pedroni coint test with panel setting

[egs]

Hi:
My data includes 9 years of data, so that I included 12 cross sections. My goal is to apply a VECM model, but first I tried to check for panel ADF and Johansen coint tests. I could not do Johanson probably because of the data span, I am not sure it pools the data, but pedroni res coint test gave me some results. I assume it pools the data so number of obs is not a problem.
According to the results panel PP rejects no coint with prob 0.035 and panel ADF rejects no unit root with 0.000.

My q is...Am I reading the results correctly? How do I read PP non parametric results and how do I decide on the rank of coint according to these results. Can I proceed with VECM from here?

Thanks...Cheers...

Pedroni Residual Cointegration Test
Series: GDPCAP TOTMALE TOTFEMALE
Date: 07/09/13 Time: 10:58
Sample: 2004 2012
Included observations: 108
Cross-sections included: 12
Null Hypothesis: No cointegration
Trend assumption: No deterministic trend
User-specified lag length: 1
Newey-West automatic bandwidth selection and Bartlett kernel

Alternative hypothesis: common AR coefs. (within-dimension)
Weighted
Statistic Prob. Statistic Prob.
Panel v-Statistic -0.648999 0.7418 -1.749357 0.9599
Panel rho-Statistic 1.633848 0.9489 1.898921 0.9712
Panel PP-Statistic -1.818791 0.0345 -2.683662 0.0036
Panel ADF-Statistic -5.197009 0.0000 -6.180580 0.0000

Alternative hypothesis: individual AR coefs. (between-dimension)

Statistic Prob.
Group rho-Statistic 2.898119 0.9981
Group PP-Statistic -5.476722 0.0000
Group ADF-Statistic -5.738165 0.0000


Cross section specific results

Phillips-Peron results (non-parametric)

Cross ID AR(1) Variance HAC Bandwidth Obs
1 0.143 63426.93 21840.50 7.00 8
2 -0.173 23716.84 4865.225 7.00 8
3 0.266 42719.46 8702.823 7.00 8
4 0.182 64013.98 22683.97 7.00 8
5 -0.721 3920.788 3920.788 0.00 8
6 0.284 67122.52 19254.21 7.00 8
7 0.159 73304.84 14451.87 7.00 8
8 -0.532 23119.29 22759.18 1.00 8
9 0.501 167240.4 188464.6 2.00 8
10 -0.150 79677.82 30786.57 7.00 8
11 -0.044 58321.83 21275.50 7.00 8
12 -0.328 65841.22 14720.44 7.00 8

Augmented Dickey-Fuller results (parametric)

Cross ID AR(1) Variance Lag Max lag Obs
1 -0.489 28916.78 1 -- 7
2 -1.037 11373.45 1 -- 7
3 -0.336 21376.95 1 -- 7
4 -0.335 38440.99 1 -- 7
5 -1.077 4280.511 1 -- 7
6 -0.271 30730.53 1 -- 7
7 -0.441 47195.47 1 -- 7
8 -0.617 25723.07 1 -- 7
9 -0.358 48285.45 1 -- 7
10 -0.509 82435.43 1 -- 7
11 -0.511 53189.39 1 -- 7
12 -0.606 67065.80 1 -- 7