Endogeneity Problems in Multilevel Estimation of Education Production Functions: an Analysis Using PISA Data


This paper explores endogeneity problems in multilevel estimation of education production functions. The focus is on level 2 endogeneity which arises from correlations between student characteristics and omitted school variables.

We first develop a theoretical model in order to show that school and peer characteristics are the by-product of student background. This theoretical framework helps the identification of the hypotheses we would like to test within the empirical part. From an econometric point of view, the correlations between student and school characteristics imply that the omission of some variables may generate endogeneity bias. Therefore, in the second section of the paper, an estimation approach based on the Mundlak (1978) technique is developed in order to tackle bias and to generate consistent estimates.

The entire analysis is undertaken in a comparative context between three countries: Germany, Finland and the UK. Each one of them represents a particular system. For instance, Finland is known for its extreme comprehensiveness, Germany for early selection and the UK for its liberalism. These countries are used to illustrate the theory and to prove that the level of bias arising from omitted variables varies according to the characteristics of education systems.