Risk Behaviours and Grazing Land Management: A Framed Field Experiment and Linkages to Range Land Condition

We use a framed field experiment considering hypothetical stocking rate decisions made by grazing enterprise managers and estimate non‐linear multinomial logit models for a range of nested non‐expected utility and expected utility models. The risk and decision‐bias parameters for five models estimated for individual responses are shown to be significantly related to land condition but in ways which suggest behavioural aspects of decision making are critical in understanding land management and stocking rate decisions. Our results show that individual heterogeneity in decision making amongst farming groups is likely to be a significant source of variation in farming intensity and technology adoption decisions. This heterogeneity does not appear to be a reflection of socio‐demographic characteristics. Furthermore, decision functions appear to be biased toward selection of simpler representative functions (e.g. Expected Utility) for sample averages. This suggests that experimental findings that Expected Utility is representative for actual decisions may be due to sample averaging rather than reflect actual behaviour.     

Efficiency tests of agricultural commodity futures markets in China

The efficiency of the Chinese wheat and soybean futures markets is studied. Formal statistical tests were conducted based on Johansen's cointegration approach for three different cash markets and six different futures forecasting horizons ranging from 1 week to 4 months. The results suggest a long-term equilibrium relationship between the futures price and cash price for soybeans and weak short-term efficiency in the soybean futures market. The futures market for wheat is inefficient, which may be caused by over-speculation and government intervention.     

Information-rich wheat markets in the early days of COVID-19

This paper uses the information implicit in commodity futures and options prices to infer market beliefs about the impact of early-stages COVID-19 on commodity market fundamentals. The particular commodity examined is soft red winter (SRW) wheat, and the timeframe is early February to late March 2020. The analysis highlights various adjustments in the cash and futures price of SRW wheat in light of surging short-run demand from consumer hoarding of staple food products, and a weakening long-run market from growing wheat stocks and an emerging global recession. This split is causing the forward curve to flatten and basis levels to invert. The change over time in the price of options on wheat futures reveals increased price volatility in response to growing uncertainty about the COVID-19 impacts. Similarly, changes in the skewness of the option's volatility smile illustrate a shift in traders’ perception about risk in the right versus left tail of the price distribution.     

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.     

Food commodity price changes and consumer welfare in Bangladesh: Valuable lessons for today

The recent rise in global food prices threatens many countries worldwide, especially the vulnerable populations. Viable coping strategies can only be designed based on the important policy lessons learned from the experiences of these countries in confronting the similar shocks of 2007–2011. However, the disproportionate effects of these events and the impacts of policy responses remain largely unexplored. We examine the impact of a food price surge and the effectiveness of various mitigating policies in Bangladesh, one of the most populous, densely populated countries in the world that is plagued by poverty. Specifically, we combine individual-level expenditure survey data with recent advances in consumer theory to examine the welfare consequences across income groups and geographic areas of the country over 2000–2016. Our empirical findings lend support to the hypothesis that the brunt of the price surge was borne by relatively less affluent and rural households, and government poverty alleviation programmes were largely ineffective.     

Measuring price discovery between nearby and deferred contracts in storable and nonstorable commodity futures markets

Using price discovery measures, including Putniņš’ (2013) information leadership share and intraday data, we quantify the proportional contribution of nearby and deferred contracts in price discovery in the corn and live cattle futures markets. On average, nearby contracts reflect information more quickly than deferred contracts in the corn market, but have a relatively less dominant role in the live cattle market. In both markets, the nearby contract loses dominance when its relative volume share dips below 50%, which typically occurs when the nearby is close to maturity. Regression results indicate that the share of price discovery is mainly related to trading volume and time to expiration in both markets. In the corn market, price discovery share between nearby and deferred contracts is also related to inverse carrying charges, crop year differences, USDA announcements, market crashes, and commodity index position rolls. Differences between corn and live cattle markets are consistent with differences in the contracts’ liquidity and commodity storability.     

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 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.     

Management flexibility,price uncertainty and the adoption of carbon forestry

A price on carbon has the potential to drive significant land use change through reforestation. Understanding the likely locations and extent of these changes is therefore a key focus for researchers and policy makers. Models of reforestation based on net present values (NPV) typically compare the economic returns of carbon forestry to alternative land uses. However, these models often neglect the impact of uncertainty. Two sources of uncertainty highly relevant to carbon forestry are the opportunity cost of the land on which the trees are established (i.e. future returns from alternative land uses) and carbon prices. In addition to foregoing the current land use, a landowner making a permanent land use change such as carbon forestry is also giving up the opportunity to change management in the future, for example by changing crop mix in response to commodity price changes. We develop a Monte Carlo model to demonstrate the value of management flexibility, based on a case study property in Australia. While in the absence of management flexibility carbon forestry is more profitable than the current land use, under uncertain future commodity prices it is less attractive to a landowner. We go on to show that, even if the returns from carbon exceed those from more flexible agricultural land use, uncertainty over future carbon prices is likely to delay the adoption of carbon forestry. Overall the models presented in this paper demonstrate that the adoption of carbon forestry is likely to be substantially lower, and slower, than models based on static values would suggest.     

Out‐of‐sample testing price discovery in commodity markets: the case of soybeans

Price discovery, a central function of futures markets, has been usually tested in‐sample by studying the common stochastic trend between spot and futures prices. Instead, to evaluate futures as anticipatory prices, we develop a forecast approach to out‐of‐sample test price discovery in a multivariate framework. We apply it to the soybeans market. Results indicate futures prices as the best available “predictors” of future spot prices, although this finding holds only on average and for certain periods, other models show forecasting gains.     

The impact of commodity price and conservation policy scenarios on deforestation and agricultural land use in a frontier area within the Amazon

Deforestation in the Amazon is caused by the complex interplay of different drivers. Price of commodities such as beef and soya, and incoming migration are paramount factors. Construction of new highways is a key aspect, as they enable a growing flow of people and economic activities, provoking an intensification of the conversion of forests into pasture and agricultural areas. The pavement of road BR-163 accelerates the expansion of the agricultural frontier from the state of Mato Grosso to Pará, inside the Amazon. Today, the Brazilian government applies two main kinds of policies to protect the environment. First by establishing conservation units (CUs) that include an array of reserve types from natural areas to indigenous lands, and second by enforcing the Forest Code (FC), a law that limits the occupation and use of forests. Legal reserve requirements for rural properties are 80% in the Amazon rainforest, 35% in the Cerrado shrublands and 20% in other regions. However, the effectiveness of these policies relies on a fragile institutional capacity, which causes a flawed monitoring, law enforcement and control. To assess the impact of effective conservation policies on land use and deforestation by 2020, we used the LUSMAPA model in combination with two scenarios, one that included different commodity price developments and migration rates and one on the assumption of the institutional strength to uphold the conservation policies. A revision of the FC from an average 80% policy target to 60% effective implementation and disregard borders of CUs by allowing 5% deforestation in CUs, that both corresponds to a ‘weak’ governmental enforcement, leads to additional deforestation of 41–57%, depending on the commodity price scenario. The results of the simulations are discussed in the light of recent policy changes in Brazil.     

Effect of yield and price risk on conversion from conventional to organic farming*

Although the benefits of organic farming are already well known, the conversion to organic farming does not proceed as the Dutch government expected. In order to investigate the conversion decisions of Dutch arable farms, a discrete stochastic dynamic utility‐efficient programming (DUEP) model is developed with special attention for yield and price risk of conventional, conversion and organic crops. The model maximizes the expected utility of the farmer depending on the farmer’s risk attitude. The DUEP model is an extension of a dynamic linear programming model that maximized the labour income of conversion from conventional to organic farming over a 10 year planning horizon. The DUEP model was used to model a typical farm for the central clay region in the Netherlands. The results show that for a risk‐neutral farmer it is optimal to convert to organic farming. However, for a more risk‐averse farmer it is only optimal to fully convert if policy incentives are applied such as taxes on pesticides or subsidies on conversion, or if the market for the organic products becomes more stable.     

环洞庭湖区经济社会发展模式优化调控研究

通过分析洞庭湖区经济社会发展的条件及现状特征,找出了在国家区域经济协调发展背景下湖区经济快速发展的新契机,进而提出了湖区经济发展模式必须优化,即在产业结构优化方面:继续抓好优质粮油生产,重点发展农产品加工业、牲畜和水产养殖业、林产品加工业、特色旅游业等;在空间组织优化方面:采取三点三线开发模式,以岳阳、常德、益阳3 点...     

Local polynomial fitting and spatial price relationships: price transmission in EU pork markets

We study price transmission processes within EU pork marketsafter the implementation of the EU single market in 1993. Wecompare results derived from non-parametric regressions withthose obtained using alternative non-linear threshold models.Both techniques support the hypothesis that prices are transmittedacross spatially separate EU pig markets and provide evidencefor asymmetric price adjustments. They also suggest the existenceof a range of price differentials where equilibrating priceadjustments are less intense. Non-parametric techniques oftensuggest a higher degree of price transmission than that impliedby threshold models.     

The Role of Farmer's Behavioral Attitudes and Heterogeneity in Futures Contracts Usage

The relationship between farmers' behavioral attitudes and use of futures contracts is examined, taking into account non-directly observable variables and the heterogeneity of farmers. The relationships are tested on a stratified data sample of 440 farmers. Cluster analysis and covariance structure equation models are used to validate the relationships. Farmers are found not to be homogenous regarding the factors influencing their use of futures. Heterogeneity at the segment level masked important effects at the aggregate level, notably risk attitude. Furthermore, several psychological constructs for farmers related to market orientation, risk exposure, market performance and entrepreneurial behavior play important roles in their use of futures contracts.     

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.     

Bubbles,Froth and Facts: Another Look at the Masters Hypothesis in Commodity Futures Markets

The Masters Hypothesis suggests that long‐only index funds were the main cause of a massive increase in commodity prices in 2007–2008 and 2011–2012. Central to the Masters Hypothesis are three basic tenets: (i) long‐only commodity index funds were directly responsible for driving futures prices higher; (ii) the deviations from fundamental value were economically very large; (iii) the impact was pervasive across commodity futures markets. There has been a great deal of empirical research on the Masters Hypothesis and commodity market bubbles. However, surprisingly few studies have found evidence that directly support the main tenets of the Masters Hypothesis. Some have attributed the lack of supporting evidence to the low‐power of time‐series tests, market efficiency issues and a lack of conditioning variables within models. In this paper, we address each of these issues using updated data and new empirical approaches. Still, price behaviour consistent with the Masters Hypothesis is surprisingly difficult to find in the data. This is an important finding given the on‐going policy debate and regulations proposed or being implemented to limit speculative positions in these markets.