The article defines efficiency bounds in certain models with identification issues. It shows how to calculate these bounds in semi-parametric models with identifying constraints, even when the information matrix is degenerate. A new convolution theorem is established in this context. The information bound is computed for standard identifiability constraints in models like probit, single-index, and ANOVA. A two-step procedure using a preliminary estimator can lead to an efficient parameter estimator.