Are education attainment levels the root cause of all good earnings news?

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An earlier post noted that the real earnings gains over the past 20 years were as clean an example of a composition effect as you’re likely to see. Earnings among full-time workers with a given level of education have shown some modest growth over time, but average earnings growth for all full-time workers has been stronger than it has been for each of its components:

Average _1997_100

 The explanation is that that the composition of educational attainments has changed, to a degree that I find striking in its size and speed:

Educ_attainments_25-54

I sort of left it at that in the earlier post, but I’m revisiting the topic with the question of how much of the good news in earnings over the last 20 years can be explained by the increase in education attainments alone. The counterfactual here is to suppose that the distribution of education attainment levels stays the same throughout the sample, while the increases in within-group earnings are the same as we observed. (I leave it as an exercise to the reader to determine if the growth in within-group earnings would have in fact been the same if education attainment rates had stayed constant.) When you run that counterfactual, you find that about one-third of the increase in the average earnings of all full-time workers can be explained by the increase in education levels:

Earnings_actual_fit

There’s another ‘good news’ feature of the data that’s worth breaking down as well: the apparent convergence in women’s and men’s earnings:

Ratio_av_mf

You can argue that the ratio is still too far from 1 and/or that progress is slow, but at least the ratio has increased. But again, things don’t look all that striking when you break that ratio out by education attainment:

Ratio_av_mf_groups

There doesn’t seem to be a lot happening to that ratio with groups. But scroll up to the second chart of this post: the gains in education attainment have gone disproportionately to women. What would have happened to the ratio if the composition of men’s and women’s educational attainments had stayed at their 1997 levels?

Ratio_av_mf_counterfactual

It looks like all of the apparent gains in ratio of women’s and men’s earnings can be explained by the simple fact that women’s improvements in educational attainment rates have outstripped those of men.

This may be well known to people who pay closer attention to these data than I do, but it was definitely new to me. Either way, the explanatory power of trends in education attainment levels is a story that appears to have gone under the radar of popular debate.

 

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Technical note: I’m sure many of you are wondering by now why I didn’t talk about medians. The answer is that I don’t know how to talk about composition effects when working with medians.

Suppose that the distribution of a population is a mixture of the form

   Mix1

The mean of the mixture is a weighted average of the means of the modes, with the same weights as in the mixture:

Mix2

In this case, you can extract directly what happens to E[y] as you change θ.

But the median of that mixture is a very different-looking animal:

Mix3

This cannot be expressed as a simple combination of the medians of the node distributions:

Mix4

This is why I’m leery of analyses based on of medians of subgroups. I don’t see the link between the median of the subgroup and the median of the population as a whole.

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