Article: Complexity of agricultural commodity cycle: a chaotic time series analysis Journal: International Journal of Agricultural Resources, Governance and Ecology (IJARGE) 2004 Vol.3 No.3/4 pp.266 - 287 Abstract: 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. Inderscience Publishers - linking academia, business and industry through research

Title: Complexity of agricultural commodity cycle: a chaotic time series analysis

Authors: Kenshi Sakai, Shunsuke Managi, Katsuhiko Demura

Addresses: Department of Eco-Regional System Science, Production Engineering Laboratory, Tokyo University of Agriculture and Technology, 3-8-5 Saiwai-cho, Fuchu, Tokyo 183, Japan. ' Graduate School of Bio-Applications and Systems Engineering, Tokyo University of Agriculture and Technology, Koganei, Tokyo 184-8588, Japan. ' Department of Agricultural Economics, Graduate School of Agriculture, Hokkaido University, N9, W9, Sapporo 060, Japan

Abstract: 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.

Keywords: chaos; nonlinear dynamics; empirical analysis; agricultural market; agricultural commodity cycle; complexity; Japan; piglet market data; government policy; fixed prices; market stability; sustainable development; sustainable agriculture.

DOI: 10.1504/IJARGE.2004.006040

International Journal of Agricultural Resources, Governance and Ecology, 2004 Vol.3 No.3/4, pp.266 - 287

Published online: 23 Jan 2005 *

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Title: Complexity of agricultural commodity cycle: a chaotic time series analysis

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