A frog on pad $i$ hops to one of the pads $(1,2,...,i,i+1)$ with equal probability. I know that if the frog starts on pad $k$ the expected number of times the frog jumps, before returning for the first time to $k$ is $e(k-1)!$ (I proved this already).
But what is the expected number of times the frog will visit pad $k+1$? I don't know how to find this. I thought that maybe we can use the fact that there is a probability of $1/(k+1)$ of visiting this the first time and then multiply this by the number of times I expect to return at $k+1$ when I start at $k+1$. If this is correct, then what is that expectation?
EDIT: Is the answer to the question really $\infty$ as michael says in the comments?
The Markov chain is irreducible, since for any pair of states $i,j$, there exists $n>0$ such that $P_{ij}^n>0$. Since the expected return time to a state is finite, each state is positive recurrent. It follows that each state is visited infinitely often.
To argue a bit more rigorously, let $F_n = \mathbb I_{\{X_n=k\mid X_0=k\}}$ and $$N_k = \sum_{n=0}^\infty F_n.$$ Then $$ \mathbb E[N_k] = \mathbb E\left[\sum_{n=0}^\infty F_n \right]. $$ By monotone convergence, this is equal to $$ \sum_{n=0}^\infty \mathbb E[F_n]. $$ We have $\mathbb E[N_k]\geqslant \mathbb E[F_0]=1$. Now assume that $\mathbb E[N_k]\geqslant m$ for some $m\geqslant 1$. Then $$\begin{align*} \mathbb E[N_k] &= m + \sum_{n=m+1}\mathbb P(F_n)\\ &\geqslant m + \mathbb P\left(\bigcup_{n=m+1}^\infty F_n\right)\\ &= m+1. \end{align*}$$ Hence $\mathbb E[N_k]=\infty$.