Matrix Completion When Missing Is Not at Random and Its Applications in Causal Panel Data Models
{{output}}
This paper develops an inferential framework for matrix completion when missing is not at random and without the requirement of strong signals. Our development is based on the observation that if the number of missing entries is small enough compared to the pa... ...