IDEAS home Printed from https://ideas.repec.org/a/csb/stintr/v12y2011i3p595-608.html
   My bibliography  Save this article

An improvement of quality of statistical matching for survey data using dynamic caliper

Author

Listed:
  • Paweł Strawiński

Abstract

Nowadays, matching is a widely used technique to estimate program net effects. The goal of the method is to establish a counterfactual state by choosing from the control pool a group that is similar to those in the treatment group. In this article we propose a modification of the matching with caliper procedure. The novelty in our approach is setting the caliper value as a fraction of estimated propensity score. The simulation results and examples are presented. Using Deheija and Wahba (1999) data benefits of the proposed approach are stressed. The obtained results indicate that proposed approach is more efficient than the one traditionally used.

Suggested Citation

  • Paweł Strawiński, 2011. "An improvement of quality of statistical matching for survey data using dynamic caliper," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 12(3), pages 595-608, December.
    • Handle: RePEc:csb:stintr:v:12:y:2011:i:3:p:595-608
    as

    Download full text from publisher

    File URL: http://index.stat.gov.pl/repec/files/csb/stintr/csb_stintr_v12_2011_i3_n22.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. A. Smith, Jeffrey & E. Todd, Petra, 2005. "Does matching overcome LaLonde's critique of nonexperimental estimators?," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 305-353.
    2. James J. Heckman & Hidehiko Ichimura & Petra E. Todd, 1997. "Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(4), pages 605-654.
    3. Lee, Myoung-jae, 2005. "Micro-Econometrics for Policy, Program and Treatment Effects," OUP Catalogue, Oxford University Press, number 9780199267699.
    4. Rajeev H. Dehejia & Sadek Wahba, 2002. "Propensity Score-Matching Methods For Nonexperimental Causal Studies," The Review of Economics and Statistics, MIT Press, vol. 84(1), pages 151-161, February.
    5. Heckman, J.J. & Hotz, V.J., 1988. "Choosing Among Alternative Nonexperimental Methods For Estimating The Impact Of Social Programs: The Case Of Manpower Training," University of Chicago - Economics Research Center 88-12, Chicago - Economics Research Center.
    6. Richard Blundell & Monica Costa Dias, 2000. "Evaluation methods for non-experimental data," Fiscal Studies, Institute for Fiscal Studies, vol. 21(4), pages 427-468, January.
    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. Dettmann, E. & Becker, C. & Schmeißer, C., 2011. "Distance functions for matching in small samples," Computational Statistics & Data Analysis, Elsevier, vol. 55(5), pages 1942-1960, May.
    2. Abebaw, Degnet & Fentie, Yibeltal & Kassa, Belay, 2010. "The impact of a food security program on household food consumption in Northwestern Ethiopia: A matching estimator approach," Food Policy, Elsevier, vol. 35(4), pages 286-293, August.
    3. Sourafel Girma & Holger Görg, 2016. "Evaluating the foreign ownership wage premium using a difference-in-differences matching approach," World Scientific Book Chapters, in: MULTINATIONAL ENTERPRISES AND HOST COUNTRY DEVELOPMENT Volume 53: World Scientific Studies in International Economics, chapter 2, pages 17-32, World Scientific Publishing Co. Pte. Ltd..
    4. A. Smith, Jeffrey & E. Todd, Petra, 2005. "Does matching overcome LaLonde's critique of nonexperimental estimators?," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 305-353.
    5. Dettmann, Eva & Becker, Claudia & Schmeißer, Christian, 2010. "Is there a Superior Distance Function for Matching in Small Samples?," IWH Discussion Papers 3/2010, Halle Institute for Economic Research (IWH).
    6. Carlos A. Flores & Oscar A. Mitnik, 2009. "Evaluating Nonexperimental Estimators for Multiple Treatments: Evidence from Experimental Data," Working Papers 2010-10, University of Miami, Department of Economics.
    7. Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
    8. Eliasson, Kent, 2006. "The Role of Ability in Estimating the Returns to College Choice: New Swedish Evidence," Umeå Economic Studies 691, Umeå University, Department of Economics.
    9. Jasmin Kantarevic & Boris Kralj, 2013. "Link Between Pay For Performance Incentives And Physician Payment Mechanisms: Evidence From The Diabetes Management Incentive In Ontario," Health Economics, John Wiley & Sons, Ltd., vol. 22(12), pages 1417-1439, December.
    10. Sourafel Girma & Holger Görg, 2016. "Multinationals’ Productivity Advantage: Scale Or Technology?," World Scientific Book Chapters, in: MULTINATIONAL ENTERPRISES AND HOST COUNTRY DEVELOPMENT Volume 53: World Scientific Studies in International Economics, chapter 1, pages 3-15, World Scientific Publishing Co. Pte. Ltd..
    11. Peter R. Mueser & Kenneth R. Troske & Alexey Gorislavsky, 2007. "Using State Administrative Data to Measure Program Performance," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 761-783, November.
    12. Richard Blundell & Monica Costa Dias, 2009. "Alternative Approaches to Evaluation in Empirical Microeconomics," Journal of Human Resources, University of Wisconsin Press, vol. 44(3).
    13. Oliver Tiemann & Jonas Schreyögg, 2012. "Changes in hospital efficiency after privatization," Health Care Management Science, Springer, vol. 15(4), pages 310-326, December.
    14. James Alm & Yongzheng Liu, 2014. "China's Tax-for-Fee Reform and Village Inequality," Oxford Development Studies, Taylor & Francis Journals, vol. 42(1), pages 38-64, March.
    15. Oliver Tiemann & Jonas Schreyögg, 2012. "Changes in hospital efficiency after privatization," Health Care Management Science, Springer, vol. 15(4), pages 310-326, December.
    16. J. Eduardo Ibarra‐Olivo & Andrés Rodríguez‐Pose, 2022. "FDI and the growing wage gap in Mexican municipalities," Papers in Regional Science, Wiley Blackwell, vol. 101(6), pages 1411-1439, December.
    17. Gustavo Canavire-Bacarreza & Luis Castro Peñarrieta & Darwin Ugarte Ontiveros, 2021. "Outliers in Semi-Parametric Estimation of Treatment Effects," Econometrics, MDPI, vol. 9(2), pages 1-32, April.
    18. Bart, COCKX & Jean, RIES, 2004. "The Exhaustion of Unemployment Benefits in Belgium. Does it Enhance the Probability of Employment ?," LIDAM Discussion Papers IRES 2004016, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
    19. Lechner, Michael & Wunsch, Conny, 2013. "Sensitivity of matching-based program evaluations to the availability of control variables," Labour Economics, Elsevier, vol. 21(C), pages 111-121.
    20. James Alm & Yongzheng Liu, 2013. "Did China's Tax-for-Fee Reform Improve Farmers' Welfare in Rural Areas?," Journal of Development Studies, Taylor & Francis Journals, vol. 49(4), pages 516-532, 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:csb:stintr:v:12:y:2011:i:3:p:595-608. 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: Beata Witek (email available below). General contact details of provider: https://edirc.repec.org/data/gusgvpl.html .

    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.