BUG: read_csv doesn't respect dtype argument for index_col
#### Code Sample

```python
import pandas as pd
from io import StringIO
data = '"zip1","zip2","mi_to_zcta5"\n'
data += '"00601","00631",5.43229145138995\n'
data += '"00601","00641",6.19718605765618'

df1 = pd.read_csv(StringIO(data), header=0, dtype={'zip1': str, 'zip2': str})
df1.zip1.dtype.name
# Object

df2 = pd.read_csv(StringIO(data), header=0, index_col='zip1', dtype={'zip1': str, 'zip2': str})
df2.index.dtype.name
# int64
```

#### Problem description

The column being read as the index should respect the dtype provided in the `dtype` argument when the name provided with `index_col` is a key in the `dtype` dict.

I couldn't find another issue with this specific problem, but please correct me if there is.

#### Expected Output

```python
df1 = pd.read_csv(StringIO(data), header=0, dtype={'zip1': str, 'zip2': str})
df1.set_index('zip1').index.dtype.name
# Object
```

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

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.4.final.0
python-bits: 64
OS: Linux
OS-release: 2.6.32-696.18.7.el6.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.22.0
pytest: 3.4.2
pip: 9.0.3
setuptools: 38.6.0
Cython: 0.27.3
numpy: 1.14.2
scipy: 1.0.0
pyarrow: 0.9.0
xarray: None
IPython: 6.2.1
sphinx: 1.7.1
patsy: 0.5.0
dateutil: 2.7.2
pytz: 2018.3
blosc: None
bottleneck: 1.2.1
tables: 3.4.2
numexpr: 2.6.4
feather: 0.4.0
matplotlib: 2.2.0
openpyxl: 2.4.9
xlrd: 1.1.0
xlwt: 1.3.0
xlsxwriter: 1.0.2
lxml: 4.2.1
bs4: 4.6.0
html5lib: 1.0.1
sqlalchemy: 1.1.15
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: 0.1.4
pandas_gbq: None
pandas_datareader: None

</details>
	