  Consider additive functionals of a Markov chain $W_k$, with stationary
(marginal) distribution and transition function denoted by $\pi$ and $Q$, say
$S_n=g(W_1)+...+g(W_n)$, where $g$ is square integrable and has mean 0 with
respect to $\pi$. If $S_n$ has the form $S_n=M_n+R_n$, where $M_n$ is a square
integrable martingale with stationary increments and $E(R_n^2)=o(n)$, then $g$
is said to admit a martingale approximation. Necessary and sufficient
conditions for such an approximation are developed. Two obvious necessary
conditions are $E[E(S_n|W_1)^2]=o(n)$ and $\lim_{n\to
\infty}E(S_n^2)/n<\infty$. Assuming the first of these, let $\Vert
g\Vert^2_+=\limsup_{n\to \infty}E(S_n^2)/n$; then $\Vert\cdot\Vert_+$ defines a
pseudo norm on the subspace of $L^2(\pi)$ where it is finite. In one main
result, a simple necessary and sufficient condition for a martingale
approximation is developed in terms of $\Vert\cdot\Vert_+$. Let $Q^*$ denote
the adjoint operator to $Q$, regarded as a linear operator from $L^2(\pi)$ into
itself, and consider co-isometries ($QQ^*=I$), an important special case that
includes shift processes. In another main result a convenient orthonormal basis
for $L_0^2(\pi)$ is identified along with a simple necessary and sufficient
condition for the existence of a martingale approximation in terms of the
coefficients of the expansion of $g$ with respect to this basis.
