The Fundamentals of Commodity Futures Returns

Commodity futures risk premiums vary across commodities and over time depending on the level of physical inventories, as predicted by the Theory of Storage. Using a comprehensive dataset on 31 commodity futures and physical inventories between 1969 and 2006, we show that the convenience yield is a decreasing, non-linear relationship of inventories. Price measures, such as the futures basis, prior futures returns, and spot returns reflect the state of inventories and are informative about commodity futures risk premiums. The excess returns to Spot and Futures Momentum and Backwardation strategies stem in part from the selection of commodities when inventories are low. Positions of futures markets participants are correlated with prices and inventory signals, but we reject the Keynesian "hedging pressure" hypothesis that these positions are an important determinant of risk premiums.

Consequences of EU Biofuel Policies on Agricultural Production and Land Use

Resource /Energy Economics and Policy, D58, Q13, Q24, Q27, Q28,

Sparsity-Cognizant Total Least-Squares for Perturbed Compressive Sampling

Solving linear regression problems based on the total least-squares (TLS) criterion has well-documented merits in various applications, where perturbations appear both in the data vector as well as in the regression matrix. However, existing TLS approaches do not account for sparsity possibly present in the unknown vector of regression coefficients. On the other hand, sparsity is the key attribute exploited by modern compressive sampling and variable selection approaches to linear regression, which include noise in the data, but do not account for perturbations in the regression matrix. The present paper fills this gap by formulating and solving TLS optimization problems under sparsity constraints. Near-optimum and reduced-complexity suboptimum sparse (S-) TLS algorithms are developed to address the perturbed compressive sampling (and the related dictionary learning) challenge, when there is a mismatch between the true and adopted bases over which the unknown vector is sparse. The novel S-TLS schemes also allow for perturbations in the regression matrix of the least-absolute selection and shrinkage selection operator (Lasso), and endow TLS approaches with ability to cope with sparse, under-determined "errors-in-variables" models. Interesting generalizations can further exploit prior knowledge on the perturbations to obtain novel weighted and structured S-TLS solvers. Analysis and simulations demonstrate the practical impact of S-TLS in calibrating the mismatch effects of contemporary grid-based approaches to cognitive radio sensing, and robust direction-of-arrival estimation using antenna arrays.Comment: 30 pages, 10 figures, submitted to IEEE Transactions on Signal Processin

A Land Market Cycle in the Netherlands

This paper develops a disequilibrium model of land prices in the Netherlands. It shows that the behaviour of traded quantities and prices of Dutch land have some resemblance with a disequilibrium land market model developed by Søgaard. An error correction model based on Søgaard’s model generates significant results with GDP and the real interest rate as explanatory variables, but regrettably farm income nor government demand for land generate significant results. If the model is correct, bubbles are characteristic for the Dutch land market, and this suggests that there is an opportunity for Dutch government to improve on the timing of buying land for nature policy.land market cycle, land prices, nature policy, Land Economics/Use,

Impact of EU Biofuel Policies on World Agricultural and Food Markets

This paper assesses the global and sectoral implications of the EU biofuels directive in a multi-region computable general equilibrium framework. Our results show that without mandatory blending or subsidies to stimulate the use of biofuel crops in the petroleum sector the targets of the EU Biofuel directive will not the reached in 2010. With mandatory blending the enhanced demand for biofuel crops has a strong impact on agriculture at the global and European level. The additional demand from the energy sector might slow down or reverse the long term process of declining agricultural prices.Biofuels, EU biofuel directive, agricultural markets, Computable General Equilibrium modeling, Agribusiness, International Relations/Trade, Research and Development/Tech Change/Emerging Technologies, Resource /Energy Economics and Policy,

Modelling the Consequences of Increasing Bioenergy Demand on Land and Feed Use

Bioenergy Production, CGE modeling, Land Demand, Feed Demand, Agricultural and Food Policy, Farm Management, Land Economics/Use,

Agricultural Incomes Development in EU till 2030: Scenario Analysis of Main Driving Factors

Europe’s rural areas are expected to witness rapid changes due to developments in demography, (agricultural) policies, global trade, climate change, technology and enlargement of the European Union. These changes will affect farmers’ production and income level and make the final outcome of this process uncertain. This paper tries to assess this uncertainty by analyzing the results of 34 scenarios of the EURURALIS project. The scenario outcomes were used to investigate agricultural income development and to analyze the impact of different combinations of macroeconomic and policy factors on agricultural income. The results of these scenarios were achieved in a modeling framework consisting of a modified version of the Global Trade Analysis Project model (GTAP) and the more ecological-environmental oriented Integrated Model to Assess the Global Environment (IMAGE).Agricultural incomes and production, agricultural policy, long-term scenarios,

Modified Mediterranean Diet for Enrichment of Short Chain Fatty Acids: Potential Adjunctive Therapeutic to Target Immune and Metabolic Dysfunction in Schizophrenia?

Growing interest in gut and digestive processes and their potential link to brain and peripheral based inflammation or biobehavioral phenotypes has led to an increasing number of basic and translational scientific reports focused on the role of gut microbiota within the context of neuropsychiatric disorders. However, the effect of dietary modification on specific gut metabolites, in association with immune, metabolic, and psychopathological functioning in schizophrenia spectrum disorders has not been well characterized. The short chain fatty acids (SCFA) acetate, butyrate, and propionate, major metabolites derived from fermentation of dietary fibers by gut microbes, interact with multiple immune and metabolic pathways. The specific pathways that SCFA are thought to target, are dysregulated in cardiovascular disease, type II diabetes, and systemic inflammation. Most notably, these disorders are consistently linked to an attenuated lifespan in schizophrenia. Although, unhealthy dietary intake patterns and increased prevalence of immune and metabolic dysfunction has been observed in people with schizophrenia; dietary interventions have not been well utilized to target immune or metabolic illness. Prior schizophrenia patient trials primarily focused on the effects of gluten free diets. Findings from these studies indicate that a diet avoiding gluten benefits a limited subset of patients, individuals with celiac disease or non-celiac gluten sensitivity. Therefore, alternative dietary and nutritional modifications such as high-fiber, Mediterranean style, diets that enrich the production of SCFA, while being associated with a minimal likelihood of adverse events, may improve immune and cardiovascular outcomes linked to premature mortality in schizophrenia. With a growing literature demonstrating that SCFA can cross the blood brain barrier and target key inflammatory and metabolic pathways, this article highlights enriching dietary intake for SCFA as a potential adjunctive therapy for people with schizophrenia

Impact of the EU Biofuels Directive on the EU food supply chain

The paper investigates the impact of the EU Biofuels Directive (BFD) on the EU agri-food supply chain using the computable general equilibrium model of the world economy named LEITAP. LEITAP is an extended version of the Global Trade Analysis Project (GTAP) model including an improved land market modeling, substitution possibilities between capital and energy as well as between different energy sources including biofuels, feed byproducts of the biofuel production process and substitution between different feed components and feed byproducts. The simulation results shows that the implementation of the EU BFD has a pronounced impact on the markets of cereals, oilseeds and sugar and shows only a limited impact on production and consumption of other agrifood commodities which are not directly affected by biofuel production. The harvested area and production of biofuel crops (grains, oilseeds) is expected to increase by 17% and 25% respectively and sugar production by 12% as a direct result the BFD. The EU-imports of these commodities are expected to rise more than twice. The increasing demand for biofuel crops and sugar will lift domestic prices of these commodities by 25% and 19% respectively but overall agri-food price inflation will be limited to 3% in the EU and to less than 1% at world market level.EU Biofuels Directive, food supply chain, indirect land use changes, computable general equilibrium model., Agricultural and Food Policy,

Mobiliteitsbeleid als klimaatbeleid of watermanagement; zelforganisatie als aangrijpingspunt voor effectieve beleidsmatige interventies

info:eu-repo/semantics/publishe