Surpress insig2u in regression output

[Marcel Issa]

When I illustrate my Regression Output:
----------------------------------------------------------------------------
(1) (2) (3) (4)
Collateral~y Collateral~y
----------------------------------------------------------------------------
main
Age 0.384** 0.00174 -0.0662 -0.0164
(0.012) (0.799) (0.164) (0.153)

Numberofem~s 0.738 0.00335 -0.129 -0.0319
(0.441) (0.737) (0.170) (0.167)

Totalassets 0.00166 0.00000753 -0.00280*** -0.000693***
(0.404) (0.752) (0.002) (0.002)

Corporatio~y -0.790 -0.00358 1.203 0.298
(0.888) (0.757) (0.397) (0.405)

Grossprofit -0.00898 -0.0000408 -0.00298 -0.000739
(0.278) (0.765) (0.113) (0.118)

Profitabil~t -0.961 -0.00436 -0.151 -0.0374
(0.130) (0.782) (0.147) (0.154)

Leverage_pct -0.192** -0.000872 -0.0663*** -0.0164***
(0.044) (0.792) (0.000) (0.000)

Loansize 0.0379** 0.000172 0.0212*** 0.00526***
(0.041) (0.809) (0.000) (0.000)

Maturity -1.563* -0.00709 -0.520*** -0.129***
(0.054) (0.813) (0.000) (0.000)

GDPGrowth_~t -2.180*** -0.00989 1.229 0.304
(0.001) (0.825) (0.256) (0.260)

Duration -1.623 -0.00736 0.491*** 0.122***
(0.199) (0.774) (0.000) (0.000)

Housebank 10.91*** 0.0495 -5.412*** -1.341***
(0.006) (0.798) (0.000) (0.000)

g1 0.355 0.0880
(0.699) (0.702)

g3 4.375*** 1.084***
(0.000) (0.000)

_cons 25.12 9.489***
(0.136) (0.000)
----------------------------------------------------------------------------
/
lnsig2u -15.03
(.)
----------------------------------------------------------------------------
N 40 40 41 41
r2_p 0.659
----------------------------------------------------------------------------
p-values in parentheses
* p<0.10, ** p<0.05, *** p<0.010

There is a row devoted to Insig2u which I dont understand. Can I surpress it in the table? Also I manually computed the pseudo r squared for the random effects logit model shown in the fourth column. Is there a way to Show it in the table?


input float Collateraldummy byte Numberofemployees long Totalassets float Corporationdummy long Grossprofit float(Profitability_pct Leverage_pct) long Loansize byte Maturity float GDPGrowth_pct double Duration byte Housebank str6 Loantype float Banks
1 28 1500 1 1600 6.25 95 475 10 1.5 0 0 "Credit" 7
0 28 1500 1 1600 6.25 95 475 10 1.5 0 0 "Credit" 1
1 15 500 1 800 8.75 50 150 10 1.5 5.75 1 "Credit" 8
1 15 500 1 800 8.75 50 30 1 1.5 5.75 1 "LC" 8
1 15 500 1 800 8.75 50 20 1 1.5 6 1 "LC" 8
1 10 387 0 815 3.435583 72 80 1 2.2 10 1 "LC" 8
1 10 415 0 830 5.060241 77 80 1 2.2 11 1 "LC" 8
1 10 400 0 850 3.529412 90 120 1 1.5 12 1 "LC" 8
0 10 415 0 830 5.060241 77 60 6 2.2 1 0 "Credit" 7
1 25 800 1 3500 3.4285715 20 100 1 1.5 4.666666666666667 0 "LC" 3
1 25 800 1 3500 3.4285715 20 620 20 1.5 0 0 "Credit" 6
1 25 800 1 3500 3.4285715 20 230 3 1.5 5 0 "LC" 5
0 8 130 0 300 23.333334 40 50 10 1.5 4.75 1 "Credit" 1
0 3 60 0 190 0 0 20 10 .5 0 1 "Credit" 1
0 8 130 0 300 23.333334 40 15 3 2.2 3 0 "LC" 3
1 12 450 1 800 8.125 26 50 10 1.5 10.083333333333334 0 "Credit" 8
1 12 462 1 830 8.192771 32 125 5 2.2 8 0 "Credit" 8
1 12 438 1 755 7.549669 30 100 5 2.2 0 0 "Credit" 4
1 12 450 1 800 8.125 26 15 1 1.5 10 0 "LC" 8
1 12 438 1 755 7.549669 30 15 1 2.2 9 0 "LC" 8
1 12 462 1 830 8.192771 32 15 1 2.2 8 0 "LC" 8
1 12 438 1 755 7.549669 30 120 1 2.2 10 0 "LC" 5
1 12 462 1 830 8.192771 32 120 1 2.2 9 0 "LC" 5
0 12 450 1 800 8.125 26 10 1 1.5 10.583333333333334 0 "LC" 5
1 10 320 1 1000 8 55 70 6 1.5 7 0 "Credit" 5
1 10 320 1 1000 8 55 100 5 1.5 5.166666666666667 0 "Credit" 4
1 12 277 1 800 9.375 60 150 4 1.5 5.083333333333333 1 "Credit" 5
1 25 720 1 1800 11.38889 45 350 3 2.2 12 1 "Credit" 5
0 25 695 1 2000 10.5 45 300 6 1.5 14 1 "Credit" 5
1 3 248 1 500 11 44 30 4 1.7 0 0 "Credit" 3
1 3 250 1 600 8.333333 50 50 5 2.2 1.33 0 "Credit" 4
0 3 248 1 500 11 44 8 1 1.7 0 0 "LC" 7
0 3 250 1 600 8.333333 50 8 1 2.2 1 0 "LC" 7
0 3 250 1 600 8.333333 50 10 3 2.2 1.083 0 "LC" 9
1 25 462 1 1750 2.2857144 45 100 1 2.2 0 0 "LC" 9
1 29 450 1 1900 2.710526 50 200 3 2.2 .5833333333333334 0 "LC" 9
1 29 450 1 1900 2.710526 50 100 1 2.2 1 0 "LC" 9
1 25 462 1 1750 2.2857144 45 250 5 2.2 0 0 "Credit" 4
1 29 440 1 2000 2.5 50 200 5 1.5 1.4166666666666667 0 "Credit" 4
1 9 360 1 415 18.795181 25 15 1 1.7 5 1 "LC" 7
1 9 350 1 435 18.62069 25 25 1 2.2 6 1 "LC" 7
1 9 345 1 430 18.60465 30 15 1 2.2 7 1 "LC" 7
1 14 1000 0 1450 7.931035 60 350 7 .5 15 1 "Credit" 7
0 15 1050 0 1500 6.666667 70 300 10 1.5 20 1 "Credit" 7
1 14 1000 0 1450 7.931035 60 150 1 .5 15 1 "LC" 7
1 15 970 0 1400 6.785714 70 150 1 2.2 16.5 1 "LC" 7
1 15 960 0 1475 6.779661 70 150 1 1.7 17.75 1 "LC" 7
1 3 350 0 400 12.5 50 20 1 1.5 7 1 "LC" 6
1 3 350 0 400 12.5 50 15 5 1.5 7 1 "Credit" 6
0 25 500 1 1100 18.181818 80 150 10 1.5 15 1 "Credit" 5
0 25 500 1 1100 18.181818 80 400 15 1.5 15 1 "Credit" 5
0 25 500 1 1100 18.181818 80 50 1 1.5 15 1 "LC" 5
0 25 620 0 2000 15 20 150 10 1.5 20 1 "Credit" 5
0 25 620 0 2000 15 20 50 1 1.5 20 1 "LC" 5
0 12 380 1 1500 6.666667 30 25 5 1.5 15 1 "Credit" 5
1 7 400 0 950 13.68421 25 300 5 1.7 3 1 "Credit" 7
0 9 425 0 1000 12.3 20 250 7 1.5 6 1 "Credit" 7
1 7 400 0 950 13.68421 25 50 1 1.7 3 1 "LC" 7
1 8 415 0 975 14.358974 20 80 1 2.2 4.333333333333333 1 "LC" 7
1 9 410 0 935 13.368984 20 80 1 2.2 5.333333333333333 1 "LC" 7
1 9 425 0 1000 12.3 20 80 1 1.5 6 1 "LC" 7
1 6 370 0 427 14.285714 42 80 5 2.2 23 1 "Credit" 5
1 6 370 0 427 14.285714 42 30 1 2.2 8 0 "LC" 6
1 6 375 0 430 13.953488 45 45 1 2.2 8.75 0 "LC" 6
0 6 370 0 427 14.285714 42 80 5 2.2 0 0 "Credit" 2
0 28 3500 1 2875 5.495652 38 500 10 .5 14 1 "Credit" 5
0 30 3625 1 3000 5 40 400 7 2.2 4 0 "Credit" 3
1 30 3625 1 3000 5 40 60 2 2.2 5 0 "LC" 4
1 30 3625 1 3000 5 40 50 2 2.2 .16666666666666666 0 "LC" 4
0 15 3100 1 2600 6.538462 50 150 3 1.8 5 0 "Credit" 3
0 15 3100 1 2600 6.538462 50 130 4 1.8 4 0 "Credit" 4
0 15 3100 1 2600 6.538462 50 50 2 1.8 4 0 "LC" 4
1 35 2650 1 2300 9 21 300 5 2.2 22 1 "Credit" 7
1 35 2710 1 2425 9.278351 28 250 7 1.7 23 1 "Credit" 7
0 33 2665 1 2400 8.75 25 50 9 2.2 25.25 1 "Credit" 7
0 33 2700 1 2350 8.297873 25 80 10 1.5 26.333333333333332 1 "Credit" 7
1 34 2710 1 2425 9.278351 28 80 1 1.7 23.166666666666668 1 "LC" 7
1 26 1980 1 1650 8.939394 26 325 10 2.2 16 1 "Credit" 7
0 26 2050 1 1700 8.941176 31 150 8 2.2 18.333333333333332 1 "Credit" 7
0 26 1930 1 1750 8.857142 33 220 5 1.5 19.166666666666668 1 "Credit" 7
0 26 2050 1 1700 8.941176 31 80 1 2.2 18.166666666666668 1 "LC" 7
end
[/CODE]

 xtset Banks

xtlogit Collateraldummy  Age Numberofemployees Totalassets Corporationdummy Grossprofit Profitability_pct Leverage_pct g1 g3 Loansize Maturity GDPGrowth_pct Duration Housebank if Loantype=="Credit", re noskip vce (cluster Banks)

display "pseudo R2"= (e(ll_0)-e(ll))/e(ll_0)

The second and fourth row are devoted to the marginal effects and the first column for the pooled logit.

[Phil Bromiley]

You didn't get a quick answer. You don't tell us what estimator you ran for your "regression output" and the output itself is hard to read. Then you move to xtlogit. I'm not sure what the bottom of the post means. Your code doesn't run - the xtlogit includes variables not in the data supplied.

Normally, we don't manipulate what Stata posts in the command window, but do manipulate what is written in table for for papers. There are many user-written programs for doing the output for papers - outreg2, estout, asdoc, etc. Stata also includes some routines to do this although they seem a little harder to use than some of the user-written options. Some of these output procedures will let you drop statistics.