33 – Applications in Time Series Analysis
Forecasting U.S. Textile Comparative Advantage Using Autoregressive Integrated Moving Average Models and Time Series Outlier Analysis
Zahra Saki
Department of Textile Technology Management, College of Textiles
Lori Rothenberg
1Department of Textile Technology Management, College of Textiles
Marguerite Moore
1Department of Textile Technology Management, College of Textiles
Ivan Kandilov
Department of Agricultural and Resource Economics, NC State University
Blanton Godfrey
Department of Textile Technology Management, College of Textiles
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.