Cross country maize market linkages in Africa: integration and price transmission across local and global markets

In order to study short‐run price shock propagation, we model twenty seven Sub‐Saharan Africa (SSA) domestic maize markets within a Global Vector Autoregression framework. The main purpose is to fully embed multilateral trade flows as a way to better structure local price transmission dynamics and interdependencies, and get a more comprehensive picture of food price shocks propagation. We found significant between‐country market contagion and prompt regional price shock propagation when trade connection exists. Yet, the integration of SSA domestic maize markets within the continent and with global markets remains generally weak. Furthermore, under regular market conditions, most local price series appear to be more responsive to regional neighbors than to global shocks.     

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.     

Energy price reform and food markets: the case of bread supply chain in Iran

Reforming energy price is the core of Iranian economic reform plan during 2010–2014. However, increasing price of energy may have adverse effects on the agricultural and food markets. This study was conducted to address these problems in the most important food of Iranian people “bread” by developing a spatial supply chain model. Results show that consumers’ welfare would experience a sharp decrease though the impacts on farmers are trivial. Also, results indicate that the key to success the reform without political backlash in the short‐run is the cash transfer program under which the government redistributes part of the reform's benefits among consumers. Per capita compensation payments would be equal to 51.50 and 46.09 US$ per year for a typical rural and urban person, respectively. Moreover, the results provide more detailed information about the market characteristics and the payments both in nationwide and regional scale as well as in different income groups.     

A quantile autoregression analysis of price volatility in agricultural markets

This paper investigates the dynamics of agricultural price volatility based on a quantile autoregression (QAR) model. The QAR model provides a flexible representation of the distribution of price and its dynamics. The approach is applied to U.S. wheat and corn markets over the period of 1980–2017. This period is of significant interest as it covers important changes in agricultural policy and increased reliance on markets. The price analysis is conducted conditional on stocks held in the previous period. We show how increasing previous stocks shift the price distribution to the left and decreases the odds of facing price spikes (by shifting down the upper tail of the price distribution). Our analysis also examines the effects of changing public stocks on prices. For both wheat and corn, this reflects changing agricultural policy, contrasting the 1980s (when public stocks were relatively high) with the post-2005 period (when public stocks became zero). We document how higher public stock ratio during the previous period did not lower the odds of facing price spikes. Applied to the wheat and corn markets, we also uncover evidence of local dynamic instability in the upper tail of the price distribution, suggesting that price instability becomes more pronounced when previous stocks are low.     

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.     

Inter‐ and intra‐seasonal crop acreage response to international food prices and implications of volatility

Understanding how producers make decisions to allot acreage among crops and how decisions about land use are affected by changes in prices and their volatility is fundamental for predicting the supply of staple crops and, hence, assessing the global food supply situation. This study makes estimations of monthly (i.e., seasonal) versus annual global acreage response models for the world's principal staple food crops: wheat, corn, soybeans, and rice. Primary emphasis is given to the magnitude and speed of the allocation process. Estimation of intra‐annual acreage elasticity is crucial for expected food supply and for input demand, especially in the light of the recent short‐term volatility in food prices. The econometric results indicate that global crop acreage responds to crop prices and price risks, input costs as well as a time trend. Depending on respective crop, short‐run elasticities are about 0.05 to 0.40; price volatility tends to reduce acreage for some of the crops; comparison of the annual and the monthly acreage response elasticities suggests that acreage adjusts seasonally around the globe to new information and expectations. Given the seasonality of agriculture, time is of an essence for acreage response. The analysis indicates that acreage allocation is more sensitive to prices in the northern hemisphere spring than in winter and the response varies across months.     

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.     

The effect of barge and ocean freight price volatility in international grain markets

Short‐run responses of export and domestic shares of total agricultural output to changes in stocks of domestic savings (SAV), development assistance (ODA), private foreign commercial capital (PFX) and other variables is investigated. A profit function approach is used. Time series data for 19 sub‐Saharan African countries are pooled into three panels using similarities in changes in economic policy regime. Statistical evidence suggests that for the panel of countries that were undertaking liberalized economic reforms, the slope coefficients of some of the variables in the models have changed significantly between 1970–1980 and 1981–1993. For the 1981–1993 period, the impacts of ODA, PFX and SAV on export and domestic shares were different for this panel. The effect of increases in agricultural labor was different across the three panels. There is also evidence that productivity growth in the export agriculture sub‐sector is negative in all the groups. It is recommended that to halt the decline in export share of agricultural output in the group of countries that have undertaken substantial improvements in economic policy environment, efforts must be made to reduce the negative impact of domestic savings and agricultural labor, while at the same time working to reduce the bias of development assistance against food security.     

The integration of energy and agricultural markets

This article addresses the evolving links between energy and agricultural markets. Prior to 2005, there was little correlation between energy and agricultural commodity prices. In 2006–2008, with the ethanol boom in the United States, there emerged a strong link between crude oil, gasoline, and corn prices. There was little link between ethanol and corn. However, in late 2008 and 2009, the markets changed as ethanol production came under severe economic pressure and 2 billion out of 12 billion gallons of capacity shut down. During this period ethanol became priced more on corn, as the breakeven corn price helped drive the ethanol market. This article explores the drivers in these markets as well as other major issues facing the corn ethanol industry in the United States such as the blend wall. The article concludes with a review of prospects of a future cellulosic biofuels industry.     

The use of organized commodity markets to manage food import price instability and risk

The article explores the possibility of insuring the price risks of wheat and maize imports of low‐income food‐deficit countries (LIFDCs). Optimal strategies for an importing agent, who hedges with futures and options are derived, based on the objective of minimizing the unpredictability of import bills. Ex post simulations for a set of LIFDCs are run on wheat and maize imports hedged with futures and options in the Chicago Board of Trade, to explore the extent to which hedging reduces the unpredictability in import bills. Simulations encompass both periods of normal price behavior, as well as the period of global upheaval that occurred in 2007 and 2008. Results show that hedging with futures alone affords agents considerable opportunities for reducing import cost unpredictability, and the same holds with options, albeit, to a lesser extent. However, during the recent price spike of 2007–2008, hedging with options would have increased the unpredictability of some countries’ maize import bills, due to the combination of erratic import patterns and pronounced market uncertainty.     

Notes on farm‐retail price transmission and marketing margin behavior

Perfect farm‐retail price transmission sometimes is taken to mean an elasticity of price transmission (EPT) equal to 1. We show that this definition is inconsistent with Gardner's (1975) model. We also show that the absolute marketing margin (defined as the difference between the retail price and farm price) responds differently to shifts in retail demand, input supply, and technical change in the marketers’ production function than does the relative marketing margin (defined as the ratio of the retail price to the farm price). The empirical implications of these results are discussed in some detail.     

Modeling price transmission between farm and retail prices: a soft switches approach

Vector error correction models (VECM) are used to model price transmission when farm and retail prices are cointegrated. To allow for nonlinearity in the cointegration process, researchers may specify thresholds to break the error correction process into regimes according to whether the retail price is above, below, or close to its equilibrium value given farm prices.  However, because the coefficients in a VECM can change when there is movement from one regime to another, the model can be discontinuous.  This implies sudden, “hard” regime changes. In this study, we extend the threshold VECM to include features of smooth transition autoregression (STAR) models. Our approach allows for gradual, soft regime changes.  An empirical application to retail cheese and farm milk prices is presented.     

Fighting global food price rises in the developing world: the response of China and its effect on domestic and world markets

This article addresses how China is being affected by and is responding to the world food crisis. So far, Chinese officials have responded to higher world prices by drawing down stocks and limiting exports of major grains. These policy instruments were not available for soybeans, so domestic prices of soy and other oilseeds have risen with international prices. Using a global CGE model, we show that the initial world price rise was largely due to higher world oil prices and demand for biofuels as opposed to other factors, especially in maize and soybeans. China's response to this shock has kept domestic grain prices low relative to world grain markets and to domestic soybean prices. As grain stocks are depleted, however, demand growth will push domestic prices back into alignment. Anticipating this pressure on consumers and accelerating supply response through public investment will facilitate adjustment.     

Extent and possible causes of intrayear agricultural commodity price volatility

Wheat, corn, rice, soybeans, and cotton experienced higher volatility in the second half of the 2000s. For the sample at hand, the unit root tests only validate a new period of high volatility for wheat and cotton. If in the next couple of years however, corn, rice and soybeans maintain their higher volatility, a new period of high volatility may also be validated statistically. Regarding the factors driving the intrayear volatility GMM estimates show that “commodity market fundamentals” i.e., the stock‐to‐use ratio and to a lesser extent the degree of internationalization, are the most systematically statistically significant coefficients among commodities. Over time, consecutive low stock‐to‐use ratios and a thin international market provoke typically high volatility. Speculative activity and liquidity in the agricultural derivative market have a stabilizing effect on the spot price, if any. Finally, “common macro” factors significantly impact volatility, especially the volatility of petrol and of exchange rates; their dispersion importance over the sample is quite sizeable. However, it is difficult to establish a link between, on the one hand, loose monetary policy, business cycle and inflation, and, on the other hand, commodity price volatility, as the sign of the estimated coefficient changes depending on the commodity and the estimated elasticities are quite low.     

Testing the central market hypothesis: a multivariate analysis of Tanzanian sorghum markets

The central market hypothesis is important in the analysis of market integration because it implies a specific market structure while avoiding a simultaneity problem. However, despite its importance, the central market hypothesis is difficult to test and is therefore often assumed. This article shows that the hypothesis can be tested in a Johansen cointegration test provided that prices are nonstationary. This approach is applied to reveal the existence of central markets for sorghum in Tanzania. The results indicate that the Tanzanian sorghum market can be grouped into two market regions, with prices being determined in a central market in each region.     

Agricultural price transmission across space and commodities during price bubbles

This article investigates agricultural price transmission during price bubbles. The empirical approach concerns the horizontal transmission of cereal prices both across different market places and across different commodities. The trade policy intervention put forward to mitigate the impact of price exuberance is considered. The analysis is performed using Italian and international weekly spot (cash) price data over years 2006–2010, a period of generalized turbulence of agricultural markets. Firstly, the properties of price time series are explored; then, interdependence across prices is specified and estimated by adopting appropriate cointegration techniques. Results suggest that the bubble had only a slight impact on the price spread and the temporary trade‐policy measure, when effective, has limited this impact.     

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.