IDEAS home Printed from
   My bibliography  Save this paper

lpdensity: Local Polynomial Density Estimation and Inference


  • Matias D. Cattaneo
  • Michael Jansson
  • Xinwei Ma


Density estimation and inference methods are widely used in empirical work. When the underlying distribution has compact support, conventional kernel-based density estimators are no longer consistent near or at the boundary because of their well-known boundary bias. Alternative smoothing methods are available to handle boundary points in density estimation, but they all require additional tuning parameter choices or other typically ad hoc modifications depending on the evaluation point and/or approach considered. This article discusses the R and Stata package lpdensity implementing a novel local polynomial density estimator proposed and studied in Cattaneo, Jansson, and Ma (2020, 2021), which is boundary adaptive and involves only one tuning parameter. The methods implemented also cover local polynomial estimation of the cumulative distribution function and density derivatives. In addition to point estimation and graphical procedures, the package offers consistent variance estimators, mean squared error optimal bandwidth selection, robust bias-corrected inference, and confidence bands construction, among other features. A comparison with other density estimation packages available in R using a Monte Carlo experiment is provided.

Suggested Citation

  • Matias D. Cattaneo & Michael Jansson & Xinwei Ma, 2019. "lpdensity: Local Polynomial Density Estimation and Inference," Papers 1906.06529,, revised Feb 2021.
  • Handle: RePEc:arx:papers:1906.06529

    Download full text from publisher

    File URL:
    File Function: Latest version
    Download Restriction: no

    References listed on IDEAS

    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. 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.
    3. Hayfield, Tristen & Racine, Jeffrey S., 2008. "Nonparametric Econometrics: The np Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i05).
    4. Duong, Tarn, 2007. "ks: Kernel Density Estimation and Kernel Discriminant Analysis for Multivariate Data in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 21(i07).
    Full references (including those not matched with items on IDEAS)


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. Mattia Filomena & Matteo Picchio, 2023. "Retirement and health outcomes in a meta‐analytical framework," Journal of Economic Surveys, Wiley Blackwell, vol. 37(4), pages 1120-1155, September.

    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. Augusto Cerqua & Guido Pellegrini & Ornella Tarola, 2022. "Can regional policies shape migration flows?," Papers in Regional Science, Wiley Blackwell, vol. 101(3), pages 515-536, June.
    2. Yoichi Arai & Yu‐Chin Hsu & Toru Kitagawa & Ismael Mourifié & Yuanyuan Wan, 2022. "Testing identifying assumptions in fuzzy regression discontinuity designs," Quantitative Economics, Econometric Society, vol. 13(1), pages 1-28, January.
    3. Kunz, Johannes S. & Zhu, Anna, 2023. "Welfare Reform and Migrant's Long-Term Labor Market Integration," IZA Discussion Papers 16285, Institute of Labor Economics (IZA).
    4. Luisa Doerr & Niklas Potrafke & Felix Roesel & Luisa Dörr, 2021. "Populists in Power," CESifo Working Paper Series 9336, CESifo.
    5. De Benedetto, Marco Alberto & De Paola, Maria & Scoppa, Vincenzo & Smirnova, Janna, 2022. "The long-run effects of college remedial education," Economics Letters, Elsevier, vol. 216(C).
    6. Divakaruni, Anantha & Jones, Howard, 2021. "Disclosure, Firm Growth, and the JOBS Act," SocArXiv 3zumb, Center for Open Science.
    7. Federico Crippa, 2024. "Manipulation Test for Multidimensional RDD," Papers 2402.10836,
    8. Matias D. Cattaneo & Rocío Titiunik, 2022. "Regression Discontinuity Designs," Annual Review of Economics, Annual Reviews, vol. 14(1), pages 821-851, August.
    9. Johannes Kunz & Anna Zhu, 2023. "Welfare Reform and Migrant’s Long-term Labor Market Integration," Papers 2023-05, Centre for Health Economics, Monash University.
    10. Martínez-Correa, Jimmy & Andersen, Steffen & d’Astous, Philippe & H. Shore, Stephen, 2020. "Cross-Program Differences in Returns to Education and the Gender Earnings Gap," Working papers 48, Red Investigadores de Economía.
    11. de Gendre, Alexandra & Lynch, John & Meunier, Aurélie & Pilkington, Rhiannon & Schurer, Stefanie, 2021. "Child Health and Parental Responses to an Unconditional Cash Transfer at Birth," IZA Discussion Papers 14693, Institute of Labor Economics (IZA).
    12. Jun Ma & Zhengfei Yu, 2020. "Empirical Likelihood Covariate Adjustment for Regression Discontinuity Designs," Papers 2008.09263,, revised May 2024.
    13. Francesco Decarolis & Raymond Fisman & Paolo Pinotti & Silvia Vannutelli, 2019. "Rules, Discretion, and Corruption in Procurement: Evidence from Italian Government Contracting," Boston University - Department of Economics - The Institute for Economic Development Working Papers Series dp-344, Boston University - Department of Economics.
    14. Eibich, Peter & Siedler, Thomas, 2020. "Retirement, intergenerational time transfers, and fertility," European Economic Review, Elsevier, vol. 124(C).
    15. David H. Bernstein & Christopher F. Parmeter, 2017. "Returns to Scale in Electricity Generation: Revisited and Replicated," Working Papers 2017-08, University of Miami, Department of Economics.
    16. El Ghouch, Anouar & Genton, Marc G. & Bouezmarni , Taoufik, 2012. "Measuring the Discrepancy of a Parametric Model via Local Polynomial Smoothing," LIDAM Discussion Papers ISBA 2012001, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    17. Kemp, Gordon C.R. & Santos Silva, J.M.C., 2012. "Regression towards the mode," Journal of Econometrics, Elsevier, vol. 170(1), pages 92-101.
    18. Luis R. Martinez & Jonas Jessen & Guo Xu, 2023. "A Glimpse of Freedom: Allied Occupation and Political Resistance in East Germany," American Economic Journal: Applied Economics, American Economic Association, vol. 15(1), pages 68-106, January.
    19. Requillart, Vincent & Nauges, Celine & Simioni, Michel & Bontemps, Christophe, 2012. "Food Safety Regulation and Firm Productivity: Evidence from the French Food Industry," 2012 First Congress, June 4-5, 2012, Trento, Italy 124378, Italian Association of Agricultural and Applied Economics (AIEAA).
    20. Degl’Innocenti, Marta & Matousek, Roman & Sevic, Zeljko & Tzeremes, Nickolaos G., 2017. "Bank efficiency and financial centres: Does geographical location matter?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 46(C), pages 188-198.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:


    Access and download statistics


    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:arx:papers:1906.06529. 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: arXiv administrators (email available below). General contact details of provider: .

    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.