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Erschienen in:
2023 | OriginalPaper | Buchkapitel
Autocorrelation of an Econometric Model
verfasst von : Preeti Singh, Sarvpal Singh
Erschienen in: Smart Trends in Computing and Communications
Verlag: Springer Nature Singapore
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Abstract
The treatment of an econometric model requires a clearly defined sequence of tasks. The identification of the model leads us to review the literature, to justify the defined relationship between the dependent variable and the independent variables. Model estimation uses the mathematical apparatus to find the equation of fit. Once the model has been estimated, it must be properly diagnosed using statistical tests. After the diagnosis phase, one can use the model to make predictions. This contribution deals with the identification, estimation, diagnosis, and prediction phases for the treatment of econometric models. Likewise, the diagnosis is deepened by developing the problems of autocorrelation, heteroscedasticity, residual normality, multicollinearity, endogeneity, and others.