IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v131y2017icp72-77.html
   My bibliography  Save this article

On the support of matching algorithms

Author

Listed:
  • Cannas, Massimo
  • Puggioni, Gavino

Abstract

In causal inference a matching algorithm assigns a subset of control units to each treated unit. Using combinatorial techniques we explore the support of matching algorithms to provide counting results and investigate the role of the dimension of the covariates’ space.

Suggested Citation

  • Cannas, Massimo & Puggioni, Gavino, 2017. "On the support of matching algorithms," Statistics & Probability Letters, Elsevier, vol. 131(C), pages 72-77.
    • Handle: RePEc:eee:stapro:v:131:y:2017:i:c:p:72-77
    DOI: 10.1016/j.spl.2017.08.009
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167715217302699
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.spl.2017.08.009?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. Martin Huber & Michael Lechner & Andreas Steinmayr, 2015. "Radius matching on the propensity score with bias adjustment: tuning parameters and finite sample behaviour," Empirical Economics, Springer, vol. 49(1), pages 1-31, August.
    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. Lechner, Michael & Sari, Nazmi, 2015. "Labor market effects of sports and exercise: Evidence from Canadian panel data," Labour Economics, Elsevier, vol. 35(C), pages 1-15.
    2. Marco Caliendo & Stefan Tübbicke, 2020. "New evidence on long-term effects of start-up subsidies: matching estimates and their robustness," Empirical Economics, Springer, vol. 59(4), pages 1605-1631, October.
    3. Caliendo, Marco & Künn, Steffen & Weißenberger, Martin, 2016. "Personality traits and the evaluation of start-up subsidies," European Economic Review, Elsevier, vol. 86(C), pages 87-108.
    4. Hille, Adrian & Schupp, Jürgen, 2015. "How Learning a Musical Instrument Affects the Development of Skills," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 44, pages 56-82.
    5. Michael C. Knaus & Steffen Otterbach, 2019. "Work Hour Mismatch And Job Mobility: Adjustment Channels And Resolution Rates," Economic Inquiry, Western Economic Association International, vol. 57(1), pages 227-242, January.
    6. Muñoz-Morales, Juan & Singh, Ruchi, 2023. "Do school shootings erode property values?," Regional Science and Urban Economics, Elsevier, vol. 98(C).
    7. Manuela Deidda & Adriana Di Liberto & Marta Foddi & Giovanni Sulis, 2015. "Employment subsidies, informal economy and women’s transition into work in a depressed area: evidence from a matching approach," IZA Journal of Labor Policy, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 4(1), pages 1-25, December.
    8. Michael Lechner & Paul Downward, 2017. "Heterogeneous sports participation and labour market outcomes in England," Applied Economics, Taylor & Francis Journals, vol. 49(4), pages 335-348, January.
    9. Pawlowski, Tim & Steckenleiter, Carina & Wallrafen, Tim & Lechner, Michael, 2021. "Individual labor market effects of local public expenditures on sports," Labour Economics, Elsevier, vol. 70(C).
    10. Michael Lechner & Anthony Strittmatter, 2019. "Practical procedures to deal with common support problems in matching estimation," Econometric Reviews, Taylor & Francis Journals, vol. 38(2), pages 193-207, February.
    11. Frölich, Markus & Huber, Martin & Wiesenfarth, Manuel, 2017. "The finite sample performance of semi- and non-parametric estimators for treatment effects and policy evaluation," Computational Statistics & Data Analysis, Elsevier, vol. 115(C), pages 91-102.
    12. Gorman, Emma & Walker, Ian, 2021. "Heterogeneous effects of missing out on a place at a preferred secondary school in England," Economics of Education Review, Elsevier, vol. 81(C).
    13. Doerr, Annabelle, 2017. "Back to work: The Long-term Effects of Vocational Training for Female Job Returners," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168213, Verein für Socialpolitik / German Economic Association.
    14. Denisova-Schmidt, Elena & Huber, Martin, 2014. "Regional Differences in Perceived Corruption among Ukrainian Firms," Economics Working Paper Series 1407, University of St. Gallen, School of Economics and Political Science.
    15. Inha Oh & Dongnyok Shim, 2020. "IT Adoption and Sustainable Growth of Firms in Different Industries—Are the Benefits Still Expected?," Sustainability, MDPI, vol. 12(22), pages 1-29, November.
    16. Goller, Daniel & Lechner, Michael & Moczall, Andreas & Wolff, Joachim, 2020. "Does the estimation of the propensity score by machine learning improve matching estimation? The case of Germany's programmes for long term unemployed," Labour Economics, Elsevier, vol. 65(C).
    17. Marco Caliendo & Stefan Tübbicke, 2019. "Do Start-Up Subsidies for the Unemployed Affect Participants’ Well-Being? A Rigorous Look at (Un-)Intended Consequences of Labor Market Policies," CEPA Discussion Papers 14, Center for Economic Policy Analysis.
    18. Gerhard Krug, 2017. "Augmenting propensity score equations to avoid misspecification bias – Evidence from a Monte Carlo simulation [Erweiterung der Propensity Score Gleichung zur Vermeidung von Fehlspezifikationen? Ein," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 11(3), pages 205-231, December.
    19. Iqbal, Hamzah & Krumer, Alex, 2017. "Discouragement Effect and Intermediate Prizes in Multi-Stage Contests: Evidence from Tennis’s Davis Cup," Economics Working Paper Series 1719, University of St. Gallen, School of Economics and Political Science.
    20. Marc Höglinger & Brigitte Wirth & Maria Carlander & Cornelia Caviglia & Christian Frei & Birgitta Rhomberg & Adrian Rohrbasser & Maria Trottmann & Klaus Eichler, 2023. "Impact of a diabetes disease management program on guideline-adherent care, hospitalization risk and health care costs: a propensity score matching study using real-world data," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 24(3), pages 469-478, April.

    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:stapro:v:131:y:2017:i:c:p:72-77. 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/wps/find/journaldescription.cws_home/622892/description#description .

    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.