In a wide range of data analysis problems, across many scientific disciplines, we only have access to biased data due to some systematic bias of the data collection procedure. In this talk, we present a general formulation of fundamental statistical estimation tasks with systematic bias and we show some recent results on how to handle two very fundamental types of systematic bias that arise frequently in econometric studies: truncation bias and self-selection bias.