Commodity index investment and food prices: does the “Masters Hypothesis” explain recent price spikes?

The “Masters Hypothesis” is the claim that unprecedented buying pressure in recent years from commodity index investors created massive bubbles in food and energy prices. The purpose of this article is to review the evidence from recent studies that investigate the empirical relationship between index investment and price movements in agricultural futures markets. One line of research uses time‐series regression tests, such as Granger causality tests, to investigate the relationship between price movements and index positions. This research provides little evidence in support of the Masters Hypothesis in agricultural futures markets. A second line of research uses cross‐sectional regression tests and studies in this area provide very limited evidence in favor of the Masters Hypothesis for agricultural futures markets. A third line of research investigates whether there is a significant relationship between commodity index trading and the difference, or spread, between futures prices of different contract maturities on the same date. These studies report a range of results depending on the type of test. However, the bulk of the evidence indicates either no relationship or a negative relationship, which is once again inconsistent with the Masters Hypothesis. Overall, this growing body of literature fails to find compelling evidence that buying pressure from commodity index investment in recent years caused a massive bubble in agricultural futures prices. The Masters Hypothesis is simply not a valid characterization of reality.     

Finding optimal price risk management instruments: the case of the Spanish potato sector

This article offers a comprehensive analysis of the problem of choosing between alternative market risk management instruments. We model farmers' behavior to optimize the certainty equivalent, formulated by a mean–variance model, by combining instruments with and without basis risk. Results are expressed as the demands for hedging with futures, forward contracts and insurance. Theoretical results are applied to a selection of Spanish producers of fresh potatoes, a sector that is exposed to significant market risks. Amsterdam's Euronext provides potato futures prices, and the recently launched revenue insurance in Spain provides the example for price insurance. Three conclusions summarize the article's main findings. First, we show that Spanish potato revenue insurance subsidies are a factor that determines the instrument rankings and choice. Second, the efficiency of insurance subsidies is generally low. Finally, the Amsterdam potato futures market does not provide a cost‐effective means to manage price risks for Spanish fresh potato growers.     

Revisiting the determinants of futures contracts success: the role of market participants

The Chicago Mercantile Exchange introduced a futures contract for distillers’ dried grains (DDGs) in early 2010, but the market became inactive only four months after its inception. While many new futures contracts do not develop into high‐volume traders, interest from DDG cash market participants indicated that this contract could be successful. Prompted by the unexpected lack of trading activity in this new futures market, we empirically revisit the question of what factors contribute to a futures contract's success and extend the literature by investigating the roles of market participants and the significance of supporting futures markets. Estimation results indicate that the market participant type—hedger or speculator—affects futures contract trade volume. More importantly, we find that the viability of new futures contracts for commodities that are jointly produced with other commodities is impacted by hedgers’ trade volume of the related futures contract. These results provide important additions into the portfolio of indicators used by commodity exchanges to more cost‐effectively evaluate new futures contract products.     

A speculative bubble in commodity futures prices? Cross‐sectional evidence

Recent accusations against speculators in general and long-only commodity index funds in particular include: increasing market volatility, distorting historical price relationships, and fueling a rapid increase and decrease in the level of commodity prices. Some researchers have argued that these market participants—through their impact on market prices—may have inadvertently prevented the efficient distribution of food aid to deserving groups. Certainly, this result—if substantiated—would counter the classical argument that speculators make prices more efficient and thus improve the economic efficiency of the food marketing system. Given the very important policy implications, it is crucial to develop a more thorough understanding of long-only index funds and their potential market impact. Here, we review the criticisms (and rebuttals) levied against (and for) commodity index funds in recent U.S. Congressional testimonies. Then, additional empirical evidence is added regarding cross-sectional market returns and the relative levels of long-only index fund participation in 12 commodity futures markets. The empirical results provide scant evidence that long-only index funds impact returns across commodity futures markets.     

Commodity price bubbles and macroeconomics: evidence from the Chinese agricultural markets

This article investigates the links between commodity price bubbles and macroeconomic factors, with an application to the agricultural commodity markets in China from 2006 to 2014. Price bubbles are identified using a newly developed, recursive right‐tailed unit root test. A Zero‐inflated Poisson model is used to analyze the factors contributing to bubbles. Results show that (a) there were speculative bubbles in most Chinese agricultural commodity futures markets during the sample period, though their presence was infrequent; (b) economic growth, money supply, and inflation have positive effects on bubble occurrences, while interest rates have a negative effect; and (c) among all macroeconomic factors considered, economic growth and money supply have the greatest impact in triggering bubbles. Our findings shed new light on the nature and formation of bubbles in the Chinese agricultural commodity markets.     

Modeling regime‐dependent agricultural commodity price volatilities

In stark contrast to financial markets, relatively little attention has been given to modeling agricultural commodity price volatility. In recent years, numerous methodologies with various strengths have been proposed for modeling price volatility in financial markets. We propose using a mixture of normals with unique GARCH processes in each component for modeling agricultural commodity prices. While a normal mixture model is quite flexible and allows for time varying skewness and kurtosis, its biggest strength is that each component can be viewed as a different market regime and thus estimated parameters are more readily interpreted. We apply the proposed model to ten different agricultural commodity weekly cash prices. Both in‐sample fit and out‐of‐sample forecasting tests confirm that the two‐state NM‐GARCH approach performs better than the traditional normal GARCH model. A significant and state‐dependent inverse leverage effect is detected only for pork in the regime where the price is expected to drop, indicating the volatility in this regime tends to increase more following a realized price rise than a realized price drop.     

Cotton market integration and the impact of China's new exchange rate regime

This article studies the integration of China's cotton market with the international market, especially the U.S. market. Investigating the futures prices from the Intercontinental Exchange (ICE) in the U.S. and the Zhengzhou Commodity Exchange (ZCE) in China with several time series models, we find that a long‐run cointegration relationship exists between these two series. The two markets share price transmissions, and based on results from an Autoregressive Conditional Heteroskedasticity (ARCH) model, we find their price volatilities are similar. We argue that China's recent exchange rate reform and its gradual liberalization in bilateral cotton trade since it joined World Trade Organization have had important impacts on these futures markets. Based on these findings, several important economic and policy implications are derived.     

Time‐varying Hedge Ratios: A Principal‐agent Approach

We use the classic agency model to derive a time‐varying optimal hedge ratio for low‐frequency time‐series data: the type of data used by crop farmers when deciding about production and about their hedging strategy. Rooted in the classic agency framework, the proposed hedge ratio reflects the context of both the crop farmer's decision and the crop farmer's contractual relationships in the marketing channel. An empirical illustration of the Dutch ware potato sector and its futures market in Amsterdam over the period 1971–2003 reveals that the time‐varying optimal hedge ratio decreased from 0.34 in 1971 to 0.24 in 2003. The hedging effectiveness, according to this ratio, is 39%. These estimates conform better with farmers’ interest in using futures contracts for hedging purposes than the much higher estimates obtained when price risk minimisation is the only objective considered.     

The interaction of speculators and index investors in agricultural derivatives markets

Through the analysis of the weekly Commodity Futures Trading Commission reports on 12 US traded agricultural commodities, we revisit the heated debate on the impact of index flows on commodities prices. After introducing a novel stock‐to‐use proxy that may be used to represent inventory variations at the intra‐month level, we show that speculators, contrary to index investors, are sensitive to commodity‐specific fundamental information. Their endogeneity to commodities markets hinders the estimation of their market impact. Regarding the market impact of index flows, the endogeneity problem is alleviated in two ways: first, we restrict the scope to agricultural commodities, for which index flows are more exogenous to market prices; second, we introduce two novel instrumental variables that are computed from index flows outside the market under analysis. We find that index investment flows are offset by commercial players, not speculators. The serial correlation of index flows may explain the tendency of speculators to synchronize with index investors. There is strong evidence of an index flows' impact in those commodities markets where speculative and index positions are the most correlated. The market impact of index flows is located in periods of liquidity stress, as is the correlation between speculative and index positions. Overall, our results demonstrate an impact of index investors on some agricultural prices and suggest that the synchronicity between speculative and index positions is an important determinant of this impact.     

Announcement effects and the theory of storage: an empirical study of lumber futures

We investigate how lumber futures returns are affected by monthly housing starts announcements and analyze the dependence of the response on lumber inventories and time to delivery. To do so we develop a generalized least squares (GLS) method to jointly analyze simultaneously traded contracts. We find that increases in the unanticipated component of housing starts announcements increase returns on lumber futures contracts. Further, and as predicted by the theory of storage but previously unrecorded, the effects of housing starts shocks decline with lumber inventories. There is also a time-to-delivery effect: near-delivery contracts respond more sharply to housing starts news than do farther-out contracts.     

Evaluating Commodity Market Efficiency: Are Cointegration Tests Appropriate?

This paper investigates the claim that the finding of cointegration between commodity spot and lagged futures rates reflects the existence of commodity arbitrage and not, as is generally accepted, long‐run market efficiency. The methodology of Kellard et al. (1999) is employed to match spot and lagged futures rates correctly for the UK wheat futures contract traded at LIFFE. Bi‐variate analysis shows that spot and lagged futures rates are cointegrated with the vector (1, ‐1), a necessary condition for market efficiency. However, at variance with asymptotic theory, in a tri‐variate VECM estimation, the spot rate, lagged futures rate and lagged domestic interest rate are shown to be cointegrated with the vector (1, ?1, 1). The “cointegration” paradox is explained by investigating the relative magnitudes of the forecast error and the domestic interest rate. The small sample results demonstrate that it is impossible to distinguish between the influence of commodity arbitrage and the existence of market efficiency using cointegration‐based tests. In summary, this work implies that such tests are not wholly appropriate for evaluating commodity market efficiency.     

Rental markets for cultivated land and agricultural investments in China

The purpose of this paper is to empirically track the progress and consequences of the emergence of cultivated land markets in China since 2000. We draw on a set of nationwide, household‐level panel data (for 2000 and 2008) and find that the markets for cultivated land rental have emerged robustly. According to our data, 19 of China's cultivated land was rented in farm operators in 2008. We also find that the nature of China's cultivated land rental contracts has become more formal and lengthened the period of time that the tenant is able to cultivate the rented‐in plots. While there may be benefits for lessors and tenants, our data show that there are falling rates of investment in organic manure. The farmers in our sample have reduced organic manure use from 13 tons/ha in 2000 to 5 tons/ha in 2008. Part of this fall is due to the rise of cultivated land rental markets. The analysis, however, does not find that improved property rights in cultivated land rental affect investment largely because property rights have largely been established by 2000, the first year of our sample. Our results, however, also show that there are forces that appear to be mitigating the negative consequences of rising cultivated land rental. After holding constant initial rental rates and other factors, we find that the gap between investment in organic manure in own land and rented‐in land is narrowing. One interpretation of our findings is that if policymakers can find ways to even further strengthen the rights of lessors and tenants as well as lengthen contract periods, farmers—even those that rent—will invest more in their land, because they will be able to capture the returns to their investments.     

Empirical measurement of credit rationing in agriculture: a methodological survey

Empirical analysis of rural credit market failure has been of key scientific and political interest in recent years. The aim of this article is to give an overview of the various methods for measuring credit rationing that are employed in the literature. Furthermore, the methods are subjected to a comparative evaluation of their specific strengths or shortcomings. Six approaches are distinguished: measurement of loan transaction costs, analysis of qualitative information collected in interviews, analysis of quantitative information collected in interviews using the credit limit concept, analysis of spill‐over effects with regard to secondary credit sources, econometric household modeling, and the econometric analysis of dynamic investment decisions. An explicit comparison with a first‐best solution is impossible in the first three approaches, since they essentially rely on a subjective assessment of borrowers' access to credit, based on qualitative or quantitative indicators. The fifth and sixth approaches allow a rigorous interpretation in the framework of neoclassical equilibrium theory. The fourth approach takes an intermediate position, since spill‐over on segmented loan markets reveals a willingness to pay with regard to the supposedly less expensive but rationed primary source. The approaches are fairly data demanding in general, usually requiring specific data on loan transactions. Even so, most approaches are applicable to cross‐sectional household data. With the exception of the first, all methods surveyed might plausibly be used to empirically detect credit rationing.     

Measuring the cost of liquidity in agricultural futures markets: Conventional and Bayesian approaches

Estimating the cost of liquidity in agricultural futures markets is challenging because bid‐ask spreads are usually not observed. Based on an ability to reflect simulated data from Roll's spread model, we assess the effectiveness of conventional and Bayesian bid‐ask spread estimators under different market conditions. Conventional serial covariance and absolute price change spread estimators appear to be biased. Hasbrouck's Bayesian estimator generates small costs of liquidity whose values depend on the correlation and noise in the data. The absolute value Bayesian estimator is precise and works well under conditions of high levels of noise and correlation usually found in agricultural futures markets. Using data from live cattle (LC) and lean hog (LH) contracts, we find similar patterns of performance that produce economically meaningful cost of liquidity differences.     

Futures markets and price stabilisation: An analysis of soybeans markets in North America

The objective of this paper was to determine whether the futures markets have a stabilising or destabilising impact on soybean's spot prices in North America. Directed acyclic graphs (DAGs) are used to test for causality between futures prices, spot prices and ending stocks, followed by time series econometric analysis. The DAGs point to the two-way causal link between futures and spot prices and a lack of a causal link between inventory/stocks and spot price volatility. Time series results, including cointegration, vector error correction, impulse response and variance decomposition analysis, indicate a large impact from futures markets on the level and volatility of soybean spot prices in both the short and long run. These results have potentially important implications, as the impact of commodity price volatility is typically asymmetric across different actors. Farmers, for example, unlike speculators, utilise price risk management (PRM) instruments such as futures markets to mitigate price risks and appear to suffer from intensified volatility precisely because of their use of these instruments. Therefore, additional policies to cope with commodity price volatility, such as direct price controls or mitigation of consequences, can have critical stabilising functions supporting farmers' welfare and regional (rural) development.     

Post–Uruguay Round price linkages between developed and developing countries: the case of rice and wheat markets

The Uruguay Round Agreement on agriculture attempted to lower distortions in global agricultural markets. However, the significant fall in commodity prices in the late 1990s may have reduced the incentives for both developed and developing countries to better integrate into world markets. This study analyzes price linkages and adjustment between developed and developing countries during the post–Uruguay Round period. Prices of two key commodities, long‐grain rice and medium‐hard wheat, are assembled for major exporters and producers. Results of multivariate cointegration analysis suggest partial market integration between developed and developing countries in the post–Uruguay Round period. Developed countries are found to be price leaders in these two markets, and in most cases, changes in their prices have relatively large impacts on those of the developing countries. Developing countries (e.g., Vietnam and Argentina) have faced considerable price adjustment due to changes in the developed countries' prices.     

Market-Based Price-Risk Management: Welfare Gains for Coffee Producers from Efficient Allocation of Resources

The volatility of coffee prices exposes coffee producers to price risk. Price risk is one of many risks faced by commodity producers in developing countries. Coffee is widely traded in the international commodity derivative markets. This offers scope for coffee producers to manage their price risk by hedging on these markets. The hedging mechanism recommended is based on the use of coffee futures and options. The mechanism involves costs, so the benefits of hedging need to be evaluated in order to assess its usefulness for producers. It emerges that the main benefit lies in producers being able to allocate resources more efficiently in the production of coffee. An analysis of theoretical and field evidence shows that this benefit can potentially be quite high, especially for risk-averse producers. This underlines the need to provide producers with access to suitable price-risk hedging mechanisms.     

Why do global long‐term scenarios for agriculture differ? An overview of the AgMIP Global Economic Model Intercomparison

Recent studies assessing plausible futures for agricultural markets and global food security have had contradictory outcomes. To advance our understanding of the sources of the differences, 10 global economic models that produce long‐term scenarios were asked to compare a reference scenario with alternate socioeconomic, climate change, and bioenergy scenarios using a common set of key drivers. Several key conclusions emerge from this exercise: First, for a comparison of scenario results to be meaningful, a careful analysis of the interpretation of the relevant model variables is essential. For instance, the use of “real world commodity prices” differs widely across models, and comparing the prices without accounting for their different meanings can lead to misleading results. Second, results suggest that, once some key assumptions are harmonized, the variability in general trends across models declines but remains important. For example, given the common assumptions of the reference scenario, models show average annual rates of changes of real global producer prices for agricultural products on average ranging between ?0.4% and +0.7% between the 2005 base year and 2050. This compares to an average decline of real agricultural prices of 4% p.a. between the 1960s and the 2000s. Several other common trends are shown, for example, relating to key global growth areas for agricultural production and consumption. Third, differences in basic model parameters such as income and price elasticities, sometimes hidden in the way market behavior is modeled, result in significant differences in the details. Fourth, the analysis shows that agro‐economic modelers aiming to inform the agricultural and development policy debate require better data and analysis on both economic behavior and biophysical drivers. More interdisciplinary modeling efforts are required to cross‐fertilize analyses at different scales.     

How much of commodity price behavior can a rational expectations storage model explain?

A rational expectations competitive storage model was applied to the U.S. corn market, to assess the aptness of this framework in explaining monthly price behavior in an actual commodity market. Relative to previous models, extensive realism was added to the model, in terms of how production activities and storage costs are specified. By modeling convenience yield, “backwardation” in prices between crop years did not depend on the unrealistic assumption of zero ending stocks. Our model generated cash prices that were distributed with positive skewness and kurtosis, and mean and variance that increased over the storage season, comparable to the persistence and the occasional spikes observed in commodity prices. Futures prices were generated as conditional expectations of cash prices at contract maturity, and the variances of futures prices exhibited realistic time–to‐maturity and seasonal patterns. Model realizations of cash and futures prices over many “years” were used to demonstrate the wide variety of price behaviors that could be observed in an efficient market with a similar market structure, implying that economic and policy implications drawn from short, historical samples of prices could be misleading.     

Did Futures Markets Stabilise US Grain Prices?

Though economists are divided over whether, in practice, futures markets reduce spot price volatility, observers of nascent nineteenth century US futures markets essentially praised the stabilising effects of this financial innovation. Indeed, such praise is understandable, particularly if, as the Chicago Board of Trade (CBOT) and others assert, “violent” spot price fluctuations were common prior to, but not after, the 1870s; the same decade that grain trade historians typically associate with the birth of the modern futures contract. And whereas these events may be unrelated, the claim is intriguing because it requires that nineteenth century futures prices fulfil their price discovery function, a property that many modern futures markets do not possess. This paper explores what role, if any, the advent of futures trading may have had on spot price volatility. I corroborate the CBOT's assertion regarding diminished spot price volatility around the 1870s and show that early futures prices did indeed fulfil their price discovery function. Moreover, I address two alternative hypotheses that relate the decline in spot price volatility to the Civil War. Ultimately, I maintain that the evolution of futures markets is the principal proximate reason why commodity spot price volatility diminished.