This study provides an overview of trends and identifies country-specific determinants of intra-industry trade (IIT) between the United States (U.S.), the European Union (EU) and the North American Free Trade Agreement (NAFTA) trading partners. We analyze the food and live animal industry at the Standard International Trade Classification (SITC) revision 4 at the 4-digit level to calculate IIT and cover the period between 2007 and 2014. To determine the country-specific determinants of IIT, we used a Generalized Least Squares (GLS) random effect model. Results indicate that the size of an economy, the relative difference in level of economic development, the real exchange rate and research and development (R&D) are positively associated with IIT, while, trade imbalance, geographical distance and available arable land are negatively correlated with the IIT share. The results suggest that countries with relatively large economies, with high levels of per capita income, that are geographically near to one another and with a low trade imbalance are associated with having comparatively high levels of IIT in the food and live animal industry. Results also show an increasing IIT trend for most U.S. trading partners in the food and live animal industry during the period of analysis. IIT and value-added agriculture both involve trade and production of differentiated products, so their increased importance is closely linked. Value-added products involve high profit margins relative to raw commodities and increased importance of value-added agriculture activities goes hand-in-hand with the growing role of IIT in total international trade in agriculture and food products and it may open the door for additional international trade.
","abstract_html":"<p>This study provides an overview of trends and identifies country-specific determinants of intra-industry trade (IIT) between the United States (U.S.), the European Union (EU) and the North American Free Trade Agreement (NAFTA) trading partners. We analyze the food and live animal industry at the Standard International Trade Classification (SITC) revision 4 at the 4-digit level to calculate IIT and cover the period between 2007 and 2014. To determine the country-specific determinants of IIT, we used a Generalized Least Squares (GLS) random effect model. Results indicate that the size of an economy, the relative difference in level of economic development, the real exchange rate and research and development (R&D) are positively associated with IIT, while, trade imbalance, geographical distance and available arable land are negatively correlated with the IIT share. The results suggest that countries with relatively large economies, with high levels of per capita income, that are geographically near to one another and with a low trade imbalance are associated with having comparatively high levels of IIT in the food and live animal industry. Results also show an increasing IIT trend for most U.S. trading partners in the food and live animal industry during the period of analysis. IIT and value-added agriculture both involve trade and production of differentiated products, so their increased importance is closely linked. Value-added products involve high profit margins relative to raw commodities and increased importance of value-added agriculture activities goes hand-in-hand with the growing role of IIT in total international trade in agriculture and food products and it may open the door for additional international trade.</p>","abstract_has_math":false,"creators":["Chakraborty, Shuvo"],"institution":null,"degree_name":"Master of Science (MS)","degree_level":"Thesis - Open Access","degree_discipline":"Economics","degree_department":null,"school":null,"contributors":["Evert Van der Sluis"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2017,"date_issued":"2017-01-01T08:00:00Z","date_published":"2017-01-01T08:00:00Z","updated_at":"2026-07-24T04:28:43Z","subjects":["agricultural trade","EU Trade","food and live animal industry","intra-industry trade","NAFTA","trade of the United States","Economics"],"languages":["en"],"rights":[],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[]},"links":{"outbound_url":"https://openprairie.sdstate.edu/etd/1174","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Evert Van der Sluis"]},{"key":"dc:creator","label":"Author","values":["Chakraborty, Shuvo"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2017-05-09T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Economics"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis - Open Access"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science (MS)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["agricultural trade","EU Trade","food and live animal industry","intra-industry trade","NAFTA","trade of the United States","Economics"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["http://rightsstatements.org/vocab/InC/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://openprairie.sdstate.edu/etd/1174"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This study provides an overview of trends and identifies country-specific determinants of intra-industry trade (IIT) between the United States (U.S.), the European Union (EU) and the North American Free Trade Agreement (NAFTA) trading partners. We analyze the food and live animal industry at the Standard International Trade Classification (SITC) revision 4 at the 4-digit level to calculate IIT and cover the period between 2007 and 2014. To determine the country-specific determinants of IIT, we used a Generalized Least Squares (GLS) random effect model. Results indicate that the size of an economy, the relative difference in level of economic development, the real exchange rate and research and development (R&D) are positively associated with IIT, while, trade imbalance, geographical distance and available arable land are negatively correlated with the IIT share. The results suggest that countries with relatively large economies, with high levels of per capita income, that are geographically near to one another and with a low trade imbalance are associated with having comparatively high levels of IIT in the food and live animal industry. Results also show an increasing IIT trend for most U.S. trading partners in the food and live animal industry during the period of analysis. IIT and value-added agriculture both involve trade and production of differentiated products, so their increased importance is closely linked. Value-added products involve high profit margins relative to raw commodities and increased importance of value-added agriculture activities goes hand-in-hand with the growing role of IIT in total international trade in agriculture and food products and it may open the door for additional international trade.
"]},{"key":"dc:title","label":"Title","values":["Intra-Industry Trade in Agricultural Products Between the United States, NAFTA and European Union Trading Partners"]}]}],"canonical_facts":{"dc:contributor":["Evert Van der Sluis"],"dc:creator":["Chakraborty, Shuvo"],"dc:date.available":["2017-05-09T07:00:00Z"],"dc:description.abstract":["This study provides an overview of trends and identifies country-specific determinants of intra-industry trade (IIT) between the United States (U.S.), the European Union (EU) and the North American Free Trade Agreement (NAFTA) trading partners. We analyze the food and live animal industry at the Standard International Trade Classification (SITC) revision 4 at the 4-digit level to calculate IIT and cover the period between 2007 and 2014. To determine the country-specific determinants of IIT, we used a Generalized Least Squares (GLS) random effect model. Results indicate that the size of an economy, the relative difference in level of economic development, the real exchange rate and research and development (R&D) are positively associated with IIT, while, trade imbalance, geographical distance and available arable land are negatively correlated with the IIT share. The results suggest that countries with relatively large economies, with high levels of per capita income, that are geographically near to one another and with a low trade imbalance are associated with having comparatively high levels of IIT in the food and live animal industry. Results also show an increasing IIT trend for most U.S. trading partners in the food and live animal industry during the period of analysis. IIT and value-added agriculture both involve trade and production of differentiated products, so their increased importance is closely linked. Value-added products involve high profit margins relative to raw commodities and increased importance of value-added agriculture activities goes hand-in-hand with the growing role of IIT in total international trade in agriculture and food products and it may open the door for additional international trade.
"],"dc:identifier":["https://openprairie.sdstate.edu/etd/1174"],"dc:language":["en"],"dc:rights":["http://rightsstatements.org/vocab/InC/1.0/"],"dc:subject":["agricultural trade","EU Trade","food and live animal industry","intra-industry trade","NAFTA","trade of the United States","Economics"],"dc:title":["Intra-Industry Trade in Agricultural Products Between the United States, NAFTA and European Union Trading Partners"],"thesis:degree_discipline":["Economics"],"thesis:degree_level":["Thesis - Open Access"],"thesis:degree_name":["Master of Science (MS)"]},"updated_at":"2026-07-24T04:28:43Z"}