read_csv dtype 'object' doesn't work for index column
I'm working on a little pandas lesson. The CSV has a column with leading '0' which should be treated as text. When I try to read the CSV and indicate that that column is the `index`, the `dtype` argument doesn't work. I can use `S7` as the `dtype` instead of `object` but @wesm [suggests using 'object'](http://stackoverflow.com/questions/16929056/pandas-read-csv-dtype-leading-zeros#comment24510329_16929535)
#### Code Sample, a copy-pastable example if possible

from StringIO import StringIO
import pandas as pd
data = """
fips,name,popest2014
0800760,"Aguilar town, Colorado",479
0800925,"Akron town, Colorado",1694
0801090,"Alamosa city, Colorado",9531
"""
error_case = pd.read_csv(StringIO(data), index_col=0, dtype={'fips': object})
print "Error case, dtype should be object "
print error_case.index.dtype # 'int64'
expected1 = pd.read_csv(StringIO(data), dtype={'fips': object})
print "Works with object, not an index column"
print expected1.fips.dtype # 'O'
expected2 = pd.read_csv(StringIO(data), index_col=0, dtype={'fips': 'S7'})
print "Works with 'S7', as an index column"
print expected2.index.dtype # 'O'
#### Expected Output

That the dtype for the FIPS column as an index would be `object`
#### output of `pd.show_versions()`
## INSTALLED VERSIONS

commit: None
python: 2.7.9.final.0
python-bits: 64
OS: Darwin
OS-release: 15.3.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8

pandas: 0.17.1
nose: None
pip: 8.0.3
setuptools: 20.1.1
Cython: None
numpy: 1.10.4
scipy: None
statsmodels: None
IPython: 4.1.1
sphinx: None
patsy: None
dateutil: 2.4.2
pytz: 2015.7
blosc: None
bottleneck: None
tables: None
numexpr: None
matplotlib: None
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: None
pymysql: None
psycopg2: None
Jinja2: None

```
```
