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Assessing the Monotonicity Assumption in IV and fuzzy RD designs

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Listed:
  • Fiorini, Mario
  • Katrien Stevens

Abstract

Whenever treatment e_ects are heterogeneous and there is sorting into treatment based on the gain, monotonicity is a condition that both Instrumental Variable and fuzzy Regression Discontinuity designs have to satisfy for their estimate to be interpretable as a LATE. However, applied economic work rarely discusses this important assumption. This is in stark contrast to the lengthy discussions dedicated to the other IV and fuzzy RD conditions. We show that monotonicity can and should be investigated using a mix of economic insights, data patterns and formal tests. This is just an extra step to validate the results. We provide examples in a variety of settings as a guide to practice.

Suggested Citation

  • Fiorini, Mario & Katrien Stevens, 2014. "Assessing the Monotonicity Assumption in IV and fuzzy RD designs," Working Papers 2014-13, University of Sydney, School of Economics.
  • Handle: RePEc:syd:wpaper:2014-13
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    File URL: http://econ-wpseries.com/2014/201413.pdf
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    References listed on IDEAS

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    1. Kasey S. Buckles & Daniel M. Hungerman, 2013. "Season of Birth and Later Outcomes: Old Questions, New Answers," The Review of Economics and Statistics, MIT Press, vol. 95(3), pages 711-724, July.
    2. Patrick Puhani & Andrea Weber, 2007. "Does the early bird catch the worm?," Empirical Economics, Springer, vol. 32(2), pages 359-386, May.
    3. Sandra E. Black & Paul J. Devereux & Kjell G. Salvanes, 2011. "Too Young to Leave the Nest? The Effects of School Starting Age," The Review of Economics and Statistics, MIT Press, vol. 93(2), pages 455-467, May.
    4. Rashmi Barua & Kevin Lang, 2009. "School Entry, Educational Attainment and Quarter of Birth: A Cautionary Tale of LATE," NBER Working Papers 15236, National Bureau of Economic Research, Inc.
    5. Lindeboom, Maarten & Llena-Nozal, Ana & van der Klaauw, Bas, 2009. "Parental education and child health: Evidence from a schooling reform," Journal of Health Economics, Elsevier, vol. 28(1), pages 109-131, January.
    6. Garry F. Barrett & Stephen G. Donald, 2003. "Consistent Tests for Stochastic Dominance," Econometrica, Econometric Society, vol. 71(1), pages 71-104, January.
    7. Dionissi Aliprantis, 2012. "Redshirting, Compulsory Schooling Laws, and Educational Attainment," Journal of Educational and Behavioral Statistics, , vol. 37(2), pages 316-338, April.
    8. Harmon, Colm & Walker, Ian, 1995. "Estimates of the Economic Return to Schooling for the United Kingdom," American Economic Review, American Economic Association, vol. 85(5), pages 1278-1286, December.
    9. Damon Clark & Heather Royer, 2013. "The Effect of Education on Adult Mortality and Health: Evidence from Britain," American Economic Review, American Economic Association, vol. 103(6), pages 2087-2120, October.
    10. Klein, Tobias J., 2010. "Heterogeneous treatment effects: Instrumental variables without monotonicity?," Journal of Econometrics, Elsevier, vol. 155(2), pages 99-116, April.
    11. Mühlenweg, Andrea & Blomeyer, Dorothea & Stichnoth, Holger & Laucht, Manfred, 2012. "Effects of age at school entry (ASE) on the development of non-cognitive skills: Evidence from psychometric data," Economics of Education Review, Elsevier, vol. 31(3), pages 68-76.
    12. Huber, Martin & Mellace, Giovanni, 2012. "Relaxing monotonicity in the identification of local average treatment effects," Economics Working Paper Series 1212, University of St. Gallen, School of Economics and Political Science.
    13. Chen, Le-Yu & Szroeter, Jerzy, 2014. "Testing multiple inequality hypotheses: A smoothed indicator approach," Journal of Econometrics, Elsevier, vol. 178(P3), pages 678-693.
    14. Philip Oreopoulos, 2006. "Estimating Average and Local Average Treatment Effects of Education when Compulsory Schooling Laws Really Matter," American Economic Review, American Economic Association, vol. 96(1), pages 152-175, March.
    15. Joshua D. Angrist & Alan B. Keueger, 1991. "Does Compulsory School Attendance Affect Schooling and Earnings?," The Quarterly Journal of Economics, Oxford University Press, vol. 106(4), pages 979-1014.
    16. Mary Silles, 2011. "The effect of schooling on teenage childbearing: evidence using changes in compulsory education laws," Journal of Population Economics, Springer;European Society for Population Economics, vol. 24(2), pages 761-777, April.
    17. Datar, Ashlesha, 2006. "Does delaying kindergarten entrance give children a head start?," Economics of Education Review, Elsevier, vol. 25(1), pages 43-62, February.
    18. Joshua D. Angrist & Stacey H. Chen, 2011. "Schooling and the Vietnam-Era GI Bill: Evidence from the Draft Lottery," American Economic Journal: Applied Economics, American Economic Association, vol. 3(2), pages 96-118, April.
    19. Guido W. Imbens & Donald B. Rubin, 1997. "Estimating Outcome Distributions for Compliers in Instrumental Variables Models," Review of Economic Studies, Oxford University Press, vol. 64(4), pages 555-574.
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    Cited by:

    1. Lionel Page & Dipanwita Sarkar & Juliana Silva-Goncalves, 2018. "Long-lasting effects of relative age at school," QuBE Working Papers 056, QUT Business School.
    2. repec:eee:jeborg:v:153:y:2018:i:c:p:38-57 is not listed on IDEAS
    3. Lionel Page & Dipanwita Sarkar & Juliana S. Goncalves, 2015. "The older the bolder? Does relative age among peers influence children's confidence and risk attitudes?," QuBE Working Papers 029, QUT Business School.
    4. repec:eee:joepsy:v:63:y:2017:i:c:p:43-81 is not listed on IDEAS
    5. Anna Godøy & Venke Furre Haaland & Ingrid Huitfeldt & Mark Votruba, 2019. "Impacts of hospital wait time on patient health and labor supply," Discussion Papers 919, Statistics Norway, Research Department.

    More about this item

    Keywords

    essential heterogeneity; monotonicity assumption; LATE; instrumental variable; regression discontinuity;

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