Example 10.1: Static Phillips Curve
use http://fmwww.bc.edu/ec-p/data/wooldridge/phillips
reg inf unem
Source | SS df MS Number of obs = 49
-------------+------------------------------ F( 1, 47) = 2.62
Model | 25.6369575 1 25.6369575 Prob > F = 0.1125
Residual | 460.61979 47 9.80042107 R-squared = 0.0527
-------------+------------------------------ Adj R-squared = 0.0326
Total | 486.256748 48 10.1303489 Root MSE = 3.1306
------------------------------------------------------------------------------
inf | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
unem | .4676257 .2891262 1.62 0.112 -.1140212 1.049273
_cons | 1.42361 1.719015 0.83 0.412 -2.034602 4.881822
------------------------------------------------------------------------------
Example 10.2: Effects of Inflation and Deficits on Interst Rates
use http://fmwww.bc.edu/ec-p/data/wooldridge/intdef
reg i3 inf def
Source | SS df MS Number of obs = 49
-------------+------------------------------ F( 2, 46) = 52.78
Model | 294.032897 2 147.016449 Prob > F = 0.0000
Residual | 128.133943 46 2.78552049 R-squared = 0.6965
-------------+------------------------------ Adj R-squared = 0.6833
Total | 422.16684 48 8.7951425 Root MSE = 1.669
------------------------------------------------------------------------------
i3 | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
inf | .6131825 .0757753 8.09 0.000 .4606547 .7657104
def | .7004054 .11807 5.93 0.000 .4627427 .938068
_cons | 1.252032 .4416346 2.83 0.007 .3630674 2.140996
------------------------------------------------------------------------------
Example 10.3: Puerto Rican Employment and the Minimum Wage
use http://fmwww.bc.edu/ec-p/data/wooldridge/prminwge
reg lprepop lmincov lusgnp
Source | SS df MS Number of obs = 38
-------------+------------------------------ F( 2, 35) = 34.04
Model | .211258194 2 .105629097 Prob > F = 0.0000
Residual | .108600157 35 .003102862 R-squared = 0.6605
-------------+------------------------------ Adj R-squared = 0.6411
Total | .319858351 37 .00864482 Root MSE = .0557
------------------------------------------------------------------------------
lprepop | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
lmincov | -.1544433 .0649015 -2.38 0.023 -.2862003 -.0226863
lusgnp | -.0121899 .0885134 -0.14 0.891 -.1918817 .1675019
_cons | -1.054413 .7654066 -1.38 0.177 -2.608271 .4994452
------------------------------------------------------------------------------
Example 10.4: Effects of Personal Exemption on Fertility Rates
use http://fmwww.bc.edu/ec-p/data/wooldridge/fertil3
summ pe
Variable | Obs Mean Std. Dev. Min Max
-------------+-----------------------------------------------------
pe | 72 100.4015 65.87563 0 243.83
reg gfr pe ww2 pill
Source | SS df MS Number of obs = 72
-------------+------------------------------ F( 3, 68) = 20.38
Model | 13183.6215 3 4394.54049 Prob > F = 0.0000
Residual | 14664.2739 68 215.651087 R-squared = 0.4734
-------------+------------------------------ Adj R-squared = 0.4502
Total | 27847.8954 71 392.223879 Root MSE = 14.685
------------------------------------------------------------------------------
gfr | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
pe | .08254 .0296462 2.78 0.007 .0233819 .1416981
ww2 | -24.2384 7.458253 -3.25 0.002 -39.12111 -9.355684
pill | -31.59403 4.081068 -7.74 0.000 -39.73768 -23.45039
_cons | 98.68176 3.208129 30.76 0.000 92.28003 105.0835
------------------------------------------------------------------------------
reg gfr pe ww2 pill pe_1 pe_2
Source | SS df MS Number of obs = 70
-------------+------------------------------ F( 5, 64) = 12.73
Model | 12959.7886 5 2591.95772 Prob > F = 0.0000
Residual | 13032.6443 64 203.635067 R-squared = 0.4986
-------------+------------------------------ Adj R-squared = 0.4594
Total | 25992.4329 69 376.701926 Root MSE = 14.27
------------------------------------------------------------------------------
gfr | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
pe | .0726718 .1255331 0.58 0.565 -.1781094 .323453
ww2 | -22.1265 10.73197 -2.06 0.043 -43.56608 -.6869198
pill | -31.30499 3.981559 -7.86 0.000 -39.25907 -23.35091
pe_1 | -.0057796 .1556629 -0.04 0.970 -.316752 .3051929
pe_2 | .0338268 .1262574 0.27 0.790 -.2184013 .286055
_cons | 95.8705 3.281957 29.21 0.000 89.31403 102.427
------------------------------------------------------------------------------
test pe_1 pe_2
( 1) pe_1 = 0.0
( 2) pe_2 = 0.0
F( 2, 64) = 0.05
Prob > F = 0.9480
Estimated LRP
display _b[pe]+_b[pe_1]+_b[pe_2]
.10071909
gen dif1=pe_1-pe
gen dif2=pe_2-pe
reg gfr pe dif1 dif2 ww2 pill
Source | SS df MS Number of obs = 70
-------------+------------------------------ F( 5, 64) = 12.73
Model | 12959.7886 5 2591.95772 Prob > F = 0.0000
Residual | 13032.6443 64 203.635067 R-squared = 0.4986
-------------+------------------------------ Adj R-squared = 0.4594
Total | 25992.4329 69 376.701926 Root MSE = 14.27
------------------------------------------------------------------------------
gfr | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
pe | .1007191 .0298027 3.38 0.001 .0411814 .1602568
dif1 | -.0057796 .1556629 -0.04 0.970 -.316752 .3051929
dif2 | .0338268 .1262574 0.27 0.790 -.2184013 .286055
ww2 | -22.1265 10.73197 -2.06 0.043 -43.56608 -.6869198
pill | -31.30499 3.981559 -7.86 0.000 -39.25907 -23.35091
_cons | 95.8705 3.281957 29.21 0.000 89.31403 102.427
------------------------------------------------------------------------------
Example 10.5: Antidumping Filings and Chemical Import
use http://fmwww.bc.edu/ec-p/data/wooldridge/barium
reg lchnimp lchempi lgas lrtwex befile6 affile6 afdec6
Source | SS df MS Number of obs = 131
-------------+------------------------------ F( 6, 124) = 9.06
Model | 19.4051456 6 3.23419093 Prob > F = 0.0000
Residual | 44.2471061 124 .356831501 R-squared = 0.3049
-------------+------------------------------ Adj R-squared = 0.2712
Total | 63.6522517 130 .489632706 Root MSE = .59735
------------------------------------------------------------------------------
lchnimp | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
lchempi | 3.1172 .479202 6.50 0.000 2.168725 4.065675
lgas | .1963049 .9066233 0.22 0.829 -1.598157 1.990766
lrtwex | .9830093 .4001536 2.46 0.015 .1909934 1.775025
befile6 | .0595742 .26097 0.23 0.820 -.4569584 .5761068
affile6 | -.0324067 .2642973 -0.12 0.903 -.5555252 .4907118
afdec6 | -.5652446 .2858353 -1.98 0.050 -1.130993 .0005035
_cons | -17.80195 21.04551 -0.85 0.399 -59.45692 23.85301
------------------------------------------------------------------------------
Change in Chinese export of barium
display 100*(exp(_b[afdec6])-1)
-43.177885
Example 10.6: Election Outcomes and Economic Performance
use http://fmwww.bc.edu/ec-p/data/wooldridge/fair
reg demvote partyWH incum pWHgnews pWHinf if year<1996
Source | SS df MS Number of obs = 20
-------------+------------------------------ F( 4, 15) = 7.37
Model | .072465402 4 .018116351 Prob > F = 0.0017
Residual | .036853881 15 .002456925 R-squared = 0.6629
-------------+------------------------------ Adj R-squared = 0.5730
Total | .109319283 19 .005753646 Root MSE = .04957
------------------------------------------------------------------------------
demvote | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
partyWH | -.0434752 .040459 -1.07 0.300 -.1297114 .0427611
incum | .0543902 .0234166 2.32 0.035 .004479 .1043014
pWHgnews | .0108466 .0041267 2.63 0.019 .0020508 .0196424
pWHinf | -.0077017 .0032567 -2.36 0.032 -.0146432 -.0007602
_cons | .481062 .0122631 39.23 0.000 .4549238 .5072002
------------------------------------------------------------------------------
Predicted value of demvote
display _b[_cons]+_b[partyWH]+_b[incum]+_b[pWHgnews]*3+_b[pWHinf]*3.019
.5012655
Example 10.7: Housing Investment and Prices
use http://fmwww.bc.edu/ec-p/data/wooldridge/hseinv
reg linvpc lprice
Source | SS df MS Number of obs = 42
-------------+------------------------------ F( 1, 40) = 10.53
Model | .254364572 1 .254364572 Prob > F = 0.0024
Residual | .966255373 40 .024156384 R-squared = 0.2084
-------------+------------------------------ Adj R-squared = 0.1886
Total | 1.22061994 41 .029771218 Root MSE = .15542
------------------------------------------------------------------------------
linvpc | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
lprice | 1.240944 .3824192 3.24 0.002 .4680455 2.013842
_cons | -.5502345 .0430266 -12.79 0.000 -.6371945 -.4632745
------------------------------------------------------------------------------
reg linvpc lprice t
Source | SS df MS Number of obs = 42
-------------+------------------------------ F( 2, 39) = 10.08
Model | .415945135 2 .207972568 Prob > F = 0.0003
Residual | .804674809 39 .020632687 R-squared = 0.3408
-------------+------------------------------ Adj R-squared = 0.3070
Total | 1.22061994 41 .029771218 Root MSE = .14364
------------------------------------------------------------------------------
linvpc | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
lprice | -.3809609 .6788352 -0.56 0.578 -1.754035 .992113
t | .0098287 .0035122 2.80 0.008 .0027246 .0169328
_cons | -.9130595 .1356134 -6.73 0.000 -1.187363 -.6387556
------------------------------------------------------------------------------
Example 10.8: Fertility Equation
use http://fmwww.bc.edu/ec-p/data/wooldridge/fertil3
reg gfr pe ww2 pill t
Source | SS df MS Number of obs = 72
-------------+------------------------------ F( 4, 67) = 32.84
Model | 18441.2357 4 4610.30894 Prob > F = 0.0000
Residual | 9406.65967 67 140.397905 R-squared = 0.6622
-------------+------------------------------ Adj R-squared = 0.6420
Total | 27847.8954 71 392.223879 Root MSE = 11.849
------------------------------------------------------------------------------
gfr | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
pe | .2788778 .0400199 6.97 0.000 .1989978 .3587578
ww2 | -35.59228 6.297377 -5.65 0.000 -48.1619 -23.02266
pill | .9974479 6.26163 0.16 0.874 -11.50082 13.49571
t | -1.149872 .1879038 -6.12 0.000 -1.524929 -.7748146
_cons | 111.7694 3.357765 33.29 0.000 105.0673 118.4716
------------------------------------------------------------------------------
reg gfr pe ww2 pill t tsq
Source | SS df MS Number of obs = 72
-------------+------------------------------ F( 5, 66) = 35.09
Model | 20236.3981 5 4047.27961 Prob > F = 0.0000
Residual | 7611.49734 66 115.325717 R-squared = 0.7267
-------------+------------------------------ Adj R-squared = 0.7060
Total | 27847.8954 71 392.223879 Root MSE = 10.739
------------------------------------------------------------------------------
gfr | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
pe | .3478126 .0402599 8.64 0.000 .2674311 .428194
ww2 | -35.88028 5.707921 -6.29 0.000 -47.27651 -24.48404
pill | -10.11972 6.336094 -1.60 0.115 -22.77014 2.530696
t | -2.531426 .3893863 -6.50 0.000 -3.308861 -1.753991
tsq | .0196126 .004971 3.95 0.000 .0096876 .0295377
_cons | 124.0919 4.360738 28.46 0.000 115.3854 132.7984
------------------------------------------------------------------------------
Example 10.9: Puerto Rican Employment
use http://fmwww.bc.edu/ec-p/data/wooldridge/prminwge
reg lprepop lmincov lusgnp t
Source | SS df MS Number of obs = 38
-------------+------------------------------ F( 3, 34) = 62.78
Model | .270947898 3 .090315966 Prob > F = 0.0000
Residual | .048910453 34 .001438543 R-squared = 0.8471
-------------+------------------------------ Adj R-squared = 0.8336
Total | .319858351 37 .00864482 Root MSE = .03793
------------------------------------------------------------------------------
lprepop | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
lmincov | -.1686946 .0442464 -3.81 0.001 -.2586142 -.078775
lusgnp | 1.057349 .1766381 5.99 0.000 .6983776 1.416321
t | -.0323541 .0050228 -6.44 0.000 -.0425616 -.0221467
_cons | -8.696287 1.295773 -6.71 0.000 -11.32961 -6.06296
------------------------------------------------------------------------------
reg lprepop lmincov lusgnp
Source | SS df MS Number of obs = 38
-------------+------------------------------ F( 2, 35) = 34.04
Model | .211258194 2 .105629097 Prob > F = 0.0000
Residual | .108600157 35 .003102862 R-squared = 0.6605
-------------+------------------------------ Adj R-squared = 0.6411
Total | .319858351 37 .00864482 Root MSE = .0557
------------------------------------------------------------------------------
lprepop | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
lmincov | -.1544433 .0649015 -2.38 0.023 -.2862003 -.0226863
lusgnp | -.0121899 .0885134 -0.14 0.891 -.1918817 .1675019
_cons | -1.054413 .7654066 -1.38 0.177 -2.608271 .4994452
------------------------------------------------------------------------------
Example 10.10: Housing Investment
use http://fmwww.bc.edu/ec-p/data/wooldridge/hseinv
reg linvpc t
Source | SS df MS Number of obs = 42
-------------+------------------------------ F( 1, 40) = 20.19
Model | .409447014 1 .409447014 Prob > F = 0.0001
Residual | .81117293 40 .020279323 R-squared = 0.3354
-------------+------------------------------ Adj R-squared = 0.3188
Total | 1.22061994 41 .029771218 Root MSE = .14241
------------------------------------------------------------------------------
linvpc | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
t | .0081459 .0018129 4.49 0.000 .0044819 .0118098
_cons | -.8412918 .044744 -18.80 0.000 -.9317228 -.7508608
------------------------------------------------------------------------------
predict linvpch, res
reg linvpch lprice t
Source | SS df MS Number of obs = 42
-------------+------------------------------ F( 2, 39) = 0.16
Model | .006498121 2 .003249061 Prob > F = 0.8548
Residual | .804674806 39 .020632687 R-squared = 0.0080
-------------+------------------------------ Adj R-squared = -0.0429
Total | .811172927 41 .019784706 Root MSE = .14364
------------------------------------------------------------------------------
linvpch | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
lprice | -.3809609 .6788352 -0.56 0.578 -1.754035 .992113
t | .0016828 .0035122 0.48 0.635 -.0054213 .0087869
_cons | -.0717677 .1356134 -0.53 0.600 -.3460716 .2025362
------------------------------------------------------------------------------
reg linvpc lprice t
Source | SS df MS Number of obs = 42
-------------+------------------------------ F( 2, 39) = 10.08
Model | .415945135 2 .207972568 Prob > F = 0.0003
Residual | .804674809 39 .020632687 R-squared = 0.3408
-------------+------------------------------ Adj R-squared = 0.3070
Total | 1.22061994 41 .029771218 Root MSE = .14364
------------------------------------------------------------------------------
linvpc | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
lprice | -.3809609 .6788352 -0.56 0.578 -1.754035 .992113
t | .0098287 .0035122 2.80 0.008 .0027246 .0169328
_cons | -.9130595 .1356134 -6.73 0.000 -1.187363 -.6387556
------------------------------------------------------------------------------
Example 10.11: Effects of Antidumping Filings
use http://fmwww.bc.edu/ec-p/data/wooldridge/barium
reg lchnimp lchempi lgas lrtwex befile6 affile6 afdec6 feb mar apr may jun jul aug sep oct nov dec
Source | SS df MS Number of obs = 131
-------------+------------------------------ F( 17, 113) = 3.71
Model | 22.8083791 17 1.34166936 Prob > F = 0.0000
Residual | 40.8438726 113 .3614502 R-squared = 0.3583
-------------+------------------------------ Adj R-squared = 0.2618
Total | 63.6522517 130 .489632706 Root MSE = .60121
------------------------------------------------------------------------------
lchnimp | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
lchempi | 3.265067 .4929297 6.62 0.000 2.288485 4.24165
lgas | -1.278206 1.389015 -0.92 0.359 -4.030094 1.473683
lrtwex | .6630341 .471303 1.41 0.162 -.2707021 1.59677
befile6 | .1397036 .2668075 0.52 0.602 -.38889 .6682973
affile6 | .0126343 .2786866 0.05 0.964 -.5394941 .5647627
afdec6 | -.5213008 .3019498 -1.73 0.087 -1.119518 .0769161
feb | -.417716 .3044432 -1.37 0.173 -1.020873 .1854408
mar | .0590529 .2647304 0.22 0.824 -.4654258 .5835316
apr | -.4514835 .2683861 -1.68 0.095 -.9832049 .0802378
may | .0333114 .2692426 0.12 0.902 -.5001067 .5667294
jun | -.2063286 .2692517 -0.77 0.445 -.7397648 .3271076
jul | .0038404 .2787666 0.01 0.989 -.5484466 .5561273
aug | -.157059 .2779935 -0.56 0.573 -.7078142 .3936962
sep | -.1341598 .2676556 -0.50 0.617 -.6644338 .3961142
oct | .051691 .2668511 0.19 0.847 -.4769892 .5803712
nov | -.246259 .2628271 -0.94 0.351 -.7669669 .2744489
dec | .1328415 .2714237 0.49 0.625 -.4048978 .6705809
_cons | 16.78074 32.4288 0.52 0.606 -47.46656 81.02804
------------------------------------------------------------------------------
test feb mar apr may jun jul aug sep oct nov dec
( 1) feb = 0.0
( 2) mar = 0.0
( 3) apr = 0.0
( 4) may = 0.0
( 5) jun = 0.0
( 6) jul = 0.0
( 7) aug = 0.0
( 8) sep = 0.0
( 9) oct = 0.0
(10) nov = 0.0
(11) dec = 0.0
F( 11, 113) = 0.86
Prob > F = 0.5852
This page prepared by Oleksandr Talavera (revised 8 Nov 2002)
Send your questions/comments/suggestions to Kit Baum
at baum@bc.edu
These pages are maintained by the Faculty Micro
Resource Center's GSA Program,
a unit of Boston College Academic Technology Services