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Evidence of randomisation bias in a large-scale social experiment: The case of ERA

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  • Sianesi, Barbara

Abstract

We set out a theoretical framework for the systematic consideration of ‘randomisation bias’, estimate the causal impact of randomisation on participation patterns in an actual trial, and propose a non-experimental way of assessing the extent to which the experimental impacts are representative of the impacts that would have been experienced by the study sample that would have been obtained in the absence of random assignment. We also extend our estimator to deal with binary outcomes and to account for selective survey non-response, and explore partial and point identification of the parameter of interest under alternative assumptions on the selection process.

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  • Sianesi, Barbara, 2017. "Evidence of randomisation bias in a large-scale social experiment: The case of ERA," Journal of Econometrics, Elsevier, vol. 198(1), pages 41-64.
  • Handle: RePEc:eee:econom:v:198:y:2017:i:1:p:41-64
    DOI: 10.1016/j.jeconom.2017.01.003
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    1. Bell, Stephen H. & Orr, Larry L., 2002. "Screening (and creaming?) applicants to job training programs: the AFDC homemaker-home health aide demonstrations," Labour Economics, Elsevier, vol. 9(2), pages 279-301, April.
    2. Manski, Charles F, 1990. "Nonparametric Bounds on Treatment Effects," American Economic Review, American Economic Association, vol. 80(2), pages 319-323, May.
    3. Richard K. Crump & V. Joseph Hotz & Guido W. Imbens & Oscar A. Mitnik, 2008. "Nonparametric Tests for Treatment Effect Heterogeneity," The Review of Economics and Statistics, MIT Press, vol. 90(3), pages 389-405, August.
    4. Charles F. Manski, 1997. "Monotone Treatment Response," Econometrica, Econometric Society, vol. 65(6), pages 1311-1334, November.
    5. 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.
    6. Lorraine Dearden & Carl Emmerson & Costas Meghir, 2009. "Conditional Cash Transfers and School Dropout Rates," Journal of Human Resources, University of Wisconsin Press, vol. 44(4).
    7. Kreider, Brent & Pepper, John V., 2007. "Disability and Employment: Reevaluating the Evidence in Light of Reporting Errors," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 432-441, June.
    8. Guido W. Imbens & Charles F. Manski, 2004. "Confidence Intervals for Partially Identified Parameters," Econometrica, Econometric Society, vol. 72(6), pages 1845-1857, November.
    9. Howard S. Bloom, 1984. "Accounting for No-Shows in Experimental Evaluation Designs," Evaluation Review, , vol. 8(2), pages 225-246, April.
    10. James J. Heckman & Jeffrey A. Smith, 1995. "Assessing the Case for Social Experiments," Journal of Economic Perspectives, American Economic Association, vol. 9(2), pages 85-110, Spring.
    11. Hunt Allcott, 2012. "Site Selection Bias in Program Evaluation," NBER Working Papers 18373, National Bureau of Economic Research, Inc.
    12. Lechner, Michael & Smith, Jeffrey, 2007. "What is the value added by caseworkers?," Labour Economics, Elsevier, vol. 14(2), pages 135-151, April.
    13. Thierry Kamionka & Guy Lacroix, 2008. "Assessing the External Validity of an Experimental Wage Subsidy," Annals of Economics and Statistics, GENES, issue 91-92, pages 357-384.
    14. Barbara Sianesi, 2014. "Dealing with randomisation bias in a social experiment: the case of ERA," IFS Working Papers W14/10, Institute for Fiscal Studies.
    15. Lavergne, Pascal, 2001. "An equality test across nonparametric regressions," Journal of Econometrics, Elsevier, vol. 103(1-2), pages 307-344, July.
    16. James Heckman & Neil Hohmann & Jeffrey Smith & Michael Khoo, 2000. "Substitution and Dropout Bias in Social Experiments: A Study of an Influential Social Experiment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 115(2), pages 651-694.
    17. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-475, March.
    18. repec:adr:anecst:y:2008:i:91-92:p:16 is not listed on IDEAS
    19. James J. Heckman & Sergio Urzua & Edward Vytlacil, 2006. "Understanding Instrumental Variables in Models with Essential Heterogeneity," The Review of Economics and Statistics, MIT Press, vol. 88(3), pages 389-432, August.
    20. Richard Blundell & Monica Costa Dias & Costas Meghir & John Van Reenen, 2004. "Evaluating the Employment Impact of a Mandatory Job Search Program," Journal of the European Economic Association, MIT Press, vol. 2(4), pages 569-606, June.
    21. Heckman, James J. & Lalonde, Robert J. & Smith, Jeffrey A., 1999. "The economics and econometrics of active labor market programs," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 31, pages 1865-2097, Elsevier.
    22. Dolton, Peter & Smith, Jeffrey A., 2011. "The Impact of the UK New Deal for Lone Parents on Benefit Receipt," IZA Discussion Papers 5491, Institute of Labor Economics (IZA).
    23. Charles F. Manski & John V. Pepper, 2000. "Monotone Instrumental Variables, with an Application to the Returns to Schooling," Econometrica, Econometric Society, vol. 68(4), pages 997-1012, July.
    24. Gary Burtless, 1995. "The Case for Randomized Field Trials in Economic and Policy Research," Journal of Economic Perspectives, American Economic Association, vol. 9(2), pages 63-84, Spring.
    25. 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.
    26. James J. Heckman & Jeffrey A. Smith, 1998. "Evaluating the Welfare State," NBER Working Papers 6542, National Bureau of Economic Research, Inc.
    27. Joseph Hotz, V. & Imbens, Guido W. & Mortimer, Julie H., 2005. "Predicting the efficacy of future training programs using past experiences at other locations," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 241-270.
    28. Charles F. Manski & John V. Pepper, 2009. "More on monotone instrumental variables," Econometrics Journal, Royal Economic Society, vol. 12(s1), pages 200-216, January.
    29. Martin Huber, 2012. "Identification of Average Treatment Effects in Social Experiments Under Alternative Forms of Attrition," Journal of Educational and Behavioral Statistics, , vol. 37(3), pages 443-474, June.
    30. Lechner, Michael, 2011. "The Estimation of Causal Effects by Difference-in-Difference Methods," Foundations and Trends(R) in Econometrics, now publishers, vol. 4(3), pages 165-224, November.
    31. Jeffrey M. Wooldridge, 2002. "Inverse probability weighted M-estimators for sample selection, attrition, and stratification," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 1(2), pages 117-139, August.
    32. Card, David & Sullivan, Daniel G, 1988. "Measuring the Effect of Subsidized Training Programs on Movements in and out of Employment," Econometrica, Econometric Society, vol. 56(3), pages 497-530, May.
    33. Charles F. Manski, 1996. "Learning about Treatment Effects from Experiments with Random Assignment of Treatments," Journal of Human Resources, University of Wisconsin Press, vol. 31(4), pages 709-733.
    34. Dubin, Jeffrey A. & Rivers, Douglas, 1993. "Experimental estimates of the impact of wage subsidies," Journal of Econometrics, Elsevier, vol. 56(1-2), pages 219-242, March.
    35. 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.
    36. James J. Heckman & Jeffrey A. Smith, 1999. "The Pre-Program Earnings Dip and the Determinants of Participation in a Social Program: Implications for Simple Program Evaluation Strategies," NBER Working Papers 6983, National Bureau of Economic Research, Inc.
    37. Heckman, James J & Smith, Jeffrey A, 1999. "The Pre-programme Earnings Dip and the Determinants of Participation in a Social Programme. Implications for Simple Programme Evaluation Strategies," Economic Journal, Royal Economic Society, vol. 109(457), pages 313-348, July.
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    Cited by:

    1. Tarek Azzam & Michael Bates & David Fairris, 2019. "Do Learning Communities Increase First Year College Retention? Testing Sample Selection and External Validity of Randomized Control Trials," Working Papers 202002, University of California at Riverside, Department of Economics.
    2. Azzam, Tarek & Bates, Michael D. & Fairris, David, 2022. "Do learning communities increase first year college retention? Evidence from a randomized control trial," Economics of Education Review, Elsevier, vol. 89(C).
    3. Jeffrey A. Smith, 2018. "The usefulness of experiments," IZA World of Labor, Institute of Labor Economics (IZA), pages 436-436, May.
    4. Potash, Eric, 2018. "Randomization bias in field trials to evaluate targeting methods," Economics Letters, Elsevier, vol. 167(C), pages 131-135.

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    More about this item

    Keywords

    Social experiments; Randomisation bias; Sample selection; Treatment effects; Matching methods; Reweighting estimators; Partial identification; External validity;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • J18 - Labor and Demographic Economics - - Demographic Economics - - - Public Policy
    • J38 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Public Policy

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