Investigating the Co-movement of Cocoa and Coffee Prices in International Markets: Evidence from Non-linear Autoregressive Distributed Lag Model and Rolling Window Methods

Abstract

The focus of this study is to empirically investigate the co-movement of Cocoa, Arabica, and Robusta coffee prices for 1960-2018. An essential contribution of the present study is using the non-linear autoregressive distributed lagged co-integration technique and rolling window-based methods for empirical analysis and to check the co-integration among variables. At the same time, the Auto Regressive Distributed Lagged (ARDL) bound test and Gregory-Hansen co-integration techniques are employed for robust analysis. The empirical estimations indicate that the positive shocks in Cocoa prices have affected Arabica and Robusta coffee prices in the short and long run. For Cocoa and Arabica coffee estimations, the one unit of positive change of cocoa price tends to increase the Arabica price with 0.1445 and 0.806 for the short run and long run, respectively. These findings suggest that the increase in cocoa price causes an increase in the demand for Arabica coffee from importing countries. Similar results are confirmed in the case of Cocoa and Arabica. At the same time, the adverse shocks in Robusta coffee prices have affected Cocoa prices with greater magnitude in the long run. Thus, our outcomes also confirm the co-movement of the coffee and cocoa prices.