A Hybrid Neural Network Method for Detecting Structural Change in Oil-Bioenergy Crops Prices System

摘要

The present study detects the structural change in oil-bioenergy crops prices system before and during the food crisis of 2007/2008 and financial crisis 2008/2010. In the recent years, rising world crude oil prices lead to increase of bioenergy production around the world. Bioenergy, in turn, affects bioenergy crops price, because it uses these commodities as inputs. We develop a hybrid neural network approach which can test the structural change of the linkages without priori knowledge of the input data distribution. And then we studies price linkages applying the hybrid neural network to two major bioenergy crops prices, including Argentina corn and Brazil soybean, along with two major crude oil price, including West Texas and Brant crude oil. The data consists of 1467 observations from January 2006 to November 2011. The empirical findings confirm that the structures of oil-bioenergy crops prices system change observably during the food crisis and the financial crisis.