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What Happens When Econometrics and Psychometrics Collide? An Example Using the PISA Data

John Jerrim (), Luis Alejandro Lopez-Agudo (), Oscar Marcenaro Gutierrez and Nikki Shure
Additional contact information
John Jerrim: University College London
Luis Alejandro Lopez-Agudo: University of Malaga

No 10847, IZA Discussion Papers from Institute of Labor Economics (IZA)

Abstract: International large-scale assessments such as PISA are increasingly being used to benchmark the academic performance of young people across the world. Yet many of the technicalities underpinning these datasets are misunderstood by applied researchers, who sometimes fail to take their complex sample and test designs into account. The aim of this paper is to generate a better understanding amongst economists about how such databases are created, and what this implies for the empirical methodologies one should (or should not) apply. We explain how some of the modelling strategies preferred by economists seem to be at odds with the complex test design, and provide clear advice on the types of robustness tests that are therefore needed when analyzing these datasets. In doing so, we hope to generate a better understanding of international large-scale education databases, and promote better practice in their use.

Keywords: replicate weights; weights; PISA; test design; sample design; plausible values (search for similar items in EconPapers)
JEL-codes: C10 C18 C55 I20 (search for similar items in EconPapers)
Pages: 36 pages
Date: 2017-06
New Economics Papers: this item is included in nep-ecm and nep-edu
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (36)

Published - published in: Economics of Education Review, 2017, 61, 51-58

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Related works:
Journal Article: What happens when econometrics and psychometrics collide? An example using the PISA data (2017) Downloads
Working Paper: What Happens When Econometrics and Psychometrics Collide? An Example Using PISA Data (2017) Downloads
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