问题
I often see regression tables in publications where the plain standard errors are reported (in parentheses), together with the robust standard errors (in brackets) below the plain standard errors. The tables also include the accompanying asterisks beside the parentheses/brackets indicating statistical significance.
What is the most sensible way to create regression reports like these?
So far, I have been using the estout package in Stata. For a given model, I could have one column with the plain standard error and another with the robust one.
For example, using estout, I could do the following:
eststo: qui reg ROE duality
eststo: qui reg ROE duality, vce(cluster firm)
esttab b(%9.3fc) ///
se(%9.3fc) ///
star (* 0.5 ** 0.25)
The aforementioned code snippet produces:
--------------------------------------------
(1) (2)
ROE ROE
--------------------------------------------
duality -8.090** -8.090*
(6.585) (7.067)
--------------------------------------------
N 647 647
--------------------------------------------
However, this table wastes column space as the point estimates of the two columns will be identical, with the only difference being the standard errors from the different variance-covariance estimators.
What I would much rather have is a table like the one below:
------------------------
(1)
ROE
-------------------------
duality -8.090
(6.585)**
[7.067]*
-------------------------
N 647
-------------------------
Note that indication of statistical significance at 0.5 and 0.25 is for illustration here only and certainly does not reflect convention.
回答1:
You just need to manually add the robust standard errors:
sysuse auto, clear
eststo clear
quietly regress price weight mpg, vce(robust)
matrix regtab = r(table)
matrix regtab = regtab[2,1...]
matrix rbse = regtab
eststo: quietly regress price weight mpg
estadd matrix rbse = rbse
esttab, cells(b se rbse)
-------------------------
(1)
price
b/se/rbse
-------------------------
weight 1.746559
.6413538
.777837
mpg -49.51222
86.15604
95.8074
_cons 1946.069
3597.05
4213.793
-------------------------
N 74
-------------------------
Formatting it to your specifications requires using the relevant options:
esttab , cells("b(fmt(a3) star)" "se(fmt(a2) par)" "rbse(fmt(a2) par([ ]))") ///
star(* 0.5 ** 0.25) addnote("Robust SE in brackets" "* p<0.5, ** p<0.25") ///
nonumbers
---------------------------
price
b/se/rbse
---------------------------
weight 1.747**
(0.64)
[0.78]
mpg -49.51
(86.2)
[95.8]
_cons 1946.1
(3597.0)
[4213.8]
---------------------------
N 74
---------------------------
Robust SE in brackets
* p<0.5, ** p<0.25
回答2:
Note that appropriate indication of significance can be displayed for both the regular standard errors and the robust standard errors separately by including the robust p-values in the estimation set and then selecting them using the pvalue() suboption within cells(). Here is an example:
sysuse auto
regress price weight mpg
est sto m1
regress price weight mpg, vce(robust)
matrix table = r(table)
matrix r_se = table[2,1...]
matrix r_p = table[4,1...]
estadd matrix r_se: m1
estadd matrix r_p: m1
regress price weight mpg turn
est sto m2
regress price weight mpg turn, vce(robust)
matrix table = r(table)
matrix r_se = table[2,1...]
matrix r_p = table[4,1...]
estadd matrix r_se: m2
estadd matrix r_p: m2
esttab m1 m2, mtitle nonumber ///
cell(b(fmt(a3)) ///
se(par star) ///
r_se(par([ ]) star pvalue(r_p)) ///
) ///
note(@starlegend)
--------------------------------------------
m1 m2
b/se/r_se b/se/r_se
--------------------------------------------
weight 1.747 3.524
(0.641)** (0.817)***
[0.778]* [1.159]**
mpg -49.51 -72.87
(86.16) (81.30)
[95.81] [97.07]
turn -395.2
(122.6)**
[177.4]*
_cons 1946.1 12744.2
(3597.0) (4760.1)**
[4213.8] [6429.0]
--------------------------------------------
N 74 74
--------------------------------------------
* p<0.05, ** p<0.01, *** p<0.001
来源：https://stackoverflow.com/questions/51816692/how-do-i-create-a-table-wth-both-plain-and-robust-standard-errors