RIEB Discussion Paper Series No.2024-32

Title

Quantitative Convergence Rates for Stochastically Monotone Markov Chains

Abstract

For Markov chains and Markov processes exhibiting a form of stochastic monotonicity (larger states shift up transition probabilities in terms of stochastic dominance), stability and ergodicity results can be obtained using order-theoretic mixing conditions. We complement these results by providing quantitative bounds on deviations between distributions. We also show that well-known total variation bounds can be recovered as a special case.

Inquiries

Takashi KAMIHIGASHI
Center for Computational Social Science (CCSS)
Research Institute for Economics and Business Administration (RIEB)
Kobe University
Rokkodai-cho, Nada-ku, Kobe
657-8501 Japan
Phone: +81-78-803-7036
FAX: +81-78-803-7059

John STACHURSKI
Research School of Economics, Australian National University