The authors deal with finite-dimensional parameter-dependent optimization problems and consider so-called monotone comparative statics whose main question is to determine conditions under which the model predictions change monotonically if the parameter values vary. The proposed method generates a vector field defined on the parameter space. Then, using this vector field a reparametrization on the parameter space is provided such that monotone comparative statics is guaranteed. Finally, some applications and an outlook on open questions are presented.