BUG: Default value for `Series(dtype=int)` is not `pd.NA`
- [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
pd.Series(index=[0], dtype=int)

```

#### Problem description

For other types, the default missing value indicator is set properly:
```Python
pd.Series(index=[0], dtype=float)
```
0   NaN
dtype: float64

```Python
pd.Series(index=[0], dtype="datetime64[ns]")
```
0   NaT
dtype: datetime64[ns]

```Python
pd.Series(index=[0], dtype=bool)
```
0    False
dtype: bool
(This might be tricky, but understandable)

However, for integer types, the default missing value is set to 0 instead of `pd.NA`, which is dangerous for interpretation.

#### Expected Output

Either

```
0    <NA>
dtype: Int64
```

or 
```
0    NaN
dtype: float64
```

makes sense, given how `int64` is converted when having missing values, the latter case may be better.

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

<details>

INSTALLED VERSIONS
------------------
commit           : c7f7443c1bad8262358114d5e88cd9c8a308e8aa
python           : 3.7.11.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
Version          : 10.0.19041
machine          : AMD64
processor        : Intel64 Family 6 Model 142 Stepping 10, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : None.None

pandas           : 1.3.1
numpy            : 1.20.3
pytz             : 2021.1
dateutil         : 2.8.2
pip              : 21.2.2
setuptools       : 52.0.0.post20210125
Cython           : 0.29.24
pytest           : 6.1.2
hypothesis       : 6.14.1
sphinx           : 4.0.2
blosc            : None
feather          : None
xlsxwriter       : 1.4.4
lxml.etree       : 4.6.3
html5lib         : 1.1
pymysql          : 1.0.2
psycopg2         : None
jinja2           : 3.0.1
IPython          : 7.22.0
pandas_datareader: None
bs4              : 4.9.3
bottleneck       : 1.3.2
fsspec           : 2021.07.0
fastparquet      : None
gcsfs            : None
matplotlib       : 3.4.2
numexpr          : 2.7.3
odfpy            : None
openpyxl         : 3.0.7
pandas_gbq       : None
pyarrow          : 3.0.0
pyxlsb           : None
s3fs             : 0.4.2
scipy            : 1.6.2
sqlalchemy       : 1.4.22
tables           : 3.6.1
tabulate         : 0.8.9
xarray           : 0.19.0
xlrd             : 2.0.1
xlwt             : 1.3.0
numba            : 0.53.0

</details>
