IDEAS home Printed from https://ideas.repec.org/a/tpr/restat/v100y2018i4p567-580.html
   My bibliography  Save this article

Endogenous Stratification in Randomized Experiments

Author

Listed:
  • Alberto Abadie

    (MIT)

  • Matthew M. Chingos

    (Urban Institute)

  • Martin R. West

    (Harvard University)

Abstract

Policymakers are often interested in estimating how policy interventions affect the outcomes of those most in need of help. This concern has motivated the practice of disaggregating experimental results by groups constructed on the basis of an index of baseline characteristics that predicts the values of individual outcomes without the treatment. This paper shows that substantial biases may arise in practice if the index is estimated by regressing the outcome variable on baseline characteristics for the full sample of experimental controls. We propose alternative methods that correct this bias and show that they behave well in realistic scenarios.

Suggested Citation

  • Alberto Abadie & Matthew M. Chingos & Martin R. West, 2018. "Endogenous Stratification in Randomized Experiments," The Review of Economics and Statistics, MIT Press, vol. 100(4), pages 567-580, October.
  • Handle: RePEc:tpr:restat:v:100:y:2018:i:4:p:567-580
    as

    Download full text from publisher

    File URL: http://www.mitpressjournals.org/doi/pdf/10.1162/10.1162/rest_a_00732
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Joshua D. Angrist & Jörn-Steffen Pischke, 2010. "The Credibility Revolution in Empirical Economics: How Better Research Design Is Taking the Con out of Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 24(2), pages 3-30, Spring.
    2. James J. Heckman & Jeffrey Smith & Nancy Clements, 1997. "Making The Most Out Of Programme Evaluations and Social Experiments: Accounting For Heterogeneity in Programme Impacts," Review of Economic Studies, Oxford University Press, vol. 64(4), pages 487-535.
    3. Lisa Sanbonmatsu & Jeffrey R. Kling & Greg J. Duncan & Jeanne Brooks-Gunn, 2006. "Neighborhoods and Academic Achievement: Results from the Moving to Opportunity Experiment," Journal of Human Resources, University of Wisconsin Press, vol. 41(4).
    4. Rodríguez-Planas, Núria, 2012. "School and Drugs: Closing the Gap – Evidence from a Randomized Trial in the US," IZA Discussion Papers 6770, Institute of Labor Economics (IZA).
    5. Susan Dynarski & Joshua Hyman & Diane Whitmore Schanzenbach, 2013. "Experimental Evidence on the Effect of Childhood Investments on Postsecondary Attainment and Degree Completion," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 32(4), pages 692-717, September.
    6. Joshua Angrist & Victor Lavy, 2009. "The Effects of High Stakes High School Achievement Awards: Evidence from a Randomized Trial," American Economic Review, American Economic Association, vol. 99(4), pages 1384-1414, September.
    7. Douglas N. Harris & Sara Goldrick-Rab, 2012. "Improving the Productivity of Education Experiments: Lessons from a Randomized Study of Need-Based Financial Aid," Education Finance and Policy, MIT Press, vol. 7(2), pages 143-169, March.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Casalin, Fabrizio & Dia, Enzo, 2019. "Information and reputation mechanisms in auctions of remanufactured goods," International Journal of Industrial Organization, Elsevier, vol. 63(C), pages 185-212.
    2. Russell, Lauren, 2019. "Better outcomes without increased costs? Effects of Georgia’s University System consolidations," Economics of Education Review, Elsevier, vol. 68(C), pages 122-135.
    3. Patterson, Richard W., 2018. "Can behavioral tools improve online student outcomes? Experimental evidence from a massive open online course," Journal of Economic Behavior & Organization, Elsevier, vol. 153(C), pages 293-321.
    4. Altmann, Steffen & Falk, Armin & Jäger, Simon & Zimmermann, Florian, 2018. "Learning about job search: A field experiment with job seekers in Germany," Journal of Public Economics, Elsevier, vol. 164(C), pages 33-49.
    5. Liang Jiang & Xiaobin Liu & Peter C. B. Phillips & Yichong Zhang, 2020. "Bootstrap Inference for Quantile Treatment Effects in Randomized Experiments with Matched Pairs," Papers 2005.11967, arXiv.org, revised Aug 2020.
    6. Nicolás de Roux & Evan Riehl, 2020. "Disrupted Academic Careers: The Returns to Time Off after High School," Documentos CEDE 018417, Universidad de los Andes - CEDE.
    7. Arash Nekoei & Andrea Weber, 2017. "Does Extending Unemployment Benefits Improve Job Quality?," American Economic Review, American Economic Association, vol. 107(2), pages 527-561, February.
    8. C de Chaisemartin & X D’HaultfŒuille, 2018. "Fuzzy Differences-in-Differences," Review of Economic Studies, Oxford University Press, vol. 85(2), pages 999-1028.
    9. Cusolito, Ana Paula & Dautovic, Ernest & McKenzie, David J., 2018. "Can Government Intervention Make Firms More Investment-Ready? A Randomized Experiment in the Western Balkans," CEPR Discussion Papers 13098, C.E.P.R. Discussion Papers.
    10. Anthony Strittmatter, 2018. "What Is the Value Added by Using Causal Machine Learning Methods in a Welfare Experiment Evaluation?," Papers 1812.06533, arXiv.org, revised Mar 2019.
    11. Olivier Sterck & Antonia Delius, 2020. "Cash Transfers and Micro-Enterprise Performance: Theory and Quasi-Experimental Evidence from Kenya," CSAE Working Paper Series 2020-09, Centre for the Study of African Economies, University of Oxford.
    12. Jules Gazeaud & Eric Mvukiyehe & Olivier Sterck, 2019. "Cash Transfers and Migration: Theory and Evidence from a Randomized Controlled Trial," CSAE Working Paper Series 2019-16, Centre for the Study of African Economies, University of Oxford.
    13. Hoen, Maria Forthun, 2020. "Immigration and the Tower of Babel: Using language barriers to identify individual labor market effects of immigration," Labour Economics, Elsevier, vol. 65(C).
    14. Onur Altindag, 2016. "Son Preference, Fertility Decline, and the Nonmissing Girls of Turkey," Demography, Springer;Population Association of America (PAA), vol. 53(2), pages 541-566, April.
    15. Abebe, Girum & Caria, Stefano & Fafchamps, Marcel & Falco, Paolo & Franklin, Simon & Quinn, Simon & Shilpi, Forhad, 2017. "Matching firms and workers in a field experiment in Ethiopia," LSE Research Online Documents on Economics 86572, London School of Economics and Political Science, LSE Library.
    16. Bernhard Schmidpeter, 2020. "The Long-Term Labor Market Effects of Parental Unemployment," Upjohn Working Papers and Journal Articles 20-322, W.E. Upjohn Institute for Employment Research.
    17. David Hardt & Markus Nagler & Johannes Rincke, 2020. "Can Peer Mentoring Improve Online Teaching Effectiveness? An RCT during the Covid-19 Pandemic," CESifo Working Paper Series 8671, CESifo.
    18. William N. Evans & Melissa S. Kearney & Brendan Perry & James X. Sullivan, 2020. "Increasing Community College Completion Rates Among Low‐Income Students: Evidence from a Randomized Controlled Trial Evaluation of a Case‐Management Intervention," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 39(4), pages 930-965, September.
    19. Onur Altindag & Theodore J. Joyce & Julie A. Reeder, 2015. "Effects of Peer Counseling to Support Breastfeeding: Assessing the External Validity of a Randomized Field Experiment," NBER Working Papers 21013, National Bureau of Economic Research, Inc.

    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. Burt S. Barnow & Jeffrey Smith, 2015. "Employment and Training Programs," NBER Chapters, in: Economics of Means-Tested Transfer Programs in the United States, Volume 2, pages 127-234, National Bureau of Economic Research, Inc.
    2. Scott Carrell & Bruce Sacerdote, 2017. "Why Do College-Going Interventions Work?," American Economic Journal: Applied Economics, American Economic Association, vol. 9(3), pages 124-151, July.
    3. Judith Favereau & Nicolas Brisset, 2016. "Randomization of What? Moving from Libertarian to "Democratic Paternalism"," GREDEG Working Papers 2016-34, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France.
    4. Stephen Gibbons & Olmo Silva & Felix Weinhardt, 2010. "Do Neighbours Affect Teenage Outcomes? Evidence from Neighbourhood Changes in England," CEE Discussion Papers 0122, Centre for the Economics of Education, LSE.
    5. Ayako Wakano & Hiroyuki Yamada & Daichi Shimamoto, 2017. "Does the Heterogeneity of Project Implementers Affect the Programme Participation of Beneficiaries?: Evidence from Rural Cambodia," Journal of Development Studies, Taylor & Francis Journals, vol. 53(1), pages 49-67, January.
    6. Jens Ludwig & Jeffrey R. Kling & Sendhil Mullainathan, 2011. "Mechanism Experiments and Policy Evaluations," Journal of Economic Perspectives, American Economic Association, vol. 25(3), pages 17-38, Summer.
    7. Heckman, James J. & Humphries, John Eric & Veramendi, Gregory, 2016. "Dynamic treatment effects," Journal of Econometrics, Elsevier, vol. 191(2), pages 276-292.
    8. Angus Deaton, 2010. "Instruments, Randomization, and Learning about Development," Journal of Economic Literature, American Economic Association, vol. 48(2), pages 424-455, June.
    9. Judith Favereau & Nicolas Brisset, 2016. "Randomization of What? Moving from Libertarian to "Democratic Paternalism". GREDEG Working Papers Series," Working Papers hal-02092638, HAL.
    10. James J. Heckman, 2010. "Building Bridges between Structural and Program Evaluation Approaches to Evaluating Policy," Journal of Economic Literature, American Economic Association, vol. 48(2), pages 356-398, June.
    11. Dionissi Aliprantis, 2011. "Assessing the evidence on neighborhood effects from moving to opportunity," Working Papers (Old Series) 1101, Federal Reserve Bank of Cleveland.
    12. Angus Deaton, 2009. "Instruments of development: Randomization in the tropics, and the search for the elusive keys to economic development," Working Papers 1128, Princeton University, Woodrow Wilson School of Public and International Affairs, Center for Health and Wellbeing..
    13. Dionissi Aliprantis, 2017. "Assessing the evidence on neighborhood effects from Moving to Opportunity," Empirical Economics, Springer, vol. 52(3), pages 925-954, May.
    14. Ismaël Mourifié & Marc Henry & Romuald Méango, 2020. "Sharp Bounds and Testability of a Roy Model of STEM Major Choices," Journal of Political Economy, University of Chicago Press, vol. 128(8), pages 3220-3283.
    15. James J. Heckman, 1991. "Randomization and Social Policy Evaluation Revisited," NBER Technical Working Papers 0107, National Bureau of Economic Research, Inc.
    16. Jeffrey Smith, 2000. "A Critical Survey of Empirical Methods for Evaluating Active Labor Market Policies," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 136(III), pages 247-268, September.
    17. Battaglia, Marianna & Lebedinski, Lara, 2015. "Equal Access to Education: An Evaluation of the Roma Teaching Assistant Program in Serbia," World Development, Elsevier, vol. 76(C), pages 62-81.
    18. Martin Schlotter & Guido Schwerdt & Ludger Woessmann, 2011. "Econometric methods for causal evaluation of education policies and practices: a non-technical guide," Education Economics, Taylor & Francis Journals, vol. 19(2), pages 109-137.
    19. Stephen B. Billings & Mark Hoekstra, 2019. "Schools, Neighborhoods, and the Long-Run Effect of Crime-Prone Peers," NBER Working Papers 25730, National Bureau of Economic Research, Inc.
    20. Card, David & Rothstein, Jesse, 2007. "Racial segregation and the black-white test score gap," Journal of Public Economics, Elsevier, vol. 91(11-12), pages 2158-2184, December.

    More about this item

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C9 - Mathematical and Quantitative Methods - - Design of Experiments

    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:tpr:restat:v:100:y:2018:i:4:p:567-580. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Ann Olson). General contact details of provider: https://www.mitpressjournals.org/ .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.