Economic Geography of U.S. Apparel Trade: Home Market and Vertical Linkage Effects

ABSTRACT

A partial equilibrium trade model is used to test the role of vertical linkages and home market effects on the pattern of U.S. apparel trade, while controlling for trade costs and comparative advantage. Input output data is used to investigate the significance of linkages between the apparel and textile industries. Industrial production data is used to provide industry specific estimates of the home market effect. We find strong evidence of home market effects that increase with the phasing out of apparel quotas. Strong linkages between the apparel and textile industries in the exporting country are positively correlated with apparel exports.

KEYWORDS:

• Economic geography
• home market
• vertical linkage
• apparel quotas

Acknowledgments

The author is very grateful to the editor and two anonymous referees for their helpful and insightful comments.

Disclosure statement

No potential conflict of interest was reported by the author.

Supplementary material

Supplemental data for this article can be accessed on the publisher’s website.

Notes

¹ One approach is to estimate the correlation between industry supply and industry demand across countries. Using this approach, Davis and Weinstein (1999, 2003) find evidence consistent with the home market effect for many manufacturing industries in the OECD and Japanese regions. Head and Ries (2001) find evidence of similar patterns of the home market effect in Canada and the United States. A second approach to estimating the home market effect is to examine the income elasticity of exports using a gravity model. Feenstra, Markusen, and Rose (2001) and Schumacher and Siliverstovs (2006) find significant home-market effects for differentiated goods, which may be capital intensive or labor intensive. Hanson and Xiang (2004) find that industries with high transport costs and more differentiated products tend to be more concentrated in large countries.

² Evans and Harrigan (2005a), Harrigan and Barrows (2009), and Brambilla, Khandelwal, and Schott (2010).

³ Spinanger (2003), Nordas (2004), Mlachila and Yang (2004), Kar and Kar (2011), and Kar and Kar (2016).

⁴ See the Appendix and Fukao, Okubo, and Stern (2003) for a detailed description of the model. The appendix can be found online at www.tandfonline.com/uitj.

⁵ Although the share of domestic textile output used in the domestic apparel industry is the ideal measure of vertical linkage, the WIOD database classifies textile and textile products (apparel) as one sector.

⁶ See Oostendorp (2012) for details.

⁷ The data has missing values for some countries. Where feasible, data for the missing years was interpolated using linear methods.

⁸ Data from OECD statistics on real minimum wage. https://stats.oecd.org/Index.aspx?DataSetCode = RMW is used to substitute for countries which were missing occupational wage data in the World Bank database.

⁹ Martínez-Zarzoso, Felicitas Nowak-Lehmann, and Vollmer (2007) propose feasible generalized least squares (FGLS) as an appropriate model if the exact form of heteroskedasticity in data is unknown, since it weighs the observations according to the square root of their variances and is robust to any form of heteroskedasticity.

¹⁰ $lny=\alpha +{\beta }_{1}ln{x}_1+{\beta }_{2}ln{x}_2+{\beta }_{3}ln{x}_{1}ln{x}_2$; $\frac{dy}{dx1}\frac{x1}{y}={\beta }_1+{\beta }_{3}ln{x}_2$, is the percent change in y from a 1% increase in x₁, holding x₂ constant.

¹¹ The estimates from the WIOD sample yield parallel results. The figures are not reported in order to conserve space.