TypeError when using statsmodels.OLS with NaNs and missing = 'drop'

[dferens]

How to reproduce:

from datetime import date
import numpy as np
import pandas as pd
import statsmodels.api as sm

X = pd.Series([np.NaN], pd.DatetimeIndex([date(2017,1,1)], freq='AS-JAN'))
Y = pd.Series([10], pd.DatetimeIndex([date(2017,1,1)], freq='AS-JAN'))
sm.OLS(X, sm.add_constant(Y), missing='drop')

Traceback:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/virtualenvs/test/lib/python2.7/site-packages/statsmodels/regression/linear_model.py", line 631, in __init__
    hasconst=hasconst, **kwargs)
  File "/virtualenvs/test/lib/python2.7/site-packages/statsmodels/regression/linear_model.py", line 526, in __init__
    weights=weights, hasconst=hasconst, **kwargs)
  File "/virtualenvs/test/lib/python2.7/site-packages/statsmodels/regression/linear_model.py", line 95, in __init__
    super(RegressionModel, self).__init__(endog, exog, **kwargs)
  File "/virtualenvs/test/lib/python2.7/site-packages/statsmodels/base/model.py", line 212, in __init__
    super(LikelihoodModel, self).__init__(endog, exog, **kwargs)
  File "/virtualenvs/test/lib/python2.7/site-packages/statsmodels/base/model.py", line 63, in __init__
    **kwargs)
  File "/virtualenvs/test/lib/python2.7/site-packages/statsmodels/base/model.py", line 88, in _handle_data
    data = handle_data(endog, exog, missing, hasconst, **kwargs)
  File "/virtualenvs/test/lib/python2.7/site-packages/statsmodels/base/data.py", line 630, in handle_data
    **kwargs)
  File "/virtualenvs/test/lib/python2.7/site-packages/statsmodels/base/data.py", line 65, in __init__
    **kwargs)
  File "/virtualenvs/test/lib/python2.7/site-packages/statsmodels/base/data.py", line 284, in handle_missing
    combined = dict(zip(combined_names, lmap(drop_nans, combined)))
  File "/virtualenvs/test/lib/python2.7/site-packages/statsmodels/base/data.py", line 282, in <lambda>
    drop_nans = lambda x: cls._drop_nans(x, nan_mask)
  File "/virtualenvs/test/lib/python2.7/site-packages/statsmodels/base/data.py", line 478, in _drop_nans
    return x.ix[nan_mask]
  File "/virtualenvs/test/lib/python2.7/site-packages/pandas/core/indexing.py", line 121, in __getitem__
    return self._getitem_axis(key, axis=0)
  File "/virtualenvs/test/lib/python2.7/site-packages/pandas/core/indexing.py", line 1077, in _getitem_axis
    return self._get_label(key, axis=axis)
  File "/virtualenvs/test/lib/python2.7/site-packages/pandas/core/indexing.py", line 136, in _get_label
    return self.obj._xs(label, axis=axis)
  File "/virtualenvs/test/lib/python2.7/site-packages/pandas/core/generic.py", line 2032, in xs
    loc = self.index.get_loc(key)
  File "/virtualenvs/test/lib/python2.7/site-packages/pandas/core/indexes/datetimes.py", line 1435, in get_loc
    stamp = Timestamp(key, tz=self.tz)
  File "pandas/_libs/tslib.pyx", line 402, in pandas._libs.tslib.Timestamp.__new__ (pandas/_libs/tslib.c:10051)
  File "pandas/_libs/tslib.pyx", line 1528, in pandas._libs.tslib.convert_to_tsobject (pandas/_libs/tslib.c:28851)
TypeError: Cannot convert input [False] of type <type 'numpy.bool_'> to Timestamp

In first call to pandas:

  File "/virtualenvs/test/lib/python2.7/site-packages/statsmodels/base/data.py", line 478, in _drop_nans
    return x.ix[nan_mask]

value of nan_mask is False.

---

version:

>>> sm.version.full_version
'0.8.0'

Tested on pandas versions 0.20.3 and 0.22.0.