Example 2.3: CEO Salary and Return on Equity
use http://fmwww.bc.edu/ec-p/data/wooldridge/ceosal1
summ salary roe
Variable | Obs Mean Std. Dev. Min Max
---------+-----------------------------------------------------
salary | 209 1281.12 1372.345 223 14822
roe | 209 17.18421 8.518509 .5 56.3
reg salary roe
Source | SS df MS Number of obs = 209
---------+------------------------------ F( 1, 207) = 2.77
Model | 5166419.04 1 5166419.04 Prob > F = 0.0978
Residual | 386566563 207 1867471.32 R-squared = 0.0132
---------+------------------------------ Adj R-squared = 0.0084
Total | 391732982 208 1883331.64 Root MSE = 1366.6
------------------------------------------------------------------------------
salary | Coef. Std. Err. t P>|t| [95% Conf. Interval]
---------+--------------------------------------------------------------------
roe | 18.50119 11.12325 1.663 0.098 -3.428195 40.43057
_cons | 963.1913 213.2403 4.517 0.000 542.7902 1383.592
------------------------------------------------------------------------------
Salary for ROE = 0
display _b[roe]*0+_b[_cons]
963.19134
Salary for ROE = 30
display _b[roe]*30+_b[_cons]
1518.2269
Example 2.4: Wage and Education
use http://fmwww.bc.edu/ec-p/data/wooldridge/wage1
summ wage
Variable | Obs Mean Std. Dev. Min Max
---------+-----------------------------------------------------
wage | 526 5.896103 3.693086 .53 24.98
reg wage educ
Source | SS df MS Number of obs = 526
---------+------------------------------ F( 1, 524) = 103.36
Model | 1179.73204 1 1179.73204 Prob > F = 0.0000
Residual | 5980.68225 524 11.4135158 R-squared = 0.1648
---------+------------------------------ Adj R-squared = 0.1632
Total | 7160.41429 525 13.6388844 Root MSE = 3.3784
------------------------------------------------------------------------------
wage | Coef. Std. Err. t P>|t| [95% Conf. Interval]
---------+--------------------------------------------------------------------
educ | .5413593 .053248 10.167 0.000 .4367534 .6459651
_cons | -.9048516 .6849678 -1.321 0.187 -2.250472 .4407687
------------------------------------------------------------------------------
Wage for educ = 0
display _b[educ]*0+_b[_cons]
-.90485161
Wage for educ = 8
display _b[educ]*8+_b[_cons]
3.4260224
Return to 4 years education
display _b[educ]*4
2.165437
Example 2.5: Voting Outcomes and Campaign Expenditures
use http://fmwww.bc.edu/ec-p/data/wooldridge/vote1
reg voteA shareA
Source | SS df MS Number of obs = 173
---------+------------------------------ F( 1, 171) = 1017.70
Model | 41486.4749 1 41486.4749 Prob > F = 0.0000
Residual | 6970.77363 171 40.7647581 R-squared = 0.8561
---------+------------------------------ Adj R-squared = 0.8553
Total | 48457.2486 172 281.728189 Root MSE = 6.3847
------------------------------------------------------------------------------
voteA | Coef. Std. Err. t P>|t| [95% Conf. Interval]
---------+--------------------------------------------------------------------
shareA | .4638239 .0145393 31.901 0.000 .4351243 .4925234
_cons | 26.81254 .8871887 30.222 0.000 25.06129 28.56379
------------------------------------------------------------------------------
Example 2.6: CEO Salary and Return on Equity
use http://fmwww.bc.edu/ec-p/data/wooldridge/ceosal1
summ salary roe
Variable | Obs Mean Std. Dev. Min Max
---------+-----------------------------------------------------
salary | 209 1281.12 1372.345 223 14822
roe | 209 17.18421 8.518509 .5 56.3
reg salary roe
Source | SS df MS Number of obs = 209
---------+------------------------------ F( 1, 207) = 2.77
Model | 5166419.04 1 5166419.04 Prob > F = 0.0978
Residual | 386566563 207 1867471.32 R-squared = 0.0132
---------+------------------------------ Adj R-squared = 0.0084
Total | 391732982 208 1883331.64 Root MSE = 1366.6
------------------------------------------------------------------------------
salary | Coef. Std. Err. t P>|t| [95% Conf. Interval]
---------+--------------------------------------------------------------------
roe | 18.50119 11.12325 1.663 0.098 -3.428195 40.43057
_cons | 963.1913 213.2403 4.517 0.000 542.7902 1383.592
------------------------------------------------------------------------------
Fitted Values and Residuals for the First 15 CEOs
predict salhat, xb
gen uhat=salary-salhat
list roe salary salhat uhat in 1/15
roe salary salhat uhat
1. 14.1 1095 1224.058 -129.0581
2. 10.9 1001 1164.854 -163.8542
3. 23.5 1122 1397.969 -275.9692
4. 5.9 578 1072.348 -494.3484
5. 13.8 1368 1218.508 149.4923
6. 20 1145 1333.215 -188.2151
7. 16.4 1078 1266.611 -188.6108
8. 16.3 1094 1264.761 -170.7606
9. 10.5 1237 1157.454 79.54626
10. 26.3 833 1449.773 -616.7726
11. 25.9 567 1442.372 -875.3721
12. 26.8 933 1459.023 -526.0231
13. 14.8 1339 1237.009 101.9911
14. 22.3 937 1375.768 -438.7678
15. 56.3 2011 2004.808 6.191895
Example 2.7: Wage and Education
use http://fmwww.bc.edu/ec-p/data/wooldridge/wage1
summ wage educ
Variable | Obs Mean Std. Dev. Min Max
---------+-----------------------------------------------------
wage | 526 5.896103 3.693086 .53 24.98
educ | 526 12.56274 2.769022 0 18
reg wage educ
Source | SS df MS Number of obs = 526
---------+------------------------------ F( 1, 524) = 103.36
Model | 1179.73204 1 1179.73204 Prob > F = 0.0000
Residual | 5980.68225 524 11.4135158 R-squared = 0.1648
---------+------------------------------ Adj R-squared = 0.1632
Total | 7160.41429 525 13.6388844 Root MSE = 3.3784
------------------------------------------------------------------------------
wage | Coef. Std. Err. t P>|t| [95% Conf. Interval]
---------+--------------------------------------------------------------------
educ | .5413593 .053248 10.167 0.000 .4367534 .6459651
_cons | -.9048516 .6849678 -1.321 0.187 -2.250472 .4407687
------------------------------------------------------------------------------
Wage for educ = 12.56
display _b[educ]*12.56+_b[_cons]
5.8824
Example 2.8: CEO Salary and Return on Equity
use http://fmwww.bc.edu/ec-p/data/wooldridge/ceosal1
reg salary roe
Source | SS df MS Number of obs = 209
---------+------------------------------ F( 1, 207) = 2.77
Model | 5166419.04 1 5166419.04 Prob > F = 0.0978
Residual | 386566563 207 1867471.32 R-squared = 0.0132
---------+------------------------------ Adj R-squared = 0.0084
Total | 391732982 208 1883331.64 Root MSE = 1366.6
------------------------------------------------------------------------------
salary | Coef. Std. Err. t P>|t| [95% Conf. Interval]
---------+--------------------------------------------------------------------
roe | 18.50119 11.12325 1.663 0.098 -3.428195 40.43057
_cons | 963.1913 213.2403 4.517 0.000 542.7902 1383.592
------------------------------------------------------------------------------
Example 2.9: Voting Outcomes and Campaign Expenditures
use http://fmwww.bc.edu/ec-p/data/wooldridge/vote1
reg voteA shareA
Source | SS df MS Number of obs = 173
---------+------------------------------ F( 1, 171) = 1017.70
Model | 41486.4749 1 41486.4749 Prob > F = 0.0000
Residual | 6970.77363 171 40.7647581 R-squared = 0.8561
---------+------------------------------ Adj R-squared = 0.8553
Total | 48457.2486 172 281.728189 Root MSE = 6.3847
------------------------------------------------------------------------------
voteA | Coef. Std. Err. t P>|t| [95% Conf. Interval]
---------+--------------------------------------------------------------------
shareA | .4638239 .0145393 31.901 0.000 .4351243 .4925234
_cons | 26.81254 .8871887 30.222 0.000 25.06129 28.56379
------------------------------------------------------------------------------
Example 2.10: A Log Wage Equation
use http://fmwww.bc.edu/ec-p/data/wooldridge/wage1
reg lwage educ
Source | SS df MS Number of obs = 526
---------+------------------------------ F( 1, 524) = 119.58
Model | 27.5606296 1 27.5606296 Prob > F = 0.0000
Residual | 120.769132 524 .230475443 R-squared = 0.1858
---------+------------------------------ Adj R-squared = 0.1843
Total | 148.329762 525 .28253288 Root MSE = .48008
------------------------------------------------------------------------------
lwage | Coef. Std. Err. t P>|t| [95% Conf. Interval]
---------+--------------------------------------------------------------------
educ | .0827444 .0075667 10.935 0.000 .0678796 .0976092
_cons | .5837726 .0973358 5.998 0.000 .3925562 .774989
------------------------------------------------------------------------------
Example 2.11: CEO Salary and Firm Sales
use http://fmwww.bc.edu/ec-p/data/wooldridge/ceosal1
reg lsalary lsales
Source | SS df MS Number of obs = 209
---------+------------------------------ F( 1, 207) = 55.30
Model | 14.0661711 1 14.0661711 Prob > F = 0.0000
Residual | 52.6559988 207 .254376806 R-squared = 0.2108
---------+------------------------------ Adj R-squared = 0.2070
Total | 66.7221699 208 .320779663 Root MSE = .50436
------------------------------------------------------------------------------
lsalary | Coef. Std. Err. t P>|t| [95% Conf. Interval]
---------+--------------------------------------------------------------------
lsales | .2566717 .0345167 7.436 0.000 .1886225 .324721
_cons | 4.821996 .2883397 16.723 0.000 4.253537 5.390455
------------------------------------------------------------------------------
Example 2.12: Student Math Performance and the School Lunch Program
use http://fmwww.bc.edu/ec-p/data/wooldridge/meap93
reg math10 lnchprg
Source | SS df MS Number of obs = 408
---------+------------------------------ F( 1, 406) = 83.77
Model | 7665.26597 1 7665.26597 Prob > F = 0.0000
Residual | 37151.9145 406 91.5071786 R-squared = 0.1710
---------+------------------------------ Adj R-squared = 0.1690
Total | 44817.1805 407 110.115923 Root MSE = 9.5659
------------------------------------------------------------------------------
math10 | Coef. Std. Err. t P>|t| [95% Conf. Interval]
---------+--------------------------------------------------------------------
lnchprg | -.3188643 .0348393 -9.152 0.000 -.3873523 -.2503763
_cons | 32.14271 .9975824 32.221 0.000 30.18164 34.10378
------------------------------------------------------------------------------
This page prepared by Oleksandr Talavera (revised 13 Sep 2002)
Send your questions/comments/suggestions to Kit Baum
at baum@bc.edu
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