BUG: Resampling PeriodIndex-ed to multiple of frequencies not working as expected
#### Code Sample, a copy-pastable example if possible

```python
In [1]: import numpy as np
 In [2]: import pandas as pd

 In [3]: s = pd.Series([2017, 2018], index=pd.period_range('2017', freq='A', periods=2))

 In [4]: s.resample('2Q', kind='period').ffill()
Warning: multiple of frequency -> timestamps
Out[4]: 
2017-03-31    2017
2017-09-30    2017
2018-03-31    2018
Freq: 2Q-DEC, dtype: int64

In [7]: s2 = pd.Series(np.arange(12), index=pd.period_range('2017-01', freq='M', periods=12))
 
In [8]: s2.resample('2Q', kind='period').mean()
Warning: multiple of frequency -> timestamps
Out[8]: 
2017-03-31     1.0
2017-09-30     5.5
2018-03-31    10.0
Freq: 2Q-DEC, dtype: float64
```

To compare with, results for resampling to base frequency (no multiples) returning PeriodIndex-ed and covering the full original time span:
<details>

```python
 In [5]: s.resample('Q', kind='period').ffill()
Out[5]: 
2017Q1    2017
2017Q2    2017
2017Q3    2017
2017Q4    2017
2018Q1    2018
2018Q2    2018
2018Q3    2018
2018Q4    2018
Freq: Q-DEC, dtype: int64

In [9]: s2.resample('Q', kind='period').mean()
Out[9]: 
2017Q1     1
2017Q2     4
2017Q3     7
2017Q4    10
Freq: Q-DEC, dtype: int64
```
</details>

#### Problem description

* I'd expect resampling PeriodIndex-ed series/dataframes would return a PeriodIndex-ed result by default, even more when given```kind='period'```.
* Moreover, I'd expect the original full time span to be covered by the resampling result (upsampling A->2Q would return 2 periods per year, downsampling M->2Q would return 2 periods per 12 months).

As indicated by the warning message, resampling to multiple of frequencies falls back to timestamp-based resampling. Both work fine when resampling to a "base" frequency without any multiple.

#### Expected Output

```python
In [4]: s.resample('2Q', kind='period').ffill()
Out[4]:
2017Q1    2017
2017Q3    2017
2018Q1    2018
2018Q3    2018
Freq: 2Q-DEC, dtype: int64

In [8]: s2.resample('2Q', kind='period').mean()
Out[8]:
2017Q1    2.5
2017Q3    8.5
Freq: 2Q-DEC, dtype: float64
```

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

<details>
INSTALLED VERSIONS
------------------
commit: None
python: 3.6.1.final.0
python-bits: 64
OS: Darwin
OS-release: 15.6.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: de_DE.UTF-8
LOCALE: de_DE.UTF-8

pandas: 0.19.2
nose: None
pip: 9.0.1
setuptools: 33.1.1.post20170320
Cython: None
numpy: 1.12.1
scipy: 0.19.0
statsmodels: 0.8.0
xarray: None
IPython: 5.3.0
sphinx: None
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2016.10
blosc: None
bottleneck: 1.2.0
tables: None
numexpr: 2.6.2
matplotlib: 2.0.0
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: 4.5.3
html5lib: 0.999
httplib2: None
apiclient: None
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.9.5
boto: None
pandas_datareader: None
</details>
