Activity Number:
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33
- Applications in Time Series Analysis
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Type:
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Contributed
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Date/Time:
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Sunday, July 29, 2018 : 2:00 PM to 3:50 PM
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Sponsor:
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Business and Economic Statistics Section
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Abstract #329678
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Presentation
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Title:
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Forecasting U.S. Textile Comparative Advantage Using Autoregressive Integrated Moving Average Models and Time Series Outlier Analysis
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Author(s):
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Lori Rothenberg* and Zahra Saki and Marguerite Moore
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Companies:
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NC State University and NC State University and NC State University
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Keywords:
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Forecasting;
Time Series;
Textiles and Apparel;
Comparative Advantage;
Additive Outlier;
Permanent Level Shift
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Abstract:
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To establish an updated understanding of the U.S. textile and apparel (TAP) industry's competitive position within the global textile environment, trade data from UN-COMTRADE (1996-2016) was used to calculate the Normalized Revealed Comparative Advantage (NRCA) index for 169 TAP categories at the four-digit Harmonized Schedule (HS) code level. Univariate time series using Autoregressive Integrated Moving Average (ARIMA) models forecast short-term future performance of Revealed categories with export advantage. Accompanying outlier analysis examined permanent level shifts that might convey important information about policy changes, influential drivers and random events.
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Authors who are presenting talks have a * after their name.