Dear members,
I'm quite newbie here. I'm so confused in determining the perfect model for my regression. I have conducted the LM test to determine whether should I use the Random Effect model or common OLS. Please help me

Here's my result on RE Regression:

Random-effects GLS regression Number of obs = 160
Group variable: bank Number of groups = 32

R-sq: Obs per group:
within = 0.0000 min = 5
between = 0.3439 avg = 5.0
overall = 0.2313 max = 5

Wald chi2(9) = 11.53
corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.2412

------------------------------------------------------------------------------
LDR | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
x1 | 7.71892 7.445196 1.04 0.300 -6.873397 22.31124
x2 | -7.521882 12.34695 -0.61 0.542 -31.72147 16.6777
x3 | -13.53032 9.615677 -1.41 0.159 -32.3767 5.31606
x4 | -4.638333 8.831311 -0.53 0.599 -21.94738 12.67072
x5 | -1.266607 10.72728 -0.12 0.906 -22.29168 19.75847
x6 | -14.92695 9.851367 -1.52 0.130 -34.23528 4.381369
x7 | 1.04999 .9551709 1.10 0.272 -.8221106 2.92209
x8 | -1.253508 .7169643 -1.75 0.080 -2.658732 .1517162
x9 | 14.31133 6.478638 2.21 0.027 1.613433 27.00923
_cons | 109.6411 24.82635 4.42 0.000 60.98236 158.2999
-------------+----------------------------------------------------------------
sigma_u | 7.8450711
sigma_e | 6.7056952
rho | .57782631 (fraction of variance due to u_i)
------------------------------------------------------------------------------

Here's my LM test after the regression:

Breusch and Pagan Lagrangian multiplier test for random effects

LDR[bank,t] = Xb + u[bank] + e[bank,t]

Estimated results:
| Var sd = sqrt(Var)
---------+-----------------------------
LDR | 110.5734 10.51539
e | 44.96635 6.705695
u | 61.54514 7.845071

Test: Var(u) = 0
chibar2(01) = 69.98
Prob > chibar2 = 0.0000

Should I use RE regression model over Common OLS model?
Thanks in advance!