## Chapter 17 - Corner Solution Responses

### Examples

```------------------------------------------------------------------------------------------
name:  SN
log:  \iiexample17.smcl
log type:  smcl
closed on:  11 May 2020, 19:26:46
. **********************************************
. * Solomon Negash - Examples
. * Wooldridge (2010). Economic Analysis of Cross-Section and Panel Data. 2nd ed.
. * STATA Program, version 16.1.

. * Chapter 17 - Corner Solution Responses
. *********************************************

. // Example 17.2 (Annual Hours Equation for Married Women)

. bcuse mroz, clear nodesc

. eststo Linear_OLS:  qui reg hours nwifeinc educ exper* age kidslt6 kidsge6

. eststo Tobit_MLE: qui tobit hours nwifeinc educ exper* age kidslt6 kidsge6, ll(0)

. estout Linear_OLS Tobit_MLE, cells(b(nostar fmt(2)) se(par fmt(2))) ///
stats(N, fmt(%9.0g) labels(Observations)) varlabels(_cons constant) ///
varwidth(10) ti("Table 17.1 OLS and Tobit Estimation of Annual Hours Worked: (hours)")

Table 17.1 OLS and Tobit Estimation of Annual Hours Worked: (hours)
------------------------------------
Linear_OLS    Tobit_MLE
b/se         b/se
------------------------------------
main
nwifeinc          -3.45        -8.81
(2.54)       (4.46)
educ              28.76        80.65
(12.95)      (21.58)
exper             65.67       131.56
(9.96)      (17.28)
expersq           -0.70        -1.86
(0.32)       (0.54)
age              -30.51       -54.40
(4.36)       (7.42)
kidslt6         -442.09      -894.02
(58.85)     (111.88)
kidsge6          -32.78       -16.22
(23.18)      (38.64)
constant        1330.48       965.31
(270.78)     (446.44)
------------------------------------
/
var..hou~)                1258926.81
(93304.48)
------------------------------------
Observat~s          753          753
------------------------------------

. * APE
. margins, dydx( nwifeinc educ exper* age kidslt6 kidsge6) post pred(ystar(0,.))

Average marginal effects                        Number of obs     =        753
Model VCE    : OIM

Expression   : E(hours*|hours>0), predict(ystar(0,.))
dy/dx w.r.t. : nwifeinc educ exper expersq age kidslt6 kidsge6

------------------------------------------------------------------------------
|            Delta-method
|      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
nwifeinc |  -5.188618   2.621409    -1.98   0.048    -10.32649   -.0507514
educ |   47.47306    12.6214     3.76   0.000     22.73558    72.21054
exper |   77.44703    9.99765     7.75   0.000     57.85199    97.04206
expersq |   -1.09736   .3155945    -3.48   0.001    -1.715914   -.4788063
age |  -32.02622    4.29211    -7.46   0.000     -40.4386   -23.61384
kidslt6 |  -526.2776   64.70619    -8.13   0.000    -653.0994   -399.4558
kidsge6 |  -9.546987   22.75224    -0.42   0.675    -54.14056    35.04659
------------------------------------------------------------------------------

. di "Scale factor = " 5.19/8.81
Scale factor = .58910329

. di "Scale factor = " 47.47/80.65
Scale factor = .58859268

. est clear

. // Example 17.3 (Testing Exogeneity of Other Income in the Hours Equation)

. reg nwifeinc huseduc educ exper expersq age kidslt6 kidsge6

Source |       SS           df       MS      Number of obs   =       753
-------------+----------------------------------   F(7, 745)       =     27.13
Model |  20676.7702         7  2953.82432   Prob > F        =    0.0000
Residual |  81120.3455       745   108.88637   R-squared       =    0.2031
Total |  101797.116       752  135.368505   Root MSE        =    10.435

------------------------------------------------------------------------------
nwifeinc |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
huseduc |   1.178155   .1609449     7.32   0.000     .8621956    1.494115
educ |   .6746951   .2136829     3.16   0.002     .2552029    1.094187
exper |  -.3129878   .1382549    -2.26   0.024    -.5844034   -.0415721
expersq |  -.0004776   .0045196    -0.11   0.916    -.0093501     .008395
age |   .3401521   .0597084     5.70   0.000     .2229354    .4573687
kidslt6 |   .8262718   .8183785     1.01   0.313    -.7803306    2.432874
kidsge6 |   .4355289   .3219888     1.35   0.177    -.1965845    1.067642
_cons |  -14.72048   3.787326    -3.89   0.000    -22.15559   -7.285382
------------------------------------------------------------------------------

. predict v2, r

. tobit hours nwifeinc educ exper expersq age kidslt6 kidsge6 v2, ll(0) nolog

Tobit regression                                Number of obs     =        753
Uncensored     =        428
Limits: lower = 0                                  Left-censored  =        325
upper = +inf                               Right-censored =          0

LR chi2(8)        =     273.76
Prob > chi2       =     0.0000
Log likelihood = -3818.0118                     Pseudo R2         =     0.0346

------------------------------------------------------------------------------
hours |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
nwifeinc |  -31.48209   16.03758    -1.96   0.050    -62.96631    .0021284
educ |   116.7811   32.75973     3.56   0.000     52.46875    181.0935
exper |   124.3485   17.87499     6.96   0.000     89.25717    159.4399
expersq |  -1.897196   .5371606    -3.53   0.000    -2.951725   -.8426674
age |  -46.89236   8.957658    -5.23   0.000    -64.47762    -29.3071
kidslt6 |  -867.9116   112.9022    -7.69   0.000    -1089.556   -646.2673
kidsge6 |  -6.326127   39.16555    -0.16   0.872    -83.21411    70.56186
v2 |   24.41828    16.5845     1.47   0.141    -8.139631    56.97619
_cons |   722.1052   475.6883     1.52   0.129    -211.7438    1655.954
-------------+----------------------------------------------------------------
var(e.hours)|    1254045   92931.19                       1084256     1450421
------------------------------------------------------------------------------

. // Example 17.4 (Annual Hours Equation for Married Women)

. eststo TrancNormual: churdle linear hours nwifeinc educ exper expersq age kidslt6 kidsge6, ///
select(nwifeinc educ exper expersq age kidslt6 kidsge6) ll(0) nolog

Cragg hurdle regression                         Number of obs     =        753
LR chi2(7)        =          .
Log likelihood = -3791.9498                     Prob > chi2       =          .

------------------------------------------------------------------------------
hours |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
hours        |
nwifeinc |     .15344   5.164277     0.03   0.976    -9.968357    10.27524
educ |  -29.85253   22.83934    -1.31   0.191    -74.61682    14.91175
exper |   72.62271   21.23627     3.42   0.001     31.00039     114.245
expersq |  -.9439964   .6090281    -1.55   0.121     -2.13767    .2496767
age |   -27.4438   8.293455    -3.31   0.001    -43.69867   -11.18893
kidslt6 |  -484.7107    153.788    -3.15   0.002    -786.1297   -183.2918
kidsge6 |  -102.6574   43.54345    -2.36   0.018     -188.001    -17.3138
_cons |   2123.516   483.2647     4.39   0.000     1176.334    3070.697
-------------+----------------------------------------------------------------
selection_ll |
nwifeinc |  -.0120237   .0048398    -2.48   0.013    -.0215096   -.0025378
educ |   .1309047   .0252542     5.18   0.000     .0814074     .180402
exper |   .1233476   .0187164     6.59   0.000     .0866641    .1600311
expersq |  -.0018871      .0006    -3.15   0.002     -.003063   -.0007111
age |  -.0528527   .0084772    -6.23   0.000    -.0694678   -.0362376
kidslt6 |  -.8683285   .1185223    -7.33   0.000    -1.100628    -.636029
kidsge6 |    .036005   .0434768     0.83   0.408     -.049208    .1212179
_cons |   .2700768    .508593     0.53   0.595    -.7267472    1.266901
-------------+----------------------------------------------------------------
lnsigma      |
_cons |   6.746137   .0514841   131.03   0.000      6.64523    6.847044
-------------+----------------------------------------------------------------
/sigma |   850.7657   43.80092                      769.1068    941.0948
------------------------------------------------------------------------------

. * Note: The coefficient and SE of age in the participation equation are not the same as in the textbook
. eststo LogNormual: churdle exp hours nwifeinc educ exper expersq age kidslt6 kidsge6,///
select(nwifeinc educ exper expersq age kidslt6 kidsge6) ll(0) nolog

Cragg hurdle regression                         Number of obs     =        753
LR chi2(7)        =     304.60
Prob > chi2       =     0.0000
Log likelihood = -3501.6219                     Pseudo R2         =     0.0417

------------------------------------------------------------------------------
hours |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
hours        |
nwifeinc |  -.0019676   .0044019    -0.45   0.655    -.0105951    .0066599
educ |  -.0385626     .02002    -1.93   0.054    -.0778011     .000676
exper |    .073237   .0177323     4.13   0.000     .0384822    .1079917
expersq |   -.001233   .0005328    -2.31   0.021    -.0022773   -.0001888
age |  -.0236706   .0071799    -3.30   0.001     -.037743   -.0095981
kidslt6 |   -.585202   .1174929    -4.98   0.000    -.8154839   -.3549201
kidsge6 |  -.0694175    .036985    -1.88   0.061    -.1419067    .0030717
_cons |   7.896267   .4220781    18.71   0.000     7.069009    8.723525
-------------+----------------------------------------------------------------
selection_ll |
nwifeinc |  -.0120237   .0048398    -2.48   0.013    -.0215096   -.0025378
educ |   .1309047   .0252542     5.18   0.000     .0814074     .180402
exper |   .1233476   .0187164     6.59   0.000     .0866641    .1600311
expersq |  -.0018871      .0006    -3.15   0.002     -.003063   -.0007111
age |  -.0528527   .0084772    -6.23   0.000    -.0694678   -.0362376
kidslt6 |  -.8683285   .1185223    -7.33   0.000    -1.100628    -.636029
kidsge6 |    .036005   .0434768     0.83   0.408     -.049208    .1212179
_cons |   .2700768    .508593     0.53   0.595    -.7267472    1.266901
-------------+----------------------------------------------------------------
lnsigma      |
_cons |  -.1232225   .0341793    -3.61   0.000    -.1902127   -.0562323
-------------+----------------------------------------------------------------
/sigma |    .884067   .0302168                      .8267833    .9453195
------------------------------------------------------------------------------

. g lhours=ln(hours)
(325 missing values generated)

. eststo ET2T: heckman lhours nwifeinc educ exper expersq age kidslt6 kidsge6, ///
select(inlf = nwifeinc educ exper expersq age kidslt6 kidsge6) nolog

Heckman selection model                         Number of obs     =        753
(regression model with sample selection)              Selected    =        428
Nonselected =        325

Wald chi2(7)      =      35.50
Log likelihood = -938.8208                      Prob > chi2       =     0.0000

------------------------------------------------------------------------------
|      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
lhours       |
nwifeinc |   .0066597   .0050147     1.33   0.184    -.0031689    .0164882
educ |  -.1193085   .0242235    -4.93   0.000    -.1667858   -.0718313
exper |  -.0334099   .0204429    -1.63   0.102    -.0734773    .0066574
expersq |   .0006032   .0006178     0.98   0.329    -.0006077    .0018141
age |   .0142754   .0084906     1.68   0.093    -.0023659    .0309167
kidslt6 |   .2080079   .1338148     1.55   0.120    -.0542643    .4702801
kidsge6 |  -.0920299   .0433138    -2.12   0.034    -.1769235   -.0071364
_cons |   8.670736    .498793    17.38   0.000      7.69312    9.648352
-------------+----------------------------------------------------------------
inlf         |
nwifeinc |  -.0096823   .0043273    -2.24   0.025    -.0181637    -.001201
educ |    .119528   .0217542     5.49   0.000     .0768906    .1621654
exper |   .0826696   .0170277     4.86   0.000      .049296    .1160433
expersq |  -.0012896   .0005369    -2.40   0.016     -.002342   -.0002372
age |  -.0330806   .0075921    -4.36   0.000    -.0479609   -.0182003
kidslt6 |  -.5040406   .1074788    -4.69   0.000    -.7146951    -.293386
kidsge6 |   .0698201   .0387332     1.80   0.071    -.0060956    .1457357
_cons |  -.3656166   .4476569    -0.82   0.414    -1.243008    .5117748
-------------+----------------------------------------------------------------
/athrho |  -2.131542    .174212   -12.24   0.000    -2.472991   -1.790093
/lnsigma |   .1895611   .0419657     4.52   0.000     .1073099    .2718123
-------------+----------------------------------------------------------------
rho |  -.9722333   .0095403                     -.9858766   -.9457704
sigma |   1.208719   .0507247                      1.113279    1.312341
lambda |  -1.175157   .0560391                     -1.284991   -1.065322
------------------------------------------------------------------------------
LR test of indep. eqns. (rho = 0):   chi2(1) =    34.10   Prob > chi2 = 0.0000

. * esttab TrancNormual LogNormual ET2T, nostar cells(b(nostar fmt(4)) se(par fmt(4))) ///
stats(N, fmt(%9.0g) labels(Observations))
. est clear

. *Alternativelly,
. eststo Participation: probit inlf nwifeinc educ exper expersq age kidslt6 kidsge6, nolog

Probit regression                               Number of obs     =        753
LR chi2(7)        =     227.14
Prob > chi2       =     0.0000
Log likelihood = -401.30219                     Pseudo R2         =     0.2206

------------------------------------------------------------------------------
inlf |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
nwifeinc |  -.0120237   .0048398    -2.48   0.013    -.0215096   -.0025378
educ |   .1309047   .0252542     5.18   0.000     .0814074     .180402
exper |   .1233476   .0187164     6.59   0.000     .0866641    .1600311
expersq |  -.0018871      .0006    -3.15   0.002     -.003063   -.0007111
age |  -.0528527   .0084772    -6.23   0.000    -.0694678   -.0362376
kidslt6 |  -.8683285   .1185223    -7.33   0.000    -1.100628    -.636029
kidsge6 |    .036005   .0434768     0.83   0.408     -.049208    .1212179
_cons |   .2700768    .508593     0.53   0.595    -.7267472    1.266901
------------------------------------------------------------------------------

. eststo NormalHurdle: truncreg hours nwifeinc educ exper expersq age kidslt6 kidsge6, ll(0) nolog
(note: 325 obs. truncated)

Truncated regression
Limit:   lower =          0                     Number of obs     =        428
upper =       +inf                     Wald chi2(7)      =      59.05
Log likelihood = -3390.6476                     Prob > chi2       =     0.0000

------------------------------------------------------------------------------
hours |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
nwifeinc |     .15344   5.164279     0.03   0.976    -9.968361    10.27524
educ |  -29.85254   22.83935    -1.31   0.191    -74.61684    14.91176
exper |   72.62273   21.23628     3.42   0.001     31.00039    114.2451
expersq |  -.9439967   .6090283    -1.55   0.121     -2.13767    .2496769
age |  -27.44381   8.293458    -3.31   0.001    -43.69869   -11.18893
kidslt6 |  -484.7109   153.7881    -3.15   0.002      -786.13   -183.2918
kidsge6 |  -102.6574   43.54347    -2.36   0.018    -188.0011   -17.31379
_cons |   2123.516   483.2649     4.39   0.000     1176.334    3070.697
-------------+----------------------------------------------------------------
/sigma |    850.766   43.80097    19.42   0.000     764.9177    936.6143
------------------------------------------------------------------------------

. eststo Lognormal: truncreg lhours nwifeinc educ exper expersq age kidslt6 kidsge6, ll(0) nolog
(note: 0 obs. truncated)

Truncated regression
Limit:   lower =          0                     Number of obs     =        428
upper =       +inf                     Wald chi2(7)      =      84.91
Log likelihood = -554.56647                     Prob > chi2       =     0.0000

------------------------------------------------------------------------------
lhours |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
nwifeinc |  -.0019676   .0044019    -0.45   0.655    -.0105951    .0066599
educ |  -.0385626     .02002    -1.93   0.054    -.0778011     .000676
exper |    .073237   .0177323     4.13   0.000     .0384822    .1079917
expersq |   -.001233   .0005328    -2.31   0.021    -.0022773   -.0001888
age |  -.0236706   .0071799    -3.30   0.001     -.037743   -.0095981
kidslt6 |   -.585202   .1174929    -4.98   0.000    -.8154839   -.3549201
kidsge6 |  -.0694175   .0369849    -1.88   0.061    -.1419067    .0030717
_cons |   7.896267    .422078    18.71   0.000      7.06901    8.723525
-------------+----------------------------------------------------------------
/sigma |   .8840669   .0302168    29.26   0.000     .8248431    .9432907
------------------------------------------------------------------------------

. est clear

. *Loglikelihood for selection model
. qui heckman lhours nwifeinc educ exper expersq age kidslt6 kidsge6, ///
select(inlf = nwifeinc educ exper expersq age kidslt6 kidsge6)

. qui sum lhours

. di "Loglikelihood for selection model = " e(ll) - r(mean)*r(N)
Loglikelihood for selection model = -3877.8798

. // Example 17.5 (Panel Data Estimation of Annual Hours Equation for Women)

. u "Wooldridge_2E\psid80_92", clear

. eststo Linear_FE: xtreg hours nwifeinc ch0_2 ch3_5 ch6_17 marr y81-y92, fe cluster(id)

Fixed-effects (within) regression               Number of obs     =     11,674
Group variable: id                              Number of groups  =        898

R-sq:                                           Obs per group:
within  = 0.0719                                         min =         13
between = 0.0936                                         avg =       13.0
overall = 0.0855                                         max =         13

F(17,897)         =      15.72
corr(u_i, Xb)  = -0.0945                        Prob > F          =     0.0000

(Std. Err. adjusted for 898 clusters in id)
------------------------------------------------------------------------------
|               Robust
hours |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
nwifeinc |  -.7752375   .3429502    -2.26   0.024    -1.448316   -.1021593
ch0_2 |  -342.3774   26.64763   -12.85   0.000    -394.6763   -290.0784
ch3_5 |  -254.1283   25.87788    -9.82   0.000    -304.9165     -203.34
ch6_17 |  -42.95787   14.88673    -2.89   0.004    -72.17475   -13.74099
marr |  -634.8048   286.1714    -2.22   0.027    -1196.448    -73.1613
y81 |  -4.819715   16.29731    -0.30   0.767    -36.80502    27.16559
y82 |  -14.88765    21.1851    -0.70   0.482     -56.4658    26.69049
y83 |   6.612531   22.49192     0.29   0.769    -37.53039    50.75545
y84 |   93.79139   25.58646     3.67   0.000      43.5751    144.0077
y85 |   88.73714   25.97019     3.42   0.001     37.76773    139.7065
y86 |   82.66214   27.36886     3.02   0.003     28.94769    136.3766
y87 |   64.28464   27.83649     2.31   0.021     9.652411    118.9169
y88 |   63.79163   29.35211     2.17   0.030     6.184826    121.3984
y89 |   72.98518   30.60838     2.38   0.017     12.91279    133.0576
y90 |   71.24956   31.55331     2.26   0.024     9.322657    133.1765
y91 |   64.67996   32.47097     1.99   0.047     .9520418    128.4079
y92 |   16.01242   33.21255     0.48   0.630    -49.17093    81.19577
_cons |    1786.02    247.297     7.22   0.000     1300.672    2271.368
-------------+----------------------------------------------------------------
sigma_u |  701.66249
sigma_e |  503.92334
rho |  .65972225   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. eststo RE_Tobit: xttobit hours nwifeinc ch0_2 ch3_5 ch6_17 marr y81-y92, ll(0) nolog

Random-effects tobit regression                 Number of obs     =     11,674
Uncensored     =      8,603
Limits: lower = 0                                  Left-censored  =      3,071
upper = +inf                               Right-censored =          0

Group variable: id                              Number of groups  =        898
Random effects u_i ~ Gaussian                   Obs per group:
min =         13
avg =       13.0
max =         13

Integration method: mvaghermite                 Integration pts.  =         12

Wald chi2(17)     =     885.58
Log likelihood  = -70627.367                    Prob > chi2       =     0.0000

------------------------------------------------------------------------------
hours |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
nwifeinc |  -2.020204    .358168    -5.64   0.000    -2.722201   -1.318208
ch0_2 |   -460.143    22.4262   -20.52   0.000    -504.0976   -416.1885
ch3_5 |  -317.5957   18.94243   -16.77   0.000    -354.7222   -280.4693
ch6_17 |   -38.5854   10.41067    -3.71   0.000    -58.98994   -18.18086
marr |  -582.5296   83.87442    -6.95   0.000    -746.9205   -418.1388
y81 |  -7.102501   31.22654    -0.23   0.820    -68.30539    54.10039
y82 |  -39.05952   31.39574    -1.24   0.213     -100.594      22.475
y83 |  -9.278637   31.37639    -0.30   0.767    -70.77523    52.21796
y84 |   102.6913    31.3145     3.28   0.001     41.31597    164.0666
y85 |   93.12736    31.4329     2.96   0.003     31.52001    154.7347
y86 |     87.314   31.46283     2.78   0.006       25.648      148.98
y87 |   54.31604   31.65836     1.72   0.086    -7.733207    116.3653
y88 |   60.95545   31.75747     1.92   0.055    -1.288037    123.1989
y89 |   77.71861   31.87821     2.44   0.015     15.23847    140.1988
y90 |   81.53764   31.98205     2.55   0.011     18.85397    144.2213
y91 |   76.12617    32.0872     2.37   0.018     13.23642    139.0159
y92 |   16.92712   32.40571     0.52   0.601     -46.5869    80.44115
_cons |   1607.144   81.81007    19.64   0.000     1446.799    1767.489
-------------+----------------------------------------------------------------
/sigma_u |   989.6984   26.72487    37.03   0.000     937.3186    1042.078
/sigma_e |   613.8584   5.010795   122.51   0.000     604.0374    623.6794
-------------+----------------------------------------------------------------
rho |   .7221742   .0111067                      .6999993     .743517
------------------------------------------------------------------------------
LR test of sigma_u=0: chibar2(01) = 9502.84            Prob >= chibar2 = 0.000

. eststo CRE_Tobit: xttobit hours nwifeinc ch0_2 ch3_5 ch6_17 marr y81-y92 nwifeincb-marrb, ///
ll(0) nolog

Random-effects tobit regression                 Number of obs     =     11,674
Uncensored     =      8,603
Limits: lower = 0                                  Left-censored  =      3,071
upper = +inf                               Right-censored =          0

Group variable: id                              Number of groups  =        898
Random effects u_i ~ Gaussian                   Obs per group:
min =         13
avg =       13.0
max =         13

Integration method: mvaghermite                 Integration pts.  =         12

Wald chi2(22)     =     933.00
Log likelihood  = -70605.118                    Prob > chi2       =     0.0000

------------------------------------------------------------------------------
hours |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
nwifeinc |  -1.517148   .3702903    -4.10   0.000    -2.242904   -.7913927
ch0_2 |  -472.0622   22.79046   -20.71   0.000    -516.7307   -427.3938
ch3_5 |  -329.3407   19.29331   -17.07   0.000    -367.1548   -291.5265
ch6_17 |  -46.22098   10.80637    -4.28   0.000    -67.40107    -25.0409
marr |   -781.187   153.2584    -5.10   0.000    -1081.568   -480.8061
y81 |  -7.528957   31.22892    -0.24   0.809    -68.73651     53.6786
y82 |  -39.57472   31.40255    -1.26   0.208    -101.1226    21.97315
y83 |  -10.55739   31.39327    -0.34   0.737    -72.08707     50.9723
y84 |   99.67446   31.32943     3.18   0.001     38.26991     161.079
y85 |   88.90949   31.45297     2.83   0.005     27.26279    150.5562
y86 |   81.79348   31.47725     2.60   0.009      20.0992    143.4878
y87 |   48.05343   31.68866     1.52   0.129     -14.0552    110.1621
y88 |   53.01979   31.79586     1.67   0.095     -9.29895    115.3385
y89 |    68.3503   31.92985     2.14   0.032     5.768946    130.9317
y90 |   71.17145   32.03871     2.22   0.026     8.376741    133.9662
y91 |   64.75592   32.15299     2.01   0.044     1.737211    127.7746
y92 |   3.632976   32.49817     0.11   0.911    -60.06226    67.32821
nwifeincb |   -6.84578   1.206342    -5.67   0.000    -9.210167   -4.481393
ch0_2b |   122.2966   380.0775     0.32   0.748    -622.6416    867.2349
ch3_5b |   255.7554    367.149     0.70   0.486    -463.8434    975.3543
ch6_17b |   53.03475   56.36095     0.94   0.347    -57.43068    163.5002
marrb |    409.108   188.5929     2.17   0.030     39.47277    778.7432
_cons |    1551.86   94.18517    16.48   0.000     1367.261     1736.46
-------------+----------------------------------------------------------------
/sigma_u |   967.6108   26.05167    37.14   0.000     916.5505    1018.671
/sigma_e |   613.7459   5.008949   122.53   0.000     603.9286    623.5633
-------------+----------------------------------------------------------------
rho |    .713102     .01129                      .6905808    .7348153
------------------------------------------------------------------------------
LR test of sigma_u=0: chibar2(01) = 9416.39            Prob >= chibar2 = 0.000

. esttab Linear_FE RE_Tobit CRE_Tobit, nostar keep(nwifeinc ch0_2 ch3_5 ch6_17 marr _cons) ///
cells(b(nostar fmt(4)) se(par fmt(4))) stats(ll N r2, fmt(%9.0g) ) ///
ti("Table 17.3 Panel Data Models for Annual Women's Labor Supply, 1980-1992")

Table 17.3 Panel Data Models for Annual Women's Labor Supply, 1980-1992
---------------------------------------------------
Linear_FE    RE_Tobit     CRE_Tobit
hours        hours        hours
b/se         b/se         b/se
---------------------------------------------------
main
nwifeinc          -0.7752      -2.0202      -1.5171
(0.3430)     (0.3582)     (0.3703)
ch0_2           -342.3774    -460.1430    -472.0622
(26.6476)    (22.4262)    (22.7905)
ch3_5           -254.1283    -317.5957    -329.3407
(25.8779)    (18.9424)    (19.2933)
ch6_17           -42.9579     -38.5854     -46.2210
(14.8867)    (10.4107)    (10.8064)
marr            -634.8048    -582.5296    -781.1870
(286.1714)    (83.8744)   (153.2584)
_cons           1786.0197    1607.1439    1551.8602
(247.2970)    (81.8101)    (94.1852)
---------------------------------------------------
ll              -88728.84    -70627.37    -70605.12
N                   11674        11674        11674
r2               .0718508
---------------------------------------------------

. log close
name:  SN
log:  iiexample17.smcl
log type:  smcl
closed on:  11 May 2020, 19:27:14
------------------------------------------------------------------------------------------
```