BUG: dataframe concat method error when using join='inner'

[joonpark72]

Code Sample, a copy-pastable example if possible

df1 = pd.DataFrame(np.arange(9).reshape(3, 3), columns=['a', 'b', 'c'])
df3 = pd.DataFrame(np.arange(20, 26).reshape(3, 2), columns=['a', 'd'], index=[2, 3, 4])
pd.concat([df1, df3], axis=1, join='inner')

   a  b  c   a   d
0  0  1  2 NaN NaN
1  3  4  5 NaN NaN

Expected Output

     a    b    c     a     d
2  6.0  7.0  8.0  20.0  21.0

output of pd.show_versions()

### INSTALLED VERSIONS
------------------
commit: None
python: 2.7.12.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 58 Stepping 9, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None

pandas: 0.18.1
nose: 1.3.7
pip: 8.1.2
setuptools: 23.0.0
Cython: 0.24
numpy: 1.11.1
scipy: 0.17.1
statsmodels: 0.6.1
xarray: None
IPython: 4.2.0
sphinx: 1.4.1
patsy: 0.4.1
dateutil: 2.5.3
pytz: 2016.4
blosc: None
bottleneck: 1.1.0
tables: 3.2.2
numexpr: 2.6.0
matplotlib: 1.5.1
openpyxl: 2.3.2
xlrd: 1.0.0
xlwt: 1.1.2
xlsxwriter: 0.9.2
lxml: 3.6.0
bs4: 4.4.1
html5lib: 0.999
httplib2: None
apiclient: None
sqlalchemy: 1.0.13
pymysql: None
psycopg2: None
jinja2: 2.8
boto: 2.40.0
pandas_datareader: 0.2.1

[jreback]

fixed by #13170 and will be in 0.19.0, coming soon. (it also preserves the dtype of the join keys)

In [39]: pd.__version__
Out[39]: '0.18.1+379.g5c955cb'

In [40]: df1
Out[40]: 
   a  b  c
0  0  1  2
1  3  4  5
2  6  7  8

In [41]: df3
Out[41]: 
    a   d
2  20  21
3  22  23
4  24  25

In [42]: pd.concat([df1, df3], axis=1, join='inner')
Out[42]: 
   a  b  c   a   d
2  6  7  8  20  21