diff --git a/arch/tests/univariate/test_volatility.py b/arch/tests/univariate/test_volatility.py
index 5767467ce8..cd6533e99b 100644
--- a/arch/tests/univariate/test_volatility.py
+++ b/arch/tests/univariate/test_volatility.py
@@ -603,6 +603,7 @@ def test_warnings(self):
         garch = GARCH()
         parameters = np.array([0.1, 0.2, 0.8, 4.0])
         studt = StudentsT()
+        warnings.simplefilter('always', UserWarning)
         with warnings.catch_warnings(record=True) as w:
             garch.simulate(parameters, 1000, studt.simulate([4.0]))
             assert_equal(len(w), 1)
diff --git a/arch/unitroot/unitroot.py b/arch/unitroot/unitroot.py
index 1d8a2fcfbd..49cc5ad0ba 100644
--- a/arch/unitroot/unitroot.py
+++ b/arch/unitroot/unitroot.py
@@ -7,6 +7,7 @@
                    array, inf, abs, log, sort, polyval, empty, argwhere, arange, squeeze)
 from numpy.linalg import pinv
 from scipy.stats import norm
+from pandas import DataFrame
 
 from statsmodels.regression.linear_model import OLS
 from statsmodels.tsa.tsatools import lagmat
@@ -167,6 +168,12 @@ def _df_select_lags(y, trend, max_lags, method):
     return ic_best, best_lag
 
 
+def _add_column_names(rhs, lags):
+    """Return a DataFrame with named columns"""
+    lag_names = ['Diff.L{0}'.format(i) for i in range(1, lags + 1)]
+    return DataFrame(rhs, columns=['Level.L1'] + lag_names)
+
+
 def _estimate_df_regression(y, trend, lags):
     """Helper function that estimates the core (A)DF regression
 
@@ -195,9 +202,10 @@ def _estimate_df_regression(y, trend, lags):
     nobs = rhs.shape[0]
     lhs = rhs[:, 0].copy()  # lag-0 values are lhs, Is copy() necessary?
     rhs[:, 0] = y[-nobs - 1:-1]  # replace lag 0 with level of y
+    rhs = _add_column_names(rhs, lags)
 
     if trend != 'nc':
-        rhs = add_trend(rhs[:, :lags + 1], trend)
+        rhs = add_trend(rhs.iloc[:, :lags + 1], trend)
 
     return OLS(lhs, rhs).fit()
 
@@ -807,6 +815,7 @@ def _compute_statistic(self):
         lags = self._lags
 
         rhs = y[:-1, None]
+        rhs = _add_column_names(rhs, 0)
         lhs = y[1:, None]
         if trend != 'nc':
             rhs = add_trend(rhs, trend)