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st: xtscc and xtpsce


From   ghislain dutheil <gdutheil@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   st: xtscc and xtpsce
Date   Thu, 16 Oct 2008 18:04:38 +0200

helo,

I wonder the diffence between --xtscc ..,fe-- and --xtpsce ...dummies, 
correlation(ar1)-- ? It seems that they make the same hypotesis :
 heteroskedastic, autocorrelated up to some lag and possibly correlated 
between the groups (panels)

but the results are quite different :



. xtpcse lm_dolc lpib_dolc lagsum  new_* , correlation(ar1) rhotype(regress)
(note: estimates of rho outside [-1,1] bounded to be in the range [-1,1])

Prais-Winsten regression, correlated panels corrected standard errors 
(PCSEs)

Group variable:   newid                         Number of obs      
=       727
Time variable:    obs                           Number of groups   
=        14
Panels:           correlated (unbalanced)       Obs per group: min 
=        51
Autocorrelation:  common AR(1)                                 avg =  
51.92857
Sigma computed by casewise selection                           max 
=        52
Estimated covariances      =       105          R-squared          =    
0.9620
Estimated autocorrelations =         1          Wald chi2(15)      =   
6052.70
Estimated coefficients     =        16          Prob > chi2        =    
0.0000

------------------------------------------------------------------------------
             |           Panel-corrected
     lm_dolc |      Coef.   Std. Err.      z    P>|z|     [95% Conf. 
Interval]
-------------+----------------------------------------------------------------
   lpib_dolc |   .4707492    .046833    10.05   0.000     .3789581    
.5625402
      lagsum |   .0183111   .0812503     0.23   0.822    -.1409366    
.1775587
  new_1 |   2.308959     .23099    10.00   0.000     1.856227    2.761691
  new_2 |   2.831064   .2640616    10.72   0.000     2.313513    3.348615
  new_3 |   2.042727    .217553     9.39   0.000      1.61633    2.469123
  new_4 |   3.725258   .2971162    12.54   0.000     3.142921    4.307595
  new_5 |   3.437277   .3115808    11.03   0.000      2.82659    4.047964
  new_6 |   2.439881   .2631095     9.27   0.000     1.924195    2.955566
  new_7 |   3.052517   .2688442    11.35   0.000     2.525592    3.579442
  new_8 |  (dropped)
  new_9 |   2.703009   .2567918    10.53   0.000     2.199707    3.206312
 new_10 |   2.110368   .2099764    10.05   0.000     1.698822    2.521914
 new_11 |   2.074326   .2524244     8.22   0.000     1.579583    2.569069
 new_12 |   2.520334   .2575537     9.79   0.000     2.015538     3.02513
 new_13 |   3.940914   .2955988    13.33   0.000     3.361551    4.520277
 new_14 |   5.234917   .4166243    12.57   0.000     4.418348    6.051486
       _cons |   -.063312   1.005865    -0.06   0.950    -2.034771    
1.908146
-------------+----------------------------------------------------------------
         rho |   .9187073




. xtscc lm_dolc lpib_dolc lagsum , fe lag(1)

Regression with Driscoll-Kraay standard errors   Number of obs     
=       727
Method: Fixed-effects regression                 Number of groups  
=        14
Group variable (i): newid                        F(  2,    13)     =    
202.94
maximum lag: 1                                   Prob > F          =    
0.0000
                                                 within R-squared  =    
0.6606

------------------------------------------------------------------------------
             |             Drisc/Kraay
     lm_dolc |      Coef.   Std. Err.      t    P>|t|     [95% Conf. 
Interval]
-------------+----------------------------------------------------------------
   lpib_dolc |   .5669392   .0394445    14.37   0.000     .4817244    
.6521539
      lagsum |  -.0010265   .1381459    -0.01   0.994    -.2994727    
.2974196
       _cons |   1.781487   1.483853     1.20   0.251    -1.424182    
4.987155


Could you help me ?

Best

Ghislain


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