IDEAS home Printed from https://ideas.repec.org/a/spr/stmapp/v34y2025i2d10.1007_s10260-025-00784-2.html
   My bibliography  Save this article

A comparison of bandwidth selectors for moderate degree local polynomial regression

Author

Listed:
  • Dongying Wang

    (Statistics, University of British Columbia)

  • W. John Braun

    (Statistics, University of British Columbia)

Abstract

This paper presents a direct-plug-in bandwidth selector for local quadratic regression and local cubic regression, leveraging existing theoretical frameworks. Through extensive simulation studies, the performance of the proposed selector is evaluated using the Mean Squared Error (MSE) and Mean Absolute Error (MAE) criteria, in comparison with established methods. Additionally, empirical coverage of confidence intervals is analyzed to further assess its effectiveness. Practical applications of the methods are illustrated using wildfire rate of spread data.

Suggested Citation

  • Dongying Wang & W. John Braun, 2025. "A comparison of bandwidth selectors for moderate degree local polynomial regression," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 34(2), pages 171-194, May.
    • Handle: RePEc:spr:stmapp:v:34:y:2025:i:2:d:10.1007_s10260-025-00784-2
    DOI: 10.1007/s10260-025-00784-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10260-025-00784-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10260-025-00784-2?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Sebastian Calonico & Matias D. Cattaneo & Max H. Farrell, 2018. "On the Effect of Bias Estimation on Coverage Accuracy in Nonparametric Inference," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(522), pages 767-779, April.
    2. Kathryn Prewitt & Sharon Lohr, 2006. "Bandwidth selection in local polynomial regression using eigenvalues," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 68(1), pages 135-154, February.
    3. Sebastian Calonico & Matias D. Cattaneo & Max H. Farrell, 2019. "nprobust: Nonparametric Kernel-Based Estimation and Robust Bias-Corrected Inference," Papers 1906.00198, arXiv.org.
    4. W. John Braun & Bruce L. Jones & Jonathan S. W. Lee & Douglas G. Woolford & B. Mike Wotton, 2010. "Forest Fire Risk Assessment: An Illustrative Example from Ontario, Canada," Journal of Probability and Statistics, Hindawi, vol. 2010, pages 1-26, July.
    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. Chalak, Karim, 2024. "Nonparametric Gini-Frisch bounds," Journal of Econometrics, Elsevier, vol. 238(1).
    2. Yi Zhang & Eli Ben-Michael & Kosuke Imai, 2022. "Safe Policy Learning under Regression Discontinuity Designs with Multiple Cutoffs," Papers 2208.13323, arXiv.org, revised Sep 2024.
    3. Balila Acurio & Alessandro Tomarchio, 2024. "The Effects of Business Credit Support Programs: Evidence from a Regression Discontinuity Design," IHEID Working Papers 20-2024, Economics Section, The Graduate Institute of International Studies.
    4. Bartnicki, Sławomir & Alimowski, Maciej & Górecki, Maciej A., 2022. "The anomalous electoral advantage: Evidence from over 17,000 mayoral candidacies in Poland," European Journal of Political Economy, Elsevier, vol. 72(C).
    5. Matias D. Cattaneo & Rocío Titiunik & Gonzalo Vazquez-Bare, 2020. "Analysis of regression-discontinuity designs with multiple cutoffs or multiple scores," Stata Journal, StataCorp LLC, vol. 20(4), pages 866-891, December.
    6. Kyle Colangelo & Ying-Ying Lee, 2019. "Double debiased machine learning nonparametric inference with continuous treatments," CeMMAP working papers CWP54/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    7. Ichimura, Hidehiko & Todd, Petra E., 2007. "Implementing Nonparametric and Semiparametric Estimators," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 74, Elsevier.
    8. Katja Maria Kaufmann & Yasemin Özdemir & Han Ye, 2022. "Spillover Effects of Old-Age Pension across Generations: Family Labor Supply and Child Outcomes," CESifo Working Paper Series 9813, CESifo.
    9. Kato, Kengo & Sasaki, Yuya, 2018. "Uniform confidence bands in deconvolution with unknown error distribution," Journal of Econometrics, Elsevier, vol. 207(1), pages 129-161.
    10. Potrafke, Niklas & Roesel, Felix, 2020. "The urban–rural gap in healthcare infrastructure: does government ideology matter?," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 54(3), pages 340-351.
    11. Matias D. Cattaneo & Richard K. Crump & Max H. Farrell & Ernst Schaumburg, 2020. "Characteristic-Sorted Portfolios: Estimation and Inference," The Review of Economics and Statistics, MIT Press, vol. 102(3), pages 531-551, July.
    12. Matteo Gamalerio & Massimo Morelli & Margherita Negri, 2021. "The Political Economy of Open Borders: Theory and Evidence on the role of Electoral Rules," BAFFI CAREFIN Working Papers 21157, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    13. Nils Braakmann & Barbara Eberth, 2024. "Can unions impose costs on employers in education strikes? Evidence from pension disputes in UK universities," Papers 2401.05183, arXiv.org.
    14. Cattaneo, Matias D. & Jansson, Michael & Ma, Xinwei, 2024. "Local regression distribution estimators," Journal of Econometrics, Elsevier, vol. 240(2).
    15. Matias D. Cattaneo & Rocio Titiunik & Ruiqi Rae Yu, 2025. "rd2d: Causal Inference in Boundary Discontinuity Designs," Papers 2505.07989, arXiv.org, revised Jun 2025.
    16. Matias D. Cattaneo & Michael Jansson & Xinwei Ma, 2020. "Simple Local Polynomial Density Estimators," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(531), pages 1449-1455, July.
    17. Fritz, Marlon, 2019. "Steady state adjusting trends using a data-driven local polynomial regression," Economic Modelling, Elsevier, vol. 83(C), pages 312-325.
    18. Benoît Le Maux & Kristýna Dostálová & Fabio Padovano, 2020. "Ideology or voters? A quasi-experimental test of why left-wing governments spend more," Public Choice, Springer, vol. 182(1), pages 17-48, January.
    19. Yikun Zhang & Yen-Chi Chen, 2025. "Doubly Robust Inference on Causal Derivative Effects for Continuous Treatments," Papers 2501.06969, arXiv.org, revised Apr 2025.
    20. Pietro Bonaldi & Mauricio Villamizar-Villegas, 2018. "An Auction-Based Test of Private Information in an Interdealer FX Market," Working papers 1, Red Investigadores de Economía.

    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:spr:stmapp:v:34:y:2025:i:2:d:10.1007_s10260-025-00784-2. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.