We develop and apply a general framework for using shocks from natural experiments to estimate key parameters in a class of structural models, via recentered instruments that exploit knowledge of the shock assignment process. This design-based identification approach imposes no restrictions on how model unobservables relate to predetermined variables, and yields a new class of optimal instruments. We show how instrument recentering relaxes strong assumptions in models of the demand for differentiated products.