IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v163y2018icp110-113.html
   My bibliography  Save this article

On the density estimation of air pollution in Beijing

Author

Listed:
  • Fan, Yanqin
  • Hou, Lei
  • Yan, Karen X.

Abstract

We apply both the kernel method and the k-nearest neighbor (k-nn) method to estimate the density of air pollutant PM2.5 in Beijing. We find that the k-nn method accommodates the data better and delivers a more reasonable density estimate than the kernel method. Then we compare the density estimates between summer and winter, rush and non-rush hours. Results suggest that the air pollution is more serious in winter and rush hours.

Suggested Citation

  • Fan, Yanqin & Hou, Lei & Yan, Karen X., 2018. "On the density estimation of air pollution in Beijing," Economics Letters, Elsevier, vol. 163(C), pages 110-113.
  • Handle: RePEc:eee:ecolet:v:163:y:2018:i:c:p:110-113
    DOI: 10.1016/j.econlet.2017.12.020
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165176517305153
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.econlet.2017.12.020?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Frank, M. & Stengos, T., 1989. "Nearest Neighbor Forecasts Of Precious Metel Rates Of Return," Working Papers 1989-2, University of Guelph, Department of Economics and Finance.
    2. Selden Thomas M. & Song Daqing, 1994. "Environmental Quality and Development: Is There a Kuznets Curve for Air Pollution Emissions?," Journal of Environmental Economics and Management, Elsevier, vol. 27(2), pages 147-162, September.
    3. Gan, Li & Li, Qi, 2016. "Efficiency of thin and thick markets," Journal of Econometrics, Elsevier, vol. 192(1), pages 40-54.
    4. Mack, Y. P. & Rosenblatt, M., 1979. "Multivariate k-nearest neighbor density estimates," Journal of Multivariate Analysis, Elsevier, vol. 9(1), pages 1-15, March.
    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. Xu, Bing & Lin, Weiran & Taqi, Syed Ali, 2020. "The impact of wind and non-wind factors on PM2.5 levels," Technological Forecasting and Social Change, Elsevier, vol. 154(C).
    2. Kuznetsov, G.V. & Malyshev, D. Yu & Kostoreva, Zh.A. & Syrodoy, S.V. & Gutareva, N. Yu., 2020. "The ignition of the bio water-coal fuel particles based on coals of different degree metamorphism," Energy, Elsevier, vol. 201(C).
    3. Weiran Lin & Qiuqin He, 2021. "The Influence of Potential Infection on the Relationship between Temperature and Confirmed Cases of COVID-19 in China," Sustainability, MDPI, vol. 13(15), pages 1-11, July.

    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. Zheng Li & Guannan Liu & Qi Li, 2017. "Nonparametric Knn estimation with monotone constraints," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 988-1006, October.
    2. Nasreen, Samia & Anwar, Sofia & Ozturk, Ilhan, 2017. "Financial stability, energy consumption and environmental quality: Evidence from South Asian economies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 1105-1122.
    3. Khan, Syed Abdul Rehman & Zaman, Khalid & Zhang, Yu, 2016. "The relationship between energy-resource depletion, climate change, health resources and the environmental Kuznets curve: Evidence from the panel of selected developed countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 468-477.
    4. Opschoor, J. (Hans) B., 1995. "Ecospace and the fall and rise of throughput intensity," Ecological Economics, Elsevier, vol. 15(2), pages 137-140, November.
    5. Sebri, Maamar, 2009. "La Zone Méditerranéenne Face à la Pollution de L’air : Une Investigation Econométrique [The Mediterranean Zone in front of Air pollution: an Econometric Investigation]," MPRA Paper 32382, University Library of Munich, Germany.
    6. Muhammad Shahbaz & Syed Jawad Hussain Shahzad & Mantu Kumar Mahalik & Perry Sadorsky, 2018. "How strong is the causal relationship between globalization and energy consumption in developed economies? A country-specific time-series and panel analysis," Applied Economics, Taylor & Francis Journals, vol. 50(13), pages 1479-1494, March.
    7. Daniel Fiorino, 2011. "Explaining national environmental performance: approaches, evidence, and implications," Policy Sciences, Springer;Society of Policy Sciences, vol. 44(4), pages 367-389, November.
    8. Tomiwa Sunday Adebayo & Abraham Ayobamiji Awosusi & Seun Damola Oladipupo & Ephraim Bonah Agyekum & Arunkumar Jayakumar & Nallapaneni Manoj Kumar, 2021. "Dominance of Fossil Fuels in Japan’s National Energy Mix and Implications for Environmental Sustainability," IJERPH, MDPI, vol. 18(14), pages 1-20, July.
    9. Mazzanti, Massimiliano & Montini, Anna & Zoboli, Roberto, 2006. "Municipal Waste Production, Economic Drivers, and 'New' Waste Policies: EKC Evidence from Italian Regional and Provincial Panel Data," Climate Change Modelling and Policy Working Papers 12053, Fondazione Eni Enrico Mattei (FEEM).
    10. Saidi Kais & Ben Mbarek Mounir, 2017. "Causal interactions between environmental degradation, renewable energy, nuclear energy and real GDP: a dynamic panel data approach," Environment Systems and Decisions, Springer, vol. 37(1), pages 51-67, March.
    11. Anastasios Xepapadeas & Esma Amri, 1998. "Some Empirical Indications of the Relationship Between Environmental Quality and Economic Development," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 11(1), pages 93-106, January.
    12. Zhenkai Yang & Mei-Chih Wang & Tsangyao Chang & Wing-Keung Wong & Fangjhy Li, 2022. "Which Factors Determine CO 2 Emissions in China? Trade Openness, Financial Development, Coal Consumption, Economic Growth or Urbanization: Quantile Granger Causality Test," Energies, MDPI, vol. 15(7), pages 1-18, March.
    13. Taguchi, Hiroyuki, 2024. "Air pollutions and its control governance in Chinese provinces in post-COVID-19 era: panel estimations of provincial environmental Kuznets curves," MPRA Paper 121488, University Library of Munich, Germany.
    14. Matthew A. Cole & Robert J.R. Elliott & Jing Zhang, 2011. "Growth, Foreign Direct Investment, And The Environment: Evidence From Chinese Cities," Journal of Regional Science, Wiley Blackwell, vol. 51(1), pages 121-138, February.
    15. Rothman, Dale S., 1998. "Environmental Kuznets curves--real progress or passing the buck?: A case for consumption-based approaches," Ecological Economics, Elsevier, vol. 25(2), pages 177-194, May.
    16. B. Venkatraja, 2021. "Does China exhibit any evidence of an Environmental Kuznets Curve? An ARDL bounds testing approach," Economic Thought journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 1, pages 88-110,111-.
    17. Pei-Ing Wu & Je-Liang Liou & Hung-Yi Chang, 2015. "Alternative exploration of EKC for $$\hbox {CO}_{2}$$ CO 2 emissions: inclusion of meta-technical ratio in quantile regression model," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(1), pages 57-73, January.
    18. Andreoni, James & Levinson, Arik, 2001. "The simple analytics of the environmental Kuznets curve," Journal of Public Economics, Elsevier, vol. 80(2), pages 269-286, May.
    19. Mina Baliamoune-Lutz, 2017. "Trade and Environmental Quality in African Countries: Do Institutions Matter?," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 43(1), pages 155-172, January.
    20. Shahbaz, Muhammad & Nasreen, Samia & Ahmed, Khalid & Hammoudeh, Shawkat, 2017. "Trade openness–carbon emissions nexus: The importance of turning points of trade openness for country panels," Energy Economics, Elsevier, vol. 61(C), pages 221-232.

    More about this item

    Keywords

    Density estimation; k-nn method; Air pollution;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

    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:eee:ecolet:v:163:y:2018:i:c:p:110-113. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ecolet .

    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.