BUG: Index.where vs Series.where mismatch
If in merge._maybe_add_join_keys we replace a call to Index.where with a call to Series.where, we get a test failure because of the following mismatch:

```
dr = pd.date_range("2001-01-01", periods=3)
lvals = pd.DatetimeIndex([dr[0], dr[1], pd.NaT])._data
rvals = pd.Categorical([dr[0], pd.NaT, dr[2]])

mask = np.array([False, False, True])

>>> pd.Series(lvals).where(~mask, rvals)._values
array([Timestamp('2001-01-01 00:00:00'), Timestamp('2001-01-02 00:00:00'),
       978480000000000000], dtype=object)

>>> pd.Index(lvals).where(~mask, rvals)._values
<DatetimeArray>
['2001-01-01 00:00:00', '2001-01-02 00:00:00', '2001-01-03 00:00:00']
Length: 3, dtype: datetime64[ns]
```

The Index version looks better behaved.  These should share an implementation.