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Consequences, Detection And Forecasting With Autocorrelated Errors
Ademola Adetunji • Olusoga Fasoranbaku
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Problem of autocorrelation arises if the assumption of the Classical Linear Regression Model that the errors terms are not autocorrelated is violated. As a consequence, the usual t, F, and 2 tests cannot be legitimately applied. This text uses various econometric approaches to critically observe the associated problems. Graphical method; Durbin-Watson method; Breush-Godfrey method; and The Runs Test were used to detect existence of autocorrelation among residuals of econometric data. In correcting autocorrelation, the method of first-difference, based on Durbin-Watson d-statistic and the dynamic forecasting techniques were used. The result gave a significantly reduced estimated autocorrelation coefficient. This improves the efficiency of the forecast and the use of various statistics in making inference.
- Format: Pocket/Paperback
- ISBN: 9783659309458
- Språk: Engelska
- Antal sidor: 88
- Utgivningsdatum: 2012-12-22
- Förlag: LAP Lambert Academic Publishing