<p>Pooled regression on a panel-data sample, <strong>indeed</strong>, <em>does not take the time dimension into account</em>. This is why it is called "pooled": we ignore the fact that for each cross-section we have a time series, and we treat the whole panel-data sample as though it were a cross-sectional one, as if, say,  $x_{it}$ and $x_{i,t+1}$ are diffrenet cross sections.</p>

CC BY-SA 3.0
2017-09-01T12:41:59.103Z
2017-09-01T14:50:15.963Z
2017-09-01T14:50:15.963Z
Alecos Papadopoulos
<p>I am struggeling to find the specific commands to achieve lower standard errors within simple regressions. </p>

<p>I would be thankful for your help.</p>

CC BY-SA 3.0
2017-09-02T01:00:55.387Z
`regress` does pooled OLS, and your `xtreg Y X1 X2 X3` with no options does the "random effects FGLS" panel regression. If you want GLS, you need to provide with a covariance structure, which is done by your `xtset firmID Time`. OLS requires nothing. To figure out what is really done under the hood, the "Methods and formulas" section of the Stata pdf manual would help.
chan1142
CC BY-SA 3.0
2017-09-07T16:02:05.563Z
The edit impoverishes the question considerably. What was the motivation?
luchonacho
<stata>
How can I achieve better standard error values in Stata?
AlexWeiß
# How can I achieve better standard error values in Stata?

(Asked by: username_0 on 2017-09-01)

I am struggeling to find the specific commands to achieve lower standard errors within simple regressions.

I would be thankful for your help.

**Tags:** stata

> **Comments:**
> **username_1**: `regress` does pooled OLS, and your `xtreg Y X1 X2 X3` with no options does the "random effects FGLS" panel regression. If you want GLS, you need to provide with a covariance structure, which is done by your `xtset firmID Time`. OLS requires nothing. To figure out what is really done under the hood, the "Methods and formulas" section of the Stata pdf manual would help.  
> **username_2**: The edit impoverishes the question considerably. What was the motivation?  

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## 1 answers

### Answer by username_3 on 2017-09-01. Score: 1

Pooled regression on a panel-data sample, **indeed**, *does not take the time dimension into account*. This is why it is called "pooled": we ignore the fact that for each cross-section we have a time series, and we treat the whole panel-data sample as though it were a cross-sectional one, as if, say, $x\_{it}$ and $x\_{i,t+1}$ are diffrenet cross sections.


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