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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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  • Zahra Saki
  • Lori Rothenberg
  • Marguerite Moor
  • Ivan Kandilov
  • A. Blanton Godfrey

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.

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  • 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," Papers 1908.04852, arXiv.org.
    • Handle: RePEc:arx:papers:1908.04852
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