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2584. The International Logistics Performance Index as A Useful Predictor of Trade openness: A Classification and Regression Tree (CART) Analysis

Invited abstract in session WB-56: Advancing mobility towards sustainable solutions IV, stream Transportation.

Wednesday, 10:30-12:00
Room: S04 (building: 101)

Authors (first author is the speaker)

1. Danny Cho
Goodman School of Business, Brock University
2. Tomson Ogwang
Economics, Brock University

Abstract

An important attribute of globalization is the escalation of the movement of goods across international borders, heightening the need for trade facilitation. In 2007, the World Bank released the maiden version of the Logistics Performance Index (LPI) as a numerical yardstick for gauging progress towards trade facilitation. The LPI is an equally weighted six-component composite index that lies between 1 (the worst-case scenario) and 5 (the best-case scenario). The LPI provides valuable information to many stakeholders around the world, including supply chain and logistics professionals, academics, and trade agencies, among others. The purpose of this paper is to examine the ability of the individual components of the LPI to predict trade openness (where trade openness is defined as the sum of exports and imports, expressed as a percentage of GDP). The empirical analysis of the latest LPI data is conducted using Classification and Regression Trees (CART), which does not only have the advantage of capturing potentially complex relationship between the individual LPI components and trade but also lead to the identification of the most important components based on the trimming algorithm. Our empirical results indicate a strong potential of CART in enhancing the usefulness of the LPI.

Keywords

Status: accepted

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