### Stata Textbook Examples Econometric Analysis of Cross Section and Panel Data by Jeffrey M. Wooldridge Chapter 5: Instrumental Variables Estimation of Single-Equation Linear Models

The data files used for the examples in this text can be downloaded in a zip file from the Stata Web site. You can then use a program such as zip to unzip the data files.
Example 5.3 on page 96 using mroz.dta.
use mroz, clear

reg educ exper expersq motheduc fatheduc huseduc if lwage ~=.

Source |       SS       df       MS              Number of obs =     428
-------------+------------------------------           F(  5,   422) =   63.30
Model |  955.830608     5  191.166122           Prob > F      =  0.0000
Residual |  1274.36565   422  3.01982382           R-squared     =  0.4286
Total |  2230.19626   427  5.22294206           Root MSE      =  1.7378

------------------------------------------------------------------------------
educ |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
exper |   .0374977   .0343102     1.09   0.275    -.0299424    .1049379
expersq |  -.0006002   .0010261    -0.58   0.559    -.0026171    .0014167
motheduc |   .1141532   .0307835     3.71   0.000     .0536452    .1746613
fatheduc |   .1060801   .0295153     3.59   0.000     .0480648    .1640955
huseduc |   .3752548   .0296347    12.66   0.000     .3170049    .4335048
_cons |   5.538311   .4597824    12.05   0.000     4.634562     6.44206
------------------------------------------------------------------------------

test motheduc fatheduc huseduc

( 1)  motheduc = 0
( 2)  fatheduc = 0
( 3)  huseduc = 0

F(  3,   422) =  104.29
Prob > F =    0.0000

ivreg lwage exper expersq (educ=fatheduc huseduc motheduc )

Instrumental variables (2SLS) regression

Source |       SS       df       MS              Number of obs =     428
-------------+------------------------------           F(  3,   424) =   11.52
Model |  33.3927368     3  11.1309123           Prob > F      =  0.0000
Residual |  189.934704   424  .447959208           R-squared     =  0.1495
Total |  223.327441   427  .523015084           Root MSE      =   .6693

------------------------------------------------------------------------------
lwage |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
educ |   .0803918    .021774     3.69   0.000     .0375934    .1231901
exper |   .0430973   .0132649     3.25   0.001     .0170242    .0691704
expersq |  -.0008628   .0003962    -2.18   0.030    -.0016415   -.0000841
_cons |  -.1868572   .2853959    -0.65   0.513    -.7478241    .3741097
------------------------------------------------------------------------------
Instrumented:  educ
Instruments:   exper expersq fatheduc huseduc motheduc
------------------------------------------------------------------------------

reg lwage exper expersq educ

Source |       SS       df       MS              Number of obs =     428
-------------+------------------------------           F(  3,   424) =   26.29
Model |  35.0222967     3  11.6740989           Prob > F      =  0.0000
Residual |  188.305144   424  .444115906           R-squared     =  0.1568
Total |  223.327441   427  .523015084           Root MSE      =  .66642

------------------------------------------------------------------------------
lwage |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
exper |   .0415665   .0131752     3.15   0.002     .0156697    .0674633
expersq |  -.0008112   .0003932    -2.06   0.040    -.0015841   -.0000382
educ |   .1074896   .0141465     7.60   0.000     .0796837    .1352956
_cons |  -.5220406   .1986321    -2.63   0.009    -.9124667   -.1316144
------------------------------------------------------------------------------
Example 5.4 on page 99.
ivreg lwage exper expersq kidslt6 kidsge6 (educ=fatheduc huseduc motheduc kidslt6 kidsge6)

Instrumental variables (2SLS) regression

Source |       SS       df       MS              Number of obs =     428
-------------+------------------------------           F(  5,   422) =    7.08
Model |  33.6045837     5  6.72091675           Prob > F      =  0.0000
Residual |  189.722857   422   .44958023           R-squared     =  0.1505
Total |  223.327441   427  .523015084           Root MSE      =  .67051

------------------------------------------------------------------------------
lwage |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
educ |   .0798678   .0223575     3.57   0.000      .035922    .1238136
exper |   .0414939   .0134453     3.09   0.002     .0150658    .0679221
expersq |  -.0008576   .0003972    -2.16   0.031    -.0016384   -.0000768
kidslt6 |  -.0313332   .0861049    -0.36   0.716    -.2005811    .1379146
kidsge6 |  -.0182224   .0271427    -0.67   0.502    -.0715741    .0351292
_cons |  -.1315325   .3038534    -0.43   0.665    -.7287871    .4657222
------------------------------------------------------------------------------
Instrumented:  educ
Instruments:   exper expersq kidslt6 kidsge6 fatheduc huseduc motheduc
------------------------------------------------------------------------------

test kidslt6 kidsge6

( 1)  kidslt6 = 0
( 2)  kidsge6 = 0

F(  2,   422) =    0.31
Prob > F =    0.7368
Example 5.5 on page 106 using nls80.dta.
use nls80, clear

ivreg lwage  exper tenure married south urban black educ (iq = kww )

Instrumental variables (2SLS) regression

Source |       SS       df       MS              Number of obs =     935
-------------+------------------------------           F(  8,   926) =   36.96
Model |  31.4665121     8  3.93331401           Prob > F      =  0.0000
Residual |  134.189771   926   .14491336           R-squared     =  0.1900
Total |  165.656283   934  .177362188           Root MSE      =  .38067

------------------------------------------------------------------------------
lwage |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
iq |   .0130473   .0049341     2.64   0.008     .0033641    .0227305
exper |     .01442   .0033208     4.34   0.000     .0079029    .0209371
tenure |   .0104562   .0026012     4.02   0.000     .0053512    .0155612
married |   .2006903   .0406775     4.93   0.000     .1208595    .2805211
south |  -.0515532   .0311279    -1.66   0.098    -.1126426    .0095361
urban |   .1767058   .0282117     6.26   0.000     .1213394    .2320722
black |  -.0225612   .0739597    -0.31   0.760    -.1677093    .1225869
educ |   .0250321   .0166068     1.51   0.132    -.0075591    .0576234
_cons |   4.592453   .3257807    14.10   0.000     3.953099    5.231807
------------------------------------------------------------------------------
Instrumented:  iq
Instruments:   exper tenure married south urban black educ kww
------------------------------------------------------------------------------

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