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This paper provides a comprehensive analysis of the degree of co-movement among the nominal price returns of 11 major energy, agricultural, and food commodities using monthly data between 1970 and 2013. The authors study the extent and the time evolution of unconditional and conditional correlations using a uniform-spacings testing approach, a multivariate dynamic conditional correlation model and a rolling regression procedure.
This paper provides a comprehensive analysis of the degree of co-movement among the nominal price returns of 11 major energy, agricultural and food commodities based on monthly data between 1970 and 2013. A uniform-spacings testing approach, a multivariate dynamic conditional correlation model and a rolling regression procedure are used to study the extent and the time-evolution of unconditional and conditional correlations. The results indicate that (i) the price returns of energy and agricultural commodities are highly correlated; (ii) the overall level of co-movement among commodities increased in recent years, especially between energy and agricultural commodities and in particular in the cases of maize and soybean oil, which are important inputs in the production of biofuels; and (iii) particularly after 2007, stock market volatility is positively associated with the co-movement of price returns across markets.
We present a simple macroeconomic model with a continuum of primary commodities used in the production of the final good, such that the real prices of commodities have a factor structure. One factor captures the combined contribution of all aggregate shocks which have no direct effects on commodity markets other than through general equilibrium effects on output, while other factors represent direct commodity shocks. Thus, the factor structure provides a decomposition of underlying structural shocks. The theory also provides guidance on how empirical factors can be rotated to identify the structural factors. We apply factor analysis and the identification conditions implied by the model to a cross-section of real non-energy commodity prices. The theoretical restrictions implied by the model are consistent with the data and thus yield a structural interpretation of the common factors in commodity prices. The analysis suggests that commodity-related shocks have generally played a limited role in global business cycle fluctuations.
There is a common perception that the prices of unrelated commodities move together. This paper re-examines this notion, using a measure of co-movement of economic time series called concordance. Concordance measures the proportion of time that the prices of two commodities are concurrently in the same boom period or same slump period. Using data on the prices of several unrelated commodities, the paper finds no evidence of co-movement in commodity prices. The results carry an important policy implication, as the study provides no support for earlier claims of irrational trading behaviour by participants in world commodity markets.
This paper was written to help bolster the case and present visual evidence demonstrating why it is important to seriously consider spatial soil fertility variability in Ghana and to promote area-specific fertilizer recommendations. Using geostatistical analysis of soil samples collected from farmer plots in three districts (Tamale Municipality, Savelugu-Nanton, and West Mamprusi in northern Ghana), the paper analyzes spatial variations in soil fertility. The results clearly show that there are variations in soil pH, organic matter content, and available phosphorous even at the community level, supporting the need for Ghana to seriously consider location-specific fertilizer recommendations.
Commodities have become an important component of many investors' portfolios and the focus of much political controversy over the past decade. This book utilizes structural models to provide a better understanding of how commodities' prices behave and what drives them. It exploits differences across commodities and examines a variety of predictions of the models to identify where they work and where they fail. The findings of the analysis are useful to scholars, traders and policy makers who want to better understand often puzzling - and extreme - movements in the prices of commodities from aluminium to oil to soybeans to zinc.
This paper investigates linkages between women’s empowerment in agriculture and the nutritional status of women and children using 2012 baseline data from the Feed the Future population-based survey in Ghana. The sample consists of 3,344 children and 3,640 women and is statistically representative of the northernmost regions of Ghana where the Feed the Future programs are operating.