Are commodity prices chaotic?

We conduct tests for the presence of low‐dimensional chaotic structure in the futures prices of four important agricultural commodities. Though there is strong evidence of non‐linear dependence, the evidence suggests that there is no long‐lasting chaotic structure. The dimension estimates for the commodity futures series are generally much higher than would be for low dimension chaotic series. Our test results indicate that autoregressive conditional heteroskedasticity (ARCH)‐type processes, with controls for seasonality and contract‐maturity effects, explain much of the non‐linearity in the data. We make a case that employing seasonally adjusted price series is important in obtaining robust results via some of the existing tests for chaotic structure. Finally, maximum likelihood methodologies, that are robust to the non‐linear dynamics, lend strong support to the Samuelson hypothesis of maturity effects in futures price changes.     

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.     

A Model of Spatial Arbitrage with Transport Capacity Constraints and Endogenous Transport Prices

This article solves a high-frequency model of price arbitrage incorporating storage and trade when the amount of trade is limited by transport capacity constraints. In equilibrium there is considerable variation in transport prices because transport prices rise when the demand to ship goods exceeds the capacity limit. This variation is necessary to attract shipping capacity into the industry. In turn, prices in different locations differ by a time varying amount. Thus while the law of one price holds, it holds because of endogenous variation in transport prices.     

SOME ILLUSTRATIONS OF CHAOS IN COMMODITY MODELS

This paper develops three commodity models which exhibit chaotic behaviour. The examples chosen are a demand system and two cobweb supply and demand models. The latter differ from the standard forms in that they include risk aversion and a new specification for the formation of price expectations. Simulation of the model highlights three implications of chaos: such systems generate complex time-paths even if the exogenous variables within the model are held constant; the simulated time path is critically sensitive to the starting value of variables, and parameter values; and the average behaviour of the system is critically sensitive to parameter and exogenous variable values. ‘Critically sensitive’ means that very small changes in parameter or starting values leads to substantial changes in the time paths of the variables in the model. These results suggest that if real commodity sectors can be characterised as chaotic systems, then the ability to conduct forecasting and policy analysis of such sectors will be severely curtailed.     

World Commodity Prices and Domestic Retail Food Price Inflation: Some Insights from the UK

We focus on two aspects of the links between world commodity prices and retail food price inflation: first, the effects of exchange rates and other input costs, and second; the effects of the duration of shocks on world commodity markets, not just the magnitude of price spikes (the latter often commanding most attention). The UK offers a natural and rather unexplored setting for the analysis. Applying time series methods to a sample of 259 monthly observations over the 1990(9)–2012(3) period we find substantial and significant long‐term partial elasticities for domestic food price inflation with respect to world food commodity prices, the exchange rate and oil prices (the latter indirectly via a relationship with world food commodity prices). Domestic demand pressures and food chain costs are found to be less substantial and significant over our data period. Interactions between the main driving variables in the system tend to moderate rather than exacerbate these partial effects. Furthermore, the persistence of shocks to these variables markedly affects their effects on domestic food prices.     

WELFARE IMPLICATIONS OF MORE ACCURATE RATIONAL FORECAST PRICES

Models are constructed to assess the welfare effects for producers, consumers and society of producers using forecast prices based on more accurate estimates of variables causing shifts in the demand for and supply of commodities. The basic model is a stochastic cobweb model in which producers' forecast price is the rational forecast price. The model is extended for many commodities, for partial producer response to more accurate forecast prices, and to include stock holding. In terms of economic surplus, producers and consumers gain from more accurate estimates of demand shift variables, producers gain and consumers lose from more accurate estimates of supply shift variables, and in both cases there is a net society gain.     

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.     

Price relationships between qualitatively differentiated agricultural products: organic and conventional wheat in Germany

Organic agriculture, which produces commodities that can be qualitatively differentiated from conventional food products, has grown into an important market in many countries. The dynamics of commodity prices in both sectors are partly interdependent, but are also shaped by independent determinants and have rarely been studied. We analyze organic food markets and their interdependencies with conventional markets in the context of wheat markets in Germany, which have been subject to a number of fundamental changes during the last two decades. Based on institutional market characteristics, we suggest a flexible Markov‐switching asymmetric time series model. We find a pronounced temporal sequence of market phases that differ in their asymmetric dynamics and the extent to which the organic price is influenced by the conventional price. Organic wheat prices tend to be increasingly connected to prices of conventional wheat.     

Effects of pricing policy on seasonal storage of wheat in Pakistan

Most studies of stockholding in less developed countries have concentrated on public, interannual stocks. A recent change in Pakistan government policy for the pricing of wheat highlights the need to examine seasonal storage issues, considering explicitly the effects of policy on the behavior of private agents who hold seasonal stocks of grain. Using H. Working's supply of storage theory and a simple monthly model, implications of the policy change for fiscal cost, private storage, and government procurement are explored. Costs of the policy could be reduced dramatically by increasing marginally the gap between the procurement and release price. Expected cost to the consumer of a wider gap would be no larger than under the previous policy.     

Renewable versus nonrenewable resources: an analysis of volatility in futures prices

This study outlines a new approach for differentiating commodity futures based on their exhaustibility. Various aspects of volatility in the futures prices of renewable resources (palm oil, coffee, soya beans, rice, wheat and corn) and nonrenewable resources (zinc, aluminium, natural gas, gold, crude oil and copper) are studied, exploring whether volatility is greater in the former than in the latter. We use a generalised autoregressive conditional heteroskedasticity (GARCH) model to test our main hypothesis that the volatility in futures prices for renewable resources has recently been equal to or greater than the volatility in futures prices for nonrenewable resources. Our key findings suggest that futures prices for some renewable resources have greater variance than those for benchmark crude oil in a simulated GARCH series. We extend our analysis using a nonlinear vector smooth transition autoregressive (VSTAR) model to test for the existence of a shifting‐mean tendency in the commodity series that we researched. We show that transition from a stable to a volatile regime is more abrupt for renewable resources.     

On the Comovement of Commodity Prices

We present strong evidence against the excess-comovement hypothesis—that the prices of commodities move together beyond what can be explained by fundamentals. Prior studies employ broad macroeconomic indicators to explain common price movements, and potentially correlated fundamentals are not controlled for. We use inventory and harvest data to fit a partial equilibrium model that more effectively captures the variation in individual prices. The model explains the majority of the comovements among commodities with high price correlation, and all of the comovements among those with marginal price correlation. Common movements in supply factors appear to play an important role in the observed comovements in commodity prices.     

The Effects of Maize Market and Policy Reforms on Price Discovery and Competitiveness in Zimbabwe, 1991–1997

Abstract

Maize is Zimbabwe's staple food. An adequate supply of maize is essential to food security and domestic stability. A series of droughts and government mismanagement of the economy led to a maize production and food security problem in the 1980s. Zimbabwe's maize marketing system was transformed dramatically from a government monopoly to a competitive market system in which prices are determined by market forces in the 1990s. This paper examines the steps that Zimbabwe took towards maize market reform and the benefits of that reform. The movement to a competitive market led to formation of a commodity exchange to improve price discovery and increase price transparency. De-regulation has increased entry and competitiveness from new private sector hammer millers and traders. Farmers, millers, and traders face new profit opportunities and new price and financial risks that have increased management responsibilities. Consumers enjoy lower cost maize meal products and more convenient service. The benefits of the 1991–1997 reforms indicate what could be achieved in the long run if prices are determined by the market, rather than by the government.     

Agricultural Producer Price Expectations

Producer price expectations underlie much of agricultural supply analysis. While producer price expectations would ideally be discovered experimentally, this is too costly. Instead, producer price expectations are usually represented in agricultural supply analysis by easily obtained hypothesized expectation formulations. In most cases, the hypothesized expectation formulations are functions of past prices. However, other formulations are sometimes used, such as current cash and futures prices, or initial payments in the case of grains marketed by the Canadian Wheat Board. This paper compares actual producer price expectations with a variety of hypothesized expectation formulations for wheat and canola in Saskatchewan. A test developed by Granger is used to determine the proxy models that are significantly dominant. The model that dominates as a proxy in the case of wheat price expectations is the two-year declining-weight moving average. The two models that dominate as a proxy in the case of canola price expectations are the first-order autoregressive and, as well, the two-year declining-weight moving average. There is no significant difference between the two models. Somewhat surprising is the performance of formulations based on futures prices. These formulations perform very poorly in representing producers' price expectations, even though they are found to be among the most accurate predictors of actual commodity prices. An even more interesting observation is the performance of the futures price model in the canola market. Even though the November contract in January explains very little of the variation in the actual commodity prices for that year, its error in predicting canola prices is not significantly greater than that of the best performing, the four-year declining-weight moving average, based upon the root mean squared error criterion.     

The behavior of commodity prices in Ethiopia

In an attempt to identify price stabilization strategies and rationalize public intervention in buffering markets, this article investigates the intertemporal dynamics of commodity prices in Ethiopia. A classical rational expectation model is modified to account for seasonal correlation of shocks. Model predictions are reduced to computable periodic threshold autoregression. Several nonlinearity tests are applied to detect threshold effects. A regime‐switching normalized maximum likelihood method is formulated to estimate thresholds and threshold autoregression parameters using monthly data from Ethiopia for the period 1996–2006. The result indicates the presence of periodic price thresholds that could be formed as a result of speculative storage. Comparison of price movements below and above thresholds indicates that prices are more correlated below the thresholds than above them. However, the effect on error variance is not very strong. Temporal arbitrage, which is the gross return from speculative storage, appears to be modest. The long‐ and short‐term implications of the findings are discussed within the context of ongoing policy debates.     

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.     

Why does on-farm storage fail to mitigate price volatility?

We analyze the role of farm stock management on price volatility under liquidity constraints and heterogeneous price expectations. In commodity markets, speculative behaviors by stockholders tend to reduce price volatility, but this is not the case in certain agricultural markets, where speculation by farmers regarding decisions to sell or store grain is subject to liquidity constraints and heterogeneous price expectations. Like stockholders, most farmers sell grain if they expect a price drop in the near future, but unlike stockholders, they are not necessarily able to purchase grain if they expect a price increase in the next period. Heterogeneous price expectations can also lead to suboptimal storage decisions, further increasing price volatility. For these reasons, the storage management behavior of farmers often fails to mitigate price drops in the way that speculation by stockholders does. We merge historical data on maize prices and household storage collected in Burkina Faso in order to build a dynamic panel over the 2005–2012 period. We show that carryover from one season to the next is associated with unexpected price drops during the preceding lean season and that carryover is associated with more frequent unexpected price drops following the subsequent post‐harvest season.     

Spatial Market Arbitrage and Threshold Cointegration

Goodwin and Piggott reported that corn and soybean prices in spatially separated markets in North Carolina exhibited threshold cointegration and that commodity prices in different markets may persistently diverge. Here, a multivariate approach is used to test for threshold cointegration and nonlinear cointegration. The results suggest that departures from the law of one price do not persist indefinitely.     

How financial investment distorts food prices: evidence from U.S. grain markets

Convergence between commodity futures prices and the underlying physical assets at each contract's expiration date is a pivotal condition for the market's functioning. Between 2005 and 2010, convergence failed for several U.S. grain markets. This article presents a price pressure‐augmented commodity storage model that links the scale of nonconvergence to financial investment channeled through indices, which are traded in commodity futures markets. The model is empirically tested, using Markov regime‐switching regression analysis. Regression results strongly support the model's predicted link between index investment and the extent of nonconvergence for three grains traded at the Chicago Board of Trade: wheat, corn, and soybeans.     

Spatial and Seasonal Price Differences for Sorghum and Sesame in Sudan

Spatial and seasonal price differences for sorghum and sesame in the Sudan are investigated. A conceptual model of competitive market behavior in time and space dimensions is adopted to test the spatial and the seasonal price differences as compared to transportation and storage costs, respectively. The large differences in sorghum prices among regions indicate a lack of market integration between producing and consuming regions. Monthly price changes for sorghum and sesame compared to storage costs indicate an opportunity to capture above normal returns to storage. Causes of these large price differences are inadequate transportation and marketing infrastructure and government policy.     

Effects of international shocks and domestic macroeconomic policies upon Brazilian agriculture

An identified vector-autoregressive model is used to analyze the transmission of external commodity shocks to the Brazilian economy. The effects of the interaction between domestic macroeconomic (monetary and exchange rate) policies and external shocks to agricultural commodity (raw material and food) prices and crude oil price upon domestic (agriculture/industry) terms of trade are estimated.