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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.
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.
Industrialization to achieve economic development has resulted in
global environmental degradation. While the impacts of industrial
activity on the natural environment are a major concern in
developed countries, much less is known about these impacts in
developing countries. This source book identifies and quantifies
the environmental consequences of industrial growth, and provides
policy advice, including the use of clean technologies and
environmentally sound production techniques, with special reference
to the developing world.The developing world is often seen as
having a high percentage of heavily polluting activities within its
industrial sector. This, combined with a substantial agricultural
sector, which contributes to deforestation, the erosion of the top
soil and desertification, has lead to extreme pressures on the
environment and impoverishes the population by destroying its
natural resource base. This crisis suggests that sound
industrialization policies are of paramount importance in a
developing countries' economic development, and calls for the
management of natural resources and the adoption of low-waste or
environmentally clean technologies. The authors consider the
industrial sector as a pollutant vis-a-vis other sectors of the
economy, and then focus on some industry-specific pollutants within
the manufacturing sector and some process-specific industrial
pollutants. They conclude by reviewing the economic implications of
promoting environmentally sound industrial development,
specifically addressing the question of the conflict or
complementarity which may exist between environmental goods and
industrial production. The book will be essential to those working
in industry, development and environmental economics.
RONALD C. DUNCAN During the 1980s, substantial advances were made
in the global modelling of commodity markets in several areas,
advances which were reflected in many of the papers delivered to
the Applied Econometrics Association meeting held at the World Bank
in Washington, DC, in October 1988. The several areas where I see
advances being made, some of which the International Commodity
Markets Division of the World Bank has taken part in, are the
following: (a) in the theoretical specification of commodity price
behaviour; (b) in the increased emphasis on modelling imperfect
markets; (c) in the incorporation of the interrelationships between
macro economic and commodity market variables; (d) in the
specification of supply response, particularly in respect of
perennial crops; and (e) in the realization of complementarity
between time series analysis and economet rically estimated
structural models. Improvements in the specification of the
commodity price formation process have probably been the most
important of the above advances. Until the early 1980s, prices were
modelled as a simple linear function of stocks. Gilbert has played
an important role in introducing the rational expecta tions
hypothesis into the specification of commodity prices. Recent work
by Gilbert, Trivedi, and Deaton and Laroque offers the possibility
of non-linear specification of the relationship between prices and
stocks within an expectational framework and of thereby capturing
the phenomenon of sharp run-ups in commodity prices. Gilbert has
also played an important role in clarifying the interrelation ships
between macroeconomic variables and primary commodity prices."
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.
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."
Taking a sequential approach to time-series model building, this
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. The authors also
provide advice on how to perform the tests using different software
packages. "This provides a nice roadmap for those doing time series
analysis, and the authors should be applauded for this... Their
approach is straightforward and logical and I believe will be
useful many practicing statisticians." --Technometrics
Part of a series, this volume comprises a selection of
methodology-oriented papers presented at the 25th International
Conference of the Applied Econometrics Association on International
Commodity Market Modelling which took place at the World Bank,
Washington, 1988. Economic and statistical analyses are obviously
of great importance in studying commodity markets. A deep knowledge
of market-clearing processes, the institutional structures of the
industries related to each commodity market whether on the supply
or demand side and the statistical methods of data handling for
inference purposes are all needed in order to make good sense of
the wealth of information on commodity market data. In addition, a
technological understanding of the economic processes underlying
each market is necessary. The agronomy of crop production, the
techniques of crop distribution from harvest to end-use, the
contributions of meteorology, the engineering of metallurgy, the
engineering of processing factories, the combating of oil spills,
the control of pollution and many other technological aspects of
the different markets are essential for a good understanding of the
forces at work in each case. Also legal and political factors play
roles in the markets and require some specialized knowledge of
their effects. Almost every market is different and so a
specialized technological background is required, but that adds
much substance to the research. By fitting together appropriate
cross-disciplinary bodies of information in commodity market
studies, a high degree of interest and analytical challenge can be
attained.
Which time series test should a researcher chose to best describe
the interactions among a set of time series variables? Aimed at
providing social scientists with practical guidelines for
identifying the appropriate multivariate time series model to use,
this book explores the nature and application of these increasingly
complex tests. Other topics it covers are joint stationarity,
testing for cointegration, testing for Granger causality, and
testing for model order, and forecast accuracy. Related models
explained include transfer function, vector autoregression, error
correction models, and others. Readers with a working knowledge of
time series regression will find this helpful book accessible.
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