{"product_id":"consequences-detection-and-forecasting-with-autocorrelated-errors-von-ademola-adetunji-und-olusoga-fasoranbaku","title":"Consequences, Detection And Forecasting With Autocorrelated Errors","description":"\u003cp\u003eProblem 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.\u003c\/p\u003e\u003cdiv class=\"aw-variant-hidden-subtitle-div\" id=\"aw-variant-subtitle-9783659309458\"\u003e\u003ch3\u003e\u003c\/h3\u003e\u003c\/div\u003e","brand":"Autorenwelt Shop","offers":[{"title":"Softcover - 9783659309458","offer_id":39485361487965,"sku":"9783659309458","price":49.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0940\/0622\/files\/9bf12d35-1f50-41a6-bb8a-98412dbc63fb.jpg?v=1776403990","url":"https:\/\/shop.autorenwelt.de\/products\/consequences-detection-and-forecasting-with-autocorrelated-errors-von-ademola-adetunji-und-olusoga-fasoranbaku","provider":"Autorenwelt Shop","version":"1.0","type":"link"}