The Dynamics of the U.S. Milk Supply: Implications for Changes in U.S. Dairy Policy

There is continuing pressure by various farm groups to attempt to solve the chronic problems in the U.S. dairy industry represented by increased milk price variability, inability to generate positive returns at the farm level, increasing role of dairy exports as an important market for U.S. dairy products, etc. As such it is important for analysts and policy makers obtain an estimate as to how responsive dairy producers are to changing economic and technological conditions. Examples of previous research used to examine supply response in the U.S. dairy sector include LaFrance and deGorter (1985), Chavas and Klemme (1986), Thraen and Hammond (1987), Chavas, Krauss and Jesse (1990), Chavas and Krauss (1990), Yavuz, et al, (1996) and USDA (2007). These analyses are limited in that either they are either fairly dated or they do not account the dynamics that are inherent in the dairy herd expansion/contraction process. The above overview of the dairy industry points to a changing industry as represented by reduced but larger dairy operations, the changing nature of U.S. dairy policy and pricing, production of new types of dairy products, etc. with much of the adjustments have occurred since the above previous analyses were undertaken and may no longer reflect the industries supply characteristics. The present study will incorporate data encompassing the 1975-2007 period and provide an update of the model original developed by Chavas and Klemme (1986). This study has three main objectives: (i) quantify the current supply structure of the U.S. dairy industry, (ii) gain insight into impacts of technological changes that have occurred over the last 25 years, (iii) based on (i) and (ii), generate forecasts of long-run milk supply response to price changes and possible future technological advancements.

Visualizing Risk Premiums in Commodity Futures Markets

Replaced with revised version of poster 07/21/10.Risk and Uncertainty,

Analyzing Relationships Between Cash and Futures Dairy Markets Using Partially Overlapping Time Series

Replaced with revised version of paper 02/10/10.partially overlapping time series, spectral analysis, risk premium, futures markets, dairy policy, dairy industry, Agribusiness, Agricultural and Food Policy, Agricultural Finance, Q13, Q14, Q18,

Pricing Options on Commodity Futures: The Role of Weather and Storage

Options on agricultural futures are popular financial instruments used for agricultural price risk management and to speculate on future price movements. Poor performance of Black’s classical option pricing model has stimulated many researchers to introduce pricing models that are more consistent with observed option premiums. However, most models are motivated solely from the standpoint of the time series properties of futures prices and need for improvements in forecasting and hedging performance. In this paper we propose a novel arbitrage pricing model motivated from the economic theory of optimal storage, and consistent with implications of plant physiology on the importance of weather stress. We introduce a pricing model for options on futures based on a Generalized Lambda Distribution (GLD) that allows greater flexibility in higher moments of the expected terminal distribution of futures price. We use times and sales data for corn futures and options for the period 1995-2009 to estimate the implied skewness parameter separately for each trading day. An economic explanation is then presented for inter-year variations in implied skewness based on the theory of storage. After controlling for changes in planned acreage, we find a statistically significant negative relationship between ending stocks-to-use and implied skewness, as predicted by the theory of storage. Furthermore, intra-year dynamics of implied skewness reflect the fact that resolution of uncertainty in corn supply is resolved between late June and middle of October, i.e. during corn growth phases that encompass corn silking through grain maturity. Impacts of storage and weather on the distribution of terminal futures price jointly explain upward sloping implied volatility curves.arbitrage pricing model, options on futures, generalized lambda distribution, theory of storage, skewness, Agribusiness, Agricultural Finance, Crop Production/Industries, Financial Economics, Research Methods/ Statistical Methods, Risk and Uncertainty, G13, Q11, Q14,

Association of Candidate Gene Polymorphisms With Chronic Kidney Disease: Results of a Case-Control Analysis in the Nefrona Cohort

Chronic kidney disease (CKD) is a major risk factor for end-stage renal disease, cardiovascular disease and premature death. Despite classical clinical risk factors for CKD and some genetic risk factors have been identified, the residual risk observed in prediction models is still high. Therefore, new risk factors need to be identified in order to better predict the risk of CKD in the population. Here, we analyzed the genetic association of 79 SNPs of proteins associated with mineral metabolism disturbances with CKD in a cohort that includes 2, 445 CKD cases and 559 controls. Genotyping was performed with matrix assisted laser desorption ionizationtime of flight mass spectrometry. We used logistic regression models considering different genetic inheritance models to assess the association of the SNPs with the prevalence of CKD, adjusting for known risk factors. Eight SNPs (rs1126616, rs35068180, rs2238135, rs1800247, rs385564, rs4236, rs2248359, and rs1564858) were associated with CKD even after adjusting by sex, age and race. A model containing five of these SNPs (rs1126616, rs35068180, rs1800247, rs4236, and rs2248359), diabetes and hypertension showed better performance than models considering only clinical risk factors, significantly increasing the area under the curve of the model without polymorphisms. Furthermore, one of the SNPs (the rs2248359) showed an interaction with hypertension, being the risk genotype affecting only hypertensive patients. We conclude that 5 SNPs related to proteins implicated in mineral metabolism disturbances (Osteopontin, osteocalcin, matrix gla protein, matrix metalloprotease 3 and 24 hydroxylase) are associated to an increased risk of suffering CKD

May Measurement Month 2018: a pragmatic global screening campaign to raise awareness of blood pressure by the International Society of Hypertension

Aims Raised blood pressure (BP) is the biggest contributor to mortality and disease burden worldwide and fewer than half of those with hypertension are aware of it. May Measurement Month (MMM) is a global campaign set up in 2017, to raise awareness of high BP and as a pragmatic solution to a lack of formal screening worldwide. The 2018 campaign was expanded, aiming to include more participants and countries. Methods and results Eighty-nine countries participated in MMM 2018. Volunteers (≥18 years) were recruited through opportunistic sampling at a variety of screening sites. Each participant had three BP measurements and completed a questionnaire on demographic, lifestyle, and environmental factors. Hypertension was defined as a systolic BP ≥140 mmHg or diastolic BP ≥90 mmHg, or taking antihypertensive medication. In total, 74.9% of screenees provided three BP readings. Multiple imputation using chained equations was used to impute missing readings. 1 504 963 individuals (mean age 45.3 years; 52.4% female) were screened. After multiple imputation, 502 079 (33.4%) individuals had hypertension, of whom 59.5% were aware of their diagnosis and 55.3% were taking antihypertensive medication. Of those on medication, 60.0% were controlled and of all hypertensives, 33.2% were controlled. We detected 224 285 individuals with untreated hypertension and 111 214 individuals with inadequately treated (systolic BP ≥ 140 mmHg or diastolic BP ≥ 90 mmHg) hypertension. Conclusion May Measurement Month expanded significantly compared with 2017, including more participants in more countries. The campaign identified over 335 000 adults with untreated or inadequately treated hypertension. In the absence of systematic screening programmes, MMM was effective at raising awareness at least among these individuals at risk

Three essays in commodity futures and options price performance

In the first essay I propose a novel pricing model for options on commodity futures motivated from the economic theory of optimal storage, and consistent with implications of plant physiology on the importance of weather stress. The model is based on a Generalized Lambda Distribution (GLD) that allows greater flexibility in higher moments of the expected terminal distribution of futures price. I find a statistically significant negative relationship between ending stocks-to-use and implied skewness, as predicted by the theory of storage. Intra-year dynamics of implied skewness reflect the fact that resolution of uncertainty in corn supply is resolved during the corn growth phase from corn silking through maturity. Impacts of storage and weather on the distribution of terminal futures prices jointly explain upward sloping implied volatility curves. In the second paper, a partially overlapping time series (POTS) model is estimated to examine price behavior in simultaneously traded Class III milk futures contracts. POTS is a latent factor model that measures price changes in futures as a linear combination of a common factor, i.e. information affecting all traded contracts, and an idiosyncratic term specific to each contract. The importance of a common factor in price volatility determination for dairy is related to capital production factors, i.e. the dairy herd. It is shown that Class III volatility decreases as contracts approach maturity. The importance of the common factor declines as one approaches maturity, implying that individual contract months are poor substitutes in hedging a specific month’s cash price risk. Thus, despite relatively low liquidity in the market, it is useful to have 12 contract delivery months per year. The third essay examines price discovery, volatility spillovers and the impacts of speculation in the dairy sector. I find that the flow of information in the mean prices is predominantly from futures to cash, while volatility spillovers are bidirectional. I propose an extension of the BEKK variance model that I refer to as GARCH-MEX. Utilizing the model to evaluate the impact of speculation I find strong evidence against the hypothesis that excessive speculation is increasing the conditional variance of futures prices

An econometric analysis of U.S. milk production: a herd dynamics model

We investigate the impacts of technological changes on supply structure of the US milk production. The econometric model used is based on aggregate annual U. S. data and is composed of three stochastic equations defining the size and herd structure of the U.S. dairy herd, average productivity and the heifer replacement rate and an identity equation defining total U.S. milk production as the product of herd size and average productivity. As our main contribution to existing literature, we have found a way to use bootstrap to test hypotheses regarding long-run price-responsiveness of supply, and we have found that 10-year elasticity of milk supply to milk price has decreased and that change in elasticity is statistically significant. We simulate the effects of different price scenarios on long-run U.S. milk supply. One finding is that using large quantities of feed stocks for bio-fuel production could affect significantly affect price of milk. We use the above results to indicate the consequences of changes in dairy policy in EU to local development. As EU abandons production quotas in milk production, we can expect strong consolidation and regional shifts in production. This can potentially have strong adverse impacts on local development in rural areas where small farms dominate

Pricing Options on Commodity Futures: The Role of Weather and Storage

Options on agricultural futures are popular financial instruments used for agricultural price risk management and to speculate on future price movements. Poor performance of Black’s classical option pricing model has stimulated many researchers to introduce pricing models that are more consistent with observed option premiums. However, most models are motivated solely from the standpoint of the time series properties of futures prices and need for improvements in forecasting and hedging performance. In this paper I propose a novel arbitrage pricing model motivated from the economic theory of optimal storage and consistent with implications of plant physiology on the importance of weather stress. I introduce a pricing model for options on futures based on a generalized lambda distribution (GLD) that allows greater flexibility in higher moments of the expected terminal distribution of futures price. I use times and sales data for corn futures and options for the period 1995-2009 to estimate the implied skewness parameter separately for each trading day. An economic explanation is then presented for inter-year variations in implied skewness based on the theory of storage. After controlling for changes in planned acreage, I find a statistically significant negative relationship between ending stocks-to-use and implied skewness, as predicted by the theory of storage. Furthermore, intra-year dynamics of implied skewness reflect the fact that uncertainty in corn supply is resolved between late June and early October, i.e., during corn growth phases that encompass corn silking and grain maturity. Impacts of storage and weather on the distribution of terminal futures price jointly explain upward-sloping implied volatility curves.arbitrage pricing model, options on futures, generalized lambda distribution, theory of storage, skewness