Oil spills on other commodities

This paper examines the effect of crude oil prices on the prices of 35 internationally traded primary commodities for the 1960–2005 period. It finds that the pass-through of crude oil price changes to the overall non-energy commodity index is 0.16. At a more disaggregated level, the fertilizer index had the highest pass-through (0.33), followed by agriculture (0.17), and metals (0.11). The prices of precious metals also exhibited a strong response to crude oil price. In terms of individual commodities, the estimates of the food group exhibited remarkable similarity while those of raw materials and metals gave a mixed picture. The implication is that if crude oil prices remain high for some time, as most analysts expect, then the recent commodity price boom is likely to last much longer than earlier booms, at least for food commodities. The other commodities, however, are likely to follow diverging paths. On the methodological side, the results show that price indices, while providing useful summary statistics, they need to be supplemented by individual commodity analysis.     

An overview of global gold market and gold price forecasting

The global gold market has recently attracted a lot of attention and the price of gold is relatively higher than its historical trend. For mining companies to mitigate risk and uncertainty in gold price fluctuations, make hedging, future investment and evaluation decisions, depend on forecasting future price trends. The first section of this paper reviews the world gold market and the historical trend of gold prices from January 1968 to December 2008. This is followed by an investigation into the relationship between gold price and other key influencing variables, such as oil price and global inflation over the last 40 years. The second section applies a modified econometric version of the long-term trend reverting jump and dip diffusion model for forecasting natural-resource commodity prices. This method addresses the deficiencies of previous models, such as jumps and dips as parameters and unit root test for long-term trends. The model proposes that historical data of mineral commodities have three terms to demonstrate fluctuation of prices: a long-term trend reversion component, a diffusion component and a jump or dip component. The model calculates each term individually to estimate future prices of mineral commodities. The study validates the model and estimates the gold price for the next 10 years, based on monthly historical data of nominal gold price.     

Forecasting precious metal price movements using trader positions

In the early 2000s, the precious metal markets entered into a new phase where a steady rise of prices had been observed until the October 2008 crash. Given the size and importance of precious metal market, as well as the hedging capacity of precious metals due to their low correlation with equity markets (Draper et al., 2006), the question we want to arise is whether trader positions predict the direction of gold, platinum, and silver spot price movements. The forecasting content of the Commodity Futures Trading Commission’s Commitment of Traders report for platinum, silver and gold prices using trader positions is investigated in a VAR framework. Granger causality tests are conducted to determine whether a relation between trader positions and market prices exists. An examination of the extreme trader positions on price movements is also conducted. The results indicate that market return is a significant parameter in explaining trader’s positions for all trader types in each of the precious metal markets under consideration after the beginning of 2000s where we detect a structural break for each of the market under study. Commercial traders are found to be negative feedback traders, that is, they sell when the prices increase in the market. On the other hand, in line with the previous literature, a positive correlation between returns and positions held by non-commercial and non-reporting traders is found. However, trader’s net positions do not lead market returns in general. There is some evidence on the forecasting ability of extreme trader positions on market returns.     

Financial and economic factors affecting the lignite prices in Turkey: An analysis of Soma and Can lignites

Using a simultaneous equation econometric model based on yearly data between 1997 and 2006 for the Aegean Lignite Enterprise this study examines factors that affect the lignite price in Turkey. The Aegean Lignite Enterprise produces and sells the lignite of Soma and Can and their data reflect the general Turkish situation. The results suggest that (1) lignite prices sold to the industry increase (decrease) depending on the decrease (increase) in the industrial production and (2) total electricity production and electricity price are the most important factors that potential investors and related persons have to take into consideration for the pricing of lignite in the thermal power plant market.     

Global Warming and Global Dioxide Emission: An Empirical Study

In this paper, the dynamic relationship between global surface temperature (global warming) and global carbon dioxide emission (CO₂) is modelled and analyzed by causality and spectral analysis in the time domain and frequency domain, respectively. Historical data of global CO₂emission and global surface temperature anomalies over 129 years from 1860–1988 are used in this study. The causal relationship between the two phenomena is first examined using the Sim and Granger causality test in the time domain after the data series are filtered by ARIMA models. The Granger causal relationship is further scrutinized and confirmed by cross-spectral and multichannel spectral analysis in the frequency domain. The evidence found from both analyses proves that there is a positive causal relationship between the two variables. The time domain analysis suggests that Granger causality exists between global surface temperature and global CO₂emission. Further, CO₂emission causes the change in temperature. The conclusions are further confirmed by the frequency domain analysis, which indicates that the increase in CO₂emission causes climate warming because a high coherence exists between the two variables. Furthermore, it is proved that climate changes happen after an increase in CO₂emission, which confirms that the increase in CO₂emission does cause global warming.     

The macroeconomic determinants of volatility in precious metals markets

This paper models the monthly price volatilities of four precious metals (gold, silver, platinum and palladium prices) and investigates the macroeconomic determinants (business cycle, monetary environment and financial market sentiment) of these volatilities. Gold volatility is shown to be explained by monetary variables, but this is not true for silver. Overall, there is limited evidence that the same macroeconomic factors jointly influence the volatility processes of the four precious metal price series, although there is evidence of volatility feedback between the precious metals. These results are consistent with the view that precious metals are too distinct to be considered a single asset class, or represented by a single index. This finding is of importance for portfolio managers and investors.     

The impact of monetary liquidity on Chinese aluminum prices

By expanding Frankel and Rose's (2009) theoretical model to consider the interaction of commodity prices with both money liquidity and expectation formation, this paper empirically studies the long-run relationship and short-term dynamics between aluminum prices and money liquidity via Vector autoregressive (VAR) and Impulse Response Function methodologies. Our results show that: (1) a cointegration relationship between money liquidity and Chinese aluminum prices exists, and monetary liquidity positively significantly influences the price over long periods; (2) a structural change has been found during the 2008 Financial Crisis and the change of Chinese monetary policies; and (3) the negative impact of production capacity mechanism on aluminum prices coexists with the positive impact of financial asset returns mechanism, to allow for varied market expectations on aluminum prices within and outside China.     

Impact of crude oil price volatility on economic activities: An empirical investigation in the Thai economy

This paper empirically examines the impact of oil price volatility on key macroeconomic indicators of Thailand. Following Andersen et al. [2004. Analytical evaluation of volatility forecasts. International Economic Review 45(4), 1079–1110], quarterly oil price volatility is measured by using the realized volatility (RV). The impact of the oil price volatility is investigated using the vector auto-regression (VAR) system. The Granger causality test, impulse response functions, and variance decomposition show that oil price volatility has significant impact on macroeconomic indicators, such as unemployment and investment, over the period from 1993Q1 to 2006Q4. Perron's [1997. Further evidence on breaking trend functions in macroeconomic variables. Journal of Econometrics 80(2), 355–385] test identifies structural breaks in all the concerned variables during the time of the Asian Financial Crisis (1997–1998). A VAR for the post-crisis period shows that the impact of oil price volatility is transmitted to budget deficit. The floating exchange rate regime introduced after the crisis may be the key contributor to this new channel of impact.     

Investor demand and spot commodity prices

The on-going debate over the influence of investor demand on spot commodity prices largely attempts to assess this influence by measuring the growth in investor demand in recent years. Given the serious data problems that plague such analyses, this article pursues another approach in the hope of providing useful insights into the impact of investor demand on spot commodity prices. It focuses on the mechanisms by which investor demand affects spot prices, and in particular on two questions. First, how does an increase in investor demand on the futures markets affect the spot market and spot price? Second, when investor demand is increasing and pushing a commodity's price up, do physical stocks of the commodity also have to be rising, as economists and others widely assume?On the first question, the article concludes that a surge in investor demand raising prices on the futures markets will have a direct and comparable effect on the spot market prices when these markets are in strong contango. However, when markets are in weak contango or backwardation, price movements in the futures markets have a much looser effect on spot prices. As a result, changes in investor demand on the futures markets may have little or no influence on spot prices in the absence of a strong contango. Instead, changes in fundamentals (that is, producer supply and consumer demand) and possibly changes in investor demand taking place directly on the spot market largely determine the spot price at such times.On the second question, the article shows that investor demand can be pushing up a commodity's price even when investor stocks are falling, despite the widespread presumption to the contrary.     

Metal prices and the business cycle

Metal price fluctuations have recently been of interest not only because of their cyclical volatility but also of their interaction with business cycles. A related issue is whether metal prices move together sufficiently to collectively reflect macroeconomic influences. Correlation or the tendency for prices to move together has been termed “comovement”, where the commonality in prices reflects the tendency of commodity markets to respond to common business cycle and trend factors. Metal prices are known to respond to macroeconomic influences and the latter might well explain the common factor which causes them to move together. Our goal is to provide an estimate of the common factor in metal prices and to relate this factor to important macroeconomic influences. The prices we study are for aluminum, copper, tin, lead and zinc; the macroeconomic variables include industrial production, consumer prices, interest rates, stock prices, and exchange rates. Our results confirm that the common factor in metal prices can be related to such macroeconomic influences.     

Long-term trends in the Real real prices of primary commodities: Inflation bias and the Prebisch-Singer hypothesis

Following the Boskin et al., (1996) report, it became widely recognized that price indexes in the U.S. and elsewhere overstate inflation. Svedberg and Tilton (2006) highlighted that this inflation bias may have important implications for estimated long-term trends in nonrenewable resource prices. ST construct an inflation-bias corrected CPI (and PPI) for the U.S. and use their corrected deflator(s) to define a so-called ‘real real’ price of copper. Their ‘real real’ price of copper is then used to re-estimate long-term trends in real copper prices. This paper proposes a quick method for obtaining inflation-bias-corrected estimates of long-run trends in real primary commodity prices directly from estimates in the published literature. Our approach obviates the need re-do existing empirical studies using a corrected or ‘real real’ price of nonrenewable resources. The two approaches are mathematically equivalent.     

The crude oil market and the gold market: Evidence for cointegration,causality and price discovery

Given that the gold market and the crude oil market are the main representatives of the large commodity markets, it is of crucial practical significance to analyze their cointegration relationship and causality, and investigate their respective contribution, from the perspective of price discovery, to the common price trend so as to interpret the dynamics of the whole large commodity market and forecast the fluctuation of crude oil and gold prices.     

A review of the PGM industry,deposit models and exploration practices: Implications for Australia's PGM potential

Australia is prospective for platinum group metal (PGM) mineralisation (in particular primary magmatic reef, primary magmatic by-product, late magmatic and hydrothermal, and alluvial placer type) but its known PGM endowment is negligible compared to that of South Africa, Russia, the USA and Canada. Most Australian PGM projects are operated by mid-cap or junior companies and form part of larger, more diverse project portfolios held by these explorers. Most projects were ‘hot’ while market conditions were favourable. However, as other metals became ‘fashionable’ and market conditions for PGM changed, so did the focus of these companies. Pure PGM companies are rare in Australia. The search for and development of PGM-only deposits in Australia are high risk business activities. No new primary PGM deposits have been discovered since the mid to late 1980s and none of the significant deposits that were discovered or evaluated in the 1980s have been mined. This review suggests that at least several A$10 million but more likely several A$100 million were sunk into PGM exploration and development projects but none advanced to the mining stage. The viability of Australian PGM projects is very sensitive to (1) metal prices, (2) the US$/A$ exchange rate, and (3) large capital expenditure requirements relative to the small size of Australian PGM-only deposits. Most PGM-only projects were initiated at times of high PGM prices. However, advanced exploration, feasibility studies and project development always lagged behind the price booms. South Africa, Russia and Canada contain approximately 98% of the known global PGM reserves. This situation has a very negative effect on the Australian PGM industry as the well-endowed nations continue to receive the lion's share of exploration spend and new projects.     

From the erosion of crude oil prices to reorganization of the oil industry

Comparison of data on world energy consumption for 1986, 1987 and 1988 indicates that the consumption of all forms of energy increased during the period, but the demand for oil increased at a lesser rate than that of other energy sources. Although the pattern varies between countries, the overall picture is one of increased use of natural gas, coal, nuclear and hydropower as an energy source. Part of the reason for the low growth in oil demand is the oil conservation measures put in place when oil was much more expensive, but may partly be due to the scepticism of many people about the future movement of oil prices. The likely continuation of a low growth market for oil has led some oil exporting countries to move downstream in an effort to secure a dependable market for their oil and oil products.     

Input–output analysis in an oil-rich economy: The case of Azerbaijan

This paper aims to provide empirical research to identify the linkages between final demand–total output, final demand–total supply, value-added ratios and prices, and also to analyze total factor productivity growth using input–output framework for 25 sectors. Studying the input–output tables for 2001 and 2006, the research estimates impact and response multipliers of non-oil sectors, as well as non-oil trading sectors. The results are important from the view of development of non-oil trading sectors and diversification of the economy in order to avoid the “resource curse”.     

Long-term iron ore price modeling: Marginal costs vs. incentive price

The paper studies and applies the approaches to forecast long-term (LT) real prices of iron ore. This price is crucial for valuation of investments in Greenfield iron ore projects on the horizon of more than 5 years. The forecast is obtained by three different approaches which are usually used by investment bank analysts: marginal costs approach and 2 approaches based on calculation of incentive price. The paper concludes that there has been a structural shift on the iron ore market and LT iron ore prices will be higher by 20–30% than the average of industry forecasters suggest. This is related to the 2 key factors which were taken into account in this study—depletion of existing iron ore deposits and targeted return on investments for new projects. In addition, escalated industry costs inflation is claimed to be the factor which will bolster nominal iron ore prices at high levels in the long-term. Using a Monte-Carlo simulation approach, confidence interval for future iron ore price was estimated.     

Is Russia suffering from Dutch Disease? Cointegration with structural break

This paper examines whether Russia suffers from “Dutch Disease” by investigating the real appreciation of the Russian ruble and the relative de-industrialization in the post Soviet Union-era. According to UNDP Russia Report (2009) the Russian economy has indeed exhibited some typical symptoms of “Dutch Disease” in recent years as upward movements in oil prices are accompanied by a reduction in the share of manufacturing output and an increase in service prices. Furthermore, the report claims that these developments may trigger a recession in Russia in the future. Using Gregory and Hansen (1996a, 1996b) and Arai and Kurozumi (2007) structural break cointegration frameworks, our results indicate that the Russian economy exhibits some typical symptoms of “Dutch Disease”. Although the diagnosis is not certain, the risk is evident. Hence, policies that would make the Russian economy more robust to shocks in the oil price need to be carefully designed and implemented.     

International coal prices

The place coal will occupy among the world's energy supplies depends on many factors, including its price trends. This paper reviews recent price trends and supports the thesis that future coal prices are independent of oil prices, and that they will fluctuate between two limits which are based on production and transport costs in the USA and Australia.     

Ongoing ascent to the helium production plateau—Insights from system dynamics

Recent, pre-downturn, disturbance in the global helium market can be traced to the tight supply–demand position, which characterizes today’s changing helium supply structure. A detailed System Dynamics model provides fresh insight into the helium question and suggests a production path that is closely associated with future natural gas production. Venting of un-extracted helium to the atmosphere remains a central issue. The model indicates that improving resource exploitation strategies might extend a production plateau that emerges in the 2030s. Substitution will result in more helium being vented. To mitigate this, the industry needs to ensure security of supply (particularly after the Bureau of Land Management reserve is sold).