BUG/COMPAT: Series bool type not promoted to object when introducing NaNs
#### Code Sample, a copy-pastable example if possible

```
In [2]: import pandas as pd

In [3]: a = pd.Series([True,False,True])

In [4]: a
Out[4]: 
0     True
1    False
2     True
dtype: bool

In [6]: a[0] = pd.np.nan

In [7]: a
Out[7]: 
0    NaN
1    0.0
2    1.0
dtype: float64
```
#### Expected Output

based on type promotions mentioned [here](http://pandas.pydata.org/pandas-docs/stable/gotchas.html#nan-integer-na-values-and-na-type-promotions) I would expect the series to get promoted to `object` to allow for `NaN`s. 

> When introducing NAs into an existing Series or DataFrame via reindex or some other means, boolean and integer types will be promoted to a different dtype in order to store the NAs. These are summarized by this table:

```
In [7]: a
Out[7]: 
0      NaN
1    False
2     True
dtype: object
```
#### output of `pd.show_versions()`

``````
In [2]: pd.show_versions()

INSTALLED VERSIONS
------------------
commit: None
python: 2.7.11.final.0
python-bits: 64
OS: Darwin
OS-release: 15.4.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: en_US.UTF-8
LANG: en_US

pandas: 0.18.0
nose: 1.3.7
pip: 8.1.1
setuptools: 20.6.7
Cython: None
numpy: 1.10.4
scipy: 0.17.0
statsmodels: None
xarray: None
IPython: 4.1.2
sphinx: 1.3.5
patsy: None
dateutil: 2.5.2
pytz: 2016.3
blosc: None
bottleneck: None
tables: None
numexpr: None
matplotlib: 1.5.1
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: 4.4.1
html5lib: 0.999
httplib2: None
apiclient: None
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.8
boto: 2.39.0```
``````
