|
Activity Number:
|
33
- Applications in Time Series Analysis
|
|
Type:
|
Contributed
|
|
Date/Time:
|
Sunday, July 29, 2018 : 2:00 PM to 3:50 PM
|
|
Sponsor:
|
Business and Economic Statistics Section
|
|
Abstract #329678
|
Presentation
|
|
Title:
|
Forecasting U.S. Textile Comparative Advantage Using Autoregressive Integrated Moving Average Models and Time Series Outlier Analysis
|
|
Author(s):
|
Lori Rothenberg* and Zahra Saki and Marguerite Moore
|
|
Companies:
|
NC State University and NC State University and NC State University
|
|
Keywords:
|
Forecasting;
Time Series;
Textiles and Apparel;
Comparative Advantage;
Additive Outlier;
Permanent Level Shift
|
|
Abstract:
|
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.
|
Authors who are presenting talks have a * after their name.
