The methods used to identify the beneficiaries of programs aiming to address persistent poverty and shocks are subject to frequent policy debates. Relying on panel data from Niger, this report simulates the performance of various targeting methods that are widely used by development and humanitarian actors. The methods include proxy-means testing (PMT), household economy analysis (HEA), geographical targeting, and combined methods. Results show that PMT performs more effectively in identifying persistently poor households, while HEA shows superior performance in identifying transiently food insecure households. Geographical targeting is particularly efficient in responding to food crises, which tend to be largely covariate. Combinations of geographical, PMT, and HEA approaches may be used as part of an efficient and scalable adaptive social protection system. Results motivate the consolidation of data across programs, which can support the application of alternative targeting methods tailored to program-specific objectives.