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This paper studies a class of models where full identiﬁcation is not necessarily assumed. We term such models partially identiﬁed. It is argued that partially identiﬁed systems are of practical importance since empirical investigators frequently proceed under conditions that are best described as apparent identiﬁcation. One objective of the paper is to explore the properties of conventional statistical procedures in the context of identiﬁcation failure. Our analysis concentrates on two major types of partially identiﬁed model: the classic simultaneous equations model under rank condition failures; and time series spurious regressions. Both types serve to illustrate the extensions that are needed to conventional asymptotic theory if the theory is to accommodate partially identiﬁed systems.
Phillips, Peter C.B., "Partially Identified Econometric Models" (1987). Cowles Foundation Discussion Papers. 1088.