Co-Movement of Commodity Prices and the Role of China in World Commodity Market

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This study will also underline the role of macro-economic shocks on co-movement of commodity prices. Study uses time series data from 2005 to 2015 encompassing one of the major macroeconomic phenomenon of the recent decade. It is pursued through study that whether it can reflect upon the influence of the global financial crisis over the price movements of commodities. The significance of this study lied with the outcomes of these three core objectives. The central theme of the research is to explore the factors which are influencing co-movement of the commodity prices. Earlier studies have highlighted the role of financialization, speculation and forecasting are the key sources of the co-movement of the commodity prices. The rationale for the study suggests that (Roache, 2012) trade concentration and visible hike in the consumption can also influence the movement of the commodity prices and hence can be contributing to the co-movement of the commodity prices. This has been the case with the United States several decades before and now this can be the similar influence of the rise in the Chinese consumption demand and this could have reflected on the movements of the commodity prices in the recent decades.

Motivation of the Study

Co-movement of commodity prices are not explored enough in the cases of developing countries. In most of the developing countries commodity markets are not fully developed. China has fairly developed commodity market it’s share in the commodity trading across globe has increased (World Bank Group, 2014) and in the 2006-07 commodity price-boom major emphasis was on increasing demand for primary commodity in China and other Asian countries (Gottschalk & Prates, 2006). There are many different commodities in the world and they are consumed in many different situations and their production processes and capacities differ significantly. Therefore, different commodities have very different supply and demand conditions and it is reasonable to assume that different commodities have independent cycles and their price movements should be relatively independent from each other. However, many scholars have found out that the co-movement of commodities occurs much more often than people anticipate and it is not uncommon that commodity prices move to the same direction. For instance, according to Pindyck & Rotemberg (1990), the existence of the co-movement of commodity prices is frequently puzzling because there is a broad set of commodities which are not related to each other have their prices move together. For example, cotton, wheat, copper, crude, gold, lumber, and cocoa are found to move together much more often than is justified by the similarity of supply and demand. Also, the co-movement is in excess of anything that could be easily explained by common economic indicators such as the aggregate demand, inflation, interest, and foreign exchange rate.

This research focuses on analyzing the phenomenon of commodity price co-movement with respect to China as it has significant impact on other commodity markets as well. The study would have many important benefits both theoretically and practically. Through studying this phenomenon, the study would contribute to the current understanding of the commodity market in terms of both supply and demand and the possible factors that impact the commodity prices. Furthermore, the study would also be important for practically purposes because it would give insights to politicians and economists about how to correctly forecast the commodity prices so that optimal economic policies would be generated to reduce the potential negative impacts of co-movements.

Theoretical Approach

This study will pursue theoretical as well as empirical approaches for dealing with its research h objectives. As the discovery of co-movement of the commodity prices is more of a financial phenomenon then economic. However, there are financial and economic both explanations have been provided to this act though various theoretical studies. Muth (1961) had used rational expectation approach while describing price movements. However, Muth’s rational expectation explanation was mainly based on the price movements in the isolated markets. Bollerslev et al (1992) have used auto regressive conditional heteroscedasticity (ARCH) model introduced by Engle. The auto-regressive characteristics of future prices even in commodity market are dealt with statistical models. But with the advancement of the forecasting, auto regressive model have become more prominent in use. Roache (2012) have used vector auto regression (VAR) model while assessing the impact of China on global commodity prices. Pndyck & Rotemberg (1990) has made pioneer contribution in the study of co-movement of commodity prices based on monthly price changes of following commodities: cotton, wheat, copper, gold, lumber, crude and cocoa. These commodities belong to a very broad spectrum. The monthly price movements of these commodities are statistically analyzed for their correlation and then macroeconomic variables are used to understand the price volatility. Since the commodities could be stored, the expectations of future markets impact the demand for storage. The demand for storage impacts the current price with the demand for consumption. According to Pindyck & Rotemberg (1990), the implication of this is that the unexpected changes in the economic condition which are commonly used for economic forecasting would immediately impact commodity prices. For instance, it is understood that the interest rate has impacts on storage because the higher the interest rate the higher the required rate of return for storage and the price would go down with less demand on storage. Therefore, the net supply of commodity could be interpreted as:

(1) [pic 1]

This shows the log price of commodity at time t. The index a’ is a measure of the changes in supply and demand and it depends on the variables that are specific to each commodity and a vector of economic variables which are known to potentially impact production. The commodities are defined to be independent if the cross price effects are negligible. Therefore, the inventory of commodities could be illustrated with the following equation:

(2)[pic 2]

Furthermore, Pindyck & Rotemberg (1990) assume that the inventory holders who are risk neutral intend to maximize profits so that the return could be illustrated by the following equation:

(3) [pic 3]

In this equation the required rate of return is related to the expectation conditional on the market information available and the holding