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st: RE: AW: moulton factor correction


From   DE SOUZA Eric <edesouza@coleurop.be>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: RE: AW: moulton factor correction
Date   Wed, 24 Jun 2009 15:32:18 +0200

Their book "Mostly Harmless Econometrics", section 8.2.1

Eric de Souza
College of Europe
Brugge (Bruges), Belgium
http://www.coleurope.eu
 

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Martin Weiss
Sent: 24 June 2009 14:36
To: statalist@hsphsun2.harvard.edu
Subject: st: AW: moulton factor correction


<> 



What is the precise reference for "Angrist and Piscke (2009)"? (Guess that should be Pischke in any event)



HTH
Martin


-----Ursprüngliche Nachricht-----
Von: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von Ana Gabriela Guerrero Serdan
Gesendet: Mittwoch, 24. Juni 2009 14:15
An: stata listserve
Betreff: st: moulton factor correction

Dear all, 

I am trying to understand why in this example when using the moulton correction developped by Angrist and Piscke (2009) I get some SE that are lower then when using the cluster option. I thought that the moulton correction will increase SE, but seems not to be the case for all coefficients. Can someone help me interpret what is going on? 


use http://www.ats.ucla.edu/stat/stata/seminars/svy_stata_intro/srs, clear regress api00 growth emer yr_rnd, robust regress api00 growth emer yr_rnd, cl(dnum) moulton api00 growth emer yr_rnd, cl(dnum)  moulton api00 growth emer yr_rnd, cl(dnum) moulton loneway api00  dnum


results below: 

thanks,
Gaby 

use http://www.ats.ucla.edu/stat/stata/seminars/svy_stata_intro/srs, clear


.   regress api00 growth emer yr_rnd, robust

Linear regression                                      Number of obs =
309
                                                       F(  3,   305) =
33.15
                                                       Prob > F      =
0.0000
                                                       R-squared     =
0.2770
                                                       Root MSE      =
111.54

----------------------------------------------------------------------------
--
             |               Robust
       api00 |      Coef.   Std. Err.      t    P>|t|     [95% Conf.
Interval]
-------------+----------------------------------------------------------
-------------+----
--
      growth |  -.1027121    .195606    -0.53   0.600    -.4876202
.2821961
        emer |  -5.444932   .5532104    -9.84   0.000    -6.533524
-4.35634
      yr_rnd |  -51.07569   20.28729    -2.52   0.012    -90.99645
-11.15493
       _cons |   740.3981   12.13784    61.00   0.000     716.5136
764.2826
----------------------------------------------------------------------------
--

. regress api00 growth emer yr_rnd, cl(dnum)

Linear regression                                      Number of obs =
309
                                                       F(  3,   185) =
19.72
                                                       Prob > F      =
0.0000
                                                       R-squared     =
0.2770
                                                       Root MSE      =
111.54

                                 (Std. Err. adjusted for 186 clusters in
dnum)
----------------------------------------------------------------------------
--
             |               Robust
       api00 |      Coef.   Std. Err.      t    P>|t|     [95% Conf.
Interval]
-------------+----------------------------------------------------------
-------------+----
--
      growth |  -.1027121   .2291703    -0.45   0.655    -.5548352
.3494111
        emer |  -5.444932   .7293969    -7.46   0.000    -6.883938
-4.005927
      yr_rnd |  -51.07569   22.83615    -2.24   0.027    -96.12844
-6.022935
       _cons |   740.3981   13.46076    55.00   0.000     713.8418
766.9544
----------------------------------------------------------------------------
--

.   moulton api00 growth emer yr_rnd, cl(dnum)

OLS Regression: standard errors                       Number of obs  =
309
adjusted for cluster effects using Moulton            R-squared      =
0.2770
                                                      Adj R-squared  =
0.2698
Number of clusters (dnum) = 186                       Root MSE       =
111.541

----------------------------------------------------------------------------
--
       api00 |      Coef.   Std. Err.      t    P>|t|     [95% Conf.
Interval]
-------------+----------------------------------------------------------
-------------+----
--
      growth |  -.1027121   .2455165    -0.42   0.676    -.5858326
.3804084
        emer |  -5.444932   .7128514    -7.64   0.000    -6.847662
-4.042203
      yr_rnd |  -51.07569   20.57651    -2.48   0.014    -91.56558
-10.58579
       _cons |   740.3981   17.78252    41.64   0.000     705.4061
775.39
----------------------------------------------------------------------------
--
Intraclass correlation in   growth =  0.2567
Intraclass correlation in     emer =  0.5444
Intraclass correlation in   yr_rnd =  0.0494
Intraclass correlation in residual =  0.3775

.   moulton api00 growth emer yr_rnd, cl(dnum) moulton

OLS Regression: standard errors                       Number of obs  =
309
adjusted for cluster effects using Moulton            R-squared      =
0.2770
                                                      Adj R-squared  =
0.2698
Number of clusters (dnum) = 186                       Root MSE       =
111.541

----------------------------------------------------------------------------
--
       api00 |      Coef.   Std. Err.      t    P>|t|     [95% Conf.
Interval]
-------------+----------------------------------------------------------
-------------+----
--
      growth |  -.1027121   .2203333    -0.47   0.641    -.5362779
.3308538
        emer |  -5.444932   .6285286    -8.66   0.000    -6.681734
-4.208131
      yr_rnd |  -51.07569   20.53625    -2.49   0.013    -91.48636
-10.66502
       _cons |   740.3981   15.49653    47.78   0.000     709.9044
770.8917
----------------------------------------------------------------------------
--
Intraclass correlation in   growth =  0.1107
Intraclass correlation in     emer =  0.4466
Intraclass correlation in   yr_rnd =  0.0794
Intraclass correlation in residual =  0.2204



. loneway api00  dnum

                    One-way Analysis of Variance for api00: 

                                              Number of obs =       310
                                                  R-squared =    0.7392

    Source                SS         df      MS            F     Prob > F
-------------------------------------------------------------------------
Between dnum           3879736.2    186    20858.797      1.87     0.0001
Within dnum            1369122.1    123    11131.074
-------------------------------------------------------------------------
Total                  5248858.3    309    16986.596

         Intraclass       Asy.        
         correlation      S.E.       [95% Conf. Interval]
         ------------------------------------------------
            0.34737     0.08516       0.18045     0.51428

         Estimated SD of dnum effect             76.97107
         Estimated SD within dnum                105.5039
         Est. reliability of a dnum mean          0.46636



      
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