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Re: st: AW: moulton factor correction


From   Ana Gabriela Guerrero Serdan <ag_guerreroserdan@yahoo.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: AW: moulton factor correction
Date   Wed, 24 Jun 2009 06:47:29 -0700 (PDT)

Hi Martin, 

Yes, its Pischke. 

In stata: 
help moulton

rgds, 
Gaby 


--- On Wed, 6/24/09, Martin Weiss <martin.weiss1@gmx.de> wrote:

> From: Martin Weiss <martin.weiss1@gmx.de>
> Subject: st: AW: moulton factor correction
> To: statalist@hsphsun2.harvard.edu
> Date: Wednesday, June 24, 2009, 7:35 AM
> 
> <> 
> 
> 
> 
> 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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