My question is related to this question here.
This says that if $S_{n}$ is a simple random walk (with steps $+1$ or $-1$ with probability $p$ and $q$ respectively) started at $S_{0}=1$, and if $T=\min\{k\geq 0:S_{k}=0\}$ then $$Z_k = \sum _{n=0}^{T-1} \textbf{1}_ {\{ S_n= k, S_{n+1}=k+1 \}}\,, Z_{0}=1 $$ is a Galton Watson Branching Process with Geometric Offspring Distribution.
My question is that how is $Z_{1}$ distributed as a Geometric $q$ variate (with the convention that the variate can take value $0$, i.e. the second description as given in Wikipedia)?
Now I can see as given in the comments that $Z_{2}=\sum_{k=1}^{Z_{1}}\xi_{k}$ where $\xi_{k}$ are iid Geometric $q$ variates. This precisely counts the random "upcrossings" from $2$ to $3$ strictly in between the $Z_{1}$ many upcrossings from $1$ to $2$. Now inductively, I can show that $Z_{n+1}=\sum_{k=1}^{Z_{n}}\xi_{k}^{(n)}$ where $\xi_{k}^{(n)}$ are iid Geometric $q$ variates which would prove that $Z_{n}$ is a branching process.
But how do I show that $Z_{1}$ has Geometric distribution?
I can see that $P(Z_{1}=k)=\sum_{m=0}^{\infty}P(Z_{1}=k|T=2m+1)P(T=2m+1)$ but this just complicates matters more as I would end up with many different ways of crossing from $1$ to $2$ for large $m$. Also I would have to multiply by the probability that $T=2m+1$ which would be $(pq)^{m}\binom{2m}{m}$.
Maybe I am missing something very trivial. Can anyone help me out with this?