Complexity of agricultural commodity cycle: a chaotic time series analysis

Most empirical investigations of agricultural markets have been conducted using linear models. Therefore, nonlinear dynamic patterns of the market cannot be predicted based on these models under any circumstances. Consequently, little is known about the role of nonlinear dynamics and the whether we can predict the market both for short- and long-term in agriculture. We utilise the real world data of piglet market data in Japan to understand nonlinear dynamics. The post-second oil crisis data showed that both short- and long-term predictions were possible with a high degree of accuracy. The pre-crisis data showed the possibility of short-term prediction, but the impossibility of long-term prediction. The results implied that the dynamics were chaotic in the pre-crisis period. Since government fixed price system was introduced after the second oil crisis, we conclude that government policy contribute to stabilise the market.