18 observations in our cross-section regressions. For this reason, we employed a relatively crude method of filling in missing Mincerian rates for countries for which we have no available data. The logic underlying this method is based on the patterns that Psacharopoulos (1994) observed in his data set, which is that Mincerian rates tend to decline with increasing levels of per capita income. As such, countries in Sub-Saharan Africa experienced rates that were relatively higher than countries in the OECD. In this light, we further increase the coverage of our data set on Mincerian rates of return to education by using the simple average of the specific country’s regional and incomegroup means of the Mincerian rates to fill in missing values. For example, to obtain an estimate of the Mincerian rate of return to education for Uganda, we took the simple mean of the regional average for Sub-Saharan African countries and the average of the low-income countries. We term this series our _extended_ series on Mincerian rates of return to education.

# **Accounting for Educational Quality**

As mentioned above, average years of schooling as the measure of educational attainment does not incorporate any adjustment for variations in quality. In recent years, there has been an increasing amount of evidence indicating that educational quality is a significant determinant of long-term economic growth. For example, Barro (2001) on including test scores into his regressions, showed that both science and mathematics test scores have a statistically significantly positive effect on growth28. Similarly, Hanushek and Kimko (2000), using their constructed indices for 31 countries for 1960-1990, do find that educational quality tends to have a statistically significant positive influence on economic growth. This positive influence on growth is still observed after controlling for effects of educational attainment, in terms of average number of years of schooling, on economic growth. Bosworth and Collins (2003) also note that failing to account for cross-country differences in educational quality is likely to be a much more serious problem for international comparisons of the correlation between incomes and education than for microeconomic studies since the quality of education within a country is likely to be relatively homogeneous.

There are two methods for accounting for the quality of education. The first utilizes measures of schooling inputs, such as education expenditures, teacher salaries, total years of schooling of the adult population (a proxy for the education of parents),

> 28 Barro (2001) also had male upper-level educational attainment as one of the independent variables.  He found that when test scores were excluded from the regressions, the estimated coefficient of the educational attainment variable was positive and highly significant.  However, on the inclusion of test scores into the regression, while the estimated coefficient of the educational attainment variable still remained positive, it became only marginally significant.  Thus Barro concluded that his results suggests that the quality and quantity of schooling both matter for growth, but that quality is much more important.