How does one interpret an element of the "transfer matrix" used to calculate frequency domain granger causality (via VAR models)? I am attempting to gain a better mathematical understanding for how autoregressive models can be used to infer frequency-domain granger causality. All freq. domain measures of causality that utilize autoregressive models convert the time-domain parameters to a frequency-based representation (i.e. take the Fourier transform of the original parameters), and then take the inverse of that representation to get the so-called "transfer matrix". This transfer matrix is referenced in many causality-related papers, and is the backbone of all freq. domain measures. Here is the derivation for the transfer matrix:

$a_{i,j}(k)$ - Autoregressive coefficient describing influence of node $j$ on node $i$ at lag=$k$ 

$p$ - Model-order (i.e. how many past time-points to use to predict the present)

$\textbf{A}(k)$ - $Q$-by-$Q$ autoregressive parameter matrix at lag=$k$. This matrix is estimated via model fitting.

$U(t)$ - Innovation noise (i.e. the difference between the model's predictions and observed data at time $t$.) 

\begin{align}
   {Y(t)} = \sum_{k=1}^{p}\textbf{A}(k)Y(t-k) + U(t) 
\end{align}

$\bar{\textbf{A}}(f)$ - Frequency representation of $\textbf{A}(k)$

$\bar{{a}}_{i,j}(f)$ - Frequency representation of autoregression describing influence of node $j$ on node $i$ at freqeuncy $f$

$\bar{a}_{i,j}(f) =
\begin{cases}
                                   1-\sum_{k=1}^{p} a_{i,j}(k) e^{-\textbf{j}2\pi f k} &amp; \text{if $i=j$} \\
                                   -\sum_{k=1}^{p} a_{i,j}(k) e^{-\textbf{j}2\pi f k)} &amp; \text{otherwise} 
  \end{cases}
$

\begin{align}
    \text{where } \textbf{j}=\sqrt{-1}
\end{align}

Note that above piecewise equation stems from taking the FT of model coefs. At least as far as I understand it. I'm not actually positive as to why this equation is piecewise and not identical for all $i$/$j$ combinations. I haven't worked with FTs very much.

$\textbf{H}(f)$ - Transfer matrix

\begin{align}
    \textbf{H}(f)=\bar{\textbf{A}}^{-1}(f)
\end{align}

Now for my question--does anyone have an intuitive definition for what the transfer matrix, or a given element of the transfer matrix ($h_{i,j}(f)$), actually represents? I can easily and intuitively understand what $a_{i,j}(k)$ represents, but I've yet to fully grasp what $h_{i,j}(f)$ represents. How does one interpret such a value in layman's terms?
Hi: At a quick glance,  the Geweke, 1982 and 1984 references on the last page of this link are probably necessary reading for understanding it.

I realize that this doesn't answer your question but I'm trying to see if I'm able to send a link without actually typing the link.
and I don't know how to do that in a comment. Hopefully it works here.