diff --git a/doc/source/whatsnew/v0.19.1.txt b/doc/source/whatsnew/v0.19.1.txt
index 8bebe5e782e3c..353e7a75dea7b 100644
--- a/doc/source/whatsnew/v0.19.1.txt
+++ b/doc/source/whatsnew/v0.19.1.txt
@@ -63,12 +63,8 @@ Bug Fixes
 - Bug in ``MultiIndex.set_levels`` where illegal level values were still set after raising an error (:issue:`13754`)
 - Bug in ``DataFrame.to_json`` where ``lines=True`` and a value contained a ``}`` character (:issue:`14391`)
 - Bug in ``df.groupby`` causing an ``AttributeError`` when grouping a single index frame by a column and the index level (:issue`14327`)
-
-
-
-
-
-
-
-
 - Bug in ``pd.pivot_table`` may raise ``TypeError`` or ``ValueError`` when ``index`` or ``columns`` is not scalar and ``values`` is not specified (:issue:`14380`)
+- Bug in ``pd.pivot_table`` may raise ``TypeError`` or ``ValueError`` when ``index`` or ``columns``
+- Bug in ``pd.to_numeric`` where a 0 was not unsigned on a downcast = 'unsigned' argument (:issue:`14401`)
+- Bug in ``pd.pivot_table`` may raise ``TypeError`` or ``ValueError`` when ``index`` or ``columns``
+  is not scalar and ``values`` is not specified (:issue:`14380`)
diff --git a/pandas/tools/tests/test_util.py b/pandas/tools/tests/test_util.py
index 8c16308d79a31..0fe2be5008dae 100644
--- a/pandas/tools/tests/test_util.py
+++ b/pandas/tools/tests/test_util.py
@@ -401,6 +401,33 @@ def test_downcast(self):
             res = pd.to_numeric(data, downcast=downcast)
             tm.assert_numpy_array_equal(res, expected)
 
+    def test_downcast_limits(self):
+        # Test the limits of each downcast. Bug: #14401. 
+        dtype_downcast_min_max = [
+                ('int8', 'integer', [np.iinfo(np.int8).min, np.iinfo(np.int8).max]),
+                ('int16', 'integer', [np.iinfo(np.int16).min, np.iinfo(np.int16).max]),
+                ('int32', 'integer', [np.iinfo(np.int32).min, np.iinfo(np.int32).max]),
+                ('int64', 'integer', [np.iinfo(np.int64).min, np.iinfo(np.int64).max]),
+                ('uint8', 'unsigned', [np.iinfo(np.uint8).min, np.iinfo(np.uint8).max]),
+                ('uint16', 'unsigned', [np.iinfo(np.uint16).min, np.iinfo(np.uint16).max]),
+                ('uint32', 'unsigned', [np.iinfo(np.uint32).min, np.iinfo(np.uint32).max]),
+                # ('uint64', 'unsigned', [np.iinfo(np.uint64).min, np.iinfo(np.uint64).max]),
+                ('int16', 'integer', [np.iinfo(np.int8).min, np.iinfo(np.int8).max + 1]),
+                ('int32', 'integer', [np.iinfo(np.int16).min, np.iinfo(np.int16).max + 1]),
+                ('int64', 'integer', [np.iinfo(np.int32).min, np.iinfo(np.int32).max + 1]),
+                ('int16', 'integer', [np.iinfo(np.int8).min - 1, np.iinfo(np.int16).max]),
+                ('int32', 'integer', [np.iinfo(np.int16).min - 1, np.iinfo(np.int32).max]),
+                ('int64', 'integer', [np.iinfo(np.int32).min - 1, np.iinfo(np.int64).max]),
+                ('uint16', 'unsigned', [np.iinfo(np.uint8).min, np.iinfo(np.uint8).max + 1]),
+                ('uint32', 'unsigned', [np.iinfo(np.uint16).min, np.iinfo(np.uint16).max + 1]),
+                # ('uint64', 'unsigned', [np.iinfo(np.uint32).min, np.iinfo(np.uint32).max + 1]),
+                ]
+
+        for dtype, downcast, min_max in dtype_downcast_min_max:
+            series = pd.to_numeric(pd.Series(min_max), downcast=downcast)
+            tm.assert_equal(series.dtype, dtype)
+
+
 if __name__ == '__main__':
     nose.runmodule(argv=[__file__, '-vvs', '-x', '--pdb', '--pdb-failure'],
                    exit=False)
diff --git a/pandas/tools/util.py b/pandas/tools/util.py
index fec56328c1721..b50bf9dc448bc 100644
--- a/pandas/tools/util.py
+++ b/pandas/tools/util.py
@@ -205,7 +205,7 @@ def to_numeric(arg, errors='raise', downcast=None):
 
         if downcast in ('integer', 'signed'):
             typecodes = np.typecodes['Integer']
-        elif downcast == 'unsigned' and np.min(values) > 0:
+        elif downcast == 'unsigned' and np.min(values) >= 0:
             typecodes = np.typecodes['UnsignedInteger']
         elif downcast == 'float':
             typecodes = np.typecodes['Float']