Heaping-Induced Bias in Regression-Discontinuity Designs / Alan I. Barreca, Jason M. Lindo, Glen R. Waddell.

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Barreca, Alan I

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Material type: Text

TextSeries: Working Paper Series (National Bureau of Economic Research) ; no. w17408.Publication details: Cambridge, Mass. National Bureau of Economic Research 2011.Description: 1 online resource: illustrations (black and white)Subject(s):

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Abstract: 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.

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Item type	Home library	Collection	Call number	Status	Date due	Barcode	Item holds
Working Paper	Biblioteca Digital	Colección NBER	nber w17408 (Browse shelf(Opens below))	Not For Loan

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September 2011.

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.