This paper addresses the issue of sample selection bias when comparing countries using International assessments like PISA (Program for International Student Assessment). Despite its widespread use, PISA rankings may be biased due to different attrition patterns in different countries, leading to inaccurate comparisons. This study proposes a methodology to correct for sample selection bias using a quantile selection model. Applying the method to PISA 2018 data, I find that correcting for selection bias significantly changes the rankings (based on the mean) of countries' educational performances. My results highlight the importance of accounting for sample selection bias in international educational comparisons.

翻译：本文探讨了在使用PISA（国际学生评估项目）等国际评估比较各国时存在的样本选择偏差问题。尽管PISA被广泛使用，但由于不同国家存在不同的样本流失模式，其排名可能存在偏差，导致不准确的比较。本研究提出了一种基于分位数选择模型的样本选择偏差校正方法。将该方法应用于PISA 2018数据，我发现校正选择偏差会显著改变各国教育表现（基于均值）的排名。研究结果强调了在国际教育比较中考虑样本选择偏差的重要性。