Pandas BUG?: Series.any / Series.all behavior for pyarrow vs. non-pyarrow empty/all-NA

Pandas version checks

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Reproducible Example

import pandas as pd

for dtype in ["bool", "boolean", "boolean[pyarrow]"]:
    ser = pd.Series([], dtype=dtype)
    print(dtype, ser.any(), ser.all())

Issue Description

bool False True
boolean False True
boolean[pyarrow] <NA> <NA>

At the moment Series.any and Series.all have inconsistent behavior for pyarrow vs. non-pyarrow dtypes for empty or all null data. The pyarrow behavior is coming from pyarrow.compute.any and pyarrow.compute.all which return null in these cases. I suspect different behavior here within pandas is likely to be problematic and confusing. Is it OK to diverge from pyarrow here in order to be more consistent within pandas?

Expected Behavior

Probably to match the behavior of non-pyarrow types

Installed Versions

.

Comment From: rhshadrach

I think the difference is in min_count; pyarrow defaults to 1 whereas pandas (where it exists) defaults to 0. I think pandas should use the pandas default when calling pyarrow.

Comment From: lukemanley

I think the difference is in min_count; pyarrow defaults to 1 whereas pandas (where it exists) defaults to 0. I think pandas should use the pandas default when calling pyarrow.

ah good point. That makes sense.