Counting Rotten Apples: Student Achievement and Score Manipulation in Italian Elementary Schools

Erich Battistin (), Michele De Nadai and Daniela Vuri ()

No 8405, IZA Discussion Papers from Institute of Labor Economics (IZA)

Abstract: We derive bounds for the average of math and language scores of elementary school students in Italy correcting for pervasive score manipulation. Information on the fraction of manipulated data is retrieved from a natural experiment that randomly assigns external monitors to schools. We show how bounds can be tightened imposing restrictions on the measurement properties of the manipulation indicator developed by the government agency charged with test administration and data collection. We additionally assume that manipulation is more likely in those classes at the lower end of the distribution of true scores. Our results show that regional rankings by academic performance are reversed once manipulation is properly taken into account.

Keywords: nonparametric bounds; measurement error; corrupt sampling; partial identification (search for similar items in EconPapers)
JEL-codes: C14 C31 C81 I21 J24 (search for similar items in EconPapers)
Pages: 41 pages
Date: 2014-08
New Economics Papers: this item is included in nep-edu
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Citations: View citations in EconPapers (3)

Published - published in: Journal of Econometrics, 2017, 200 (2), 344-362

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Related works:
Journal Article: Counting rotten apples: Student achievement and score manipulation in Italian elementary Schools (2017)
Working Paper: Counting Rotten Apples: Student Achievement and Score Manipulation in Italian Elementary Schools (2016)
Working Paper: Counting Rotten Apples: Student Achievement and Score Manipulation in Italian Elementary Schools (2014)
Working Paper: Counting Rotten Apples: Student Achievement and Score Manipulation in Italian Elementary Schools (2014)
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