Results 211 to 220 of about 62,108 (262)

Systems of Simultaneous Equations

1978
In previous chapters we examined extensively the GLM under a variety of circumstances. A common feature of these discussions was a certain aspect of unidirectionality. Generally, variations in the explanatory (right-hand) variables were transmitted to the dependent (left-hand) variable, but not vice versa.
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Method‐of‐moment view of linear simultaneous equation systems [PDF]

Statistica Neerlandica, 2008
In this paper, we review the modern method‐of‐moment‐based approaches to identification and estimation of linear simultaneous equation systems. First, we present the rank condition for the structural form (SF) parameter identification. The rank condition comes naturally and is much easier to understand than that in the conventional reduced‐form‐based ...
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The Bias of Instrumental Variable Estimators of Simultaneous Equation Systems

International Economic Review, 1977
This paper examines the discussion in the econometric literature of the conditioins which instruments should satisfy in order to be used in the single equation Iiistrumental Variable (IV) estimation of structural parameters in a simultaneouIs equation system. The Two Stage Least Squares (TSLS) estimator can be interpreted as an IV estimator.
Phillips, Garry D A, Hale, C
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Simultaneous Equations Systems

1995
AbstractLinear system modelling is structured in 10 stages from the general to the specific. The dynamic statistical system is the maintained model, defined by the variables of interest, their distributions, whether they are modelled or non‐modelled, and their lag polynomials. An econometric model is a (possibly) simultaneous‐equations entity, which is
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Coefficients of correlation for simultaneous equation systems

Journal of Econometrics, 1977
Abstract This paper presents measures of correlation for use with either a single equation within a simultaneous system or for the whole system, which specifically account for the identifying restrictions. The measures lie between zero and one and have the same interpretation as the familiar R 2 used with classical least squares.
Carter, Richard A. L., Nagar, Anirudh L.
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Systems of Dynamic Simultaneous Equations

1991
This chapter serves to point out some possible extensions of the models considered so far and to draw attention to potential problems related to such extensions. So far, we have assumed that all stochastic variables of a system have essentially the same status in that they are all determined within the system.
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STRUCTURAL IDENTIFICATION METHOD OF SIMULTANEOUS EQUATIONS SYSTEMS

IFAC Proceedings Volumes, 2002
The objective of this paper is to develop a method for selection of the ...
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TESTING FOR SERIAL CORRELATION IN SYSTEMS OF SIMULTANEOUS REGRESSION EQUATIONS

Biometrika, 1957
where y is a vector of jointly dependent variables, x is a vector of predetermined or independent variables, e is a vector of errors, and A and B are matrices of unknown parameters. It is usual to assume that A is square and non-singular, that the e's are random variables with zero means and constant variance matrix, and that the x's are either ...
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Estimation of Simultaneous Equations Systems

1974
A certain class of estimators for the parameters of a simultaneous equations (S.E.) system can be shown to have an interpretation as an ordinary least squares (OLS) estimator. In view of this fundamental unity of estimation procedures, it would be desirable at this stage to review carefully the estimation problem in the context of the general linear ...
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The coefficient of determination and simultaneous equation systems

Journal of Econometrics, 1980
Abstract In this paper we show that the Carter-Nagar (1977) R2's for single structural equations and systems are in fact R2 for the reduced form where the partially restricted reduced form estimation method is employed. We also show that the results of McElroy (1977) may be used to derive the Carter-Nagar system measure. If the reduced form equations
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