setidentifying
Set identification, also known as partial identification, is a concept in statistics and econometrics where a model and the observed data determine a set of possible values for a parameter rather than a single point. In these cases the data are insufficient to identify the parameter uniquely, so the identified set comprises all parameter values that cannot be ruled out given the model and the data.
The identified set is defined by the model’s constraints, such as moment equalities or inequalities, rather
Inference under set identification uses methods that acknowledge uncertainty about the true parameter within the identified
Applications of set identification appear in econometrics, particularly in models with incomplete information, weak instruments, or