“Missingness Graphs” (m-graphs) are causal graphical models used for processing missing data. They portray the causal mechanisms responsible for missingness and thus encode knowledge about the underlying process that generates data. Using m-graphs, we develop methods to determine if there exists a consistent estimator for a given quantity of interest such as joint distributions, conditional distributions and causal effects. Our methods apply to all types of missing data including the notorious a…