7 about 6.8 years for the full sample of countries, and 6.3 years for the sub-sample of less developed countries. So, if Mexican schooling levels had been below the turning point, it is conceivable that the rapid increase of education attainment in the 1980s may have contributed to greater earnings inequality via an increased inequality of schooling attainment.

The evidence does not support this explanation for the increased earnings inequality in Mexico: using Ram's (1990) method of calculation based on 5 schooling levels, the mean level of schooling in Mexico was 6.45 years in 1984 and 7.65 years in 1994. This means that Mexico started in 1984 with a mean level of schooling that was slightly above the "turning point" according to the LDC subsample and slightly below the turning point for the full sample of countries, while it ended up in 1994 with a mean schooling level substantially above the turning point. If the curvilinear relation is evenly distributed around the turning point, we should clearly expect the inequality of schooling in Mexico to have declined over that decade.

This conclusion is confirmed by decomposing the change of the Gini Index between 1984 and 1994 into the proportion that is attributable to changes in the wage rate, in hours worked and in education attainment. Table 3 presents the results of such an exercise, both for the distribution of Wage and Salary incomes, as well as the broader Monetary income concept. For each income concept, several "synthetic" Gini indexes are calculated:<sup>5</sup> the first two, Gini-1984 and Gini-1994, are based on the distribution of wage rates, hours worked and education attainment that pertain in each year. The next three indexes are derived by recalculating the 1984 Gini index after successively replacing the 1984 distribution of wage rates, hours worked and schooling attainment by its 1994 counterpart. The second column under each income concept reports the value of each Gini index calculated in this manner, while the third column reports the percentage difference of these values relative to the original 1984 Gini index.

Table 3: Sources of Increased Earnings Inequality

|**Wage**|**s & Salaries**<br>|**Monet**|**ary Inc**<br>|**ome**<br>|
|---|---|---|---|---|
||Level %change over<br>Gini-84||Level|%change over<br>Gini-84|
|Gini 1984|0.2281<br>0.0|Gini 1984|0.1712|<br>0.0|
|Gini 1994|0.3034<br>33.0|Gini 1994|0.2812|<br>64.3|
|Gini-Awage|0.2962<br>29.9|Gini-Awage|0.2543|<br>48.5|
|Gini-Ahours|0.2208<br>-3.2|Gini-Ahours|0.1696|<br>-0.9|
|Gini-Aeducation|0.2222<br>-2.6|Gini-Aeducatio|n 0.1710|<br>-0.1|

Source: Own calculations based on data from Tables I and 2.

Note: the %-changes in the lower half of each column do not add up to the %-difference between Gini-94 and Gini-84 due to large rounding errors.

Table 3 indicates that the "synthetic" Gini index increased by 33 percent between 1984 and 1994 (under the Wage and Salary income concept) and that over 90

> 5 These "synthetic" Gini indexes are constructed under the assumption that all the individuals with a given schooling level earn the same wage rate and work the same number of hours as the averages shown for each schooling level in Table 2.