We are interested in the relation between Gini coefficients of
education, educational variables, and growth. We specify a system of 14
difference equations with lagged dependent variables in education
variables, as well as a growth regression, auxiliary equations for
savings and investment ratios, and the growth of the labour force and
estimate all of them simultaneously. Having a closed system of 18
equations we run simulations, which show that for the panel average
enrolment in tertiary education will go beyond 90%, and therefore drive
transitional growth rates and average years of schooling to high levels
and reduce inequality over time. This will be achieved by reductions in
gender gaps, higher enrolment rates, and lower dropout rates, lower
pupil-teacher ratios and higher public expenditure on education. There
are no simple one-way causalities. Policies enhancing savings ratios and
enrolment in tertiary education have the largest effects through the
Keywords: Gini coefficients, education, growth, simultaneous equation system.
JEL-code: E24, H52, O11, 15, 40.