PERF: concat perf
For `Series[period]`, `pd.concat` is about 6x slower than `PeriodArray._concat_same_type`. There's always going to be some overhead, but I  wonder how much we can narrow this.

```python
In [1]: import numpy as np
   ...: import pandas as pd
   ...:
   ...: a = np.random.randint(2000, 2100, size=1000)
   ...: b = np.random.randint(2000, 2100, size=1000)
   ...:
   ...: x = pd.core.arrays.period_array(a, freq='B')
   ...: y = pd.core.arrays.period_array(b, freq='B')
   ...:
   ...: s = pd.Series(x)
   ...: t = pd.Series(y)


In [2]: %timeit pd.concat([s, t], ignore_index=True)
523 µs ± 22.6 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)

In [3]: %timeit x._concat_same_type([x, y])
90.1 µs ± 948 ns per loop (mean ± std. dev. of 7 runs, 10000 loops each)
```