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Difference-in-Differences with a Misclassified Treatment

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  • Akanksha Negi

    (Monash University)

  • Digvijay S. Negi

    (Ashoka University)

Abstract

This paper studies identification and estimation of the average treatment effect of a latent treated subpopulation in difference-in-difference designs when the observed treatment is differentially (or endogenously) mismeasured for the truth. Common examples include misreporting and mistargeting. We propose a twostep estimator which corrects for the empirically common phenomenon of onesided misclassification in the treatment status. The solution uses a single exclusion restriction embedded in a partial observability probit to point-identify the latent parameter. We demonstrate the method by revisiting two large-scale national programs in India; one where pension benefits are under-reported and second where the program is mistargeted.

Suggested Citation

  • Akanksha Negi & Digvijay S. Negi, 2024. "Difference-in-Differences with a Misclassified Treatment," Working Papers 121, Ashoka University, Department of Economics.
    • Handle: RePEc:ash:wpaper:121
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    1. Kaushal, Neeraj & Muchomba, Felix M., 2015. "How Consumer Price Subsidies affect Nutrition," World Development, Elsevier, vol. 74(C), pages 25-42.
    2. Brent Kreider, 2010. "Regression Coefficient Identification Decay in The Presence of Infrequent Classification Errors," The Review of Economics and Statistics, MIT Press, vol. 92(4), pages 1017-1023, November.
    3. Esther Duflo, 2003. "Grandmothers and Granddaughters: Old-Age Pensions and Intrahousehold Allocation in South Africa," The World Bank Economic Review, World Bank, vol. 17(1), pages 1-25, June.
    4. Paul Niehaus & Sandip Sukhtankar, 2013. "Corruption Dynamics: The Golden Goose Effect," American Economic Journal: Economic Policy, American Economic Association, vol. 5(4), pages 230-269, November.
    5. Aigner, Dennis J., 1973. "Regression with a binary independent variable subject to errors of observation," Journal of Econometrics, Elsevier, vol. 1(1), pages 49-59, March.
    6. David L. Sjoquist & John V. Winters, 2016. "The Effects of State Merit Aid Programs on Attendance at Elite Colleges," Southern Economic Journal, John Wiley & Sons, vol. 83(2), pages 527-549, October.
    7. Rossella Calvi & Arthur Lewbel & Denni Tommasi, 2022. "LATE With Missing or Mismeasured Treatment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(4), pages 1701-1717, October.
    8. Celhay, Pablo & Meyer, Bruce D. & Mittag, Nikolas, 2024. "What leads to measurement errors? Evidence from reports of program participation in three surveys," Journal of Econometrics, Elsevier, vol. 238(2).
    9. Irene Botosaru & Federico H. Gutierrez, 2018. "Difference‐in‐differences when the treatment status is observed in only one period," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(1), pages 73-90, January.
    10. Lucie Gadenne & Samuel Norris & Monica Singhal & Sandip Sukhtankar, 2024. "In-Kind Transfers as Insurance," American Economic Review, American Economic Association, vol. 114(9), pages 2861-2897, September.
    11. Tommasi, Denni & Zhang, Lina, 2024. "Bounding program benefits when participation is misreported," Journal of Econometrics, Elsevier, vol. 238(1).
    12. David L. Sjoquist & John V. Winters, 2015. "State Merit Aid Programs and College Major: A Focus on STEM," Journal of Labor Economics, University of Chicago Press, vol. 33(4), pages 973-1006.
    13. DiTraglia, Francis J. & García-Jimeno, Camilo, 2019. "Identifying the effect of a mis-classified, binary, endogenous regressor," Journal of Econometrics, Elsevier, vol. 209(2), pages 376-390.
    14. David L. Sjoquist & John V. Winters, 2015. "State Merit-Based Financial Aid Programs And College Attainment," Journal of Regional Science, Wiley Blackwell, vol. 55(3), pages 364-390, June.
    15. Jeffrey A. Groen & Anne E. Polivka, 2008. "The Effect of Hurricane Katrina on the Labor Market Outcomes of Evacuees," American Economic Review, American Economic Association, vol. 98(2), pages 43-48, May.
    16. César Martinelli & Susan Wendy Parker, 2009. "Deception and Misreporting in a Social Program," Journal of the European Economic Association, MIT Press, vol. 7(4), pages 886-908, June.
    17. Bruce D. Meyer & Wallace K. C. Mok & James X. Sullivan, 2015. "Household Surveys in Crisis," Journal of Economic Perspectives, American Economic Association, vol. 29(4), pages 199-226, Fall.
    18. Alberto Abadie, 2005. "Semiparametric Difference-in-Differences Estimators," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(1), pages 1-19.
    19. Giovanni Andrea Cornia & Frances Stewart, 1993. "Two errors of targeting," Journal of International Development, John Wiley & Sons, Ltd., vol. 5(5), pages 459-496, September.
      • Giovanni Andrea Cornia & Frances Stewart, 1993. "Two Errors of Targeting," Papers iopeps93/54, Innocenti Occasional Papers, Economic Policy Series.
    20. Thomas C. Buchmueller & John DiNardo & Robert G. Valletta, 2011. "The Effect of an Employer Health Insurance Mandate on Health Insurance Coverage and the Demand for Labor: Evidence from Hawaii," American Economic Journal: Economic Policy, American Economic Association, vol. 3(4), pages 25-51, November.
    21. Thomas J. Kane & Cecilia E. Rouse & Douglas Staiger, 1999. "Estimating Returns to Schooling When Schooling is Misreported," Working Papers 798, Princeton University, Department of Economics, Industrial Relations Section..
    22. Kerstin Bruckmeier & Regina T. Riphahn & Jürgen Wiemers, 2021. "Misreporting of program take-up in survey data and its consequences for measuring non-take-up: new evidence from linked administrative and survey data," Empirical Economics, Springer, vol. 61(3), pages 1567-1616, September.
    23. Case, Anne & Deaton, Angus, 1998. "Large Cash Transfers to the Elderly in South Africa," Economic Journal, Royal Economic Society, vol. 108(450), pages 1330-1361, September.
    24. Erich Battistin & Barbara Sianesi, 2011. "Misclassified Treatment Status and Treatment Effects: An Application to Returns to Education in the United Kingdom," The Review of Economics and Statistics, MIT Press, vol. 93(2), pages 495-509, May.
    25. Jeffrey A. Groen & Anne E. Polivka, 2008. "The Effect of Hurricane Katrina on the Labor Market Outcomes of Evacuees," Working Papers 415, U.S. Bureau of Labor Statistics.
    26. Steven J. Haider & Melvin Stephens, 2025. "Correcting for Misclassified Binary Regressors Using Instrumental Variables," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 43(3), pages 592-602, July.
    27. Nguimkeu, Pierre & Denteh, Augustine & Tchernis, Rusty, 2019. "On the estimation of treatment effects with endogenous misreporting," Journal of Econometrics, Elsevier, vol. 208(2), pages 487-506.
    28. Arthur Lewbel, 2007. "Estimation of Average Treatment Effects with Misclassification," Econometrica, Econometric Society, vol. 75(2), pages 537-551, March.
    29. Vivi Alatas & Abhijit Banerjee & Rema Hanna & Benjamin A. Olken & Julia Tobias, 2012. "Targeting the Poor: Evidence from a Field Experiment in Indonesia," American Economic Review, American Economic Association, vol. 102(4), pages 1206-1240, June.
    30. Frazis, Harley & Loewenstein, Mark A., 2003. "Estimating linear regressions with mismeasured, possibly endogenous, binary explanatory variables," Journal of Econometrics, Elsevier, vol. 117(1), pages 151-178, November.
    31. Eric V. Edmonds & Kristin Mammen & Douglas L. Miller, 2005. "Rearranging the Family?: Income Support and Elderly Living Arrangements in a Low-Income Country," Journal of Human Resources, University of Wisconsin Press, vol. 40(1).
    32. Takuya Ura, 2018. "Heterogeneous treatment effects with mismeasured endogenous treatment," Quantitative Economics, Econometric Society, vol. 9(3), pages 1335-1370, November.
    33. Meyer, Bruce D. & Mittag, Nikolas, 2017. "Misclassification in binary choice models," Journal of Econometrics, Elsevier, vol. 200(2), pages 295-311.
    34. AIGNER, Dennis J., 1973. "Regression with a binary independent variable subject to errors of observation," LIDAM Reprints CORE 130, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    35. Mark A. Loewenstein & James R. Spletzer, 1997. "Delayed Formal on-the-job Training," ILR Review, Cornell University, ILR School, vol. 51(1), pages 82-99, October.
    36. Prabhu Pingali & Anaka Aiyar & Mathew Abraham & Andaleeb Rahman, 2019. "Transforming Food Systems for a Rising India," Palgrave Studies in Agricultural Economics and Food Policy, Palgrave Macmillan, number 978-3-030-14409-8, June.
    37. Aprajit Mahajan, 2006. "Identification and Estimation of Regression Models with Misclassification," Econometrica, Econometric Society, vol. 74(3), pages 631-665, May.
    38. Timothy Besley & Rohini Pande & Vijayendra Rao, 2012. "Just Rewards? Local Politics and Public Resource Allocation in South India," The World Bank Economic Review, World Bank, vol. 26(2), pages 191-216.
    39. Sitakanta Panda, 2015. "Political Connections and Elite Capture in a Poverty Alleviation Programme in India," Journal of Development Studies, Taylor & Francis Journals, vol. 51(1), pages 50-65, January.
    40. Callaway, Brantly & Sant’Anna, Pedro H.C., 2021. "Difference-in-Differences with multiple time periods," Journal of Econometrics, Elsevier, vol. 225(2), pages 200-230.
    41. Asri, Viola, 2019. "Targeting of social transfers: Are India’s poor older people left behind?," World Development, Elsevier, vol. 115(C), pages 46-63.
    42. Thomas J. Kane & Cecilia Rouse & Douglas Staiger, 1999. "Estimating Returns to Schooling When Schooling is Misreported," Working Papers 798, Princeton University, Department of Economics, Industrial Relations Section..
    43. Sant’Anna, Pedro H.C. & Zhao, Jun, 2020. "Doubly robust difference-in-differences estimators," Journal of Econometrics, Elsevier, vol. 219(1), pages 101-122.
    44. Guy Stecklov & Alexander Weinreb & Calogero Carletto, 2018. "Can incentives improve survey data quality in developing countries?: results from a field experiment in India," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(4), pages 1033-1056, October.
    45. Andy Lin & Denni Tommasi & Lina Zhang, 2024. "Bounding program benefits when participation is misreported: Estimation and inference with Stata," Stata Journal, StataCorp LLC, vol. 24(2), pages 185-212, June.
    46. Bollinger, Christopher R., 1996. "Bounding mean regressions when a binary regressor is mismeasured," Journal of Econometrics, Elsevier, vol. 73(2), pages 387-399, August.
    47. Poirier, Dale J., 1980. "Partial observability in bivariate probit models," Journal of Econometrics, Elsevier, vol. 12(2), pages 209-217, February.
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