BUG: convert_dtypes throws a ValueError when called on an empty DataFrame
- [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.

---

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

```python
# Your code here
import pandas as pd

pd.DataFrame().convert_dtypes()
```

#### Problem description

convert_dtypes throws a "ValueError: No objects to concatenate" exception when called on an empty DataFrame. I find that a problem because I have use cases of chaining up DataFrame transform calls fluently that may result in an empty DataFrame before the convert_dtypes call. I don't want want to break up the transform calls to check for an empty DataFrame or handle the ValueError.

#### Expected Output

I expect calling convert_dtypes on an empty DataFrame should return an empty DataFrame without error.

```python
import pandas as pd

df = pd.DataFrame().convert_dtypes()
assert df.empty
```

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

<details>

INSTALLED VERSIONS
------------------
commit           : f2c8480af2f25efdbd803218b9d87980f416563e
python           : 3.8.8.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 20.3.0
Version          : Darwin Kernel Version 20.3.0: Thu Jan 21 00:07:06 PST 2021; root:xnu-7195.81.3~1/RELEASE_X86_64
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : en_AU.UTF-8
LOCALE           : en_AU.UTF-8

pandas           : 1.2.3
numpy            : 1.20.1
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 21.0.1
setuptools       : 49.6.0.post20200917
Cython           : None
pytest           : 6.0.2
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : 1.3.7
lxml.etree       : 4.6.2
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.21.0
pandas_datareader: None
bs4              : 4.9.3
bottleneck       : 1.3.2
fsspec           : 0.8.2
fastparquet      : 0.5.0
gcsfs            : None
matplotlib       : 3.3.4
numexpr          : 2.7.3
odfpy            : None
openpyxl         : 3.0.7
pandas_gbq       : None
pyarrow          : 3.0.0
pyxlsb           : None
s3fs             : 0.2.2
scipy            : 1.5.3
sqlalchemy       : 1.3.23
tables           : 3.6.1
tabulate         : 0.8.7
xarray           : 0.16.1
xlrd             : 2.0.1
xlwt             : None
numba            : 0.51.2

</details>
