On Mon, 16 Apr 2018, Sven Schreiber wrote:
Am 16.04.2018 um 17:52 schrieb Riccardo (Jack) Lucchetti:
> On Mon, 16 Apr 2018, Sven Schreiber wrote:
>> I mean, either the factor is right or it's wrong, it cannot be
>> "unnecessary" unless the omission is balanced by something else.
>
> Ah, I think I get it now.
>
> If I understand your point correctly, the \hat{Sigma} matrix shown in the
> unnumbered equation right after the sentence "Rather, one computes the
> sandwich filling by summation as" should be mutlipied by $T$.
>
> Is that right?
Yes, either multiply the RHS of that equation through by T, so that the
definition of \hat{Sigma} becomes something else, or multiply Sigma itself by
T everywhere.
Hm, I see. I personally would prefer redefining the $\Gamma$ matrices. I'd
go from
<LaTeX>
Rather, one computes the sandwich filling by summation as
%
\[
\hat{\Sigma} = \hat{\Gamma}(0) + \sum_{j=1}^p w_j
\left(\hat{\Gamma}(j) + \hat{\Gamma}'(j) \right)
\]
%
where the $k \times k$ sample autocovariance matrix $\hat{\Gamma}(j)$,
for $j \geq 0$, is given by
\[
\hat{\Gamma}(j) = \frac{1}{T} \sum_{t=j+1}^T
\hat{u}_t \hat{u}_{t-j}\, X'_t\, X_{t-j}
\]
and $w_j$ is the weight given to the autocovariance at lag $j > 0$.
</LaTeX>
to
<LaTeX>
Rather, one computes the sandwich filling by summation as
%
\[
\hat{\Sigma} = \hat{\Gamma}(0) + \sum_{j=1}^p w_j
\left(\hat{\Gamma}(j) + \hat{\Gamma}'(j) \right)
\]
%
where the $k \times k$ matrix $\hat{\Gamma}(j)$,
for $j \geq 0$, is proportional (by a factor $T$) to the sample
autocovariance matrix, and is given by
\[
\hat{\Gamma}(j) = \sum_{t=j+1}^T
\hat{u}_t \hat{u}_{t-j}\, X'_t\, X_{t-j},
\]
where $w_j$ is the weight given to the autocovariance at lag $j > 0$.
</LaTeX>
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Riccardo (Jack) Lucchetti
Dipartimento di Scienze Economiche e Sociali (DiSES)
Università Politecnica delle Marche
(formerly known as Università di Ancona)
r.lucchetti(a)univpm.it
http://www2.econ.univpm.it/servizi/hpp/lucchetti
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