Abstract:In multi-period stochastic optimization problems, the future optimal decision is a random variable whose distribution depends on the parameters of the optimization problem. We analyze how the expected value of this random variable changes as a function of the dynamic optimization parameters in the context of Markov decision processes. We call this analysis stochastic comparative statics. We derive both comparative statics results and stochastic comparative statics results showing how the current and future opt… Show more
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