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School Entry, Educational Attainment and Quarter of Birth: A Cautionary Tale of LATE

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  • Rashmi Barua
  • Kevin Lang

Abstract

Partly in response to increased testing and accountability, states and districts have been raising the minimum school entry age, but existing studies show mixed results regarding the effects of entry age. These studies may be severely biased because they violate the monotonicity assumption needed for LATE. We propose an instrument not subject to this bias and show no effect on the educational attainment of children born in the fourth quarter of moving from a December 31 to an earlier cutoff. We then estimate a structural model of optimal entry age that reconciles the different IV estimates including ours. We find that one standard instrument is badly biased but that the other diverges from ours because it estimates a different LATE. We also find that an early entry age cutoff that is applied loosely (as in the 1950s) is beneficial but one that is strictly enforced is not.

Suggested Citation

  • 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.
  • Handle: RePEc:nbr:nberwo:15236
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    Cited by:

    1. Dionissi Aliprantis, 2014. "When Should Children Start School?," Journal of Human Capital, University of Chicago Press, vol. 8(4), pages 481-536.
    2. Chaisemartin, Clément de, 2014. "Tolerating defiance? Local average treatment effects without monotonicity," CAGE Online Working Paper Series 197, Competitive Advantage in the Global Economy (CAGE).
    3. Dionissi Aliprantis, 2012. "Redshirting, Compulsory Schooling Laws, and Educational Attainment," Journal of Educational and Behavioral Statistics, , vol. 37(2), pages 316-338, April.
    4. Ben Edwards & Mario Fiorini & Katrien Stevens & Matthew Taylor, 2013. "Is Monotonicity in an IV and RD Design Testable? No, But You Can Still Check on it," Working Paper Series 7, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
    5. Barua, Rashmi, 2014. "Intertemporal substitution in maternal labor supply: Evidence using state school entrance age laws," Labour Economics, Elsevier, vol. 31(C), pages 129-140.
    6. Shao, Ling, 2014. "Estimating the relationship between calculated financial need and actual aid received using quarter of birth instruments," Economics of Education Review, Elsevier, vol. 42(C), pages 165-174.
    7. Toru Kitagawa, 2013. "A bootstrap test for instrument validity in heterogeneous treatment effect models," CeMMAP working papers CWP53/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    8. Klein, Tobias J., 2010. "Heterogeneous treatment effects: Instrumental variables without monotonicity?," Journal of Econometrics, Elsevier, vol. 155(2), pages 99-116, April.
    9. Dionissi Aliprantis, 2013. "Covariates and causal effects: the problem of context," Working Papers (Old Series) 1310, Federal Reserve Bank of Cleveland.
    10. Rashmi Barua & Marian Vidal-Fernandez, 2014. "No Pass No Drive: Education and Allocation of Time," Journal of Human Capital, University of Chicago Press, vol. 8(4), pages 399-431.
    11. Huber Martin & Wüthrich Kaspar, 2019. "Local Average and Quantile Treatment Effects Under Endogeneity: A Review," Journal of Econometric Methods, De Gruyter, vol. 8(1), pages 1-27, January.
    12. Toru Kitagawa, 2013. "A bootstrap test for instrument validity in heterogeneous treatment effect models," CeMMAP working papers 53/13, Institute for Fiscal Studies.
    13. Huber, Martin & Wüthrich, Kaspar, 2017. "Evaluating local average and quantile treatment effects under endogeneity based on instruments: a review," FSES Working Papers 479, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    14. Clément de Chaisemartin, 2017. "Tolerating defiance? Local average treatment effects without monotonicity," Quantitative Economics, Econometric Society, vol. 8(2), pages 367-396, July.
    15. Rasmus Landersø & Helena Skyt Nielsen & Marianne Simonsen, 2017. "School Starting Age and the Crime‐age Profile," Economic Journal, Royal Economic Society, vol. 127(602), pages 1096-1118, June.
    16. Zhang, Kexin, 2023. "The long-term impact of higher education: Evidence from the Gaokao reinstatement in China," Economics of Education Review, Elsevier, vol. 97(C).
    17. Clément de Chaisemartin & Xavier d'Haultfoeuille, 2012. "Late Again with Defiers," PSE Working Papers halshs-00699646, HAL.
    18. 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.
    19. Attar, Itay & Cohen-Zada, Danny, 2017. "The Effect of School Entrance Age on Educational Outcomes: Evidence Using Multiple Cutoff Dates and Exact Date of Birth," IZA Discussion Papers 10568, Institute of Labor Economics (IZA).
    20. Oscar David Marcenaro Gutierrez & Luis Alejandro Lopez-Agudo, 2016. "Disentangling the effect of students’ maturity on academic achievement," Investigaciones de Economía de la Educación volume 11, in: José Manuel Cordero Ferrera & Rosa Simancas Rodríguez (ed.), Investigaciones de Economía de la Educación 11, edition 1, volume 11, chapter 29, pages 535-550, Asociación de Economía de la Educación.
    21. Dionissi Aliprantis, 2012. "When should children start school?," Working Papers (Old Series) 1126, Federal Reserve Bank of Cleveland.
    22. Patrizia Ordine & Giuseppe Rose & Daniela Sposato, 2014. "Gift Of Time And Family Gift: The Effect Of Early School Entry On Pupils Performance," Working Papers 201408, Università della Calabria, Dipartimento di Economia, Statistica e Finanza "Giovanni Anania" - DESF.
    23. Elliott Fan & Jin-Tan Liu & Yen-Chien Chen, 2014. "Is the 'Quarter of Birth' Endogenous? Evidence From One Million Siblings in Taiwan," NBER Working Papers 20444, National Bureau of Economic Research, Inc.
    24. 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.

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    More about this item

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • I20 - Health, Education, and Welfare - - Education - - - General
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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