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Sinopsis
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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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.
Biografía del autor
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
Publicado por
LAP LAMBERT Academic Publishing Dez 2012, 2012
ISBN 10: 3659309451
ISBN 13: 9783659309458
Nuevo
Taschenbuch
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: 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. Nº de ref. del artículo: 9783659309458
Cantidad disponible: 2 disponibles
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Consequences, Detection And Forecasting With Autocorrelated Errors
Publicado por
LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3659309451
ISBN 13: 9783659309458
Nuevo
Tapa blanda
Librería: moluna, Greven, Alemania
Calificación del vendedor: 4 de 5 estrellas
Condición: 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. Nº de ref. del artículo: 5147509
Cantidad disponible: Más de 20 disponibles
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Consequences, Detection And Forecasting With Autocorrelated Errors
Publicado por
LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3659309451
ISBN 13: 9783659309458
Nuevo
Taschenbuch
Librería: AHA-BUCH GmbH, Einbeck, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: 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. Nº de ref. del artículo: 9783659309458
Cantidad disponible: 1 disponibles
Imagen del vendedor
Consequences, Detection And Forecasting With Autocorrelated Errors
Publicado por
LAP LAMBERT Academic Publishing Dez 2012, 2012
ISBN 10: 3659309451
ISBN 13: 9783659309458
Nuevo
Taschenbuch
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: 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. Nº de ref. del artículo: 9783659309458
Cantidad disponible: 2 disponibles