Electricity theft is a serious issue for distribution companies around the world. Often linked to criminal activities, it is dangerous for the grid and the neighborhoods. While placing measurement points at each bus would allow an easy detection, it is not a practical approach. In this project, a multi-timescale theft estimation (MISTE) method that takes advantage of smart-meters as well as the sparse grid sensing infrastructure that is being envisaged for state estimation is proposed. It combines power and voltage measurement across time to detect any inconsistency caused by electricity theft. Contrary to existing approaches which are snapshot-based and assume smart-meters to be able to measure instantaneous power consumption, the proposed method models smart-meters as energy measurement devices and combines the measurement timescales of the smart-meters and the PMUs in the computations. The detection performance of the proposed approach will be compared to the state of the art theft detection methods. Both the true positive rate as well as the false negative rate will be considered, which few papers have discussed previously. Insights on the impact of theft location on theft detection will also be given.