BUG: Inconsistent data type conversion with .sum
- [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.

---

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

```python
import pandas as pd
s = pd.Series([1, 2, 3, 4, 5])
print(s.sum().dtype)                    # int64
print(s.astype("float16").sum().dtype)  # float16
print(s.astype("float32").sum().dtype)  # float32
print(s.astype("int16").sum().dtype)    # int64 ???
print(s.astype("uint8").sum().dtype)    # int64 ???
```

#### Problem description

Summing a `float16` Series/DataFrame returns `float16` values.
Summing a `float32` Series/DataFrame returns `float32` values.
However, summing integer Series/DataFrames always returns `int64` values, regardless of their original type ( `int16`,  `uint8` etc.).

#### Expected Output

Summing `int32` values should return `int32` values, just like summing `float32` values returns `float32` values.

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

<details>

INSTALLED VERSIONS
------------------
commit           : db08276bc116c438d3fdee492026f8223584c477
python           : 3.8.5.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
Version          : 10.0.16299
machine          : AMD64
processor        : Intel64 Family 6 Model 78 Stepping 3, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : Italian_Italy.1252

pandas           : 1.1.3
numpy            : 1.19.3
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 20.2.4
setuptools       : 50.3.0.post20201006
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : None
IPython          : None
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : None
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
pyxlsb           : None
s3fs             : None
scipy            : None
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : None

</details>
