Ambiguous high scores: The All-Russian Olympiad in economics during the COVID-19 pandemic

Timur Magzhanov () and Anna Sagradyan ()
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Timur Magzhanov: Moscow State University, CMASF, Moscow, Russian Federation;
Anna Sagradyan: Moscow State University, Moscow, Russian Federation

Applied Econometrics, 2023, vol. 70, 89-108

Abstract: This paper evaluates the change in the contribution of factors to the probability of students’ success at the All-Russian Olympiad in Economics during the COVID-19 pandemic using classical econometric models and binary quantile regression (BQR). No works were found in the Russian literature where BQR would be applied. However, in our opinion, it has great potential both for studying the effects’ heterogeneity and for solving probability prediction problems. Empirical results show that the contribution of school rating to success at the municipal stage decreased in the 2020/21 season compared to the 2019/20 season. High score at the municipal stage (winner status) became a weaker predictor of success at the regional stage in the 2020/21 season compared to the 2019/20 season. The reason for this change may lie in a decrease in the tasks’ complexity (due to a change in their structure), a higher opportunity for cheating (due to weak and non-mandatory proctoring) or both.

Keywords: online education; All-Russian Olympiad in economics; COVID-19; binary quantile regression (search for similar items in EconPapers)
JEL-codes: C21 I21 (search for similar items in EconPapers)
Date: 2023
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