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

by Anastasia Dimiski

Institution: University of Guelph
Department: Department of Economics and Finance
Degree: PhD
Year: 2022
Keywords: Students’ performance; pre-primary education; Gini regression coefficient; BMA methodology; PISA
Posted: 3/25/2025
Record ID: 2255724
Full text PDF: https://atrium.lib.uoguelph.ca/xmlui/handle/10214/26778


Abstract

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.

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