A Program for Box-Cox Transformation in Regression Models with Heteroskedastic and Autoregressive Residuals

T.C. Liem, M. Gaudry and M.G. Dagenais

Cahiers de recherche from Universite de Montreal, Departement de sciences economiques

Abstract: L-1.2 Is a Program Designed to Deal with the Specification of the Functional Form in the Generalized Single-Equation Regression Model When the Functional Form of Heteroskedasticity of the Residuals, Which May Also Be Autocorrelated, Is Fully Analysed. Fixed Or Estimated Parameters in the Box-Cox Transformations Can Be Associated with the Dependent and Groups of Independent Variables, Which May Be Simultaneously Modified by a Chosen Autocorrelation Structure in Which the Autoregressive Parameters Are Estimated, and by a Selected Functional Form of Heteroskedasticity in Which Covariance Matrix of All Parameter Estimates of the System Is Computed. a Number of Useful Outputs, Including Elaborate Statistics Associated with Forecasts and Plots of the Likelihood Functions, Can Also Be Obtained.

Keywords: Correlation Analysis; Heteroskedasticity; Evaluation Techniques; Evaluation (search for similar items in EconPapers)
Pages: 81P pages
Date: 1987
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Persistent link: https://EconPapers.repec.org/RePEc:mtl:montde:8714

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