(2008), Gilbert (2010), Gruber and Vigfusson (2012) and Byrne, Fazio and Fiess (2013) on the co-movement of commodity prices, we evaluate if the correlations across markets are driven by real interest rates and by the volatility of stock market returns (a proxy for uncertainty in stock markets).

The empirical results that we present show that the price returns of related commodities are generally highly correlated. The uniform spacings methodology indicates strong and positive correlations within cereal crops, between cereal crops and soybean oil (a reference agricultural commodity), and within energy commodities. We also find an increase in the degree of co-movement between energy and agricultural commodity price returns in recent years, particularly maize (another agricultural commodity that we use as a reference) and soybean oil, which are important inputs in the production of biofuels. The evolution of the estimated dynamic conditional correlations confirm the presence of high levels of co-movement between the returns of energy commodities and maize and soybean oil in the past few years and a rising level of co-movement by the end of the sample. Our results provide evidence the emergence of even stronger interlinkages between energy and agricultural markets in recent years, likely determined by the expansion of the biofuel industry. The concluding linear regression analysis that we propose suggests that several of the observed correlations within and across energy and agricultural markets are positively affected by the behavior of financial markets (measured by the volatility of stock market returns) particularly after 2007, but not by changes in macroeconomic conditions (measured by a real interest rate).

The remainder of the paper is organized as follows. In Section 2 we describe the data and the statistical properties of the price returns included in the analysis. We also present the results of the breakpoint analysis that we perform to estimate breaks in the dynamics of nominal price returns. In Section 3 we discuss empirical results concerning the extent of cross-section correlation in the data, the dynamic conditional correlations of nominal price returns and the statistical relevance of two potential driving factors (real interest rates and volatility of stock markets) of unconditional co-movement between commodity price returns. In Section 4 we draw the conclusions.

# **2 Commodity Prices and Breakpoints in Price Return Dynamics**

Monthly prices of 11 commodities are the core of the dataset. We focus on the main energy products (coal, crude oil and natural gas), agricultural crops (barley, maize, rice, sorghum, soybean oil and wheat) and food products (coffee and sugar). Time series from January 1970 to May 2013 are obtained from the World Bank Commodity Price Data.<sup>5</sup> Figure 2 shows the evolution of nominal commodity prices series over the period under investigation. Energy and agricultural prices follow similar patterns, in particular (i) crude oil and coal, (ii) soybean oil and rice, and (iii) maize, wheat, barley and sorghum. Most of these prices reach peaks around the global food price crisis in 2007-2008 and, generally, in the last two years of the

> ratio.

> 5 Data are publicly available from `http://go.worldbank.org/4ROCCIEQ50` . Table 4 in Appendix B provides further details on the specific commodities included in the sample.

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