What caused the mid-2000s world commodity price “bubble” and the recent commodity price growth? Some have suggested that rapid global industrial growth over the past decade is the key driver of price growth. Others have argued that high commodity prices are a result of excessively loose monetary policy. The purpose of this paper is to extend the current research in this area by incorporating emerging economies, the BRIC (Brazil, Russia, India, and China) nations specifically, into global measures.
The paper uses a vector error correction (VEC) model and computes variance decomposition and impulse response functions (IRFs).
The empirical analysis suggest that the “demand channel” plays a large part in explaining commodity price growth whether BRIC countries are included or excluded from the analysis. However, excess liquidity may also play a part in explaining price growth. In addition, factoring in BRIC country data leads to the conclusion that unexpected movements in liquidity eventually explain more of the variation in commodity prices than unexpected demand shocks. This specific result is not caught in the sample that only incorporates advanced economies.
Despite the theory of Frankel (1986) and the findings of previous global vector autoregression (VAR)/VEC analyses, interest rates, especially shocks, have a minimal impact on consumer and commodity prices. Perhaps future studies should include an interest rate in their analysis that more closely reflects interest rates associated with information used by commodity consumers, producers, and investors. Some analyses such as Hua (1998) use the LIBOR rate, which is highly associated with developed financial markets in the advanced economies. Data quality and availability in the BRIC countries severely limited the length of the time period analyzed and the frequency of the data. Finding longer sample periods or higher frequency data can help to minimize bias in future research. In this paper, monetary aggregates and short-term interest rates were loosely connected to monetary policy. It would also be interesting to directly examine how special programs like quantitative easing influenced global liquidity.
The results of the IRFs and variance decompositions confirm some of the previous findings reported in Belke et al. (2010), Hua (1998), and Swaray (2008) that suggest that positive shocks to liquidity positively impact commodity prices. In particular, both samples suggest that this is a short-run impact that occurs after two quarters. However, in the sample that includes information about liquidity from BRIC countries, excess liquidity positively affects commodity prices after six and seven quarters as well. The insignificant results of Granger causality tests of the effect of monetary variables on commodity prices suggests that this relationship is limited to movements in liquidity that is unexpected by agents in the system. These “shocks” could be attributed to a number of factors including exogenous monetary policy changes such as the unprecedented responses by the Federal Reserve during and after the 2008 global financial crisis.
First, empirical research that claims to analyze relationships at a “global” level needs to account for the growing influence of emerging economies and not simply the advanced economies. Otherwise, results may be biased as they were when too much of the forecast error variance in commodity prices was attributed to shocks to output when it should have been attributed to shocks to excess liquidity. Second, those who criticize expansionary monetary policy in the advanced countries, especially by the Federal Reserve, for pushing up commodity prices should also direct their attention toward monetary authorities elsewhere, especially the BRIC countries, since information on excess liquidity from these countries adds to the influence that global excess liquidity has on commodity prices. Third, monetary policymakers in the advanced countries need to closely monitor liquidity in the BRIC countries, since the discrepancies between the ALL and ADV samples suggests that BRIC excess liquidity affects commodity prices in a way that cannot be captured by examining advanced country data alone.
No other paper in this area looked at the BRIC countries.
JEL Classification — E30, E52, Q01
The authors are indebted to Andrea Zaghini for sharing the methodology for how the PPP exchange rates were calculated in Sousa and Zaghini (2007, 2008).
Landgraf, S. and Chowdhury, A. (2015), "Factoring emerging markets into the relationship between global liquidity and commodities", Journal of Economic Studies, Vol. 42 No. 4, pp. 622-640. https://doi.org/10.1108/JES-11-2013-0171Download as .RIS
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