Fun With Stata and Jogging

This morning, I ran a longer distance than I ever had before. Just an 8k, for those who jog regularly. But the prospect of running five miles--five miles--filled me with the sort of dread that I assume SEC defensive linemen have when they approach final exams in Diff EQ.

What was my time? It was very bad, by the standards of people who run: 10:29/mile. By my standards, this is very, very good---not far off from what I ran in the single mile when I was in middle school but for much, much longer.

Anyway, I wanted to have some fun, so I grabbed the race results from a Web site and decided to do some analysis.

Table 1 displays the results of ordinary least-squares estimates of running times per mile for the participants in the Jingle All the Way 8K Race this morning. Scanty information is available, so the models are pretty spare. Nevertheless they do have some pretty strong results.

Table 1. OLS models of time per mile in seconds
for the Jingle All The Way Race, December 2011.

	(1)	(2)	(3)
	Overall	Men Only	Women Only
age	1.642***	1.264***	1.955***
	(11.52)	(5.84)	(10.29)
female	78.24***
	(25.03)
_cons	484.3***	497.8***	552.2***
	(85.19)	(60.89)	(84.93)
N	4726	1709	3017
t statistics in parentheses * p < 0.05, ** p < 0.01, *** p < 0.001

As you can see, women are significantly--significantly--slower than men. For a runner of the same age, women are 78 seconds slower than men. Moreover, women slow down with age somewhat faster than men, losing nearly 2 seconds from their mile time for each year they get older. Compare that with men, who slow by only about 1.3 seconds per year.

The point is reinforced by the figure, which displays kernel density estimates for women's and men's time. On the other hand, there are way, way more women than men running, so it is possible that men just don't run if they're not competitive. (Please, God, I'm not trying to do causal analysis here ... )