Stochastic Comparative Statics in Markov Decision Processes

In multiperiod stochastic optimization problems, the future optimal decision is a random variable whose distribution depends on parameters of problem. I analyze how expected value this changes as function dynamic in context Markov processes. call analysis comparative statics. derive both statics results and showing current decisions change response to single-period payoff function, discount factor, initial state system, transition probability function. apply my various models from economics operations research literature, including investment theory, pricing models, controlled walks, comparisons stationary distributions.