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  • pcse or vce robust? wald results not showing

    Code:
     xtreg roa npl stdta de ltdr avinf_npl avinf_stdta avinf_de avinf_ltdr, re vce(robust)
    
    Random-effects GLS regression                   Number of obs      =        80
    Group variable: id                              Number of groups   =         8
    
    R-sq:  within  = 0.6739                         Obs per group: min =        10
           between = 0.5108                                        avg =      10.0
           overall = 0.6129                                        max =        10
    
                                                    Wald chi2(7)       =         .
    corr(u_i, X)   = 0 (assumed)                    Prob > chi2        =         .
    
                                         (Std. Err. adjusted for 8 clusters in id)
    ------------------------------------------------------------------------------
                 |               Robust
             roa |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
    -------------+----------------------------------------------------------------
             npl |  -.2263572   .0303436    -7.46   0.000    -.2858296   -.1668848
           stdta |   .1056417    .035604     2.97   0.003     .0358592    .1754242
              de |  -.8938725   .3424584    -2.61   0.009    -1.565079   -.2226665
            ltdr |  -.0258621   .0233812    -1.11   0.269    -.0716884    .0199641
       avinf_npl |   .0141532   .0024576     5.76   0.000     .0093365    .0189699
     avinf_stdta |  -.0106536   .0021378    -4.98   0.000    -.0148436   -.0064636
        avinf_de |   .0718727   .0279978     2.57   0.010      .016998    .1267474
      avinf_ltdr |   .0012853   .0011808     1.09   0.276    -.0010289    .0035996
           _cons |   3.839852   1.845138     2.08   0.037     .2234476    7.456256
    -------------+----------------------------------------------------------------
         sigma_u |          0
         sigma_e |  .85396652
             rho |          0   (fraction of variance due to u_i)
    ------------------------------------------------------------------------------

  • #2
    Code:
    Breusch-Pagan / Cook-Weisberg test for heteroskedasticity 
             Ho: Constant variance
             Variables: fitted values of roa
    
             chi2(1)      =    83.82
             Prob > chi2  =   0.0620

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