Non-energy Commodity Research Articles

Energy and non-energy commodities: An asymmetric approach towards portfolio diversification in the commodity market

We investigate the presence of short- and long-run asymmetric relationships between energy and non-energy commodities for weekly data from January 2010 to June 2018. Using the non-linear ARDL methodology, we show that oil prices have significant long-run negative effects on the prices of gold and silver, indicating that for both metal commodities, oil price increases lead to more decrease than the subsequent oil prices decrease. Crude oil, among other energy commodities, is found to offer more diversification benefits when combined with gold or silver; however minimal diversification benefits can result from combining crude oil with wheat or platinum. Gas futures, among other energy markets, offer more diversification opportunities when combined with copper, wheat, platinum or palladium, while coal offers maximum diversification benefits when combined with gold, silver or wheat. Our results are robust when NARDL is applied to the daily data and also when the analysis is conducted using the causality-in-quantiles test.

Understanding Dynamic Conditional Correlations between Oil, Natural Gas and Non-Energy Commodity Futures Markets

We look at the dynamic conditional correlations (DCCs) between oil, natural gas and other non-energy commodity futures markets, obtained from a DCC-GARCH model over the period 1998-2014. They are positive and display a sharp increase around year 2008 and a subsequent decrease. The DCCs between energy and metals are larger than the energy-agriculture ones. To understand how macroeconomic and financial factors, as well as speculative activity, influence them, we estimate an ARDL(1,1) model, adopting a pooled mean group (PMG) estimator. We observe that macroeconomic and financial variables are significantly correlated with the energy-agriculture and energy-metals DCCs. Speculative activity contributes to explain the energy-agriculture DCCs but not those of the energy-metals.

Interactions in Swiss households’ energy demand: A holistic approach

This article analyzes the interactions and possible trade-offs between direct energy consumption and embodied energy requirement of households in Switzerland in order to assess the net impacts of standard energy policies focusing exclusively on direct energy use. Direct and embodied energy demand of Swiss households are estimated by combining consumption data of a national expenditure survey with data on energy intensity from life-cycle analysis. Using a system of equations and an instrumental variable approach, we find that both domains are driven by same determinants, but that there is no evidence for significant substitution between them. We also find an increasing effect of income on both domains, with particularly important effects on embodied energy. From a policy perspective, our findings highlight a concern that economic growth could bring about an increasing global energy demand through energy requirement for non-energy commodities. However, the wide-spread policies targeting direct energy are unlikely to cause a substantial shift in household consumption to embodied energy.

Measuring portfolio risk of non-energy commodity using time-varying vine copula

In literature, many empirical studies have used the vine copula to measure and analyse the risk of stock indices, energetic products or crypto currencies portfolio (e.g., Zhang et al., 2014; Shahzad et al., 2018; Boako et al., 2019). These studies used mainly the VaR and ES with different versions of vine copula. However, few works have focused on a portfolio composed of non-energy commodities. Our aim in this work is to model the dependence between non-energy commodities returns by modelling standardised residuals obtained from univariate GARCH model by different versions of time varying vine copula, to quantify risk of N-dimensional non-energy commodity portfolio by VaR and ES and to compare the predictive performance of this method with traditional and competitive traditional univariate VaR methods. Empirical results suggest that risk quantifies generated by AR-GARCH vine copula methods with student-t distribution are sufficiently accurate at both low and high confidence levels. Given these results, we recommend the application of vine copula method to understanding the non-energy commodity behaviours which are very important to investors, producers, consumers, and policy makers.

Long Run Relationship between Energy & Agricultural Commodities: Testing in Indian Context Using Cointegration & Causality Approach

It is being surmised in certain quarters that the price volatility in the market for crude oil is spilling over to the non-energy commodity markets. The aim of the present research is to measure and document the impact of crude oil market on the agricultural commodity markets in India by investigating their long run relationship. This study uses the Johansen's cointegration analysis and the Granger causality technique to explore the existence of a relationship between the prices of crude oil and agricultural commodities over the long-term horizon. The results and implications of the current work can be of special utility to the different stakeholders in the markets for agricultural commodities like participants of the commodity exchanges, traders, commission agents and producers. The previous studies in this area have not individually investigated the long-term price relationship between the various agricultural commodities and crude oil in India.

Measuring portfolio risk of non-energy commodity using time-varying vine copula

Measuring portfolio risk of non-energy commodity using time-varying vine copula

Efficiency and Forecast Performance of Commodity Futures Markets

The present study empirically investigates market efficiency and the potential factors of inefficiency in the main non-energy commodity futures markets: maize, soybeans and wheat. With efficient markets, futures prices can be used as commodity price forecasts, with inefficient markets futures prices are not able to predict spot prices. Technically, exploring the drivers of inefficiency means to assess the determinants of forecast errors, i.e. the factors affecting the difference between realized spot prices and predicted future spot prices. The analysis is carried out using first a traditional test of efficiency for spot and futures prices and then implementing a more sophisticated GARCH analysis at a daily and weekly frequency. The results show that maize, soybeans and wheat markets are not informationally efficient. The realized price volatility of futures markets, the time to maturity, open interest, trading volumes and speculative measures are significant factors explaining forecast errors. In particular, short-term speculation (scalping activity) increases the noise in the information formation process. Similarly, price volatility, lack of liquidity and long contract maturity horizon raise forecast errors, while long-term speculation and speculative pressure reduce errors. The analysis suggests that knowing the causes of forecast errors, would allow to control for such factors and therefore to ameliorate the forecast accuracy of commodity prices.

Volatility Spillovers Arising from the Financialization of Commodities

This paper examines whether the proliferation of new index products, such as commodity-tracking exchange-traded funds (ETFs), amplified the volatility transmission channel introduced by financialization. This paper focuses on the volatility spillover effects among crude oil, metals, agriculture, and non-energy commodity markets. The results show financialization has an impact on the volatility of commodity prices, predominantly for non-energy commodities. However, the impact on volatility is not symmetric across all commodities. The analysis of index investment and investors’ positions in futures markets shows that, when a relationship exists, it is generally negatively correlated with the realized volatility of non-energy commodities. Using realized volatility in the difference-in-difference model provides estimates that are inconsistent with other findings that non-energy commodities, traded as a part of indices, have experienced higher volatility. The results are similar to the index investment and futures market analysis, where increased participation by investors through new investment products has put download pressure on realized volatility.

The U.S. Shale Oil Revolution and the Behavior of Commodity Prices

The United States is committed to technological improvements in horizontal drilling and hydraulic fracturing in its drive of toppling the world's leading oil producers by the mid-2020s and evolving into a net oil exporter by 2030. Consequently, these technological innovations revolutionized the U.S. oil sector and the international oil market with increasing relevance of the shale oil and attendant shock spillovers to financial and commodity markets. Upon these attractions and consistent with evidence in the literature, we trace the oil price and commodity price dynamics to the shale oil revolution using a recursive structural VAR model of the shale supply shocks. In line with the standard practice of ensuring sensitivity of results, we conduct analyses such as impulse responses, forecast-error variance decomposition, and historical decompositions to accommodate energy and nonenergy commodity components. We show, in addition to the popular view in the extant literature, that the shale oil revolution is not only associated with the recent oil price plunge, but also responsible for the tumble in the total energy-based commodity prices with crude oil price being just a component.

From boom to bust: a typology of real commodity prices in the long run

This paper considers the evidence on real commodity prices over 160 years for 30 commodities representing 7.89 trillion USD worth of production in 2011. In so doing, it suggests and documents a complete typology of real commodity prices, comprising long-run trends, medium-run cycles, and short-run boom/bust episodes. The findings of the paper can be summarized as follows: real commodity prices of both energy and non-energy commodities have been on the rise from 1950 across all weighting schemes; there is a consistent pattern, in both past and present, of commodity price super-cycles which entail decades-long positive deviations from these long-run trends with the latest set of super-cycles likely at their peak; these commodity price super-cycles are punctuated by booms and busts which are historically pervasive and becoming more exacerbated over time. These last elements of boom and bust are also found to be particularly bearing in determining real commodity price volatility as well as potentially bearing in influencing growth in commodity exporting economies.

Global Commodity and Oil Price Movements, Macroeconomic Performance and Challenges for an Emerging Economy: The Indian Experience

Commodity and oil price fluctuations have significant bearing on domestic macroeconomic performance and macroeconomic policymaking of an emerging economy. The article explores the impact of non-energy commodity and oil price fluctuations on output, inflation and real exchange rate (RER) in India; and commodity and oil constituting sizeable imports. The empirical analysis carried out through vector error correction model (VECM) for the post-liberalization period 1991–2014 clearly points out that commodity and oil price shocks have a significant impact on the variation in output and prices accounting for RER adjustment and the role of a developed financial market (private credit). The RER adjusts to commodity and oil price shocks, accounting for foreign exchange reserves and financial markets (private credit). The impulse response functions indicate that one standard deviation shock in commodity and oil price persists for three to eight quarters over domestic prices and output. While these results point to lessening of commodity and oil imports through a series of medium and long-term structural-cum-policy reform measures, in the immediate, they also lend a role of intervention by monetary authority (central bank) in pursuit of inflation targeting. Conjointly, pursuance of countercyclical fiscal policy to stabilize domestic output and prices in short run are called for.

Fertility-rate recovery and double-income policies require solving the carbon gap under the Paris Agreement

In 2015, in response to the Paris Agreement for mitigating an increase in global temperatures, the Japanese government committed itself to reducing greenhouse gas (GHG) emissions by 26% below 2013 levels by 2030. In the same year, the government also committed itself to overcoming the barriers to economic growth imposed by an aging society with a low birthrate by implementing socio-economic policies referred to as “A Society in Which All Citizens are Dynamically Engaged”. Regarding achievement of these two national targets, this study examines the extent to which increases in the total fertility rate and the number of double-income households would impact the domestic carbon footprint (CF) associated with household consumption in 2030. The findings show that the total household CF in 2030 would range from 683 to 815 Mt-CO2eq/y, depending on the consumer preferences resulting from implementation of the socio-economic policies. This implies that, compared with a business-as-usual scenario, the GHG emissions associated with household consumption would need to be reduced by more 7.8–29% in order to meet the CF target that can be set using the CF for 2009 and the reduction target proposed in the Paris Agreement. Furthermore, the household CF for non-energy commodities would need to be reduced by 17–28% in order to satisfy the trade-off between the socio-economic policies and the emissions mitigation target for 2030, even if the current CO2 emissions targets for household energy use and private car use are achieved.

Bitcoin for energy commodities before and after the December 2013 crash: diversifier, hedge or safe haven?

ABSTRACTWe study the relationship between Bitcoin and commodities by assessing the ability of Bitcoin to act as a diversifier, hedge, or safe haven against daily movements in commodities in general, and energy commodities in particular. We focus on energy commodities because energy, in the form of electricity, is an essential input in the Bitcoin production. For the entire period, results show that Bitcoin is a strong hedge and a safe-haven against movements in both commodity indices. We further examine whether that ability is also present for non-energy commodities and our analysis show insignificant results when energy commodities are excluded from the general commodity index. We also account for the December 2013 Bitcoin price crash and our results reveal that Bitcoin hedge and safe-haven properties against commodities and energy commodities are only present in the pre-crash period, whereas in the post-crash period Bitcoin is no more than a diversifier. In addition to uncovering the time-varying role of Bitcoin, we highlight the dissimilarity in the dynamic correlations between the extreme downward and extreme upward movements.

Competitive Advantage of Yemeni Export in the US Market

This paper explores competitive advantage of Yemeni export in the market of the USA. Yemen has been placed under a special situation since the “Arab Spring” in 2011; therefore, our analyses study the eleven years prior to the war, between 2000 and 2011, and employ 2-digit SITCs to identify the various products for the selected study period. Balassa’s index has been utilized to measure revealed competitive advantage (RCA). This approach is universally popular and is widely reported in literature; however, we are cognizant to the fact that this index may not be empirically relevant. Despite this drawback, Balassa’s index has a feature for gross sectoral competiveness of the examined country or a group of countries. According to our empirical analyses using Balassa’s index, we identified Yemen to have competitive advantages at the global level during international trade in the selected study period. The competitive advantage was restricted to a few groups of energy and non-energy commodities.

Oil and non-energy commodity markets: An empirical analysis of volatility spillovers and hedging effectiveness

AbstractAlthough a large number of empirical papers have examined the price spillover in global oil and non-energy commodity markets, very little is known about the volatility transmission between these two markets. The present study aims to conceal this gap by investigating the volatility cross effects between oil and three different non-energy commodity markets. Using the bivariate VAR-GARCH models, we do not find any evidence of volatility linkage between oil and agricultural product markets during the sample period used. We, however, document that oil market sends volatility to both metal and non-energy aggregate markets. This finding is not surprising, since petroleum-related products are one of the major production inputs in metal industries and hence the production process of metals largely depends on the crude oil market. Since various financial assets are traded on the basis of commodity markets, our results are beneficial for portfolio diversification and hedging decisions. Policy-makers could a...

INTRODUCTION TO MACROECONOMIC DYNAMICS SPECIAL ISSUE ON DYNAMICS OF OIL AND COMMODITIES PRICES

This special issue of Macroeconomic Dynamics presents a timely and fresh body of high-quality research on the complexity and evolution of the international oil markets, the dynamics of the price of oil, and the financialization and the interconnections of oil, energy, and nonenergy commodity markets.

Effects of carbon tax on social welfare: A case study of China

Almost all countries around the world concern about the emission of greenhouse gas. The most widely used model of carbon tax is based on complete competition model of energy market, which, however, cannot completely reflect the real condition. This article establishes a social optimal welfare model that based on oligopoly competition of energy department. According to the model, the article calculates the substitution elasticity of factors in China’s energy sectors, non-energy department and consumption preference in domestic energy and non-energy commodities. Based on the social optimal welfare model, the effect on social welfare caused by carbon taxes in different links is further evaluated. The results show that a certain amount of carbon tax in the production link raises the social welfare, while in consumption and redistribution links lowers the social welfare. Specifically, the absolute value of marginal social welfare in the redistribution link is larger. Moreover, the values of the three types of carbon taxes vary under different redistribution demands though the variation trends of tax in the same link are similar. As a result, a small amount of carbon tax on the production link contributes to the growth of social welfare.

Impact of fossil fuel subsidy reform in China: estimations of household welfare effects based on 2007–2012 data

Changing the energy subsidy mechanism is a priority of China’s ongoing market-based energy reform. Using the 2007–2012 empirical data, this paper applies an input–output model to evaluate the welfare effects, that is, the expenditure increments of five income groups in 28 provinces, associated with the possible policy scenario of removing the subsidies for fossil fuels. The key findings of this study include, first, that the total indirect welfare effects (i.e. the additional money spent on non-energy commodities) are two-to-three times as large as the direct ones (i.e. the additional money spent on energy). Second, removing the oil subsidy leads to an additional expenditure of 19.74 CNY annually for each resident, which is much larger than the effect of removing the natural gas and coal subsidies. Third, the composition of the indirect effect varies significantly among income groups, because food expenditure contributes to approximately two-thirds of the total indirect effect on average. Finally, the welfare effect is very sensitive to the income level. To promote the smooth reform of the fossil fuel subsidies, we suggest that the government should deal with the coal industry initially, pay special attention to the indirect expense increase, and compensate low-income households for the welfare losses.

The Impact of the Euro Area Macroeconomy on Global Commodity Prices

The aim of this paper is to analyse the links between real and financial processes in the euro area and energy and non-energy commodity prices. Monthly data spanning 1997:1 to 2013:12 and the structural VAR model are used to uncover the relationship between global commodity prices and the euro area economy. The analysis is performed for three sub-periods in order to capture potential changes in this relationship over time. The main finding is that commodity prices in the euro area do not respond to impulses from production (economic activity), whereas commodity prices strongly react to impulses from financial processes, i.e. interest rates in the euro area and the exchange rate of the dollar against the euro, especially in the run-up to the global financial crisis. The study also provides evidence of a tightening relationship between energy and non-energy commodity prices.

Does the euro area macroeconomy affect global commodity prices? Evidence from a SVAR approach

This paper investigates the effects of real and financial processes in the euro area macroeconomy on energy and non-energy commodity prices. The relations implied by the proposed theoretical model are examined within the structural VAR framework for three sub-periods. Our main finding is that, although global commodity prices are indeed related to real and financial processes in the euro area macroeconomy, the relations among them are not stable over time. Energy prices and interest rates depart from real processes in the pre-crisis period, whereas the relative importance of real and financial factors changes for non-energy commodity price index.