BUG: Create empty dataframe with string dtype fails "data type not understood"
- [x] I have checked that this issue has not already been reported.

- [x] I have confirmed this bug exists on the latest version of pandas.

- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.

---

#### Code Sample, a copy-pastable example

```python
In [1]: import pandas as pd

In [2]: pd.DataFrame({'a': ['b']}, dtype='string')
Out[2]:
   a
0  b

In [3]: pd.DataFrame(columns=['a'], dtype='string')
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-3-2e577cc30885> in <module>
----> 1 pd.DataFrame(columns=['a'], dtype='string')

~/lib/miniconda/envs/xport/lib/python3.8/site-packages/pandas/core/frame.py in __init__(self, data, index, columns, dtype, copy)
    433             )
    434         elif isinstance(data, dict):
--> 435             mgr = init_dict(data, index, columns, dtype=dtype)
    436         elif isinstance(data, ma.MaskedArray):
    437             import numpy.ma.mrecords as mrecords

~/lib/miniconda/envs/xport/lib/python3.8/site-packages/pandas/core/internals/construction.py in init_dict(data, index, columns, dtype)
    232         # no obvious "empty" int column
    233         if missing.any() and not is_integer_dtype(dtype):
--> 234             if dtype is None or np.issubdtype(dtype, np.flexible):
    235                 # GH#1783
    236                 nan_dtype = object

~/lib/miniconda/envs/xport/lib/python3.8/site-packages/numpy/core/numerictypes.py in issubdtype(arg1, arg2)
    391     """
    392     if not issubclass_(arg1, generic):
--> 393         arg1 = dtype(arg1).type
    394     if not issubclass_(arg2, generic):
    395         arg2_orig = arg2

TypeError: data type not understood

In [4]: pd.DataFrame(columns=['a'], dtype='float')
Out[4]:
Empty DataFrame
Columns: [a]
Index: []
```

#### Problem description

When trying to create an empty dataframe, one can specify some dtypes, like `'float'`, but `dtype='string'` raises `TypeError: data type not understood`.

#### Expected Output

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

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.8.2.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 19.4.0
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.0.3
numpy            : 1.18.2
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 20.0.2
setuptools       : 46.1.3.post20200330
Cython           : None
pytest           : 5.4.1
hypothesis       : None
sphinx           : 3.0.1
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.13.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : None
matplotlib       : None
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
pytest           : 5.4.1
pyxlsb           : None
s3fs             : None
scipy            : None
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
xlsxwriter       : None
numba            : None

</details>
