Using Google Trends Data by Yousefi Djamil (8 results)
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Taschenbuch. Condition: Neu. Using Google Trends Data in Forecasting Economic Variables | Time Series Analysis | Djamil Yousefi | Taschenbuch | Englisch | 2019 | LAP LAMBERT Academic Publishing | EAN 9786200478412 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[…dot]de | Anbieter: preigu.
Language: English
Published by LAP LAMBERT Academic Publishing Dez 2019 2019
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This work investigates in a forecast application whether the forecast accuracy of the US unemployment growth rate can be improved when the time series model is augmented with Google Trends data. The empirical analysis is based on up… to 10 distinct Google Trends search terms, which show a sufficiently high correlation with the target variable US unemployment rate. A Google index from the 10 Google search terms is derived by estimating a Factor model with the method of principal component analysis. By using a VAR model it is empirically shown that the forecast accuracy of the US unemployment growth rate can be improved by augmenting the model with the Google search terms. 88 pp. Englisch.
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Yousefi DjamilDjamil Yousefi, M.Sc. University of Konstanz, Major in Econometrics and Applied EconomicsThis work investigates in a forecast application whether the forecast accuracy of the US unemployme…nt growth rate can be impro.
Language: English
Published by LAP LAMBERT Academic Publishing Dez 2019 2019
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Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This work investigates in a forecast application whether the forecast accuracy of the US unemployment growth rate can be improved when the time series model is augmented with Google Trends data. The empirical analysis is based on up to…10 distinct Google Trends search terms, which show a sufficiently high correlation with the target variable US unemployment rate. A Google index from the 10 Google search terms is derived by estimating a Factor model with the method of principal component analysis. By using a VAR model it is empirically shown that the forecast accuracy of the US unemployment growth rate can be improved by augmenting the model with the Google search terms.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 88 pp. Englisch.
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This work investigates in a forecast application whether the forecast accuracy of the US unemployment growth rate can be improved when the time series model is augmented with Google Trends data. The empirical analysis is based on up to 1…0 distinct Google Trends search terms, which show a sufficiently high correlation with the target variable US unemployment rate. A Google index from the 10 Google search terms is derived by estimating a Factor model with the method of principal component analysis. By using a VAR model it is empirically shown that the forecast accuracy of the US unemployment growth rate can be improved by augmenting the model with the Google search terms.
