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Activity Number:
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267
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Type:
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Contributed
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Date/Time:
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Tuesday, August 4, 2009 : 8:30 AM to 10:20 AM
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Sponsor:
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Business and Economic Statistics Section
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| Abstract - #305707 |
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Title:
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Forecasting and Estimation Models of GDP
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Author(s):
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Les Yen*+
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Companies:
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University of Phoenix
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Address:
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, Vienna, VA, 22180,
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Keywords:
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Real gross domestic product ; ARMA(p,q) ; Regression model with feedback
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Abstract:
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Real gross domestic product (R-GDP) follows a long-run trend or time series where temporary contractions affect it's long term level. Research economists have developed highly technical forecasting methods using processes that are similar to those of an ARMA(p,q) process. Some success were achieved using regression-type models based on data observed over a stationary time series in predicting the recession of the 1970s and 1990s. This paper focuses on the identification part of the modeling strategy. In particular, we introduce a dynamic regression model with feedback to evaluate the R-GDP growth during the recession period when economic stimuli are introduced.
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- Authors who are presenting talks have a * after their name.
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