Modeling and Forecasting Primary Commodity Prices. This item is unavailable.Modeling and Forecasting Primary Commodity Prices

Recent economic growth in China and other Asian countries has led to increased commodity demand which has caused price rises and accompanying price fluctuations not only for crude oil but also for the many other raw materials. Such trends mean that world commodity markets are once again under intense scrutiny. This book provides new insights into the modeling and forecasting of primary commodity prices by featuring comprehensive applications of the most recent methods of statistical time series analysis. The latter utilize econometric methods concerned with structural breaks, unobserved components, chaotic discovery, long memory, heteroskedasticity, wavelet estimation and fractional integration. Relevant tests employed include neural networks, correlation dimensions, Lyapunov exponents, fractional integration and rescaled range. The price forecasting involves structural time series trend plus cycle and cyclical trend models. Practical applications focus on the price behaviour of more than twenty international commodity markets.

Professor Walter C. Labys is Benedum Distinguished Scholar in the Agricultural and Resource Economics Program at West Virginia University, USA. He is Gunnar Myrdal Scholar at the United Nations Economics Commission for Europe and has been Faculty Research Associate of the Group on Applied Econometric Research at the University of the Mediterranean (Aix-Marseille) in France. Over the past thirty years, Professor Labys has pioneered in the development and application of econometric methods important for analyzing commodity price behaviour, the modelling of agricultural, mineral and energy markets, and the impact of commodity markets on the stability and growth of surrounding developing economies. He has authored and co-authored more than fourteen books and numerous articles in leading journals of agricultural, energy and resource economics as well as international trade.