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An IERI – International Educational Research Institute Journal

Table 4 Variables’ definitions

From: Does early tracking affect learning inequalities? Revisiting difference-in-differences modeling strategies with international assessments

Individual variables

Definition

Population under study

 Natives

Children with at least one parent born in the country

Social background

 Books at home

Ln(n° books at home)

Children report the number of books at home, based on pictures depicting different numbers of shelves

Classification in PIRLS is 0–10; 11–25; 26–100; 101–200, > 200

Classification in PISA is 0–10; 11–25; 26–100; 101–200, 201–500, > 500

The last two classes in PISA have been aggregated, so the two classifications are now identical. We have considered the central value in each class (500 in the highest class)

In practice we use the following values:

Ln(5) = 1.61; Ln(13) = 2.56; Ln(63) = 4.14; Ln(150) = 5.01; Ln(500) = 6.21

 Parents with tertiary education

At least one parents with tertiary education = 1

No parents with tertiary education = 0

Control variables

 Age

Country-specific quartiles’ dummy variables (1°–4°)

We consider age in classes to allow for non-linear effects. The effect of age on test scores is unlikely to be linear. On the one side, the literature reports consistent evidence that older children tend to perform better (for example, in systems where regular children enter first grade in a given calendar year, children born in January tend to perform better than children born in December). On the other side, older children might be weaker. In some countries, there is flexibility in the age of first entry at school, so immature children might enter later, In other countries, poor performing children may be forced to repeat the school year, so older children are likely to be children who have experienced a grade failure

Quartiles are country-specific. This is particularly relevant for PIRLS,

as regular age and age variability of 4th grade children varies

substantially across countries

 Gender

Female = 0, Male = 1