to_numeric not correctly converting decimal type to float
#### Code Sample, a copy-pastable example if possible

```python
import pandas as pd
import decimal 

# Set up date
data = {'line': [1,2,3,4],
        'decimal': [12345678.1, 12345678.01, 12345678.001, 12345678.0001],
        'original': [12345678.1, 12345678.01, 12345678.001, 12345678.0001]}
df = pd.DataFrame(data)

df.to_csv('df.csv', index=False)

# Convert 'decimal' to decimal type
df = pd.read_csv('df.csv', converters={'decimal': decimal.Decimal})

df['float_n'] = pd.to_numeric(df['decimal'], downcast='float', errors='coerce')
df['float_a'] = df['decimal'].astype(float)

for index, row in df.iterrows():
    print(row['float_n'], row['float_a'])

```
#### Problem description

I'm using to_numeric to convert the results of a database query from a decimal type to a float. I've found that to_numeric rounds the result in some cases giving an incorrect answer. Converting the data using astype correctly converts the data.

I can't reproduce my example here because it uses a database call and it's a work project, but I have created sample code that shows the same behavior. 

Here's the output from my example:

12345678.0 12345678.1
12345678.0 12345678.01
12345678.0 12345678.001
12345678.0 12345678.0001

The first column is the result of the to_numeric conversion, the second column is the result of the astype(float) conversion. These columns should contain the same values, but they don't. to_numeric is rounding the results and astype isn't.

#### Expected Output

12345678.1 12345678.1
12345678.01 12345678.01
12345678.001 12345678.001
12345678.0001 12345678.0001

In other words, to_numeric and astype should give the same result - to_numeric should not round the data.

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

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.4.final.0
python-bits: 64
OS: Darwin
OS-release: 17.6.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: en_US.UTF-8
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.22.0
pytest: 3.3.2
pip: 10.0.1
setuptools: 38.4.0
Cython: 0.27.3
numpy: 1.14.0
scipy: 1.0.0
pyarrow: None
xarray: None
IPython: 6.2.1
sphinx: 1.6.6
patsy: 0.5.0
dateutil: 2.6.1
pytz: 2017.3
blosc: None
bottleneck: 1.2.1
tables: 3.4.2
numexpr: 2.6.4
feather: None
matplotlib: 2.1.2
openpyxl: 2.4.10
xlrd: 1.1.0
xlwt: 1.2.0
xlsxwriter: 1.0.2
lxml: 4.1.1
bs4: 4.6.0
html5lib: 1.0.1
sqlalchemy: 1.2.1
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None

</details>
