new_contents: """
  Tests for prediction of state space models
  
  Author: Chad Fulton
  License: Simplified-BSD
  """
  
  from __future__ import division, absolute_import #, print_function
  
  import numpy as np
  import pandas as pd
  
  import warnings
  from statsmodels.tsa.statespace import sarimax
  from numpy.testing import assert_equal, assert_allclose, assert_raises
  from nose.exc import SkipTest
  
  
  def test_predict_dates():
      index = pd.date_range(start='1950-01-01', periods=11, freq='D')
      np.random.seed(324328)
      endog = pd.Series(np.random.normal(size=10), index=index[:-1])
  
      # Basic test
      mod = sarimax.SARIMAX(endog, order=(1, 0, 0))
      res = mod.filter(mod.start_params)
  
      # In-sample prediction should have the same index
      pred = res.predict()
      assert_equal(len(pred), mod.nobs)
      assert_equal(pred.index.values, index[:-1].values)
      # Out-of-sample forecasting should extend the index appropriately
      fcast = res.forecast()
      assert_equal(fcast.index[0], index[-1])
  
      # Simple differencing in the SARIMAX model should eliminate dates of
      # series eliminated due to differencing
      mod = sarimax.SARIMAX(endog, order=(1, 1, 0), simple_differencing=True)
      res = mod.filter(mod.start_params)
      pred = res.predict()
      # In-sample prediction should lose the first index value
      assert_equal(mod.nobs, endog.shape[0] - 1)
      assert_equal(len(pred), mod.nobs)
      assert_equal(pred.index.values, index[1:-1].values)
      # Out-of-sample forecasting should still extend the index appropriately
      fcast = res.forecast()
      assert_equal(fcast.index[0], index[-1])
subject: Add (failing) test for predict dates.