question about F statistics

[Raymond Zhang]

Hello everyone, I would like to ask a question about the PowerPoint slides for Chapter 8 of Wooldridge's Introductory Econometrics. In the slide, using the dataset WAGE1, the calculated F-statistic is 17.95, but the one I calculated is 42.7?

Here is my code:

. use WAGE1, clear
.
. reg lwage educ exper expersq
Source | SS df MS Number of obs = 526
-------------+---------------------------------- F(3, 522) = 74.67
Model | 44.5393713 3 14.8464571 Prob > F = 0.0000
Residual | 103.79038 522 .198832146 R-squared = 0.3003
-------------+---------------------------------- Adj R-squared = 0.2963
Total | 148.329751 525 .28253286 Root MSE = .44591
------------------------------------------------------------------------------
lwage | Coefficient Std. err. t P>|t| [95% conf. interval]
-------------+----------------------------------------------------------------
educ | 0.0904 0.0075 12.10 0.000 0.0757 0.1050
exper | 0.0410 0.0052 7.89 0.000 0.0308 0.0512
expersq | -0.0007 0.0001 -6.16 0.000 -0.0009 -0.0005
_cons | 0.1280 0.1059 1.21 0.227 -0.0801 0.3361
------------------------------------------------------------------------------
. test exper expersq
( 1) exper = 0
( 2) expersq = 0
F( 2, 522) = 42.70
Prob > F = 0.0000


Best wishes!

Raymond

[Andrew Musau]

Probably, whoever wrote those slides is mixing up the two Wooldridge wage datasets—wage1 and wage2. The sign of the intercept coefficient is also incorrect.

use "http://fmwww.bc.edu/ec-p/data/wooldridge//wage1", clear
reg lwage educ c.exper##c.exper
testparm c.exper##c.exper

use "http://fmwww.bc.edu/ec-p/data/wooldridge//wage2", clear
reg lwage educ c.exper##c.exper
testparm c.exper##c.exper

Res.:

. use "http://fmwww.bc.edu/ec-p/data/wooldridge//wage1", clear

. 
. reg lwage educ c.exper##c.exper

      Source |       SS           df       MS      Number of obs   =       526
-------------+----------------------------------   F(3, 522)       =     74.67
       Model |  44.5393702         3  14.8464567   Prob > F        =    0.0000
    Residual |  103.790392       522  .198832168   R-squared       =    0.3003
-------------+----------------------------------   Adj R-squared   =    0.2963
       Total |  148.329762       525   .28253288   Root MSE        =    .44591

---------------------------------------------------------------------------------
          lwage | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
           educ |   .0903658    .007468    12.10   0.000     .0756948    .1050368
          exper |   .0410089   .0051965     7.89   0.000     .0308002    .0512175
                |
c.exper#c.exper |  -.0007136   .0001158    -6.16   0.000     -.000941   -.0004861
                |
          _cons |   .1279975   .1059323     1.21   0.227    -.0801085    .3361034
---------------------------------------------------------------------------------

. 
. testparm c.exper##c.exper

 ( 1)  exper = 0
 ( 2)  c.exper#c.exper = 0

       F(  2,   522) =   42.70
            Prob > F =    0.0000

. 
. 
. 
. use "http://fmwww.bc.edu/ec-p/data/wooldridge//wage2", clear

. 
. reg lwage educ c.exper##c.exper

      Source |       SS           df       MS      Number of obs   =       935
-------------+----------------------------------   F(3, 931)       =     46.75
       Model |  21.6887824         3  7.22959414   Prob > F        =    0.0000
    Residual |  143.967512       931  .154637499   R-squared       =    0.1309
-------------+----------------------------------   Adj R-squared   =    0.1281
       Total |  165.656294       934  .177362199   Root MSE        =    .39324

---------------------------------------------------------------------------------
          lwage | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
----------------+----------------------------------------------------------------
           educ |   .0779866   .0066242    11.77   0.000     .0649864    .0909867
          exper |    .016256     .01354     1.20   0.230    -.0103164    .0428285
                |
c.exper#c.exper |    .000152    .000567     0.27   0.789    -.0009607    .0012647
                |
          _cons |   5.517432   .1248186    44.20   0.000     5.272474    5.762391
---------------------------------------------------------------------------------

. 
. testparm c.exper##c.exper

 ( 1)  exper = 0
 ( 2)  c.exper#c.exper = 0

       F(  2,   931) =   17.95
            Prob > F =    0.0000