Country‐Specific Determinants of Horizontal and Vertical Intra‐industry Agri‐food Trade: The Case of the EU New Member States

Abstract

Intra‐industry trade (IIT) has become a widespread phenomenon with a growing role in international trade, though agricultural trade is usually neglected in empirical works. This article identifies the determinants of horizontal and vertical intra‐industry agri‐food trade between New Member States (NMS) and the EU‐27 in 1999–2010, by applying static and dynamic models with different specifications to panel data. Results show that IIT is mainly of a vertical nature in the NMS, though the majority of NMS export low quality agri‐food products to EU‐27 markets. Factor endowments are negatively related to agri‐food horizontal intra‐industry trade (HIIT), but positively to vertical intra‐industry trade (VIIT). Economic size is positively and significantly related to both types of IIT, while distance and IIT are found to be negatively related in both cases. Results also suggest that HIIT and VIIT are greater if a New Member State exports agri‐food products to another NMS while EU accession has had positive and significant impacts on both HIIT and VIIT, suggesting that economic integration fosters IIT.

Country- and industry-specific determinants of intra-industry trade in agri-food products in the Visegrad countries

“…Our fi ndings are similar to the majority of the literature (Fertő, 2005;Turkcan and Ates, 2010;Jámbor, 2014) who found a negative relationship between vertical IIT and GDP per capita differences. Similarly to studies on manufacturing sectors, the results do not support comparative advantage explanation of vertical IIT (Milgram-Baleix and MoroEgido, 2010).…”

“…However, low values for total IIT (the sum of vertical and horizontal IIT) suggest that IIT prevails in the agri-food trade of these countries with the EU in the analysed period. These fi ndings are consistent with the results of previous research (Fertő, 2005;Jámbor, 2014) and with earlier studies indicating that proportion of the IIT was higher for food products involving a greater degree of processing (McCorriston and Sheldon, 1991;Qasmi and Fausti, 2001). …”

“…Differences in country size and income were positively related to IIT as is FDI, while distance and IIT showed a negative relationship. Jámbor (2014) and Fertő and Jámbor (2015) analysed country-specifi c determinants of IIT for agri-food products for the post-socialist EU Member States and found that factor endowments are ambiguously related to HIIT and VIIT in agri-food products. Economic size was found to be positively and signifi cantly related to both types of IIT, while distance and IIT were found to be negatively related in both cases.…”

“…In estimating the determinants of IIT, this study applies the generalised method of moments (GMM) panel model elaborated by Blundell and Bond (1998) and used in the recent literature (Leitão, 2012;Jámbor, 2014). Although many other static panel data techniques are available in the literature including pooled OLS, fi xed effects (FE) and random effects (RE), feasible generalised least squares (FGLS) and the panel-corrected standard errors (PCSE) method, they are criticised for many reasons.…”

Determinants of the revealed comparative advantages: The case of the European ham trade

“…Many other static and dynamic panel data techniques are available including the pooled OLS, the fixed effects (FE) and the random effects (RE), the feasible generalised least squares (FGLS) and the GMM-SYS method, though contrary to the recent studies (Leitao 2012;Jámbor 2014;Fertő and Jámbor 2015), the PCSE method provided the best results for our sample.…”