read_csv ignores dtype for empty CSV files
#### Code Sample, a copy-pastable example if possible

```python
>>> import io
>>> import pandas as pd
>>> pd.read_csv(io.StringIO('foo,bar'), header=0, dtype=np.float64).values
array([], shape=(0, 2), dtype=object)
```
#### Problem description

CSV reader doesn't respect the given dtype `np.float64` but sets `object` dtype instead.

#### Expected Output

```python
array([], shape=(0, 2), dtype=float64)
```

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

<details>
INSTALLED VERSIONS
------------------
commit: None
python: 3.5.2.final.0
python-bits: 64
OS: Linux
OS-release: 4.8.8-gnu-1
machine: x86_64
processor: 
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.19.1
nose: 1.3.7
pip: 8.1.2
setuptools: 28.8.0
Cython: 0.25.1
numpy: 1.11.2
scipy: 0.18.1
statsmodels: None
xarray: None
IPython: 5.1.0
sphinx: 1.4.8
patsy: None
dateutil: 2.6.0
pytz: 2016.7
blosc: None
bottleneck: None
tables: 3.3.0
numexpr: 2.6.1
matplotlib: 1.5.3
openpyxl: None
xlrd: 1.0.0
xlwt: None
xlsxwriter: None
lxml: None
bs4: 4.5.1
html5lib: None
httplib2: 0.9.2
apiclient: 1.5.5
sqlalchemy: 1.1.4
pymysql: None
psycopg2: 2.6.2 (dt dec pq3 ext lo64)
jinja2: 2.8
boto: None
pandas_datareader: None
</details>
