df.to_stata fails when a column of type object contains only None
#### Code Sample, a copy-pastable example if possible

```python
import pandas as pd
df = pd.DataFrame({'a': ['a', None]})
df.to_stata('test.dta')
df = pd.DataFrame({'a': [None, 'a']})
df.to_stata('test.dta')
df = pd.DataFrame({'a': [None, None]})
df.to_stata('test.dta')
# ValueError: Writing general object arrays is not supported
```

#### Problem description

The `df.to_stata()` method writes columns containing `None` without error when there is at least one string value in the column, but fails if the column contains only `None`. It's unclear what data type to write a column of `None` as, so maybe that's why this isn't supported? I would propose that a column with values of only `None` be written as `str1` with empty strings.

I came across this error because I read in a Parquet file with `pd.read_parquet()` and was unable to write the file to Stata format. In the Parquet schema, the column had type `BYTE_ARRAY UTF8`, but since the column had only missing values, it was read into Pandas as only `None`.

#### Expected Output

Stata file written to disk with missing values for the column with `None`.

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

<details>

```
INSTALLED VERSIONS
------------------
commit: None
python: 3.6.4.final.0
python-bits: 64
OS: Linux
OS-release: 4.15.0-38-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.23.4
pytest: 3.3.2
pip: 18.0
setuptools: 40.0.0
Cython: 0.28.3
numpy: 1.14.2
scipy: 1.0.0
pyarrow: 0.11.1
xarray: None
IPython: 6.5.0
sphinx: 1.6.6
patsy: 0.5.0
dateutil: 2.7.3
pytz: 2017.3
blosc: None
bottleneck: 1.2.1
tables: 3.4.2
numexpr: 2.6.4
feather: None
matplotlib: 2.1.2
openpyxl: 2.4.10
xlrd: 1.1.0
xlwt: 1.3.0
xlsxwriter: 1.0.2
lxml: 4.1.1
bs4: 4.6.3
html5lib: 1.0.1
sqlalchemy: 1.1.14
pymysql: None
psycopg2: 2.7.5 (dt dec pq3 ext lo64)
jinja2: 2.10
s3fs: None
fastparquet: 0.1.5
pandas_gbq: None
pandas_datareader: None
```

</details>
