2011

This paper investigates volatility spillover across crude oil market and wheat and corn markets. The corn commodity is taken here to assess the impact of change in demand for biofuel on wheat market. Results of multivariate GARCH model show evidence of corn price volatility transmission to wheat market . Our results indicate that while shocks (unexpected news) in crude oil market have significant impact on volatility in wheat and corn markets, the effect of crude oil price changes on corn and wheat markets is insignificant. The impulse response analysis indicate shocks in oil markets have permanent effect on food commodity price changes. Also indicated that fertilizers markets influenced by own-shocks and shocks in oil markets.

International Journal of Business and Globalisation, 2012

This paper investigates volatility spillover across crude oil market and wheat and corn markets. The corn commodity is taken here to assess the impact of change in demand for biofuel on wheat market. Results of multivariate GARCH model show evidence of corn price volatility transmission to wheat market. Our results indicate that while shocks (unexpected news) in crude oil market have significant impact on volatility in wheat and corn markets, the effect of crude oil price changes on wheat and corn prices is insignificant. The impulse response analysis also indicates shocks in oil markets have permanent effect on wheat and corn price changes. This reveals the influence of future crude oil markets on global food price volatility. Also indicated that fertilisers markets influenced by own-shocks and shocks in oil markets. Thus, shocks in crude oil markets have direct and indirect effects (via fertilisers markets) on food commodity markets.

This paper quantified the behaviour and extent of oil price and selected food commodity price volatilities using a multivariate-BEKK GARCH model to analyse the shocks and volatility transmission effect between crude oil and these commodities prices during 1990-2015. In line with the properties of time series data, a series of test such as collinearity, unit root as well as the presence of ARCH effects were conducted. The objective of this paper was to understand the most volatile commodity due to changes in world crude oil price returns and explore ways to reduce volatility relevant to food security and its stability for future planning purposes. The paper further used real price returns and demeans for normalization. Empirical results showed significant volatility transmission effects between crude oil and the all the food commodity except for dairy. Strong correlations existed between crude oil price returns and meat, cereal, edible oils and sugars. Shocks were also observed food commodity prices and its first lags.

This paper quantified the behaviour and extent of oil price and selected food commodity price volatilities using a multivariate-BEKK GARCH model to analyse the shocks and volatility transmission effect between crude oil and these commodities prices during 1990-2015. In line with the properties of time series data, a series of test such as collinearity, unit root as well as the presence of ARCH effects were conducted. The objective of this paper was to understand the most volatile commodity due to changes in world crude oil price returns and explore ways to reduce volatility relevant to food security and its stability for future planning purposes. The paper further used real price returns and demeans for normalization. Empirical results showed significant volatility transmission effects between crude oil and the all the food commodity except for dairy. Strong correlations existed between crude oil price returns and meat, cereal, edible oils and sugars. Shocks were also observed food commodity prices and its first lags.

Energy Economics, 2013

This paper examines volatility transmission in oil, ethanol and corn prices in the United States between 1997 and 2011. We follow a multivariate GARCH approach to evaluate the level of interdependence and the dynamics of volatility across these markets. Preliminary results indicate a higher interaction between ethanol and corn markets in recent years, particularly after 2006. We only observe, however, significant volatility spillovers from corn to ethanol prices but not the converse. We also do not find major cross-volatility effects from oil to corn markets. The results do not provide evidence of volatility in energy markets stimulating price volatility in grain markets.

2017

Crude Oil prices are thought to have direct and indirect effect through the exchange rate on the international agricultural commodities prices. The aim of this paper is to examine the interdependence relationship between crude oil futures prices, US dollar exchange rate, and international agricultural commodities prices, including corn (maize), sorghum, wheat, sugar, coconut oil, fishmeal, olive oil, palm oil, groundnut oil, groundnuts, rapeseed oil, soybean meal, soybean oil, soybeans, and sunflower prices. Using autoregressive (AR) model with an exponential generalized autoregressive conditional heteroskedasticity (EGARCH), namely AR-EGARCH model, we describe mean and variance equation in EGARCH model and then extract GARCH variance time series to investigate the volatility spillover from crude oil returns and US dollar exchange rate to the international agricultural commodities returns. To this end, the vector auto-regression (VAR) and vector error correction model (VECM) Granger...

Modern Economy, 2011

The upward movement in oil and food prices in the 2000s has attracted interest in the information transmission mechanism between the two markets. This paper investigates the volatility spillover between oil, food consumption item, and agricultural raw material price indexes for the period January 1980 to April 2008. The results of the Cheung-Ng procedure show that variation in oil prices does not Granger cause the variance in food and agricultural raw material prices. Since there is no volatility spillover from oil markets to food and agricultural raw material markets, investors can benefit from risk diversification. However, there is bi-directional spillover between agricultural raw material and food markets.

Natural Resources, 2014

Food commodity prices have recently increased sharply and become more volatile, highlighting greater uncertainty in markets and threatening global food security. High fuel prices combined with legislative mandates have increased biofuel production raising the average cost of food on the global market and particularly in developing countries and established a link between crude oil and agricultural prices. We investigate the role of biofuels in explaining increased volatility in food commodities. Multivariate GARCH models and volatility decompositions are estimated on grains and crude oil daily prices over a twelve-year sample from 2000-2011. We find increases in correlations and co-movements between grains and crude oils prices after 2006 and particularly in 2008 when crude oil prices were high. Increased volatility in grains during the 2008-09 spike was largely due to shocks transmitted from crude oil to grains especially corn, wheat and soybean prices.

2 ULYSSES project assess the literature on prices volatility of food, feed and non-food commodities. It attempt to determine the causes of markets' volatility, identifying the drivers and factors causing markets volatility. Projections for supply shocks, demand changes and climate change impacts on agricultural production are performed to assess the likelihood of more volatile markets. ULYSSES is concerned also about the impact of markets' volatility in the food supply chain in the EU and in developing countries, analysing traditional and new instruments to manage price risks. It also evaluates impacts on households in the EU and developing countries. Results will help the consortium draw policy-relevant conclusions that help the EU define market management strategies within the CAP after 2013 and inform EU's standing in the international context. The project is led by Universidad Politécnica de Madrid.

Agricultural Economics (Zemědělská ekonomika), 2016

Th e paper examines the price volatility spillovers among the crude oil, soybeans, corn, wheat, and sugar futures markets over the period 1/1/2006-11/29/2013. We separately investigate the periods of the pre-crisis, the crisis, and the post-crisis in fi nancial markets. We use the Yang-Zhang estimators for the historical volatility and fi nd that there is a volatility sprawl from the crude oil to corn markets. Th ere is also bi-directional causality between the corn and soybeans markets. In addition, we observe signifi cant volatility spillovers from both the soybeans and the corn markets to the wheat markets. Th e results are also valid in a diff erent sub-period analysis.