Type inferencing makes assignment of datetime to an object Series non-idempotent
#### Code Sample, a copy-pastable example if possible

```
>>> import pandas as pd
>>> s = pd.Series()
>>> ts = pd.Timestamp('2016-01-01')
>>> s['a'] = None
>>> s['b'] = ts
>>> s
a                   None
b    1451606400000000000
dtype: object
```

OK, no worries, we got coerced to integer. Now let's just redo the **same assignment**:

```
>>> s['b'] = ts
>>> s
a                   None
b    2016-01-01 00:00:00
dtype: object
```

That's ... suprising. This is probably just an unfortunate feature of a type inference algorithm, but it's awfully shocking.

#### Related examples for testing
#18410
#21143

#### Expected Output

The two outputs above would be identical; I'd prefer that they were both the second form (with timestamp information preserved), but anything consistent would be better than the current state.
#### output of `pd.show_versions()`

```
>>> pd.show_versions()

INSTALLED VERSIONS
------------------
commit: None
python: 2.7.11.final.0
python-bits: 64
OS: Darwin
OS-release: 15.6.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8

pandas: 0.18.1
nose: None
pip: 8.1.2
setuptools: 25.1.4
Cython: None
numpy: 1.11.1
scipy: None
statsmodels: None
xarray: None
IPython: None
sphinx: None
patsy: None
dateutil: 2.5.3
pytz: 2016.6.1
blosc: None
bottleneck: None
tables: None
numexpr: None
matplotlib: None
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: None
boto: None
pandas_datareader: None
```
