title: The index on the time dimension must be either numeric or date-like error
body: <p>I am trying to do a panel regression with</p>
  <pre><code>from linearmodels.panel import PooledOLS
  import statsmodels.api as sm
  </code></pre>
  <p>but I encountered a problem with my index. For the regression I need a Multiindex, so I have a Dummy variable and the time (see below). The two indicies are a_c ( a dummy variable for all 10 countries of my analysis) and Timestamp (the date).</p>
  <pre><code>                i_ct    preemu  postemu  γ1             γ2
  α_c Timestamp   
  
  10  2020-06-24  -0.04   0.00    0.02    -1.110223e-16   2.000000e-02
      2020-06-25  0.05    0.00    -0.04   -1.000000e-02   1.000000e-02
      2020-06-26  0.02    0.00    0.05    0.000000e+00    1.000000e-02
      2020-06-29  0.00    0.00    0.02    -2.000000e-02   -1.110223e-16
      2020-06-30  0.08    0.00    0.00    2.000000e-02    -6.000000e-02   
  </code></pre>
  <p>When I run the regression</p>
  <pre><code>exog_vars = ['preemu','postemu','γ1','γ2']
  exog = sm.add_constant(beta_panel[exog_vars])
  mod = PooledOLS(beta_panel.i_ct, exog)
  pooled_res = mod.fit()
  print(pooled_res)
  </code></pre>
  <p>I get this error:</p>
  <pre><code>ValueError: The index on the time dimension must be either numeric or date-like
  </code></pre>
  <p>But when the timestamp is not in the index I get this error:</p>
  <pre><code>Series can only be used with a 2-level MultiIndex
  </code></pre>
  <p>Anyone knows why it could throw the first error?</p>