BUG: don't lose dtypes when concatenating empty array-likes
I develop an application that does quite a bit of data manipulation. Being aware of `pandas` being functional-but-not-really-heavily-optimized I use it to maintain label consistency and for grouping/merging data, heavy-duty maths is usually done with `numpy` ufuncs. The application contains entities that have no data at the beginning and receive data over their lifetimes. Every once in a while an incoming data chunk will contain no data for a certain entity. Usually it's fine but if the entity was just created the following happens:

``` python
In [1]: pd.__version__ 
Out[1]: '0.13.0rc1-92-gf6fd509'

In [2]: data = pd.Series(dtype=np.float)

In [3]: chunk = pd.Series(dtype=np.float)

In [4]: pd.concat([data, chunk])
Out[4]: Series([], dtype: object)

```

After that ufuncs like `isnan` cease to work on `data.values` since its dtype has changed to `object`. This PR fixes it.
