Consequences, Detection And Forecasting With Autocorrelated Errors,Used

Consequences, Detection And Forecasting With Autocorrelated Errors,Used

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SKU: DADAX3659309451
Brand: LAP Lambert Academic Publishing
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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; DurbinWatson method; BreushGodfrey method; and The Runs Test were used to detect existence of autocorrelation among residuals of econometric data. In correcting autocorrelation, the method of firstdifference, based on DurbinWatson dstatistic 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.

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