newey-west adjustment not working properly in OLS
It looks newey-west adjustment is not working properly in OLS when 'cluster' is set to 'time' or 'entity'. Specifically, pandas.stats.plm.py lines 791-794 don't have any effect. Should that be replaced with: xox = math.newey_west(m, nw_lags, nobs, df, nw_overlap)? 

Here is some code to reproduce the issue.

import numpy
from pylab import *
from pandas import *

T = 100
panel_size = 3
data_dimensions = [T, panel_size]

xs_per_y = WidePanel({
    'predictor a' : numpy.random.normal(size=data_dimensions),
    'predictor b' : numpy.random.normal(size=data_dimensions)
})
# y = B_a + B_b + noise

ys = xs_per_y['predictor a'] + xs_per_y['predictor b'] + numpy.random.normal(size=data_dimensions)

print ols(y=ys, x=xs_per_y, pool=True, cluster = 'time')    
# we expect the following t-stats to be smaller, but they are the same as the previous OLS

print ols(y=ys, x=xs_per_y, pool=True, cluster = 'time', nw_lags=10)
