Logistics and transport are becoming increasingly important in international trade relations. Logistic Performance Index (LPI) analyses the differences between countries, providing a general picture of customs procedures, logistics costs and the quality of the infrastructure necessary for overland and maritime transport. The aim of this article is to analyse the impact that each of the components that make up the LPI has on emerging countries' trade, employing a gravity model. Furthermore, the study also aims to detect possible advances in logistics in these countries, which are grouped into five regions (Africa, South America, Far East, Middle East and Eastern Europe) by comparing the first LPI data published in 2007 with the most recent data, released in 2012. The results obtained reveal that improvements in any of the components of the index cause the country to increase its volume of trade. Specifically, LPI components are becoming increasingly important for the countries in Africa, South America and Eastern Europe.
This article aims to analyse the importance of logistics performance in European Union (EU) exports over a sample period in order to detect possible advances on behalf of Member States. We will estimate several gravity equations using the Logistics Performance Index (LPI) and its components as characteristic proxy variables of trade facilitation. In order to avoid the possible heterogeneity caused by sample bias, we will employ the two-stage model proposed by Heckman. The estimations of the gravity models using the two-stage Heckman model for 26 EU countries lead to the conclusion that logistics were more important for exporting nations than importing nations in both
Logistics and transport increasingly play a pivotal role in international trade relations. The Logistics Performance Index (LPI) measures the on-the-ground efficiency of trade supply chains or logistics performance. The aim of this paper is to propose a data envelopment analysis (DEA) approach to compute a synthetic index of overall logistics performance (DEA-LPI) and benchmark the logistics performance of the countries with LPI. Dealing with the six dimensions of LPI, the proposed approach uses DEA as a tool for multiple criteria decision making (MCDM). Furthermore, the paper also analyses the potential differences observed when using different variables, namely income and geographical area. Our findings suggest that the logistics performance depends largely on income and geographical area. High income countries are in the group of best performers, which is highly dominated by the EU.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.