In Table 2.6 we looked at the data relating average hourly earnings and education, as measured by years of schooling. Using that data, if we regress27 average hourly earnings (Y) on education (X), we obtain the following results.
var (ft) _ 0.7649 se (ft) _ 0.8746 var (#>) _ 0.00483 se (82) _ 0.0695 r2 _ 0.9077 a2 _ 0.8816
As the regression results show, there is a positive association between education and earnings, an unsurprising finding. For every additional year of schooling, the average hourly earnings go up by about 72 cents an hour. The intercept term is positive but it may have no economic meaning. The r2 value suggests that about 89 percent of the variation in average hourly earnings is explained by education. For cross-sectional data, such a high r2 is rather unusual.
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