This study uses a recently developed statistical methodology based on \(R^{2}\) decomposition to examine the connectivity among wheat prices in Italy. It is firstly shown through a simulation study that the \(R^{2}\) decomposition methodology is able to capture the presence of dependence among variables and to detect changes in the level of dependence among those variables. The methodology is then applied to wheat prices of Italian cities over the period 1780–1895, which is characterized by wars and territorial reshuffling. The empirical results show that the dynamics of connectivity tends to change in proximity of such events. Supplementary materials accompanying this paper appear online.
