A Computational Approach to Finding Causal Economic Laws

I-Lok Chang, P.A.V.B. Swamy, Charles Hallahan and George Tavlas

Computational Economics, 2000, vol. 16, issue 1/2, 105-136

Abstract: This paper states four realities of econometric model building and shows that an econometric model can be causal only if the interpretations given to its coefficients are consistent with these realities. A numerically stable algorithm for estimating such a model subject to equality and inequality constraints on the model parameters is presented. This algorithm is designed in such a way that it can be applied even when the matrix of observations on the model‘s independent variables and the covariance matrix of the model‘s errors are deficient in rank.

Keywords: realities of econometric model building; causality; random coefficient models; nonlinear programming (search for similar items in EconPapers)
Date: 2000
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