st: Scientific notation in regression estimates (e.g., 2.5e-16)

[Jessica Chan <jchan87012@gmail.com>]

Dear Statalisters,

My quantile regression output is displaying very small coefficients
(basically 0), and displaying these in scientific notation format.

1. Does this reflect an error in the modelling or estimation procedures? Do
these represent perfectly valid estimates, or should I be wary of using
these estimates?

Note, I'm using quantile regression, so I'm thinking this has something to
do with estimating the medians rather than the averages (e.g., due to
precision, the regression results are returning, for example,
0.0000000015 rather than 0).

Here is a fictitious example:

sysuse nlsw88
qreg age occupation
qreg age race
qreg age occupation race

*occupation is entered as a categorical variable for illustration purposes
*in the first model, note that age and occupation are unrelated, as
expected, and that the coefficient is 0 (i.e., no difference in median age
between occupations)
*in the third model, note that the coefficient for occupation is very small
and in scientific notation (but given the results of the first model, I
think this is fair to assume that it represents 0).

2. Separately, how should I interpret regression output that has missing t or z
statistics, and "point estimate" confidence intervals?  In the above
example, I note that the standard error is present, so I'm thinking
this is just a limitation of the output display and that a very large
value for the t or z statistic (i.e., generated by dividing the beta
estimate by the very small SE) is displayed as "." instead of the
large value (e.g., 5e10).

Thanks for your help,

J
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