Before revision:  We propose a framework in which we can partially learn the optimal dynamic regime and ordering of welfares, relaxing sequential randomization assumptions commonly employed in the literature . We establish the sharp partial ordering of counterfactual welfares with respect to dynamic regimes by using a series of linear programs.
After revision:  We propose a framework in which we can partially learn the optimal dynamic regime and ordering of welfares, relaxing sequential randomization assumptions commonly employed in the literature but instead using (binary) instrumental variables. We propose the notion of sharp partial ordering of counterfactual welfares with respect to dynamic regimes by using a series of linear programs.