Modeling Africa’s Demand for Iron and Steel Importation: An International Market Estimation Method Perspective

Abstract

This paper describes the first part of my PhD research project where Africa’s Demand for Iron and Steel Importation Long-Term Relationship with its explanatory variables is investigated. We employ a panel of 19 African countries for a period that spans from 1994 to 2012. We consider the long-term relationship that may exist between the iron and steel importations and the explanatory variables used (GDP per capita, investment in infrastructure, real effective exchange rate, and the number of urban population). The empirical analysis is divided in three parts in this study. In the first part, the panel unit root tests and stationary tests revealed that all variables have a unit root; in first differences, they are stationary, these variables are integrated of order 1 or I (1) and the level of the variables are I (1). In the second part, the different cointegration tests conducted between the dependent variable and the explanatory variables result in the confirmation of the fact that they are cointegrated. In the third part, an estimation of the long-run relationship is carried out with Panel Error Correction Modeling (ECM) using Pooled Mean Group Regression Methods. The importations of iron and steel are positively correlated with all the independent variables of the model. All estimated coefficients are positive and significant at 1% level of significance. The usual determinants of importations (demand factor and factor price competitiveness) are significant in the modeling of iron and steel importations and signs are consistent with expectations except the real effective exchange rate.