Fractional Integration in Agricultural Futures Price Volatilities

This article tests whether the volatility of agricultural futures prices exhibits fractional integration. Volatility series were constructed for fourteen agricultural futures price series with over 5,300 observations per series. The volatility series exhibit strong long-term dependence, which is an indicator of fractional integration. A fractional integration model, FIGARCH(1,  d , 1), performs significantly better than a traditional volatility model, GARCH(1,1), in modeling agricultural futures price volatility.     

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.     

Using a functional approach to test trending volatility in the price of Mexican and international agricultural products

In this article, we extend the traditional GARCH(1,1) model by including a functional trend term in the conditional volatility of a time series. We derive the main properties of the model and apply it to all agricultural commodities in the Mexican CPI basket, as well as to the international prices of maize, wheat, swine, poultry, and beef products for three different time periods that implied changes in price regulations and behavior: before the North American Free Trade Agreement (NAFTA; 1987–1993), post‐NAFTA (1994–2005), and commodity supercycle (2006–2014). The proposed model seems to adequately fit the volatility process and, according to heteroscedasticity tests, also outperforms the ARCH(1) and GARCH(1,1) models, some of the most popular approaches used in the literature to analyze price volatility. Our results show that, consistent with anecdotal evidence, price volatility trends increased from the period 1987–1993 to 1994–2005. From 1994–2005 to 2006–2014, trends decreased but the persistence of volatility increased for most products, especially for international commodities. In addition, we identify some agricultural products such as avocado, beans, and chicken that, due to their increasing price volatility trends in the 2006–2014 period, may present a risk for food inflation in the short run.     

Evaluating price transmission between global agricultural markets and consumer food price indices in the European Union

This paper uses error correction models to evaluate the extent to and speed at which world agricultural commodity price movements affect consumer food prices in the European Union member states. We consider three types of world commodity price indices, each containing different commodities and weighting criteria. Results reveal a long‐run relationship between world agricultural commodity and consumer food prices in over half of the member states. Consumer prices in different member states and categories of member states respond differently to specific world price indices, suggesting that there are disparities in the structure and the efficiency of their food markets. The eurozone founders generally have lower transmission elasticities. This should be taken into account when predicting the impacts of extreme world price volatility and consumer food price rises, prompting governments to pay attention to the most vulnerable households.     

Market interdependence and volatility transmission among major crops

This article provides a comprehensive analysis of the dynamics of volatility across major agricultural commodities in the United States. Volatility interactions across markets may lower the effectiveness of diversification strategies to mitigate price risks and should be taken into account when analyzing the pricing behavior of different agricultural commodities. We follow a multivariate GARCH approach to evaluate the time evolution of conditional correlations and volatility transmission across corn, wheat, and soybeans price returns on a daily, weekly, and monthly basis. The period of analysis is from 1998 to 2012. The estimation results indicate a lack of lead‐lag relationships between corn, wheat, and soybeans price returns at the mean level. We find, however, important volatility spillovers across commodities, particularly at the weekly and monthly level. Wheat and corn seem to play a major role in terms of volatility transmission. Despite the supposed higher financial market integration of agricultural commodities, we do not observe that agricultural markets have become more interdependent in recent years.     

Volatility in Oilseeds and Vegetable Oils Markets: Drivers and Spillovers

Food price volatility has re‐emerged as an important topic of political discussion since the food price crisis of 2007–2008. Different volatility drivers have been identified for different markets in the theoretical and empirical literature. However, there is no comprehensive analysis that considers a large number of potential drivers and investigates their joint effects in a dynamic model of interrelated markets. Our study provides such a volatility analysis for the oilseeds and vegetable oils markets. We use a common GARCH approach and a VAR model to identify volatility drivers and spillover effects. Our results show that exchange rate volatility is very important. However, the hotly debated financialisation of commodity markets is not found to be volatility increasing in our monthly data. Impulse response functions show strong spillover effects. Because many volatility drivers found to be important in other markets have no significant effect in our study, our results suggest that volatility drivers are market specific. This implies that any volatility‐reducing policies need to be designed for the market in question.     

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.     

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.     

Food Price Pass‐Through and the Role of Domestic Margin Services

The recent volatility in international agricultural markets has drawn attention to the impact of rising international agricultural prices and the induced price‐insulating measures on consumer food prices. Analyses based on simulation models on this topic typically ignore the role of domestic margin services. We extend the standard Global Trade Analysis Project (GTAP) model to allow for variations in the share of domestic margin services in consumed food across countries. This approach enables us to differentiate consumer prices from producer prices. Following the extension, the results show that domestic margin services reduce the consumer food price volatility for all countries, especially in high‐income countries, where the share of domestic margin services in final food consumption is higher. The effect of price‐insulating border policies is also reduced in the extended model. We find that our extension of the GTAP model greatly improves simulations of the 2007 surge in international agricultural prices. We validate our extension of the GTAP model by showing that the econometrically estimated food price pass‐through is decreasing with income and thus, is smaller in high‐income countries.     

A simple model of endogenous agricultural commodity price fluctuations with storage

A debate has been raging for centuries regarding the effects of interannual storage on commodity prices. Most analysts consider storage to function as a price stabilizer, while others place it at the core of an explanation of intriguing features of commodity price series, such as skewed distributions. Most studies have been developed in the context of the theory of competitive storage where random shocks affect supply or demand. Recently, the endogenous chaotic behavior of markets has become another possible hypothesis regarding the origin of commodity price fluctuations. We develop a nonlinear cobweb model with intra‐ and interannual storage, risk averse agents, and adaptive expectations. Like the theory of competitive storage, this nonlinear cobweb model with storage can reproduce some of the stylized facts of agricultural commodity prices (autocorrelation of first rank, low kurtosis, and skewness). In addition, the effects of storage on price variation are mixed. In the presence of interannual storage, chaotic price series show less variation compared to a situation without interannual storage but we find that storage contributes to the endogenous volatility of prices by making chaotic dynamics more likely.     

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.     

Are Shocks Transitory or Permanent? An Inquiry into Agricultural Commodity Prices

This paper contributes to the contentious topic of whether shocks to agricultural commodity prices are permanent or transitory. This is an important issue with regards to forecasting, economic modelling of agricultural prices and risk management. Past studies have not accounted for important characteristics of agricultural prices that matter when testing whether shocks to prices are permanent or transitory. These include the presence or absence of a deterministic trend, the possible break in the trend, non‐stationary volatility, and the problem of the initial deviation of commodity prices from their long‐run mean or trend. We conduct a comprehensive test that incorporates all these characteristics known to plague agricultural commodity prices. Though the conclusion is mixed, the balance is in favour of agricultural price shocks being permanent in nature. This result departs from the general view that in theory, agricultural prices should be stationary, suggesting that the controversy of whether shocks to agricultural prices are temporary or permanent is not yet over.     

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.     

The Variable Response of Agricultural Supply to World Price Instability in Developing Countries

This paper analyses the effect of world price instability on the agricultural supply from developing countries and determines to what extent this effect is dependent upon the macroeconomic environment. Producers from agricultural commodity‐exporting countries are particularly vulnerable to the fluctuations of world prices: they are widely exposed to price shocks and have little ability to cope with them. Nevertheless, the effectiveness of risk‐coping strategies is conditioned by the influence of macroeconomic factors (infrastructure, inflation and financial deepening). Thus country‐specific price indices are established, and the response of production indices to price instability indices is estimated by using a panel model including macroeconomic variables which interact with price instability. Such analysis is based on a sample of 25 countries between 1961 and 2002. The results highlight a significant negative effect of the world price instability on supply, and further show that high inflation, weak infrastructure and a poorly developed financial system exacerbate this effect.     

Collateral‐free lending with risk‐contingent credit for agricultural development: indemnifying loans against pulse crop price risk in India

This article addresses the problem of collateral‐free lending in the context of agricultural development. We investigate a viable alternative to traditional credit products through the development of risk‐contingent credit for operating loans and farm mortgages and apply the concept to agricultural loans for pulse crops in India. Risk‐contingent credit mitigates business and financial risk by reducing debt obligations depending on the embedded commodity options whose payoffs are linked with commodity price fluctuations. We analyze daily commodity spot prices for pulse crops in India and show how risk‐contingent structured financial instruments can be priced in practice.     

What Does Granger Causality Prove? A Critical Examination of the Interpretation of Granger Causality Results on Price Effects of Index Trading in Agricultural Commodity Markets

The influence of index trading on price levels, returns, spreads or volatility in agricultural commodity markets is frequently investigated with bivariate Granger Causality (GC) tests. A joint review of existing empirical studies reveals scant and inconsistent evidence of GC from index activity to prices. Some findings of reverse GC from prices to index activity are reported. The literature offers three different interpretations of GC test results: (i) as prima facie causal evidence; (ii) as a test for informational efficiency of the markets; or (iii) as a test for the ability of one variable to improve the forecast of another variable. A critical examination of these interpretations against an extended theoretical background reveals that none allows direct inferences about the existence or absence of an influence from index trading activity on the price mechanism in the market. This severely limits the usefulness of a stand‐alone application of GC tests.     

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.     

World market integration for export and food crops in developing countries: a case study for Mali and Nicaragua

Using a generalized error correction model, this article measures and compares market integration for export cash crops versus imported food crops for Mali and Nicaragua, and computes transmission elasticities between changes in the goods’ border and domestic prices. Both Mali and Nicaragua obtain the bulk of their export revenue from a particular agricultural commodity—cotton for Mali and coffee for Nicaragua—and both import the same key staple food of rice. To reap the economic gains from this trade specialization, the two countries’ agriculture must be well‐integrated into world markets. The two countries present an important policy contrast that affects their degree of world market integration and price transmission. In Mali, a parastatal enterprise controls its cotton industry, while Nicaragua has less state direction over agriculture. Reflecting this difference, the results show that for both its main export and import commodity, Nicaragua is more integrated into world markets and has higher price transmission than Mali. The results for Nicaragua also show much higher integration and price transmission for its main agricultural export (coffee) than its major import (rice).     

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.     

FTA,Exchange rate pass‐through and export price behavior – Lessons from the Australian dairy sector

The growing number of bilateral and regional free trade agreements (FTAs) alongside exchange rate volatility has raised a question on whether these affect exporters’ pricing behaviors, hence competitiveness. This study contributes to this topic by examining Australian dairy export price behavior across eight major markets taking into account the extent of pass‐through of exchange rate and tariff as well as FTAs between Australia and its trading partners. Commodity‐level dairy trade data from 1996 to 2016 and the feasible generalized least squares methods are employed. The study finds incomplete pass‐through at the industry level. The dairy export prices decrease by 1.7% if Australian dollar depreciates by 10%, while 10% tariff reduction is associated with 0.7% export price cut. Results at the commodity level show different pricing behaviors across destination and commodity markets. Overall, apart from the tariff effects, there is minimal evidence of the impacts of FTAs on dairy export prices.