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Abstract

A misspecification testing strategy designed to ensure that the statistical assumptions underlying a system of equations are appropriate is outlined. The system tests take into account information in, and interactions between, all equations in the system and can be used in a wide variety of applications where systems of equations are estimated. The system testing approach is demonstrated by modeling U.S. consumer demand for meats. The example illustrates how the approach can be used to disentangle issues regarding structural change and other forms of model misspecification.

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