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Synopsis
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 χ2 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.
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ADETUNJI, ADEMOLA ABIODUN was born in Osogbo, Osun State, Nigeria some three decades ago.He is a young and ambitious scholar with a number of academic scholarships and publications to his credit.He is an aspiring researcher with major interest in Econometrics and Categorical Data Analysis.
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Consequences, Detection And Forecasting With Autocorrelated Errors
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LAP LAMBERT Academic Publishing Dez 2012, 2012
ISBN 10: 3659309451
ISBN 13: 9783659309458
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Taschenbuch
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 88 pp. Englisch. Seller Inventory # 9783659309458
Quantity: 2 available
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Consequences, Detection And Forecasting With Autocorrelated Errors
Published by
LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3659309451
ISBN 13: 9783659309458
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Seller: moluna, Greven, Germany
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Adetunji AdemolaADETUNJI, ADEMOLA ABIODUN was born in Osogbo, Osun State, Nigeria some three decades ago.He is a young and ambitious scholar with a number of academic scholarships and publications to his credit.He is an aspiring rese. Seller Inventory # 5147509
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Consequences, Detection And Forecasting With Autocorrelated Errors
Published by
LAP LAMBERT Academic Publishing Dez 2012, 2012
ISBN 10: 3659309451
ISBN 13: 9783659309458
New
Taschenbuch
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. Neuware -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.Books on Demand GmbH, Überseering 33, 22297 Hamburg 88 pp. Englisch. Seller Inventory # 9783659309458
Quantity: 2 available
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Consequences, Detection And Forecasting With Autocorrelated Errors
Published by
LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3659309451
ISBN 13: 9783659309458
New
Taschenbuch
Seller: AHA-BUCH GmbH, Einbeck, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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. Seller Inventory # 9783659309458
Quantity: 1 available