arXiv 19 Sep 2023 · Econometrics
arXiv:2309.10642 · PDF · DOI · OpenAlex · Extracted main text
This paper addresses the critical issue of sample selection bias in cross-country comparisons based on international assessments such as the Programme for International Student Assessment (PISA). Although PISA is widely used to benchmark educational performance across countries, it samples only students who remain enrolled in school at age 15. This introduces survival bias, particularly in countries with high dropout rates, potentially leading to distorted comparisons. To correct for this bias, I develop a simple adjustment of the classical Heckman selection model tailored to settings with fully truncated outcome data. My approach exploits the joint normality of latent errors and leverages information on the selection rate, allowing identification of the counterfactual mean outcome for the full population of 15-year-olds. Applying this method to PISA 2018 data, I show that adjusting for selection bias results in substantial changes in country rankings based on average performance. These results highlight the importance of accounting for non-random sample selection to ensure accurate and policy-relevant international comparisons of educational outcomes.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | J. Ringarp (2016) Pisa lends legitimacy: A study of education policy changes in germany and sweden after 2000 | 0.511 | 2 | 1 | 100% |
| 2 | J. G. Cromley (2009) Reading achievement and science proficiency: International comparisons from the programme on international student assessment | 0.405 | 1 | 1 | 100% |
| 3 | J. J. Heckman (1979) Sample selection bias as a specification error | 0.405 | 1 | 1 | 100% |
| 4 | M. Jakubowski and A. Pokropek (2015) Reading achievement progress across countries | 0.405 | 1 | 1 | 100% |
| 5 | T. Knighton, P. Brochu, and T. Gluszynski (2010) Measuring up: Canadian results of the oecd pisa study: the performance of canada's youth in reading, mathematics and science: 20… | 0.405 | 1 | 1 | 100% |
| 6 | P. Knodel, K. Martens, and D. Niemann (2013) Pisa as an ideational roadmap for policy change: exploring germany and england in a comparative perspective | 0.405 | 1 | 1 | 100% |
| 7 | M. O. Martin et al (2000) International comparisons of student achievement | 0.405 | 1 | 1 | 100% |
| 8 | P. J. McEwan and J. H. Marshall (2004) Why does academic achievement vary across countries? evidence from cuba and mexico | 0.405 | 1 | 1 | 100% |
| 9 | B. McGaw (2008) The role of the oecd in international comparative studies of achievement | 0.405 | 1 | 1 | 100% |
| 10 | P. Nagy (1996) International comparisons of student achievement in mathematics and science: A canadian perspective | 0.405 | 1 | 1 | 100% |
Showing the top 10 of 14 scored citations.