Econometrics Journal, Royal Economic Society, vol. 21(1), pages 1-68, February.
    10. Gan, Hongwu & Guo, Mengmeng & Li, Jian & Niu, Geng & Zhou, Yang, 2025. "Air pollution and household stock market participation," Journal of Banking & Finance, Elsevier, vol. 172(C).
    11. Zhe Michelle Dong & Han Lin Shang & Aaron Bruhn, 2022. "Air Pollution and Mortality Impacts," Risks, MDPI, vol. 10(6), pages 1-21, June.
    12. Julius J. Andersson, 2019. "Carbon Taxes and CO2 Emissions: Sweden as a Case Study," American Economic Journal: Economic Policy, American Economic Association, vol. 11(4), pages 1-30, November.
    13. Bingxia Wang & Mohd Azmi Haron & Zailan Siri, 2024. "The Impact of Air Pollution Risk on the Sustainability of Crop Insurance Losses," Sustainability, MDPI, vol. 16(19), pages 1-23, October.
    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. Arne Henningsen & Guy Low & David Wuepper & Tobias Dalhaus & Hugo Storm & Dagim Belay & Stefan Hirsch, 2024. "Estimating Causal Effects with Observational Data: Guidelines for Agricultural and Applied Economists," IFRO Working Paper 2024/03, University of Copenhagen, Department of Food and Resource Economics.
    2. Moritz A. Drupp & Ulrike Kornek & Jasper N. Meya & Lutz Sager, 2021. "Inequality and the Environment: The Economics of a Two-Headed Hydra," CESifo Working Paper Series 9447, CESifo.
    3. Tingting Xie & Yong Wang & Ye Yuan, 2024. "Health Benefits from Improved Air Quality: Evidence from Pollution Regulations in China’s “ $$2{+}26$$ 2 + 26 ” Cities," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 87(5), pages 1175-1221, May.
    4. Tao Lin & Wenhao Qian & Hongwei Wang & Yu Feng, 2022. "Air Pollution and Workplace Choice: Evidence from China," IJERPH, MDPI, vol. 19(14), pages 1-23, July.
    5. Huber, Martin, 2019. "An introduction to flexible methods for policy evaluation," FSES Working Papers 504, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    6. Zining Liu & Cheng Wan, 2024. "Air pollution and the burden of long‐term care: Evidence from China," Health Economics, John Wiley & Sons, Ltd., vol. 33(6), pages 1241-1265, June.
    7. Waddell, Glen R. & McDonough, Robert, 2022. "Mean Convergence, Combinatorics, and Grade-Point Averages," IZA Discussion Papers 15414, IZA Network @ LISER.
    8. 'Agoston Reguly, 2021. "Discovering Heterogeneous Treatment Effects in Regression Discontinuity Designs," Papers 2106.11640, arXiv.org, revised Aug 2025.
    9. Qi, Jianhong & Wang, Shanshan & Zhang, Zhitong, 2024. "Export cost of air pollution: A regression discontinuity design," Structural Change and Economic Dynamics, Elsevier, vol. 71(C), pages 337-353.
    10. Yiqi Liu & Yuan Qi, 2023. "Using Forests in Multivariate Regression Discontinuity Designs," Papers 2303.11721, arXiv.org, revised Jun 2025.
    11. Ma, Yuxuan, 2021. "Does Bad Air Quality Contribute to Obesity? Evidence from Chinas Central Heating System," Warwick-Monash Economics Student Papers 18, Warwick Monash Economics Student Papers.
    12. Justin Whitehouse & Qizhao Chen & Morgane Austern & Vasilis Syrgkanis, 2025. "Inference on Optimal Policy Values and Other Irregular Functionals via Softmax Smoothing," Papers 2507.11780, arXiv.org, revised Mar 2026.
    13. Jason M. Lindo & Nicholas J. Sanders & Philip Oreopoulos, 2010. "Ability, Gender, and Performance Standards: Evidence from Academic Probation," American Economic Journal: Applied Economics, American Economic Association, vol. 2(2), pages 95-117, April.
    14. Marcel Fafchamps & Julien Labonne, 2017. "Do Politicians’ Relatives Get Better Jobs? Evidence from Municipal Elections," The Journal of Law, Economics, and Organization, Oxford University Press, vol. 33(2), pages 268-300.
    15. Davide Viviano & Jelena Bradic, 2019. "Synthetic learner: model-free inference on treatments over time," Papers 1904.01490, arXiv.org, revised Aug 2022.
    16. Ivan A Canay & Vishal Kamat, 2018. "Approximate Permutation Tests and Induced Order Statistics in the Regression Discontinuity Design," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 85(3), pages 1577-1608.
    17. De Paola, Maria & Scoppa, Vincenzo, 2015. "Procrastination, academic success and the effectiveness of a remedial program," Journal of Economic Behavior & Organization, Elsevier, vol. 115(C), pages 217-236.
    18. Arteaga, Irma & Heflin, Colleen & Gable, Sara, 2016. "The impact of aging out of WIC on food security in households with children," Children and Youth Services Review, Elsevier, vol. 69(C), pages 82-96.
    19. Elek, Péter & Bíró, Anikó, 2021. "Regional differences in diabetes across Europe – regression and causal forest analyses," Economics & Human Biology, Elsevier, vol. 40(C).
    20. Humlum, Maria Knoth & Kristoffersen, Jannie H.G. & Vejlin, Rune, 2017. "College admissions decisions, educational outcomes, and family formation," Labour Economics, Elsevier, vol. 48(C), pages 215-230.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:gam:jsusta:v:17:y:2025:i:19:p:8620-:d:1758169. 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.