# st: RE: F-stat of excl inst too big in robsut estimation with dummydependent variable (xtivreg2)

 From mparrat@bu.edu To "Rodrigo Alfaro A." Subject st: RE: F-stat of excl inst too big in robsut estimation with dummydependent variable (xtivreg2) Date Tue, 01 Apr 2008 17:35:34 -0400

In the sample employed in the exercise I posted I am allowing for household heads to be working abroad (but still having the household in the home country) so that the instrument made sense for them too (they don?t need to have children since they are the earners themselves). However, in this case the statistics are contradictory or at least confusing. So, should I be worried about the F-stat being that large? How large should the F-stat be for one to worry about it? In most of my first stage estimations I get F-stats between 40 and 80, but then I got this one of 5712, or another one of 584. How big is too big?

Many thanks,

Monica

Quoting "Rodrigo Alfaro A." <ralfaro@bcentral.cl>:

```Monica,

It seems that you have some sort of "local instruments". That means
```
```that
```
```for one group your instruments can "explain" well the instrumented
variable (your R2 of 31%) meanwhile for the other group those
```
```explain
```
```badly the endogenous variable (5%). When you collapse them into one
```
```big
```
```group you end up with 8% (*). I think that you could keep the
```
```analysis
```
```at the subsample level, maybe there are other more relevant
```
```instruments
```
```for each group that lost significance in the collapse analysis.
```
```Think a
```
```labor-example, you could have a educational policy that helps
less-skilled worked (primary education) but has no effect in
college-education.

I hope this helps you.

Rodrigo.

(*) That could be explained by the dispersion generated by the
```
```small R2.
```
```For example, we can think on the collapsed R2 as an harmonic
```
```average of
```
```subsample R2's: 1/R2 = w1*(1/R21) + w2*(1/R22), where R21 and R22
```
```are
```
```the R2's of the subsamples, and w1 and w2 are the weigths based on
```
```the
```
```realtive size of the subsamples. Your first group (young) weights
```
```0.46
```
```(=4959/10799, there are 87 lost cases!), then 1/R2 = 0.46*(1/0.31)
```
```+
```
```0.54*(1/0.05), with that R2 = 0.08.

-----Mensaje original-----
De: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] En nombre de
mparrat@bu.edu
Enviado el: Martes, 01 de Abril de 2008 01:44 a.m.
Para: statalist@hsphsun2.harvard.edu
Asunto: st: F-stat of excl inst too big in robsut estimation with
dummydependent variable (xtivreg2)

Hi,

I need some help understanding why the F-statistic of the excluded
instruments is so big for a subset of my sample.

I am estimating an IV fe model using xtivreg: y x1 x2 t ct (x1=z),
```
```fe
```
```robust fwl(t ct) i(nidhogar) t(year).  My full sample is composed
```
```by
```
```1334 households and 9 years (10886 obs. in total).  The dependent
variable is a dummy taking the value of 1 if the household owns a
business and zero otherwise.  The endogenous variable is an income
variable truncated at zero for all households but taking positive
values for some households in all or some years.   In addition I
```
```am
```
```controlling for time-varying household characteristics, time
```
```dummies and
```
```community-time dummies (there are 8 communities- too few to cluster
```
```on).
```
```I use the fwl option to partial out the time and community-time
```
```dummies.
```
```The instrument is a variable similar to the endogenous variable,
```
```that
```
```is, an income type variable but exogenous. I am confident about my
instrument doing a good job in correcting for endogeneity.  Also,
```
```in
```
```previous versions I had included additional instruments and tested
```
```for
```
```overidentification, endogeneity and redundancy and this one
```
```performed
```
```quite well.

Looking at the results of the full sample, I believe the estimation
```
```is
```
```just fine.  My concern is that when I partition the sample in two
(household heads younger and older than 39 years old) the
```
```F-statistic of
```
```excluded instruments becomes very large for the sample of younger
```
```heads
```
```(5712.73).  However, standard errors in both first stage and main
regression and other statistics seem fine.  What could be
```
```happening?
```
```What am I missing? Are my results still valid? How can I fix this,
```
```if
```
```there is something to fix?

```
```Schaffer) in
```
```which the problem was the F-stat not being reported in a
heteroskedastic-robust estimation with dummy variables.  My
```
```intuition is
```
```that in my case the opposite might be happening, but not sure? I
```
```checked
```
```and my dependent variable takes the value of 1 for 23% of the
observations in the sample of young heads.

The sample size for the two age groups is: 3477 observations (591
```
```hhs)
```
```and 7727 (1031 hhs).

Below I?m copying the results of the estimations using the full
```
```sample
```
```and the restricted samples.  Please let me know if further
```
```information
```
```is needed.

Regards,

Monica

FULL SAMPLE:

.  xtivreg2 dabus_sum
```
```dagro lnpland_manz `agesq' `hhcharact' `ctfe' `te'  ( potincm_fo
```
```=
```
````inst80s_fo'  ) , fe i(nidhogar) r first ffirst rf fwl(`ctfe'
```
````te') ;
```
```Warning - singleton groups detected.  38 observation(s) not used.
Warning - collinearities detected
Vars dropped:  dcomm1_99 dcomm2_98 dcomm3_99 dcomm4_96 dcomm5_94
dcomm7_98
dcomm8_99 dyr9

FIXED EFFECTS ESTIMATION
------------------------
Number of groups =      1334                    Obs
```
```per group: min =
```
```2

```
```                   avg =
```
```8.2

```
```                   max =
```
```9

Reduced-form regression: dabus_sum
----------------------------------

FIXED EFFECTS ESTIMATION
------------------------
Number of groups =      1334                    Obs
```
```per group: min =
```
```2

```
```                   avg =
```
```8.2

```
```                   max =
```
```9

OLS estimation
--------------

Statistics robust to heteroskedasticity

```
```          Number of obs =
```
```10886

```
```          F(  6,  9546) =
```
```11.03

```
```          Prob > F      =
```
```0.0000
Total (centered) SS     =  280.0052317
```
```Centered R2   =
```
```0.0155
Total (uncentered) SS   =  280.0052317
```
```Uncentered R2 =
```
```0.0155
Residual SS             =  275.6691323
```
```  Root MSE      =
```
```.1699

```
```------------------------------------------------------------------------
```
```------
|               Robust
dabus_sum |      Coef.   Std. Err.      t
```
```P>|t|     [95% Conf.
```
```Interval]

```
```-------------+----------------------------------------------------------
```
```-------------+------
dagro |  -.1568444   .0304295    -5.15
```
``` 0.000    -.2164927
```
```-.0971961
lnpland_manz |  -.0091142   .0113462    -0.80   0.422
```
```-.0313552
```
```.0131269
```
``` 0.000     .0156569
```
```.0333311
ageheadsqr |  -.0001439   .0000387    -3.72   0.000
```
```  -.0002198
```
```-.0000681
kids14less |    .003819    .003182     1.20   0.230
```
```  -.0024184
```
```.0100565
potincm80s~o |  -.0143489   .0072045    -1.99   0.046
```
```-.0284713
```
```-.0002265

```
```------------------------------------------------------------------------
```
```------
```
```kids14less
```
```                       potincm80s_fo

```
```------------------------------------------------------------------------
```
```------

First-stage regressions
-----------------------

First-stage regression of potincm_fo:

FIXED EFFECTS ESTIMATION
------------------------
Number of groups =      1334                    Obs
```
```per group: min =
```
```2

```
```                   avg =
```
```8.2

```
```                   max =
```
```9

OLS estimation
--------------

Statistics robust to heteroskedasticity

```
```          Number of obs =
```
```10886

```
```          F(  6,  9546) =
```
```16.47

```
```          Prob > F      =
```
```0.0000
Total (centered) SS     =  10371.54444
```
```Centered R2   =
```
```0.0902
Total (uncentered) SS   =  10371.54444
```
```Uncentered R2 =
```
```0.0902
Residual SS             =  9436.014852
```
```  Root MSE      =
```
```.9942

```
```------------------------------------------------------------------------
```
```------
|               Robust
potincm_fo |      Coef.   Std. Err.      t
```
```P>|t|     [95% Conf.
```
```Interval]

```
```-------------+----------------------------------------------------------
```
```-------------+------
dagro |    .031293   .0752245     0.42
```
``` 0.677    -.1161631
```
```.1787491
lnpland_manz |  -.0771407   .0256491    -3.01   0.003
```
```-.1274185
```
```-.026863
agehead |  -.0498908   .0247468    -2.02   0.044
```
```  -.0983999
```
```-.0013818
ageheadsqr |   .0011953    .000256     4.67   0.000
```
```   .0006935
```
```.0016972
kids14less |  -.0290633   .0182759    -1.59   0.112
```
```  -.0648879
```
```.0067613
potincm80s~o |   .6552578   .1159389     5.65   0.000
```
``` .4279929
```
```.8825227

```
```------------------------------------------------------------------------
```
```------
```
```kids14less
```
```                       potincm80s_fo

```
```------------------------------------------------------------------------
```
```------
Partial R-squared of excluded instruments:   0.0839
Test of excluded instruments:
F(  1,  9546) =    31.94
Prob > F      =   0.0000

Summary results for first-stage regressions
-------------------------------------------

Variable    | Shea Partial R2 |   Partial R2    |  F(  1,
```
```9546)
```
```P-value
potincm_fo  |     0.0839      |     0.0839      |
```
```  31.94
```
```0.0000

NB: first-stage F-stat heteroskedasticity-robust

Underidentification tests
Ho: matrix of reduced form coefficients has rank=K-1
```
```(underidentified)
```
```Ha: matrix has rank=K (identified)

```
```     Chi-sq(1)      P-value
```
```Anderson canon. corr. -N*ln(1-CCEV) LR stat.      837.05
```
```   0.0000
```
```Cragg-Donald N*CDEV statistic
```
``` 874.82         0.0000
```
```Robust chi-square statistic
```
```31.96         0.0000
```
```Weak identification tests
Ho: equation is weakly identified
Cragg-Donald (N-L)*CDEV/L1 F-statistic            874.27
Robust F-statistic
```
``` 31.94
```
```See main output for Cragg-Donald weak id test critical values

NB: Anderson and Cragg-Donald under- and weak identification stats
```
```not
```
```robust
Robust identification stats heteroskedasticity-robust

Weak-instrument-robust inference
Tests of joint significance of endogenous regressors B1 in main
```
```equation
```
```Ho: B1=0 and overidentifying restrictions are valid
Anderson-Rubin test          F(1,9546)=3.97
```
```P-val=0.0464
```
```Anderson-Rubin test          Chi-sq(1)=3.97
```
```P-val=0.0463
```
```Stock-Wright S statistic     Chi-sq(1)=2.98      P-val=0.0845
NB: Test statistics heteroskedasticity-robust

Number of observations N           =      10886
Number of regressors   K           =          6
Number of instruments  L           =          6
Number of excluded instruments L1  =          1

IV (2SLS) estimation
--------------------

Statistics robust to heteroskedasticity

```
```          Number of obs =
```
```10886

```
```          F(  6,  9546) =
```
```11.10

```
```          Prob > F      =
```
```0.0000
Total (centered) SS     =  280.0052317
```
```Centered R2   =
```
```0.0008
Total (uncentered) SS   =  280.0052317
```
```Uncentered R2 =
```
```0.0008
Residual SS             =  279.7700696
```
```  Root MSE      =
```
```.1711

```
```------------------------------------------------------------------------
```
```------
|               Robust
dabus_sum |      Coef.   Std. Err.      z
```
```P>|z|     [95% Conf.
```
```Interval]

```
```-------------+----------------------------------------------------------
```
```-------------+------
potincm_fo |  -.0218981   .0100669    -2.18   0.030
```
```  -.0416289
```
```-.0021673
dagro |  -.1561592   .0302779    -5.16
```
``` 0.000    -.2155027
```
```-.0968156
lnpland_manz |  -.0108034    .010944    -0.99   0.324
```
```-.0322532
```
```.0106464
```
``` 0.000     .0143827
```
```.0324203
ageheadsqr |  -.0001177   .0000403    -2.92   0.003
```
```  -.0001967
```
```-.0000388
kids14less |   .0031826   .0032288     0.99   0.324
```
```  -.0031456
```
```.0095109

```
```------------------------------------------------------------------------
```
```------
Anderson canon. corr. LR statistic (underidentification test):
837.049

```
```       Chi-sq(1) P-val =
```
```0.0000
Test statistic(s) not robust

```
```------------------------------------------------------------------------
```
```------
Cragg-Donald F statistic (weak identification test):
874.270
Stock-Yogo weak ID test critical values: 10% maximal IV size
16.38
15%
```
```maximal IV size
```
```8.96
20%
```
```maximal IV size
```
```6.66
25%
```
```maximal IV size
```
```5.53
Test statistic(s) not robust
Source: Stock-Yogo (2005).  Reproduced by permission.

```
```------------------------------------------------------------------------
```
```------
Hansen J statistic (overidentification test of all instruments):
0.000

```
```     (equation exactly
```
```identified)

```
```------------------------------------------------------------------------
```
```------
Instrumented:         potincm_fo
```
```kids14less
```
```Excluded instruments: potincm80s_fo Partialled-out (FWL): dcomm1_91
dcomm1_92 dcomm1_93 dcomm1_94 dcomm1_95
dcomm1_96 dcomm1_97 dcomm1_98
```
```dcomm2_91 dcomm2_92
```
```                       dcomm2_93 dcomm2_94 dcomm2_95
```
```dcomm2_96 dcomm2_97
```
```                       dcomm2_99 dcomm3_91 dcomm3_92
```
```dcomm3_93 dcomm3_94
```
```                       dcomm3_95 dcomm3_96 dcomm3_97
```
```dcomm3_98 dcomm4_91
```
```                       dcomm4_92 dcomm4_93 dcomm4_94
```
```dcomm4_95 dcomm4_97
```
```                       dcomm4_98 dcomm4_99 dcomm5_91
```
```dcomm5_92 dcomm5_93
```
```                       dcomm5_95 dcomm5_96 dcomm5_97
```
```dcomm5_98 dcomm5_99
```
```                       dcomm7_91 dcomm7_92 dcomm7_93
```
```dcomm7_94 dcomm7_95
```
```                       dcomm7_96 dcomm7_97 dcomm7_99
```
```dcomm8_91 dcomm8_92
```
```                       dcomm8_93 dcomm8_94 dcomm8_95
```
```dcomm8_96 dcomm8_97
```
```                       dcomm8_98 dyr2 dyr3 dyr4 dyr5
```
```dyr6 dyr7 dyr8
```
```                       nb: variable counts and
```
```small-sample adjustments
```
```                       do not include partialled-out
```
```variables.
```
```Dropped collinear:    dcomm1_99 dcomm2_98 dcomm3_99 dcomm4_96
```
```dcomm5_94
```
```                       dcomm7_98 dcomm8_99 dyr9

```
```------------------------------------------------------------------------
```
```------

. xtivreg2 dabus_sum
```
```dagro lnpland_manz `agesq' `hhcharact' `ctfe' `te'  ( potincm_fo
```
```=
```
````inst80s_fo'  ) if dagehead2539 ==1  , fe i(nidhogar) r first
```
```ffirst
```
```rf fwl(`ctfe' `te') ;
```
```Warning - singleton groups detected.  69 observation(s) not used.
Warning - collinearities detected
Vars dropped:  dcomm1_99 dcomm2_99 dcomm3_99 dcomm4_99 dcomm5_97
dcomm7_98
dcomm8_99 dyr9

FIXED EFFECTS ESTIMATION
------------------------
Number of groups =       749                    Obs
```
```per group: min =
```
```2

```
```                   avg =
```
```6.6

```
```                   max =
```
```9

Reduced-form regression: dabus_sum
----------------------------------

FIXED EFFECTS ESTIMATION
------------------------
Number of groups =       749                    Obs
```
```per group: min =
```
```2

```
```                   avg =
```
```6.6

```
```                   max =
```
```9

OLS estimation
--------------

Statistics robust to heteroskedasticity

```
```          Number of obs =
```
```4959

```
```          F(  6,  4204) =
```
```7.23

```
```          Prob > F      =
```
```0.0000
Total (centered) SS     =  119.6871152
```
```Centered R2   =
```
```0.0322
Total (uncentered) SS   =  119.6871152
```
```Uncentered R2 =
```
```0.0322
Residual SS             =  115.8295136
```
```  Root MSE      =
```
```.166

```
```------------------------------------------------------------------------
```
```------
|               Robust
dabus_sum |      Coef.   Std. Err.      t
```
```P>|t|     [95% Conf.
```
```Interval]

```
```-------------+----------------------------------------------------------
```
```-------------+------
dagro |  -.1429524   .0403911    -3.54
```
``` 0.000    -.2221404
```
```-.0637645
lnpland_manz |  -.0025269   .0153996    -0.16   0.870
```
```-.0327183
```
```.0276645
```
``` 0.009     .0091058
```
```.0626891
ageheadsqr |  -.0003511   .0002082    -1.69   0.092
```
```  -.0007592
```
```.000057
kids14less |   .0056506   .0051194     1.10   0.270
```
```  -.0043861
```
```.0156873
potincm80s~o |  -.0641757   .0172277    -3.73   0.000
```
```-.0979511
```
```-.0304002

```
```------------------------------------------------------------------------
```
```------
```
```kids14less
```
```                       potincm80s_fo

```
```------------------------------------------------------------------------
```
```------

First-stage regressions
-----------------------

First-stage regression of potincm_fo:

FIXED EFFECTS ESTIMATION
------------------------
Number of groups =       749                    Obs
```
```per group: min =
```
```2

```
```                   avg =
```
```6.6

```
```                   max =
```
```9

OLS estimation
--------------

Statistics robust to heteroskedasticity

```
```          Number of obs =
```
```4959

```
```          F(  6,  4204) =
```
```1000.42

```
```          Prob > F      =
```
```0.0000
Total (centered) SS     =  1882.108159
```
```Centered R2   =
```
```0.3080
Total (uncentered) SS   =  1882.108159
```
```Uncentered R2 =
```
```0.3080
Residual SS             =   1302.35443
```
```  Root MSE      =
```
```.5566

```
```------------------------------------------------------------------------
```
```------
|               Robust
potincm_fo |      Coef.   Std. Err.      t
```
```P>|t|     [95% Conf.
```
```Interval]

```
```-------------+----------------------------------------------------------
```
```-------------+------
dagro |   .0813442    .070368     1.16
```
``` 0.248    -.0566143
```
```.2193027
lnpland_manz |  -.0382054   .0165208    -2.31   0.021
```
``` -.070595
```
```-.0058159
```
``` 0.012     .0218132
```
```.1791809
ageheadsqr |  -.0009395   .0006719    -1.40   0.162
```
```  -.0022568
```
```.0003778
kids14less |  -.0212255   .0166119    -1.28   0.201
```
```  -.0537936
```
```.0113425
potincm80s~o |   .9976588   .0131996    75.58   0.000
```
``` .9717807
```
```1.023537

```
```------------------------------------------------------------------------
```
```------
```
```kids14less
```
```                       potincm80s_fo

```
```------------------------------------------------------------------------
```
```------
Partial R-squared of excluded instruments:   0.3043
Test of excluded instruments:
F(  1,  4204) =  5712.73
Prob > F      =   0.0000

Summary results for first-stage regressions
-------------------------------------------

Variable    | Shea Partial R2 |   Partial R2    |  F(  1,
```
```4204)
```
```P-value
potincm_fo  |     0.3043      |     0.3043      |
```
```5712.73
```
```0.0000

NB: first-stage F-stat heteroskedasticity-robust

Underidentification tests
Ho: matrix of reduced form coefficients has rank=K-1
```
```(underidentified)
```
```Ha: matrix has rank=K (identified)

```
```     Chi-sq(1)      P-value
```
```Anderson canon. corr. -N*ln(1-CCEV) LR stat.     1527.72
```
```   0.0000
```
```Cragg-Donald N*CDEV statistic
```
```1841.71         0.0000
```
```Robust chi-square statistic
```
```5720.89         0.0000
```
```Weak identification tests
Ho: equation is weakly identified
Cragg-Donald (N-L)*CDEV/L1 F-statistic           1839.09
Robust F-statistic
```
``` 5712.73
```
```See main output for Cragg-Donald weak id test critical values

NB: Anderson and Cragg-Donald under- and weak identification stats
```
```not
```
```robust
Robust identification stats heteroskedasticity-robust

Weak-instrument-robust inference
Tests of joint significance of endogenous regressors B1 in main
```
```equation
```
```Ho: B1=0 and overidentifying restrictions are valid
Anderson-Rubin test          F(1,4204)=13.88
```
``` P-val=0.0002
```
```Anderson-Rubin test          Chi-sq(1)=13.90
```
``` P-val=0.0002
```
```Stock-Wright S statistic     Chi-sq(1)=5.61      P-val=0.0178
NB: Test statistics heteroskedasticity-robust

Number of observations N           =       4959
Number of regressors   K           =          6
Number of instruments  L           =          6
Number of excluded instruments L1  =          1

IV (2SLS) estimation
--------------------

Statistics robust to heteroskedasticity

```
```          Number of obs =
```
```4959

```
```          F(  6,  4204) =
```
```6.80

```
```          Prob > F      =
```
```0.0000
Total (centered) SS     =  119.6871152
```
```Centered R2   =
```
```0.0067
Total (uncentered) SS   =  119.6871152
```
```Uncentered R2 =
```
```0.0067
Residual SS             =  118.8838886
```
```  Root MSE      =
```
```.168

```
```------------------------------------------------------------------------
```
```------
|               Robust
dabus_sum |      Coef.   Std. Err.      z
```
```P>|z|     [95% Conf.
```
```Interval]

```
```-------------+----------------------------------------------------------
```
```-------------+------
potincm_fo |  -.0643263   .0173661    -3.70   0.000
```
```  -.0983631
```
```-.0302894
dagro |  -.1377199   .0407396    -3.38
```
``` 0.001     -.217568
```
```-.0578717
lnpland_manz |  -.0049845   .0154831    -0.32   0.748
```
```-.0353308
```
```.0253617
```
``` 0.002     .0149734
```
```.0697507
ageheadsqr |  -.0004116   .0002127    -1.94   0.053
```
```  -.0008284
```
```5.30e-06
kids14less |   .0042853   .0051692     0.83   0.407
```
```  -.0058461
```
```.0144167

```
```------------------------------------------------------------------------
```
```------
Anderson canon. corr. LR statistic (underidentification test):
1527.719

```
```       Chi-sq(1) P-val =
```
```0.0000
Test statistic(s) not robust

```
```------------------------------------------------------------------------
```
```------
Cragg-Donald F statistic (weak identification test):
1839.088
Stock-Yogo weak ID test critical values: 10% maximal IV size
16.38
15%
```
```maximal IV size
```
```8.96
20%
```
```maximal IV size
```
```6.66
25%
```
```maximal IV size
```
```5.53
Test statistic(s) not robust
Source: Stock-Yogo (2005).  Reproduced by permission.

```
```------------------------------------------------------------------------
```
```------
Hansen J statistic (overidentification test of all instruments):
0.000

```
```     (equation exactly
```
```identified)

```
```------------------------------------------------------------------------
```
```------
Instrumented:         potincm_fo
```
```kids14less
```
```Excluded instruments: potincm80s_fo Partialled-out (FWL): dcomm1_91
dcomm1_92 dcomm1_93 dcomm1_94 dcomm1_95
dcomm1_96 dcomm1_97 dcomm1_98
```
```dcomm2_91 dcomm2_92
```
```                       dcomm2_93 dcomm2_94 dcomm2_95
```
```dcomm2_96 dcomm2_97
```
```                       dcomm2_98 dcomm3_91 dcomm3_92
```
```dcomm3_93 dcomm3_94
```
```                       dcomm3_95 dcomm3_96 dcomm3_97
```
```dcomm3_98 dcomm4_91
```
```                       dcomm4_92 dcomm4_93 dcomm4_94
```
```dcomm4_95 dcomm4_96
```
```                       dcomm4_97 dcomm4_98 dcomm5_91
```
```dcomm5_92 dcomm5_93
```
```                       dcomm5_94 dcomm5_95 dcomm5_96
```
```dcomm5_98 dcomm5_99
```
```                       dcomm7_91 dcomm7_92 dcomm7_93
```
```dcomm7_94 dcomm7_95
```
```                       dcomm7_96 dcomm7_97 dcomm7_99
```
```dcomm8_91 dcomm8_92
```
```                       dcomm8_93 dcomm8_94 dcomm8_95
```
```dcomm8_96 dcomm8_97
```
```                       dcomm8_98 dyr2 dyr3 dyr4 dyr5
```
```dyr6 dyr7 dyr8
```
```                       nb: variable counts and
```
```small-sample adjustments
```
```                       do not include partialled-out
```
```variables.
```
```Dropped collinear:    dcomm1_99 dcomm2_99 dcomm3_99 dcomm4_99
```
```dcomm5_97
```
```                       dcomm7_98 dcomm8_99 dyr9

```
```------------------------------------------------------------------------
```
```------

. xtivreg2 dabus_sum
```
```dagro lnpland_manz `agesq' `hhcharact' `ctfe' `te'  ( potincm_fo
```
```=
```
````inst80s_fo'  ) if dagehead4065 ==1 , fe i(nidhogar) r first
```
```ffirst rf
```

```fwl(`ctfe' `te') ;
```
```Warning - singleton groups detected.  56 observation(s) not used.
Warning - collinearities detected
Vars dropped:  dcomm1_99 dcomm2_95 dcomm3_96 dcomm4_97 dcomm5_98
dcomm7_99
dcomm8_99 dyr9

FIXED EFFECTS ESTIMATION
------------------------
Number of groups =       830                    Obs
```
```per group: min =
```
```2

```
```                   avg =
```
```7.0

```
```                   max =
```
```9

Reduced-form regression: dabus_sum
----------------------------------

FIXED EFFECTS ESTIMATION
------------------------
Number of groups =       830                    Obs
```
```per group: min =
```
```2

```
```                   avg =
```
```7.0

```
```                   max =
```
```9

OLS estimation
--------------

Statistics robust to heteroskedasticity

```
```          Number of obs =
```
```5840

```
```          F(  6,  5004) =
```
```9.95

```
```          Prob > F      =
```
```0.0000
Total (centered) SS     =  130.6892353
```
```Centered R2   =
```
```0.0200
Total (uncentered) SS   =  130.6892353
```
```Uncentered R2 =
```
```0.0200
Residual SS             =  128.0706507
```
```  Root MSE      =
```
```.16

```
```------------------------------------------------------------------------
```
```------
|               Robust
dabus_sum |      Coef.   Std. Err.      t
```
```P>|t|     [95% Conf.
```
```Interval]

```
```-------------+----------------------------------------------------------
```
```-------------+------
dagro |  -.1704666   .0498948    -3.42
```
``` 0.001    -.2682824
```
```-.0726509
lnpland_manz |  -.0023589   .0059152    -0.40   0.690
```
```-.0139553
```
```.0092375
```
``` 0.000     .0437689
```
```.0838389
ageheadsqr |  -.0005301   .0000889    -5.97   0.000
```
```  -.0007043
```
```-.0003559
kids14less |   .0099594   .0049148     2.03   0.043
```
```   .0003242
```
```.0195947
potincm80s~o |   .0093771   .0038328     2.45   0.014
```
``` .0018631
```
```.0168911

```
```------------------------------------------------------------------------
```
```------
```
```kids14less
```
```                       potincm80s_fo

```
```------------------------------------------------------------------------
```
```------

First-stage regressions
-----------------------

First-stage regression of potincm_fo:

FIXED EFFECTS ESTIMATION
------------------------
Number of groups =       830                    Obs
```
```per group: min =
```
```2

```
```                   avg =
```
```7.0

```
```                   max =
```
```9

OLS estimation
--------------

Statistics robust to heteroskedasticity

```
```          Number of obs =
```
```5840

```
```          F(  6,  5004) =
```
```7.64

```
```          Prob > F      =
```
```0.0000
Total (centered) SS     =  8142.451572
```
```Centered R2   =
```
```0.0463
Total (uncentered) SS   =  8142.451572
```
```Uncentered R2 =
```
```0.0463
Residual SS             =  7765.373403
```
```  Root MSE      =
```
```1.246

```
```------------------------------------------------------------------------
```
```------
|               Robust
potincm_fo |      Coef.   Std. Err.      t
```
```P>|t|     [95% Conf.
```
```Interval]

```
```-------------+----------------------------------------------------------
```
```-------------+------
dagro |   .0590806   .1640592     0.36
```
``` 0.719    -.2625472
```
```.3807085
lnpland_manz |  -.1176091   .0390987    -3.01   0.003
```
```-.1942598
```
```-.0409584
```
``` 0.627    -.1005861
```
```.1669916
ageheadsqr |   .0003195   .0006371     0.50   0.616
```
```  -.0009294
```
```.0015684
kids14less |  -.0352024    .031388    -1.12   0.262
```
```  -.0967366
```
```.0263317
potincm80s~o |   .5135334   .1413639     3.63   0.000
```
``` .2363982
```
```.7906685

```
```------------------------------------------------------------------------
```
```------
```
```kids14less
```
```                       potincm80s_fo

```
```------------------------------------------------------------------------
```
```------
Partial R-squared of excluded instruments:   0.0446
Test of excluded instruments:
F(  1,  5004) =    13.20
Prob > F      =   0.0003

Summary results for first-stage regressions
-------------------------------------------

Variable    | Shea Partial R2 |   Partial R2    |  F(  1,
```
```5004)
```
```P-value
potincm_fo  |     0.0446      |     0.0446      |
```
```  13.20
```
```0.0003

NB: first-stage F-stat heteroskedasticity-robust

Underidentification tests
Ho: matrix of reduced form coefficients has rank=K-1
```
```(underidentified)
```
```Ha: matrix has rank=K (identified)

```
```     Chi-sq(1)      P-value
```
```Anderson canon. corr. -N*ln(1-CCEV) LR stat.      228.47
```
```   0.0000
```
```Cragg-Donald N*CDEV statistic
```
``` 233.76         0.0000
```
```Robust chi-square statistic
```
```13.21         0.0003
```
```Weak identification tests
Ho: equation is weakly identified
Cragg-Donald (N-L)*CDEV/L1 F-statistic            233.48
Robust F-statistic
```
``` 13.20
```
```See main output for Cragg-Donald weak id test critical values

NB: Anderson and Cragg-Donald under- and weak identification stats
```
```not
```
```robust
Robust identification stats heteroskedasticity-robust

Weak-instrument-robust inference
Tests of joint significance of endogenous regressors B1 in main
```
```equation
```
```Ho: B1=0 and overidentifying restrictions are valid
Anderson-Rubin test          F(1,5004)=5.99
```
```P-val=0.0145
```
```Anderson-Rubin test          Chi-sq(1)=5.99
```
```P-val=0.0144
```
```Stock-Wright S statistic     Chi-sq(1)=6.48      P-val=0.0109
NB: Test statistics heteroskedasticity-robust

Number of observations N           =       5840
Number of regressors   K           =          6
Number of instruments  L           =          6
Number of excluded instruments L1  =          1

IV (2SLS) estimation
--------------------

Statistics robust to heteroskedasticity

```
```          Number of obs =
```
```5840

```
```          F(  6,  5004) =
```
```9.91

```
```          Prob > F      =
```
```0.0000
Total (centered) SS     =  130.6892353
```
```Centered R2   =
```
```0.0038
Total (uncentered) SS   =  130.6892353
```
```Uncentered R2 =
```
```0.0038
Residual SS             =  130.1981904
```
```  Root MSE      =
```
```.1612

```
```------------------------------------------------------------------------
```
```------
|               Robust
dabus_sum |      Coef.   Std. Err.      z
```
```P>|z|     [95% Conf.
```
```Interval]

```
```-------------+----------------------------------------------------------
```
```-------------+------
potincm_fo |   .0182599   .0079422     2.30   0.021
```
```   .0026936
```
```.0338263
dagro |  -.1715454   .0502306    -3.42
```
``` 0.001    -.2699957
```
```-.0730952
lnpland_manz |  -.0002114   .0060272    -0.04   0.972
```
```-.0120245
```
```.0116017
```
``` 0.000      .043177
```
```.0832183
ageheadsqr |   -.000536   .0000894    -6.00   0.000
```
```  -.0007111
```
```-.0003608
kids14less |   .0106022   .0049372     2.15   0.032
```
```   .0009254
```
```.020279

```
```------------------------------------------------------------------------
```
```------
Anderson canon. corr. LR statistic (underidentification test):
228.468

```
```       Chi-sq(1) P-val =
```
```0.0000
Test statistic(s) not robust

```
```------------------------------------------------------------------------
```
```------
Cragg-Donald F statistic (weak identification test):
233.478
Stock-Yogo weak ID test critical values: 10% maximal IV size
16.38
15%
```
```maximal IV size
```
```8.96
20%
```
```maximal IV size
```
```6.66
25%
```
```maximal IV size
```
```5.53
Test statistic(s) not robust
Source: Stock-Yogo (2005).  Reproduced by permission.

```
```------------------------------------------------------------------------
```
```------
Hansen J statistic (overidentification test of all instruments):
0.000

```
```     (equation exactly
```
```identified)

```
```------------------------------------------------------------------------
```
```------
Instrumented:         potincm_fo
```
```kids14less
```
```Excluded instruments: potincm80s_fo Partialled-out (FWL): dcomm1_91
dcomm1_92 dcomm1_93 dcomm1_94 dcomm1_95
dcomm1_96 dcomm1_97 dcomm1_98
```
```dcomm2_91 dcomm2_92
```
```                       dcomm2_93 dcomm2_94 dcomm2_96
```
```dcomm2_97 dcomm2_98
```
```                       dcomm2_99 dcomm3_91 dcomm3_92
```
```dcomm3_93 dcomm3_94
```
```                       dcomm3_95 dcomm3_97 dcomm3_98
```
```dcomm3_99 dcomm4_91
```
```                       dcomm4_92 dcomm4_93 dcomm4_94
```
```dcomm4_95 dcomm4_96
```
```                       dcomm4_98 dcomm4_99 dcomm5_91
```
```dcomm5_92 dcomm5_93
```
```                       dcomm5_94 dcomm5_95 dcomm5_96
```
```dcomm5_97 dcomm5_99
```
```                       dcomm7_91 dcomm7_92 dcomm7_93
```
```dcomm7_94 dcomm7_95
```
```                       dcomm7_96 dcomm7_97 dcomm7_98
```
```dcomm8_91 dcomm8_92
```
```                       dcomm8_93 dcomm8_94 dcomm8_95
```
```dcomm8_96 dcomm8_97
```
```                       dcomm8_98 dyr2 dyr3 dyr4 dyr5
```
```dyr6 dyr7 dyr8
```
```                       nb: variable counts and
```
```small-sample adjustments
```
```                       do not include partialled-out
```
```variables.
```
```Dropped collinear:    dcomm1_99 dcomm2_95 dcomm3_96 dcomm4_97
```
```dcomm5_98
```
```                       dcomm7_99 dcomm8_99 dyr9

```
```------------------------------------------------------------------------
```
```------

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