Simultaneous equations with covariance restrictions

Identification in Linear Simultaneous Equations Models with Covariance Restrictions: An Instrumental Variables Interpretation

Necessary and sufficient conditions for Identlflability with linear coefficient and covarlance restrictions are developed. In practical terms, covarlance restrictions aid identification if and only if they imply either that (1) a set of endogenous variables is predetermined in a particular equation (generalizing the notion of recursiveness) or (11) an identifiable residual is predetermined in a...

Identifiability of Dynamic Stochastic General Equilibrium Models with Covariance Restrictions

This article is concerned with identification problem of parameters of Dynamic Stochastic General Equilibrium Models with emphasis on structural constraints, so that the number of observable variables is equal to the number of exogenous variables. We derived a set of identifiability conditions and suggested a procedure for a thorough analysis of identification at each point in the parameters sp...

Conditional Moment Restrictions and Triangular Simultaneous Equations∗

We examine whether a causal interpretation can be given to the function identified by the conditional moment restriction (CMR). It is shown that in a general nonseparable triangular system the CMR does not identify the average structural function (ASF) nor any other structural object. This implies that the CMR identifies a causal relation only if the model is structurally separable in observabl...

Working Paper Department of Economics Efficient Estimation and Identification of Simultaneous Equation Models with Covariance Restrictions

Structural Modeling with Weak Instrumentation and Covariance Restrictions

This paper considers estimating a panel data simultaneous equations model under both coefficient and covariance matrix restrictions in a scenario where one or the other set of identifying restrictions may be invalid or may hold only weakly. We study the limiting properties of various estimators in an asymptotic framework, which takes both the cross-sectional dimension N and the time dimension T...