Premium
Determinants and Relationships in Sectoral Trade: A Bilateral Model for Knitwear Clothing
Author(s) -
Chakrabarty Subhajit,
Nag Biswajit,
Dasgupta Pinaki,
Rastogi Siddhartha K.
Publication year - 2016
Publication title -
thunderbird international business review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.553
H-Index - 37
eISSN - 1520-6874
pISSN - 1096-4762
DOI - 10.1002/tie.21787
Subject(s) - clothing , context (archaeology) , economics , bilateral trade , competition (biology) , vector autoregression , product (mathematics) , explanatory power , clothing industry , international economics , recession , emerging markets , textile industry , international trade , econometrics , macroeconomics , history , paleontology , ecology , philosophy , geometry , mathematics , archaeology , epistemology , political science , law , china , biology
The generalized aggregated trade models do not capture the industry or product‐specific competitive situation and overgeneralize the bilateral cases. As a result, product‐specific trade determinants at the sectoral or bilateral level cannot be sufficiently drawn from such generalized models. This holds true for knitwear clothing products, an important component of international textile trade. To remedy this, we propose a sector‐specific bilateral model in the context of knitwear clothing exports from India to the United States. This pair of countries is chosen due to unilateral trade flows as well as to underline the contrasting features of developed north versus developing south. The vector autoregression ( VAR ) model was found more appropriate than other available modeling choices. We used monthly frequency data from January 2006 to December 2012. The traditional determinants such as exchange rate and price competitiveness remain relevant. Chinese competition emerges as a significant determinant, which underlines the relevance of a sector‐specific bilateral trade model. The 2009 recession showed a clear impact, albeit for only a few months. Our model is parsimonious but has more explanatory power than generalized models. Policy researchers may further explore the model for more fine‐tuned policy on sector‐specific factors. © 2016 Wiley Periodicals, Inc .