Three Essays in the Economics of pre-primary school education: An application of Gini-BMA methodology

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Dimiski, Anastasia
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University of Guelph

Existing theoretical and empirical evidence on the determinants of students’ performance reveals a direct link between pre-primary education and achievement test scores in primary school. Relying on the first-of-its-kind 2015 wave data from the Programme of International Student Assessment (PISA), the present study analyses the associations between students’ performance in science and a broad set of variables, including regressors that proxy pre-primary education. Employing a Gini Regression Bayesian Model Averaging (BMA) approach to account for model uncertainty, it is found that non-attendance in pre-primary education is a robust determinant with a negative impact on students’ performance in science. This result is confirmed both under Gini-BMA and OLS-BMA methodology.

Students’ performance, pre-primary education, Gini regression coefficient, BMA methodology, PISA
Dimiski, Anastasia. (2021). Factors that Affect Students' Performance In Science: An Application Using Gini-BMA Methodology On PISA 2015 Dataset. Review of Economic Analysis. 13: 157-211.