Solved – Pesaran cross-sectional dependence test in panel data

panel datastata

I was testing the cross sectional independence test using Pesaran CD test in Stata 10 for the panel data using the N=50 and T=18. After running the fixed effect with time dummies (effects), I got a negative value for the test with the p value >1 (which is not possible). I checked the paper on this: http://www.stata-journal.com/article.html?article=st0113, but they didn't talk about the negative value at all. I would really appreciate if you can help me to interpret the results. 

xtreg Y  X1 X2 i.year,fe

Fixed-effects (within) regression               Number of obs      =       900
Group variable: state                           Number of groups   =        50

R-sq:  within  = 0.4336                         Obs per group: min =        18
       between = 0.0417                                        avg =        18
       overall = 0.3772                                        max =        18

                                                F(19,825)          =     33.24
corr(u_i, Xb)  = -0.0215                        Prob > F           =    0.0000

------------------------------------------------------------------------------
            Y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
           X1 |  -.0008466   .0005767    -1.47   0.142    -.0019787    .0002854
           X2 |    .185078   .0304043     6.09   0.000     .1253991     .244757
             |
        year |
       1993  |  -.0101846   .0029659    -3.43   0.001    -.0160061   -.0043631
       1994  |  -.0173621   .0028749    -6.04   0.000     -.023005   -.0117192
       1995  |  -.0046886   .0029062    -1.61   0.107     -.010393    .0010159
       1996  |  -.0175546   .0028879    -6.08   0.000     -.023223   -.0118862
       1997  |   -.009572    .002962    -3.23   0.001     -.015386    -.003758
       1998  |   -.012109   .0029123    -4.16   0.000    -.0178254   -.0063926
       1999  |  -.0097348   .0029043    -3.35   0.001    -.0154356   -.0040341
       2000  |  -.0137918   .0028784    -4.79   0.000    -.0194416   -.0081419
       2001  |    .004144   .0029323     1.41   0.158    -.0016116    .0098996
       2002  |   .0188509   .0028925     6.52   0.000     .0131733    .0245285
       2003  |   .0058601   .0028772     2.04   0.042     .0002127    .0115076
       2004  |  -.0005801   .0028731    -0.20   0.840    -.0062195    .0050594
       2005  |  -.0085907   .0029534    -2.91   0.004    -.0143877   -.0027937
       2006  |   -.018118   .0028702    -6.31   0.000    -.0237516   -.0124843
       2007  |  -.0164648   .0028771    -5.72   0.000    -.0221121   -.0108174
       2008  |  -.0352191   .0028805   -12.23   0.000    -.0408731   -.0295652
       2009  |   .0094679   .0032904     2.88   0.004     .0030094    .0159265
             |
       _cons |   .0467515   .0024088    19.41   0.000     .0420234    .0514797
-------------+----------------------------------------------------------------
     sigma_u |  .00686051
     sigma_e |  .01433916
         rho |   .1862708   (fraction of variance due to u_i)
------------------------------------------------------------------------------
F test that all u_i=0:     F(49, 825) =     4.02             Prob > F = 0.0000


xtcsd, pesaran abs
 Pesaran's test of cross sectional independence =    -2.673, Pr = 1.9925
  Average absolute value of the off-diagonal elements =     0.215

Best Answer

The relevant lines in the code file xtcsd.ado, to view which type

viewsource xtcsd.ado

are 163-165, which read

    di in gr "Pesaran's test of cross sectional independence = "/*
    */in ye %9.3f `pesaran' in gr ", Pr = " %6.4f /*
    */ in ye 2*(1-norm(abs(`pesaran')))

The last line of code is the one that produces the p-value, and it behaves as expected under version control, with the value of the statistic that you get

. version 9: di 2*(1-norm(abs(-2.673)))
.00751763

So, there is no ostensible reason why your computed statistic should result in an abnormal p-value. I suggest you set trace on and check what is going on, or show us the output.

By the way, you should check what version of the xtcsd package you have. You can check using

. which xtcsd
*! version 1.1.1        R.E. De Hoyos and V. Sarafidis 16may2006
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