Potential analysis for positive recurrent Markov chains with asymptotically zero drift: Power-type asymptotics

We consider a positive recurrent Markov chain on R⁺${\mathbb{R}}^{+}$ with asymptotically zero drift which behaves like −_c1/x$-c_1/x$ at infinity; this model was first considered by Lamperti. We are interested in tail asymptotics for the stationary measure. Our analysis is based on construction of a harmonic function which turns out to be regularly varying at infinity. This harmonic function allows us to perform non-exponential change of measure. Under this new measure Markov chain is transient with drift like _c2/x$c_2/x$ at infinity and we compute the asymptotics for its Green function. Applying further the inverse transform of measure we deduce a power-like asymptotic behaviour of the stationary tail distribution. Such a heavy-tailed stationary measure happens even if the jumps of the chain are bounded. This model provides an example where possibly bounded input distributions produce non-exponential output.