IDEAS home Printed from https://ideas.repec.org/p/diw/diwwpp/dp659.html
   My bibliography  Save this paper

mhbounds - Sensitivity Analysis for Average Treatment Effects

Author

Listed:
  • Sascha O. Becker
  • Marco Caliendo

Abstract

Matching has become a popular approach to estimate average treatment effects. It is based on the conditional independence or unconfoundedness assumption. Checking the sensitivity of the estimated results with respect to deviations from this identifying assumption has become an increasingly important topic in the applied evaluation literature. If there are unobserved variables which affect assignment into treatment and the outcome variable simultaneously, a hidden bias might arise to which matching estimators are not robust. We address this problem with the bounding approach proposed by Rosenbaum (2002), where mhbounds allows the researcher to determine how strongly an unmeasured variable must influence the selection process in order to undermine the implications of the matching analysis.

Suggested Citation

  • Sascha O. Becker & Marco Caliendo, 2007. "mhbounds - Sensitivity Analysis for Average Treatment Effects," Discussion Papers of DIW Berlin 659, DIW Berlin, German Institute for Economic Research.
    • Handle: RePEc:diw:diwwpp:dp659
    as

    Download full text from publisher

    File URL: https://www.diw.de/documents/publikationen/73/diw_01.c.55697.de/dp659.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Andrea Ichino & Fabrizia Mealli & Tommaso Nannicini, 2008. "From temporary help jobs to permanent employment: what can we learn from matching estimators and their sensitivity?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(3), pages 305-327.
    2. Manski, Charles F., 1992. "Identification Problems In The Social Sciences," SSRI Workshop Series 292716, University of Wisconsin-Madison, Social Systems Research Institute.
    3. Tommaso Nannicini, 2007. "Simulation-based sensitivity analysis for matching estimators," Stata Journal, StataCorp LLC, vol. 7(3), pages 334-350, September.
    4. Marco Caliendo & Sabine Kopeinig, 2008. "Some Practical Guidance For The Implementation Of Propensity Score Matching," Journal of Economic Surveys, Wiley Blackwell, vol. 22(1), pages 31-72, February.
    5. DiPrete, Thomas A. & Gangl, Markus, 2004. "Assessing bias in the estimation of causal effects: Rosenbaum bounds on matching estimators and instrumental variables estimation with imperfect instruments," Discussion Papers, Research Unit: Labor Market Policy and Employment SP I 2004-101, WZB Berlin Social Science Center.
    6. 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.
    7. James Heckman & Hidehiko Ichimura & Jeffrey Smith & Petra Todd, 1998. "Characterizing Selection Bias Using Experimental Data," Econometrica, Econometric Society, vol. 66(5), pages 1017-1098, September.
    8. Marco Caliendo & Reinhard Hujer & Stephan L. Thomsen, 2008. "The employment effects of job-creation schemes in Germany: A microeconometric evaluation," Advances in Econometrics, in: Modelling and Evaluating Treatment Effects in Econometrics, pages 381-428, Emerald Group Publishing Limited.
    9. Sascha O. Becker & Andrea Ichino, 2002. "Estimation of average treatment effects based on propensity scores," Stata Journal, StataCorp LLC, vol. 2(4), pages 358-377, November.
    10. Manski, Charles F, 1990. "Nonparametric Bounds on Treatment Effects," American Economic Review, American Economic Association, vol. 80(2), pages 319-323, May.
    11. Robert J. LaLonde, 1984. "Evaluating the Econometric Evaluations of Training Programs with Experimental Data," Working Papers 563, Princeton University, Department of Economics, Industrial Relations Section..
    12. Alberto Abadie & David Drukker & Jane Leber Herr & Guido W. Imbens, 2004. "Implementing matching estimators for average treatment effects in Stata," Stata Journal, StataCorp LLC, vol. 4(3), pages 290-311, September.
    13. LaLonde, Robert J, 1986. "Evaluating the Econometric Evaluations of Training Programs with Experimental Data," American Economic Review, American Economic Association, vol. 76(4), pages 604-620, September.
    14. Guido W. Imbens, 2004. "Nonparametric Estimation of Average Treatment Effects Under Exogeneity: A Review," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 4-29, February.
    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. 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.
    2. Marco Caliendo & Sabine Kopeinig, 2008. "Some Practical Guidance For The Implementation Of Propensity Score Matching," Journal of Economic Surveys, Wiley Blackwell, vol. 22(1), pages 31-72, February.
    3. Tommaso Nannicini, 2007. "Simulation-based sensitivity analysis for matching estimators," Stata Journal, StataCorp LLC, vol. 7(3), pages 334-350, September.
    4. Bruno Arpino & Arnstein Aassve, 2013. "Estimating the causal effect of fertility on economic wellbeing: data requirements, identifying assumptions and estimation methods," Empirical Economics, Springer, vol. 44(1), pages 355-385, February.
    5. Miguel Angel Malo & Fernando Muñoz-Bullón, 2006. "Employment promotion measures and the quality of the job match for persons with disabilities," Hacienda Pública Española / Review of Public Economics, IEF, vol. 179(4), pages 79-111, September.
    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. Jones A.M & Rice N, 2009. "Econometric Evaluation of Health Policies," Health, Econometrics and Data Group (HEDG) Working Papers 09/09, HEDG, c/o Department of Economics, University of York.
    8. Maren Duvendack & Richard Palmer-Jones, 2012. "High Noon for Microfinance Impact Evaluations: Re-investigating the Evidence from Bangladesh," Journal of Development Studies, Taylor & Francis Journals, vol. 48(12), pages 1864-1880, December.
    9. Caliendo, Marco & Künn, Steffen, 2011. "Start-up subsidies for the unemployed: Long-term evidence and effect heterogeneity," Journal of Public Economics, Elsevier, vol. 95(3), pages 311-331.
    10. 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.
    11. Christian K.M. Kingombe, 2012. "The Linkage between Outcome Differences in Cotton Production and Rural Roads Improvements - A Matching Approach," IHEID Working Papers 12-2012, Economics Section, The Graduate Institute of International Studies.
    12. 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).
    13. Caliendo, Marco & Mahlstedt, Robert & Mitnik, Oscar A., 2017. "Unobservable, but unimportant? The relevance of usually unobserved variables for the evaluation of labor market policies," Labour Economics, Elsevier, vol. 46(C), pages 14-25.
    14. Andrea Ichino & Fabrizia Mealli & Tommaso Nannicini, 2008. "From temporary help jobs to permanent employment: what can we learn from matching estimators and their sensitivity?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(3), pages 305-327.
    15. Liane Faltermeier & Awudu Abdulai, 2009. "The impact of water conservation and intensification technologies: empirical evidence for rice farmers in Ghana," Agricultural Economics, International Association of Agricultural Economists, vol. 40(3), pages 365-379, May.
    16. 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.
    17. Duvendack, Maren & Palmer-Jones, Richard, 2011. "The microfinance of reproduction and the reproduction of microfinance: understanding the connections between microfinance, empowerment, contraception and fertility in Bangladesh in the 1990s," MPRA Paper 32384, University Library of Munich, Germany.
    18. Edgar Silva Quintero & José Alberto Molina & J. Ignacio Gimenez-Nadal, 2016. "How Forced Displacements Caused by a Violent Conflict Affect Wages in Colombia," Working Papers id:10876, eSocialSciences.
    19. Hagen, Tobias, 2016. "Econometric Evaluation of a Placement Coaching Program for Recipients of Disability Insurance Benefits in Switzerland," VfS Annual Conference 2016 (Augsburg): Demographic Change 145736, Verein für Socialpolitik / German Economic Association.
    20. Maoyong Fan & Yanhong Jin, 2015. "The Effects of Weight Perception on Adolescents’ Weight-Loss Intentions and Behaviors: Evidence from the Youth Risk Behavior Surveillance Survey," IJERPH, MDPI, vol. 12(11), pages 1-29, November.

    More about this item

    Keywords

    matching; treatment effects; sensitivity analysis; unobserved heterogeneity;
    All these keywords.

    JEL classification:

    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General

    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:diw:diwwpp:dp659. 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: Bibliothek (email available below). General contact details of provider: https://edirc.repec.org/data/diwbede.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.