IDENTIFICATION: IT'S PERFORMANCE THAT COUNTS
Generate an AI Snapshot to get a quick, structured summary of this paper.
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
TL;DR
Two different forms of identifying restrictions are discussed and compared in a Monte Carlo framework and it is found that, using ordinary least squares as the estimating technique, the two types of identification perform much differently and thus they should not be confused.
Abstract
ABSTRACT This paper discusses two different forms of identifying restrictions and compares them in a Monte Carlo framework. A similar analysis is performed to illuminate how the identification procedures affect problems of mis‐specification. It is found that, using ordinary least squares as the estimating technique, the two types of identification perform much differently and thus they should not be confused. Similar results hold in the mis‐specification case.