Series with dtype=object does unexpected type conversion
#### Code Sample, a copy-pastable example if possible

```python
# Example 1

timestamp = pd.Timestamp(1412526600000000000)
series = pd.Series([], dtype=object)
series['timestamp'] = timestamp
type(series.timestamp)

# Example 2

series = pd.Series([], dtype=object)
series['anything'] = 300.0
series['timestamp'] = timestamp
type(series.timestamp)

```
#### Problem description

In the first example, the timestamp is still a Timestamp.

In the second example, the timestamp gets converted to int.

#### Expected Output

I expected the timestamp to continue to be a Timestamp, especially because the dtype of the Series is object.  Why are the types of the values getting converted?

#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.5.final.0
python-bits: 64
OS: Linux
OS-release: 4.4.0-128-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.utf8
LOCALE: en_US.UTF-8

pandas: 0.23.0
pytest: 3.5.1
pip: 10.0.1
setuptools: 39.1.0
Cython: 0.28.2
numpy: 1.14.3
scipy: 1.1.0
pyarrow: None
xarray: None
IPython: 6.4.0
sphinx: 1.7.4
patsy: 0.5.0
dateutil: 2.7.3
pytz: 2018.4
blosc: None
bottleneck: 1.2.1
tables: 3.4.3
numexpr: 2.6.5
feather: None
matplotlib: 2.2.2
openpyxl: 2.5.3
xlrd: 1.1.0
xlwt: 1.3.0
xlsxwriter: 1.0.4
lxml: 4.2.1
bs4: 4.6.0
html5lib: 1.0.1
sqlalchemy: 1.2.7
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
</details>
