Forecasting U.S. Textile Comparative Advantage Using Autoregressive Integrated Moving Average Models and Time Series Outlier Analysis
Open Access
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Type Preprint
Year 2019
Language English
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Strategic Management & Leadership

Forecasting U.S. Textile Comparative Advantage Using Autoregressive Integrated Moving Average Models and Time Series Outlier Analysis

Zahra Saki , Lori Rothenberg, Marguerite Moor, Ivan Kandilov, A. Blanton Godfrey
External / Open Access
2019 arXiv Preprint

Abstract

To establish an updated understanding of the U.S. textile and apparel (TAP) industrys 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.
Full Title Forecasting U.S. Textile Comparative Advantage Using Autoregressive Integrated Moving Average Models and Time Series Outlier Analysis
Primary Author Zahra Saki
Co-Authors Lori Rothenberg, Marguerite Moor, Ivan Kandilov, A. Blanton Godfrey
Publication Type Preprint
Year 2019
Journal arXiv Preprint
Category Strategic Management & Leadership
Institution External / Open Access
Access Open Access
Added to Library March 24, 2026

Cite This Publication

APA
Zahra Saki, Lori Rothenberg, Marguerite Moor, Ivan Kandilov, A. Blanton Godfrey (2019). *Forecasting U.S. Textile Comparative Advantage Using Autoregressive Integrated Moving Average Models and Time Series Outlier Analysis*. External / Open Access.
MLA
Zahra Saki. *Forecasting U.S. Textile Comparative Advantage Using Autoregressive Integrated Moving Average Models and Time Series Outlier Analysis*. External / Open Access, 2019.