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Running and Jumping Variables in RD Designs

Author

Listed:
  • Alan Barreca
  • Melanie Guldi
  • Jason M. Lindo
  • Glen R. Waddell

    (Department of Economics, Tulane University)

Abstract

This study demonstrates that regression discontinuity designs will arrive at biased estimates when attributes related to outcomes predict heaping in the running variable. We discuss several approaches to diagnosing and correcting for this type of problem. Our primary example focuses on the use of birth weights as a running variable. We begin by showing that birth weights are measured most precisely for children of white and highly educated mothers. As a result, less healthy children, who are more likely to be of low socioeconomic status, are disproportionately represented at multiples of round numbers. For this reason, RD estimates using birth weight as the running variable will be biased in a manner that leads one to conclude that it is "good" to be strictly less than any 100-gram cutoff. As such, prior estimates of the effects of very low birth weight classification (Almond, Doyle, Kowalski, and Williams 2010) have been overstated and appear to be zero. We also demonstrate potential problems using days of birth or grade point averages as running variables.

Suggested Citation

  • Alan Barreca & Melanie Guldi & Jason M. Lindo & Glen R. Waddell, 2010. "Running and Jumping Variables in RD Designs," Working Papers 1001, Tulane University, Department of Economics.
  • Handle: RePEc:tul:wpaper:1001
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    File URL: http://repec.tulane.edu/RePEc/pdf/tul1001.pdf
    File Function: First version, 2010
    Download Restriction: no

    File URL: http://repec.tulane.edu/RePEc/pdf/tul1001r1.pdf
    File Function: Revised version, 2011
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    Citations

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    Cited by:

    1. Fletcher, Jason M. & Tokmouline, Mansur, 2017. "The Effects of Academic Probation on College Success: Regression Discontinuity Evidence from Four Texas Universities," IZA Discussion Papers 11232, Institute of Labor Economics (IZA).
    2. Sa A. Bui & Steven G. Craig & Scott A. Imberman, 2011. "Is Gifted Education a Bright Idea? Assessing the Impact of Gifted and Talented Programs on Achievement," NBER Working Papers 17089, National Bureau of Economic Research, Inc.
    3. Paco Martorell & Isaac McFarlin, Jr. & Yu Xue, 2014. "Does Failing a Placement Exam Discourage Underprepared Students from Going to College?," Education Finance and Policy, MIT Press, vol. 10(1), pages 46-80, November.

    More about this item

    Keywords

    regression discontinuity; birth weight; infant mortality;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior

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