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.
This book provides a framework for analyzing and forecasting a variety of mineral and energy markets and related industries. Such modeling activity has been at the forefront of the economic and engineering professions for some time, having received a major stimulus fC?llowing the first oil price shock in 1973. Since that time, other shocks have affected these markets and industries, causing disequilibrium economic adjustments which are difficult to analyze and to predict. Moreover, geopolitics remains an important factor which can destabilize crude oil markets and associated refining industries. Mineral and energy modeling, consequently, has become a major interest of energy-related corporations, mining and drilling companies, metal manufacturers, public utilities, investment banks,. national government agencies and international organizations. This book hopes to advance mineral and energy modeling as follows: (1) The modeling process is presented sequentially by leading the model builder from model specification, estimation, simulation, and validation to practical model applications, including explaining history, analyzing policy, and market and price forecasting; (2) New developments in modeling approaches are presented which encompass econometric market and industry models, spatial equilibrium and programming models, optimal resource depletion models, input-output models, economic sector models, and macro oriented energy interaction models (including computable general equilibrium); (3) The verification and application of the models is considered not only individually but also in relation to the performance of alternative modeling approaches; and (4) The modeling framework includes a perspective on new directions, so that the present model building advice will extend into the future.
Originally published in 1984 this book remains as relevant as when it was first published. At that time the oil crises of the 1970s and the growing international debt burden highlighted the extent to which events in primary commodity markets continue to influence the economies of developing and industrialized economies alike. Commodity modelling has become a valuable tool in efforts to predict and understand the behaviour of commodity markets and thereby reduce their fluctuations. This book provides an overview of the nature of the different types of commodity model as well as their diverse applications. In non-technical language the reader is introduced to the underlying modelling methodologies, including their advantages, limitations and commodity specific implications. The book will be of interest to commodity economists, traders and analysts, economic planners and those involved in agricultural, mineral and energy modelling.
Taking a sequential approach to time-series model building, this easy-to-use and widely applicable book explores how to test for stationarity, normality, independence, linearity, model order, and properties of the residual process. The authors clearly define each testing procedure and offer examples to illustrate each concept. They also offer sound advice on how to perform the tests using different software packages.
Industrialization to achieve economic development has resulted in global environmental degradation. This book identifies/quantifies environmental consequences of industrial growth, and provides policy advice, including the use of clean technologies, with reference to the developing world.
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.
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