qreg - Stata
qreg - Stata
qreg - Stata
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<strong>qreg</strong> — Quantile regression 15<br />
By default, bs<strong>qreg</strong>, s<strong>qreg</strong>, and i<strong>qreg</strong> use 20 replications. We can control the number of<br />
replications by specifying the reps() option:<br />
. bs<strong>qreg</strong> price weight length i.foreign, reps(1000)<br />
(fitting base model)<br />
Bootstrap replications (1000)<br />
1 2 3 4 5<br />
.................................................. 50<br />
.................................................. 100<br />
.................................................. 150<br />
.................................................. 200<br />
.................................................. 250<br />
.................................................. 300<br />
.................................................. 350<br />
.................................................. 400<br />
.................................................. 450<br />
.................................................. 500<br />
.................................................. 550<br />
.................................................. 600<br />
.................................................. 650<br />
.................................................. 700<br />
.................................................. 750<br />
.................................................. 800<br />
.................................................. 850<br />
.................................................. 900<br />
.................................................. 950<br />
.................................................. 1000<br />
Median regression, bootstrap(1000) SEs Number of obs = 74<br />
Raw sum of deviations 142205 (about 4934)<br />
Min sum of deviations 108822.6 Pseudo R2 = 0.2347<br />
price Coef. Std. Err. t P>|t| [95% Conf. Interval]<br />
weight 3.933588 2.659349 1.48 0.144 -1.370316 9.237492<br />
length -41.25191 69.29744 -0.60 0.554 -179.4613 96.95748<br />
foreign<br />
Foreign 3377.771 1096.197 3.08 0.003 1191.474 5564.068<br />
_cons 344.6489 5916.939 0.06 0.954 -11456.31 12145.61<br />
A comparison of the standard errors is informative.<br />
<strong>qreg</strong> bs<strong>qreg</strong> bs<strong>qreg</strong><br />
Variable <strong>qreg</strong> vce(robust) reps(20) reps(1000)<br />
weight 1.329 1.694 3.124 2.660<br />
length 45.46 51.74 83.71 69.30<br />
1.foreign 885.4 728.5 1057. 1095.<br />
cons 5182. 5096. 7053. 5917.<br />
The results shown above are typical for models with heteroskedastic errors. (Our dependent variable<br />
is price; if our model had been in terms of ln(price), the standard errors estimated by <strong>qreg</strong> and<br />
bs<strong>qreg</strong> would have been nearly identical.) Also, even for heteroskedastic errors, 20 replications is<br />
generally sufficient for hypothesis tests against 0.
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