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st: ecm via xtrc


From   "Podesta', Federico" <[email protected]>
To   <[email protected]>
Subject   st: ecm via xtrc
Date   Tue, 13 May 2008 17:19:06 +0200

Dear all, 

I am using a time series cross-section  data set including 465 observations (31 annual observations for 15 countries). My dependent variable is social security transfer (SSTRAN), while covariates are left power (LEFTCUM), unemployment rate (UNEM), percentage of the inactive population (DEPRATIO), and trade openness (TRADE). All these variables seem non-stationary processes. Consequently, I mean to estimate an panel error correction model- So if I estimate this kind of model via a simple OLS procedure, the parameter for the lagged dependent level variable which represents a measure of equilibrium properties, is quite low  (-0.014) (see belo the STATA output). nevertheless, if estimate a random coefficient error correction model via xtrc STATA command, the parameter for the lagged dependent level variable increases strongly. In this case it is -0.30 (see STATA output below). A part from the problem of the statistical significance of the coefficient, this implies that the adjus!
 tment process among variables is considerably faster.
On the basis of this, I wonder if it is statistically reasonable estimate an error correction model using xtrc STATA command?
Why if one controls causal heterogeneity via a random coefficient model, the adjustment process should be faster than a basic specification?

Thanks a lot in advance for any your help
Best regards 
Federico Podest�


. reg dsstran lsstran dleftcum lleftcum dunem lunem ddepratio ldepratio dtrade ltrade 

      Source |       SS       df       MS              Number of obs =     450
-------------+------------------------------           F(  9,   440) =   28.44
       Model |  73.1523504     9  8.12803894           Prob > F      =  0.0000
    Residual |  125.736581   440  .285764957           R-squared     =  0.3678
-------------+------------------------------           Adj R-squared =  0.3549
       Total |  198.888931   449  .442959758           Root MSE      =  .53457

------------------------------------------------------------------------------
     dsstran |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     lsstran |  -.0138686   .0075559    -1.84   0.067    -.0287187    .0009816
    dleftcum |   .0639292   .0739955     0.86   0.388    -.0814992    .2093577
    lleftcum |   .0013023   .0037215     0.35   0.727    -.0060118    .0086165
       dunem |   .4283545   .0308134    13.90   0.000     .3677947    .4889143
       lunem |  -.0295548   .0094424    -3.13   0.002    -.0481127   -.0109969
   ddepratio |    .135711   .0872411     1.56   0.121    -.0357501     .307172
   ldepratio |   .0020256   .0103268     0.20   0.845    -.0182705    .0223216
      dtrade |  -.0188634   .0072521    -2.60   0.010    -.0331164   -.0046104
      ltrade |   .0024225   .0012992     1.86   0.063     -.000131     .004976
       _cons |   .3227546   .3836955     0.84   0.401    -.4313491    1.076858



. xtrc dsstran lsstran dleftcum lleftcum dunem lunem ddepratio ldepratio dtrade ltrade 

Random-coefficients regression                  Number of obs      =       450
Group variable: cc                              Number of groups   =        15

                                                Obs per group: min =        30
                                                               avg =      30.0
                                                               max =        30

                                                Wald chi2(9)       =    113.31
                                                Prob > chi2        =    0.0000

------------------------------------------------------------------------------
     dsstran |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     lsstran |   -.292154    .084294    -3.47   0.001    -.4573672   -.1269408
    dleftcum |   .1335818    .290957     0.46   0.646    -.4366835     .703847
    lleftcum |   .1331348   .1545065     0.86   0.389    -.1696924     .435962
       dunem |   .5189076   .1106382     4.69   0.000     .3020606    .7357545
       lunem |   .0747792   .0588429     1.27   0.204    -.0405507    .1901092
   ddepratio |   .0108599   .3924658     0.03   0.978     -.758359    .7800788
   ldepratio |  -.0173162   .0737059    -0.23   0.814    -.1617772    .1271448
      dtrade |  -.0033899   .0184207    -0.18   0.854    -.0394938     .032714
      ltrade |   .0043399     .01749     0.25   0.804    -.0299398    .0386197
       _cons |   2.725573   2.747165     0.99   0.321    -2.658771    8.109917
------------------------------------------------------------------------------
Test of parameter constancy:    chi2(140) =   353.60      Prob > chi2 = 0.0000

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