Several countries have implemented programs that use test scores to rank schools, and to reward or penalize them based on their students' average performance. Recently, Kane and Staiger (2002) have warned that imprecision in the measurement of school-level test scores could impede these efforts. There is little evidence, however, on how seriously noise hinders the evaluation of the impact of these interventions. We examine these issues in the context of Chile's P-900 program a country-wide intervention in which resources were allocated based on cutoffs in schools' mean test scores. We show that transitory noise in average scores and mean reversion lead conventional estimation approaches to greatly overstate the impacts of such programs. We then show how a regression discontinuity design that utilizes the discrete nature of the selection rule can be used to control for reversion biases. While the RD analysis provides convincing evidence that the P-900 program had significant effects on test score gains, these effects are much smaller than is widely believed.
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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number
10118.
Length: Date of creation: Nov 2003 Date of revision: Publication status: published as Chay, Kenneth Y., Patrick J. McEwan and Miguel Urquiola. "The Central Role Of Noise In Evaluating Interventions That Use Test Score To Rank Schools," American Economic Review, 2005, v95(4,Sep), 1237-1258. Handle: RePEc:nbr:nberwo:10118
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Paul Glewwe & Nauman Ilias & Michael Kremer, 2003.
"Teacher Incentives,"
NBER Working Papers
9671, National Bureau of Economic Research, Inc.
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