Casting bool to object during join
```python
import pandas as pd

core_df = pd.DataFrame([
    {'id': 1},
    {'id': 2},
]).set_index('id')

df1 = pd.DataFrame([
    {'id': 1, 'foo': True},
    {'id': 2, 'foo': False},
]).set_index('id')

df2 = pd.DataFrame([
    {'id': 1, 'bar': 3},
    {'id': 2, 'bar': 4},
    {'id': 3, 'bar': 4},  # Adding a new row in df2 is required to create the issue
]).set_index('id')

result = core_df.join([df1, df2])
print(result.dtypes)
# With pandas 0.24.2
# foo     bool  <- stays a bool
# bar    int64
# dtype: object
#
# With pandas 0.25.1
# foo    object  <- Changed to object
# bar     int64
# dtype: object

```
#### Problem description

This is a kind of subtle issue when upgrading from `0.24` to `0.25`. When joining dataframes onto an initial dataframe, if one of the dataframes being joined in has an extra row compared to the other it will cause any boolean columns to be cast to object columns. This is a change in behavior from 0.24 which would leave them as bools. 

#### Expected Output

In the example above I would expect the `foo` column to remain of dtype `bool`.

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

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.3.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 18.6.0
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 0.25.1
numpy            : 1.16.3
pytz             : 2019.1
dateutil         : 2.8.0
pip              : 19.0.3
setuptools       : 41.1.0
Cython           : None
pytest           : 4.4.1
hypothesis       : None
sphinx           : 2.0.1
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : 0.9.3
psycopg2         : None
jinja2           : 2.10.1
IPython          : None
pandas_datareader: None
bs4              : 4.7.1
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : None
matplotlib       : 3.1.1
numexpr          : 2.6.9
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : 0.13.0
pytables         : None
s3fs             : None
scipy            : 1.2.1
sqlalchemy       : 1.3.3
tables           : 3.5.2
xarray           : None
xlrd             : None
xlwt             : None
xlsxwriter       : None

</details>
