Every step changes the population by one, so has the parity of when . Hence . A return in two steps has positive probability from every state, and all return times are even, so the period of a state in a Markov chain is exactly two.
Each transition exchanges the even and odd classes. Since is an invariant distribution, their masses are equal: . The chain sampled at times , restricted to the even states, is irreducible and positive recurrent, and it is aperiodic because its diagonal entries are positive. Its stationary distribution is on even . The countable-state Markov chain convergence theorem applied to this sampled chain yieldsSince , the full sequence has no limit. Its time average nevertheless tends to by the countable-state Markov chain ergodic theorem.
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