This paper presents a predictive control approach for stabilizing a target manifold in the state space of a nonlinear system while optimizing economic performance on/near this manifold. The control design is based on a transverse normal form description of the dynamics. While a stabilizing transversal NMPC acts as an outer control loop to stabilize a target neighborhood of the manifold, a tangential inner loop NMPC refines the remaining degrees of freedom to the benefit of economic performance without compromising manifold stability. The proposed two-stage approach is especially interesting for embedded system applications when the computationally attractive stabilizing transversal NMPC formulation is augmented with an “approximate” economic refinement step. We discuss the stability and performance properties of the resulting control scheme and show its efficacy in an illustrative example.