I ran into a step in an argument that I can't quite figure out. It's basically how they use a limit that I don't seem to understand. The context is local-to-unity asymptotics in vector autoregressions, so I figured some people doing empirical work might know.
We have a $K \times K$ diagonal matrix $\Lambda := \text{diag}\left( \lambda_1, \dots, \lambda_K \right)$ and we define $h := \left[ \delta T \right]$ where $[.]$ refers to the integer part of a number and $\delta \in (0,1)$ is some fraction. We'd like to know what happens to $\Lambda^h$ as $T \rightarrow \infty$. The textbook notes that \begin{align*} \lim_{T \rightarrow \infty} \left( 1 + \frac{\delta \lambda_k}{T} \right)^T = e^{\delta \lambda_k} \; \forall k=1,\dots,K \end{align*} and infers that $\Lambda^h \rightarrow e^{\delta \Lambda} := \text{diag}\left( e^{\delta \lambda_1}, \dots, e^{\delta \lambda_K} \right)$. I don't quite follow what is going on. I see that the first limit is correct, but I fail to see how the conclusion follows. If it helps, later the authors actually use the reasoning to claim that $C^h \rightarrow e^{\delta C}$, but $C := I_K + \Lambda/T$. Now, in that case we have $\left( C^h \right)_{k,k} = \left( 1 + \frac{\lambda_k}{T} \right)^{[\delta T]}$. I still am having trouble seeing how the hell $\delta$ can be brought inside to invoke the above argument, but the expression is closer.
Anyone can help me out here?