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Heaping-Induced Bias in Regression-Discontinuity Designs / Alan I. Barreca, Jason M. Lindo, Glen R. Waddell.
- Format:
- Book
- Author/Creator:
- Barreca, Alan I.
- Series:
- Working Paper Series (National Bureau of Economic Research) no. w17408.
- NBER working paper series no. w17408
- Language:
- English
- Physical Description:
- 1 online resource: illustrations (black and white);
- Place of Publication:
- Cambridge, Mass. National Bureau of Economic Research 2011.
- Summary:
- This study uses Monte Carlo simulations to demonstrate that regression-discontinuity designs arrive at biased estimates when attributes related to outcomes predict heaping in the running variable. After showing that our usual diagnostics are poorly suited to identifying this type of problem, we provide alternatives. We also demonstrate how the magnitude and direction of the bias varies with bandwidth choice and the location of the data heaps relative to the treatment threshold. Finally, we discuss approaches to correcting for this type of problem before considering these issues in several non-simulated environments.
- Notes:
- Print version record
- September 2011.
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