IDEAS home Printed from https://ideas.repec.org/p/hal/wpaper/hal-01691528.html
   My bibliography  Save this paper

A SAS macro to estimate Average Treatment Effects with Propensity Score Matching

Author

Listed:
  • Nicolas Moreau

    (CEMOI - Centre d'Économie et de Management de l'Océan Indien - UR - Université de La Réunion)

Abstract

This paper presents a SAS macro to estimate the Average Treatment Effect (ATE) and the Average Treatment Effect for the Treated (ATET) based on propensity score with nearest neighbor matching. The robust standard errors derived in Abadie and Imbens (2016) are computed.

Suggested Citation

  • Nicolas Moreau, 2018. "A SAS macro to estimate Average Treatment Effects with Propensity Score Matching," Working Papers hal-01691528, HAL.
    • Handle: RePEc:hal:wpaper:hal-01691528
    Note: View the original document on HAL open archive server: https://hal.science/hal-01691528
    as

    Download full text from publisher

    File URL: https://hal.science/hal-01691528/document
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Cattaneo, Matias D., 2010. "Efficient semiparametric estimation of multi-valued treatment effects under ignorability," Journal of Econometrics, Elsevier, vol. 155(2), pages 138-154, April.
    2. Alberto Abadie & Guido W. Imbens, 2016. "Matching on the Estimated Propensity Score," Econometrica, Econometric Society, vol. 84, pages 781-807, March.
    3. Matias D. Cattaneo, 2010. "multi-valued treatment effects," The New Palgrave Dictionary of Economics,, Palgrave Macmillan.
    4. Alberto Abadie & David Drukker & Jane Leber Herr & Guido W. Imbens, 2004. "Implementing matching estimators for average treatment effects in Stata," Stata Journal, StataCorp LP, vol. 4(3), pages 290-311, September.
    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. Delprato, Marcos & Akyeampong, Kwame, 2019. "The effect of working on students’ learning in Latin America: Evidence from the learning survey TERCE," International Journal of Educational Development, Elsevier, vol. 70(C), pages 1-1.
    2. Rahul Singh & Liyuan Xu & Arthur Gretton, 2020. "Kernel Methods for Causal Functions: Dose, Heterogeneous, and Incremental Response Curves," Papers 2010.04855, arXiv.org, revised Oct 2022.
    3. Difang Huang & Jiti Gao & Tatsushi Oka, 2022. "Semiparametric Single-Index Estimation for Average Treatment Effects," Papers 2206.08503, arXiv.org, revised Oct 2022.
    4. Knox, Melissa A. & Oddo, Vanessa M. & Walkinshaw, Lina Pinero & Jones-Smith, Jessica, 2020. "Is the public sweet on sugary beverages? Social desirability bias and sweetened beverage taxes," Economics & Human Biology, Elsevier, vol. 38(C).
    5. Susan Athey & Guido W. Imbens, 2017. "The State of Applied Econometrics: Causality and Policy Evaluation," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 3-32, Spring.
    6. Roberto ESPOSTI, 2014. "To match, not to match, how to match: Estimating the farm-level impact of the CAP-first pillar reform (or: How to Apply Treatment-Effect Econometrics when the Real World is;a Mess)," Working Papers 403, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    7. Andrea Morescalchi, 2021. "A new career in a new town. Job search methods and regional mobility of unemployed workers," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 20(2), pages 223-272, May.
    8. Lee, Ying-Ying, 2018. "Efficient propensity score regression estimators of multivalued treatment effects for the treated," Journal of Econometrics, Elsevier, vol. 204(2), pages 207-222.
    9. Esposti, Roberto, 2014. "The Impact of the 2005 CAP-First Pillar Reform as a Multivalued Treatment Effect -Alternative Estimation Approaches," 2014 Third Congress, June 25-27, 2014, Alghero, Italy 173005, Italian Association of Agricultural and Applied Economics (AIEAA).
    10. Rothe, Christoph, 2016. "The Value of Knowing the Propensity Score for Estimating Average Treatment Effects," IZA Discussion Papers 9989, Institute of Labor Economics (IZA).
    11. Ainembabazi, John Herbert & Abdoulaye, Tahirou & Feleke, Shiferaw & Alene, Arega & Dontsop-Nguezet, Paul M. & Ndayisaba, Pierre Celestin & Hicintuka, Cyrille & Mapatano, Sylvain & Manyong, Victor, 2018. "Who benefits from which agricultural research-for-development technologies? Evidence from farm household poverty analysis in Central Africa," World Development, Elsevier, vol. 108(C), pages 28-46.
    12. Sant’Anna, Pedro H.C. & Zhao, Jun, 2020. "Doubly robust difference-in-differences estimators," Journal of Econometrics, Elsevier, vol. 219(1), pages 101-122.
    13. Stojčić, Nebojša, 2021. "Social and private outcomes of green innovation incentives in European advancing economies," Technovation, Elsevier, vol. 104(C).
    14. Ay, Jean-Sauveur & Le Gallo, Julie, 2021. "The Signaling Values of Nested Wine Names," Working Papers 321851, American Association of Wine Economists.
    15. Katie Meara & Francesco Pastore & Allan Webster, 2020. "The gender pay gap in the USA: a matching study," Journal of Population Economics, Springer;European Society for Population Economics, vol. 33(1), pages 271-305, January.
    16. Shaibu Baanni Azumah & Abraham Zakaria & Rosaine N. Yegbemey & Philips A. Apalogta & Vishal Dagar & Abass Mahama, 2022. "Climate Smart Production, Gross Income, and Downstream Risk Characterization of Rice Farmers in Ghana," Journal of Agricultural Studies, Macrothink Institute, vol. 10(2), pages 13-35, June.
    17. Hong, Yan-Zhen & Chang, Hung-Hao & Dai, Yong-Wu, 2018. "Is deregulation of forest land use rights transactions associated with economic well-being and labor allocation of farm households? Empirical evidence in China," Land Use Policy, Elsevier, vol. 75(C), pages 694-701.
    18. Michael C. Knaus, 2021. "A double machine learning approach to estimate the effects of musical practice on student’s skills," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(1), pages 282-300, January.
    19. Ma, Wanglin & Vatsa, Puneet & Zheng, Hongyun, 2022. "Cooking fuel choices and subjective well-being in rural China: Implications for a complete energy transition," Energy Policy, Elsevier, vol. 165(C).
    20. W K Newey & S Stouli, 2022. "Heterogeneous coefficients, control variables and identification of multiple treatment effects [Multivalued treatments and decomposition analysis: An application to the WIA program]," Biometrika, Biometrika Trust, vol. 109(3), pages 865-872.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:hal:wpaper:hal-01691528. 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.