BUG: Fix `pd.to_numeric` to have consistent behavior for date-like arguments
- [ ] closes #43280
- [x] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them
- [ ] whatsnew entry

`pd.to_numeric` was having an inconsistent behavior when using in datelike objects and was returning wrong result when using with `pd.NaT`


**In master:**
```python
>>> import pandas as pd
>>> from datetime import datetime
>>> from functools import partial
>>> pd.to_numeric(datetime(2021, 8, 22), errors="coerce")
nan
>>> pd.to_numeric(pd.Series(datetime(2021, 8, 22)), errors="coerce")
0    1629590400000000000
dtype: int64
>>> pd.Series([datetime(2021, 8, 22)]).apply(partial(pd.to_numeric), errors="coerce")
0   NaN
dtype: float64
>>>
>>> pd.to_numeric(pd.NaT, errors="coerce")
nan
>>> pd.to_numeric(pd.Series(pd.NaT), errors="coerce")
0   -9223372036854775808
dtype: int64
>>> pd.Series(pd.NaT).apply(partial(pd.to_numeric), errors="coerce")
0   NaN
dtype: float64

```

**In this PR:**
```python
>>> import pandas as pd
>>> from datetime import datetime
>>> from functools import partial
>>> pd.to_numeric(datetime(2021, 8, 22), errors="coerce")
nan
>>> pd.to_numeric(pd.Series(datetime(2021, 8, 22)), errors="coerce")
0   NaN
dtype: float64
>>> pd.Series([datetime(2021, 8, 22)]).apply(partial(pd.to_numeric), errors="coerce")
0   NaN
dtype: float64
>>>
>>> pd.to_numeric(pd.NaT, errors="coerce")
nan
>>> pd.to_numeric(pd.Series(pd.NaT), errors="coerce")
0   NaN
dtype: float64
>>> pd.Series(pd.NaT).apply(partial(pd.to_numeric), errors="coerce")
0   NaN
dtype: float64
```

Please let me know if this approach makes sense so I can add the tests.
Hello @hec10r! Thanks for updating this PR. We checked the lines you've touched for [PEP 8](https://www.python.org/dev/peps/pep-0008) issues, and found:





There are currently no PEP 8 issues detected in this Pull Request. Cheers! :beers: 

##### Comment last updated at 2021-08-31 14:35:27 UTC i thing already data is consider as object , then why you again defining as a object @jreback Thanks for your review.

This PR will likely be close and I will open a new one based on the discussion that we had in https://github.com/pandas-dev/pandas/issues/43280. It would be great to have your input there as well. This pull request is stale because it has been open for thirty days with no activity. Please update or respond to this comment if you're still interested in working on this. Thanks for the PR but as mentioned in https://github.com/pandas-dev/pandas/issues/43280#issuecomment-910349096, this will probably need a different approach. Closing due to being stale