Teacher Education and Development Study in Mathematics - IEA

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TEACHER PAY AND STUDENT MATHEMATICS ACHIEVEMENT
3. Teacher Relative Pay and Student
Performance
Income distribution across countries and student performance
If better student performance is positively related to higher relative teacher pay because
of a more equal income distribution, we could expect, for example, that societies with
a more equal income distribution will generally be societies with relatively equitable
pay scales across occupations. Thus, differences between teacher pay and pay in other
occupations are likely to be smaller in these societies than in societies marked by
large income inequalities. One question we consequently decided to explore was this:
Does student performance across countries and regions of countries relate to income
inequality? We considered that an answer to this question would provide a clue as to
whether the main story about student performance and teacher pay is about income
distribution rather than societal emphasis on paying teachers more.
To test the proposition that student performance may relate to income inequality at the
national level, we used the reported results of two international tests of mathematics—
Trends in International Mathematics and Science Study (TIMSS), administered by
the International Association for the Evaluation of Educational Achievement (IEA),
and Progress in International Student Achievement (PISA), administered by the
Organisation for Economic Co-operation and Development (OECD).
The TIMSS assessment measures have been given to fourth and eighth graders in many
countries over several iterations: 1995 (also given to seventh graders in this year), 1999,
2003, and 2007. TIMSS focuses on mathematics and science. The PISA assessment
measures have also been administered in many countries—to 15-year-olds—with
iterations occurring in 2000, 2003, and 2006. PISA focuses on mathematics, science,
and reading. The two programs of study have somewhat different purposes: TIMSS is
more interested in assessing the effect of curriculum differences across countries; PISA
is more concerned with how well students are learning critical thinking skills needed for
working in the 21st-century labor market.
We estimated the relationship of the average test scores on the studies’ tests to income
inequality, controlling for GDP per capita and using income inequality data from all
countries participating in TIMSS and PISA for which such data were available. There
are many measures of income inequality; each has its particular advantages and
disadvantages in estimating the distribution of income. For our estimates, we used the
Gini coefficient. We took our estimates of the coefficients from two large databases
assembled by the World Bank (World Bank, 2005; see also Deininger & Squire, 1996).
We regressed the average mathematics scores in each test by country on the most recent
Gini coefficient (multiplied by 100) available for that country and the GDP per capita in
purchasing power parity dollars (PPP$) for the year 2000. For each test, the relationship
between average test score and the Gini coefficient was negative and statistically
significant. The coefficient for the GDP per capita was positive and usually statistically
significant (except for TIMSS 1995). Table 4 presents the results. The results suggest
that the more equal the income distribution and the higher the GDP per capita in a
country, the more likely it will be that students attain the higher average test scores. We
also tried other specifications, including controlling for the country’s total population