Supply-Driven Input-Output Multipliers

The paper raises and discusses issues related to the derivation, behaviour and characteristics of input-output multipliers where the exogenous changes are not assumed in elements of final demand but in total outputs of sectors and commodities. These multipliers are more appropriate for use in impact analysis of policies which influence farm outputs, than the traditional final demand multipliers. The paper estimates also such “supply-driven” multipliers for 16 farm commodities of US agriculture. The empirical analysis shows that despite the variability in the multipliers' values, two rather solid groups of commodities which feel the strongest impacts of different crop and livestock output changes respectively, can be found. Several commodities are common to both groups, verifying also the significance of some indirect linkages between farm and non-farm commodities. However, the final demand sectors absorb the largest part of the initial exogenous change itself.     

A hybrid commodity price‐forecasting model applied to the sugar–alcohol sector

Accurate price forecasting for agricultural commodities can have significant decision‐making implications for suppliers, especially those of biofuels, where the agriculture and energy sectors intersect. Environmental pressures and high oil prices affect demand for biofuels and have reignited the discussion about effects on food prices. Suppliers in the sugar–alcohol sector need to decide the ideal proportion of ethanol and sugar to optimise their financial strategy. Prices can be affected by exogenous factors, such as exchange rates and interest rates, as well as non‐observable variables like the convenience yield, which is related to supply shortages. The literature generally uses two approaches: artificial neural networks (ANNs), which are recognised as being in the forefront of exogenous‐variable analysis, and stochastic models such as the Kalman filter, which is able to account for non‐observable variables. This article proposes a hybrid model for forecasting the prices of agricultural commodities that is built upon both approaches and is applied to forecast the price of sugar. The Kalman filter considers the structure of the stochastic process that describes the evolution of prices. Neural networks allow variables that can impact asset prices in an indirect, nonlinear way, what cannot be incorporated easily into traditional econometric models.     

A Family of Differential Input Demand Systems with Application to Greek Agriculture

This paper develops a family of input demand systems via alternative parametrisations of Theil's differential model. Each member of this family is as flexible as any other locally flexible functional form. More importantly, selection among the competing family members is possible via simple parameter restrictions. The family of differential input demand systems is applied to the agricultural sector in Greece for the period 1961–96. Formal tests suggest that the model with the CBS-type effects dominates the alternative models. Divisia and price elasticities are calculated from the selected model and a decomposition of changes in the demand for inputs into technical change, total input volume, substitution, and residual effects is performed. The empirical results are quite reasonable. Overall, the analysis in this paper indicates that, in certain cases, the differential approach may provide an attractive alternative to the dual approach in modelling production behaviour.     

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.     

Consumption of Economic Information in Agriculture

We develop a model of decision makers' demand for agricultural economic information services. This model treats choice of external decision-support services as a function of actors' assessment of how alternative investments in information complement their internal competencies. Data from a survey in four commodity systems are used to evaluate hypotheses as to how human capital, and functional role of actors in commodity systems affect demand for variously formatted information. By focusing on three axes of heterogeneity—diversity among decision makers, information service providers, and information—we are able to identify key structural and functional relationships in agricultural economic information systems.     

Elegy,ode or panegyric? Practising agricultural economics in Australia, 1975–99

Changes are investigated in the Australian agricultural economics profession, 1975–99, using a conventional microeconomics framework of supply and demand for agricultural economists. Aggregate exogenous factors such as changes in the agricultural and tertiary education sectors, and changes in beliefs about the proper role of government, have changed both supply and demand conditions for agricultural economists. The profession has responded by shifting its focus away from narrowly agricultural policy, especially marketing policy, towards areas of market failure such as environmental and natural resource issues.     

A roller coaster ride: an empirical investigation of the main drivers of the international wheat price

Over the last decade, commodity prices have registered substantial booms and busts marked by extreme volatility. Wheat in particular, one of the main nonoil commodities, has registered a roller coaster in price levels which seems to be inconsistent with supply and demand fundamentals. To acutely investigate the drivers of wheat prices and quantify their impact, a vector error correction model (VECM) has been used. The exogenous variables have been distinguished into four groups: market‐specific factors, broad macroeconomic determinants, speculative components, and weather variables. The quadriangulation of the determinants will enable us to better understand the movements in wheat price and identify the specific role of each component. The results show that a mix of factors are contributing to wheat price movements, including speculation, global demand, and real effective exchange rate.     

A CROSS-COMMODITY APPRAISAL OF DEMAND-RAISING RESEARCH BENEFITS: PORK AND CHICKEN IN AUSTRALIA

A multi-commodity model is developed for evaluating the gains from research which raises the demand for a commodity, and applied to the pig and chicken industries in Australia. The major finding is that the gain to pork producers is larger, and the gain to consumers smaller, with a cross-commodity consideration than without. Bigger differences in results are observed with larger values of the cross-price elasticity between pork and chicken, and with a larger shift in demand for chicken. However, the aggregate benefits to the Australian pig industry are not significantly affected by price changes in the market for chicken. The implication of the analysis is that, by ignoring the cross-market feedback between commodities closely related in consumption, consumers (or taxpayers) of the commodity experiencing a rise in demand may bear a higher-than-optimal outlay on public research directed to increasing the demand for that commodity.     

Quantifying the structure of food demand in China: An econometric approach

This article examines food demand structure and its dynamics for 11 commodities in urban China. The analysis is based on household‐level expenditure survey data for two cross‐sectional surveys of Chinese households pertaining to food expenditure patterns during 1995 and 2003. Pre‐committed components of commodity demands, that are insensitive to economic variables, are explored. We use the generalized quadratic almost ideal demand system (GQAIDS) for its empirical superiority to the generalized almost ideal demand system (GAIDS), and estimate the associated parameters via full information maximum likelihood procedure (FIML) accounting for endogeneity of total expenditures on food for home consumption (FAH). We also use quality‐adjusted commodity unit values to control for quality differences resulting from commodity aggregation and food choice. Furthermore, we derive GQAIDS elasticity formulas, and estimate income elasticities without restrictions. The results partially support the hypothesis that an average Chinese household has incorporated elements of Western diet (fine grains) into traditional Chinese food diet over time. Moreover, the outcome of a simple test developed here points to possible preference changes for a majority of food staples under study.     

An Empirical Comparison of "Frisch" and "Time Series" Demand price Elasticities for individual Commodities

In a classical article in 1959, Ragnar Frisch [8] developed a procedure, which, under the assumption of want independence¹ and given commodity budget shares, income elasticities, and one own-price elasticity, allows one to calculate a complete matrix of own and cross price elasticities. Between broad commodity groups such an assumption (want independence) has becme increasingly accepted and in fact under the label of separability has formed the basis for a family of demand models that are increasingly used to estimate demand elasticities for broad commodity groups (the linear expenditure system, the Rotterdam model, etc.). At the individual commodity level however, the assumption of want independence seems less viable, e.g., the utility one derives from pork is in general not considered independent from one's consumption of beef. However, it has become increasingly common (and apparently acceptable) to find the Frisch methodology utilized to develop demand price elasticity estimates for individual agricultural commodities [4, 7, 17].     

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.     

Effect of information formats on information services: analysis of four selected agricultural commodities in the USA

We analyze sources of information in agricultural markets to understand patterns of demand for decision support services and the division of labor in the supply of these services. Information formatting—qualitative variation that determines accessibility and relevance of information in specific contexts—prohibits universal access to informational content. Information formats give rise to both transaction costs and complementarities reflected in patterns of information exchange in commodity systems. Controlling for actors' structural roles and levels of education, we develop a hedonic model of information demand such that actors seek information that is formatted to meet their needs and capabilities. Employing survey data, we explain elements of observed patterns of information exchange in four commodity systems in the USA. Results point to opportunities to expand our understanding of socioeconomic processes underlying production and consumption of decision support.     

‘Deal’ or ‘No Deal’? Impacts of Alternative Post‐Brexit Trade Agreements on UK Agriculture

Brexit will have important implications for UK agricultural commodity markets due to potentially significant changes to trade flows. We quantify the sectoral impacts on UK agriculture of three illustrative scenarios, which capture a broad range of potential trade arrangements: Bespoke Free Trade Deal , WTO Default and Unilateral Trade Liberalisation . It is estimated that the projected market impacts are relatively small if the UK negotiates a Bespoke Free Trade Agreement with the EU. The projected impacts are much greater under the two other scenarios, which capture potential trade arrangements if ‘no deal’ is reached. The high tariffs imposed under the WTO default scenario lead to significant adjustments in trade between the UK and EU‐27, with the impact on the domestic UK market depending on whether the UK is a net importer or a net exporter of the relevant commodity. All sectors experience price and production declines under the trade liberalisation scenario in which the UK unilaterally sets tariffs on imports from both the EU‐27 and the rest of the world to zero; the impacts are particularly severe in the beef and sheep sectors where international competition is very strong.     

Agricultural Trade Liberalization in a Multi-sector World Model

Impacts of agricultural and nonagricultural trade liberalization on agriculture are assessed in a multi-commodity, multi-country framework. By modeling simultaneously all goods sectors of the economy, we evaluate the importance of: (a) relative price changes between sectors, and (b) income and exchange-rate adjustments that follow trade liberalization in a world of floating rates. Specifically, we compare two cases using a static world policy simulation (SWOPSIM) model: agricultural multilateral liberalization and complete multilateral liberalization with floating exchange rates for all countries/regions. In both cases agricultural commodity prices tend to increase, an effect which is more pronounced when currency values adjust. The developing countries, in particular Argentina, Brazil and Mexico, have the most significant advances in agricultural and total production when exchange rates vary. Moreover, the gains from international trade are extended to all countries/regions explicitly specified in the model.     

An Analysis of Public Agricultural Research in the Canadian Prairie Provinces

This study has developed a four-equation model of agricultural research in Canada using some aspects of special interest theory, institutional theory and economic variables. The demand, supply and allocation equations were developed with special reference to the Canadian agricultural research sector and the more restrictive prairie agricultural research sector. The conceptual model developed is designed to explain the allocation of public expenditures on commodity specific applied research. The reduced-form equation of the model was estimated for 6 commodity classes (2 crops, 4 livestock groups) to test the applicability of the model over the commodity groups.
The evaluation of the reduced-form equation model and the implications that derive from it give an interesting view of the Canadian research sector. Some variables did perform as a priori expected with relative consistency and certain equations performed very well. These results lead to some implications for the Canadian agricultural research sector.
The general performance of the reduced-form equation and its ability to explain the total variation of expenditures on commodity specific agricultural research gives limited support to the model developed. Nevertheless the results tend to indicate that agricultural research is responsive to economic and institutional variables.     

Convenience yield and the theory of storage: applying an option‐based approach

We propose that an options‐based approach is a superior alternative to the traditional cost‐of‐carry method to model both the behaviour of convenience yields and the commodity price responses to changes in inventory levels. This approach is shown to be more robust and avoids the simplifying assumptions embedded in cost‐of‐carry valuation which fully accounts for the non‐negativity constraint on inventory. Unlike the cost‐of‐carry approach, the options‐based approach does not treat the convenience yield as an exogenous factor. This offers a more natural measure of implied convenience yields in commodity trading strategies. We test the relationship between convenience yields and inventory levels for a number of liquidly traded base metals using both methods. Our results show that the relationship between convenience yields and inventory levels is strongly defined under the options‐based approach in line with market beliefs. This result is consistent with other studies that have used the options‐based approach in other nonmetals commodity markets.     

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.     

The Use of Conditional Cost Functions to Generate Estimable Mixed Demand Systems

Mixed demand systems have been virtually ignored in empirical work solely because derivation of these systems requires closed forms for both direct and indirect utility functions. This article proposes the alternative of using a conditional cost function to generate empirical mixed demand models. This approach allows the estimation of mixed demand systems, which are explicit in an unobservable variable (utility), but may lack a closed form representation in terms of observable variables such as prices, quantities and expenditure. Results indicate that this approach is operationally feasible, which opens up a wider range of mixed demand specifications in static analyses.     

A Marketing Approach to Commodity Futures Exchanges: A Case Study of the Dutch Hog Industry

This paper proposes a marketing strategic approach to commodity futures exchanges to optimise the (hedging) services offered. First, the environment of commodity futures exchanges is examined. Second, the threats and opportunities of commodity futures exchanges are analysed. Our analysis demonstrates that market orientation is an important element in the market strategies of commodity futures exchanges. Our market strategic framework is applied to the Dutch hog futures market. It is concluded that market penetration is an appropriate strategy. Consequently, to identify the variables that distinguish between farmers who initiate futures positions and farmers who do not, we conducted a discriminant analysis on data gathered from 418 Dutch hog farmers. The discriminant analysis shows that latent variables, such as farmers' perceived performance, farmers' reference price and farmers' market orientation, are important discriminating variables. Furthermore, farmers' cash market behaviour (in terms of the frequency of selling in the spot market) is an important discriminating variable as well. The usefulness of these results as input for a penetration policy is demonstrated.