BUG: specifying fill_value in pandas.DataFrame.shift() messes with index of empty dataframes
- [ x] I have checked that this issue has not already been reported.

- [ x] I have confirmed this bug exists on the latest version of pandas.

- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.

---

**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug.

#### Code Sample, a copy-pastable example

```python
import pandas as pd

# create empty df, and set a multi index
empty_df = pd.DataFrame(columns=["a", "b", "c"])
multi_index_empty_df = empty_df.set_index(keys=["a", "b"])

# index is different when applying shift on grouping when specifying a fill value
assert multi_index_empty_df.groupby(["a","b"]).shift(1).index.names == multi_index_empty_df.groupby(["a","b"]).shift(1, fill_value=0).index.names

```

#### Problem description
I discovered this problem when a unit test failed on a function that performed a groupby and shift on an empty dataframe.

Specifying `fill_value` in pandas.DataFrame.shift() should not alter the index that was set on a dataframe. This is not the case for empty dataframes with a multi-index, as the example above shows. 

#### Expected Output
When executing:
```python
multi_index_empty_df.groupby(["a","b"]).shift(1).index.names
```
I get the output:
```
FrozenList(['a', 'b'])
```

But when executing
```python
multi_index_empty_df.groupby(["a","b"]).shift(1, fill_value=0).index.names
```
I should get the same output, but instead I get
```
FrozenList([None])
```
#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.1.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 18.7.0
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : en_US.UTF-8
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.0.5
numpy            : 1.19.0
pytz             : 2018.7
dateutil         : 2.7.5
pip              : 18.1
setuptools       : 40.6.3
Cython           : 0.29.2
pytest           : 4.0.2
hypothesis       : None
sphinx           : 1.8.2
blosc            : None
feather          : None
xlsxwriter       : 1.1.2
lxml.etree       : 4.2.5
html5lib         : 1.0.1
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.19.0
pandas_datareader: None
bs4              : 4.6.3
bottleneck       : 1.2.1
fastparquet      : None
gcsfs            : None
lxml.etree       : 4.2.5
matplotlib       : 3.2.2
numexpr          : 2.6.8
odfpy            : None
openpyxl         : 2.5.12
pandas_gbq       : None
pyarrow          : None
pytables         : None
pytest           : 4.0.2
pyxlsb           : None
s3fs             : None
scipy            : 1.5.1
sqlalchemy       : 1.2.15
tables           : 3.4.4
tabulate         : None
xarray           : None
xlrd             : 1.2.0
xlwt             : 1.3.0
xlsxwriter       : 1.1.2
numba            : 0.41.0

</details>
