Gross domestic product (GDP) comes under the heading of National Accounts, Which is a subject in macroeconomics. This study aims at to find appropriate VAR (Vector Autoregressive) model for the variables agriculture, industry and services in multivariate time series, to check out the causality among the variables agriculture, industry, and service. In addition to data description and forecasting, here the VAR model is also used for structural inference and policy analysis. But before these we must verify the validation of the model in different time period, because a forecasting model may lose its validity and suitability as time progresses.The basic aim of this study was to check out the causality or inter dependency between the variables agriculture, industry and services on GDP of Bangladesh. Also to forecast the increasing GDP using VAR model. From the above study and estimation, VAR is an appropriate model for the GDP of Bangladesh. The author also found various measures of forecasting accuracy for the model. Author have found strong evidence of inter dependency or causality among the three underlying variable.
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La Sra. Naz Afrin Sultana está cursando actualmente una maestría en el Instituto de Investigación y Capacitación Estadísticas (ISRT) de la Universidad de Dhaka de Bangladesh. Recibió su título de B.S. del mismo instituto. Sus intereses de investigación incluyen las estadísticas bayesianas, el análisis multivariado, etc.
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Gross domestic product (GDP) comes under the heading of National Accounts, Which is a subject in macroeconomics. This study aims at to find appropriate VAR (Vector Autoregressive) model for the variables agriculture, industry and services in multivariate time series, to check out the causality among the variables agriculture, industry, and service. In addition to data description and forecasting, here the VAR model is also used for structural inference and policy analysis. But before these we must verify the validation of the model in different time period, because a forecasting model may lose its validity and suitability as time progresses.The basic aim of this study was to check out the causality or inter dependency between the variables agriculture, industry and services on GDP of Bangladesh. Also to forecast the increasing GDP using VAR model. From the above study and estimation, VAR is an appropriate model for the GDP of Bangladesh. The author also found various measures of forecasting accuracy for the model. Author have found strong evidence of inter dependency or causality among the three underlying variable. 64 pp. Englisch. Bestandsnummer des Verkäufers 9783845400860
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Gross domestic product (GDP) comes under the heading of National Accounts, Which is a subject in macroeconomics. This study aims at to find appropriate VAR (Vector Autoregressive) model for the variables agriculture, industry and services in multivariate time series, to check out the causality among the variables agriculture, industry, and service. In addition to data description and forecasting, here the VAR model is also used for structural inference and policy analysis. But before these we must verify the validation of the model in different time period, because a forecasting model may lose its validity and suitability as time progresses.The basic aim of this study was to check out the causality or inter dependency between the variables agriculture, industry and services on GDP of Bangladesh. Also to forecast the increasing GDP using VAR model. From the above study and estimation, VAR is an appropriate model for the GDP of Bangladesh. The author also found various measures of forecasting accuracy for the model. Author have found strong evidence of inter dependency or causality among the three underlying variable. Bestandsnummer des Verkäufers 9783845400860
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Sultana Naz AfrinMs.Naz Afrin Sultana is currently pursing M.S. at the Institute of Statistical Research and Training (ISRT) of Dhaka University from Bangladesh. She received her B.S. degree from the same institute. Her research inte. Bestandsnummer des Verkäufers 5480268
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Gross domestic product (GDP) comes under the heading of National Accounts, Which is a subject in macroeconomics. This study aims at to find appropriate VAR (Vector Autoregressive) model for the variables agriculture, industry and services in multivariate time series, to check out the causality among the variables agriculture, industry, and service. In addition to data description and forecasting, here the VAR model is also used for structural inference and policy analysis. But before these we must verify the validation of the model in different time period, because a forecasting model may lose its validity and suitability as time progresses.The basic aim of this study was to check out the causality or inter dependency between the variables agriculture, industry and services on GDP of Bangladesh. Also to forecast the increasing GDP using VAR model. From the above study and estimation, VAR is an appropriate model for the GDP of Bangladesh. The author also found various measures of forecasting accuracy for the model. Author have found strong evidence of inter dependency or causality among the three underlying variable.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 64 pp. Englisch. Bestandsnummer des Verkäufers 9783845400860
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Taschenbuch. Zustand: Neu. GDP OF BANGLADESH: INTER DEPENDENCY WITH RELEVANT VARIABLES | A VAR Model Approach | Naz Afrin Sultana | Taschenbuch | 64 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783845400860 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 106910576
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