The Effect of the El Nino Southern Oscillation on U.S. Corn Production and Downside Risk

El Nino Southern Oscillation (ENSO) teleconnections imply anomalous weather conditions around the globe, causing yield shortages, price changes, and even civil unrests. Extreme ENSO events may cause catastrophic damages to crop yields, thus amplifying downside risk for producers. This study presents a framework for quantifying the effects of climate on crop yield distributions. An empirical application provides estimates of the effect that ENSO events have on the means of U.S. county-level corn yield distributions, as well as the probabilities of catastrophic crop loss. Our findings demonstrate that ENSO events strongly influence these probabilities systematically over large production regions, which has important implications for research and policy analysis in the production, risk management, climate change, and civil unrest literatures.Climate, El Nino Southern Oscillation, Maximum Entropy, Risk Management, Yield Distribution, Crop Production/Industries, Environmental Economics and Policy, Production Economics,

Agricultural Arbitrage, Adjustment Costs, and the Intensive Margin

Farmland and capital are an important and rapidly expanding component of the agricultural economy, and empirical evidence suggests that these assets are quasi-fixed in that adjustment costs are incurred when holdings are altered. Increased interest in the rate of return for investing in farmland suggests that an important consideration is the effect of adjustment costs on this return. A novel theoretical model is developed that ties together contributions from the farmland pricing and adjustment cost literatures, and the first order conditions for a utility maximizing decision maker are rearranged into intertemporal arbitrage equations that are similar in spirit to traditional finance models. The common assumptions that land and capital are quasi-fixed assets, and that production is characterized by constant returns to scale are tested and the evidence supports these assumptions. An empirical application of the arbitrage equations provides evidence that risk aversion and adjustment costs are jointly significant components of agricultural production, and that adjustment costs generate significant changes in the rate of return to farmland. The results have important policy implications as sluggish supply response due to quasi-fixity can lead to dramatically inflated commodity prices, and an accurate measure of the farmland return can help determine how far the extensive margin will expand or contract in response to a variety of policy scenarios, such as the subsidization of corn for ethanol, an increase in the variety of subsidized crop insurance products, or the introduction of new revenue support programs such as ACRE.Arbitrage, Adjustment Costs, Farmland, Asset Pricing, Capital, Cost Function, Risk, Production, Agricultural Finance, Consumer/Household Economics, Crop Production/Industries, Farm Management, Financial Economics, Land Economics/Use, Production Economics, Risk and Uncertainty,

A Mixed Effects Model of Crop Yields for Purposes of Premium Determination

Farm income is highly variable due to annual price and yield uncertainties. The federally subsidized crop insurance program is an important tool for managing this risk, and has grown from a relatively modest program to one that encompasses the majority of productive cropland in the country. The success of this program depends on identification of actuarially fair insurance premium rates, which in turn depends on accurate estimation of farm-level yield distributions. We use the confidential U.S. Department of Agriculture Risk Management Agency (RMA) panel dataset to estimate farm-specific distributions of yields and actually fair crop insurance premiums. Our ongoing work includes using the difference between our estimated actually fair premiums and RMA's to predict which insurance contracts farmers select. Ultimately, we will predict potential efficiency gains from using our empirical model for premium determination.Yield, Crop Insurance, Policy, Mixed Model, Agricultural and Food Policy,

A hyperparasite affects the population dynamics of a wild plant pathogen

Peer reviewe

Perturbative Expansion around the Gaussian Effective Potential of the Fermion Field Theory

We have extended the perturbative expansion method around the Gaussian effective action to the fermionic field theory, by taking the 2-dimensional Gross-Neveu model as an example. We have computed both the zero temperature and the finite temperature effective potentials of the Gross-Neveu model up to the first perturbative correction terms, and have found that the critical temperature, at which dynamically broken symmetry is restored, is significantly improved for small value of the flavour number.Comment: 14pages, no figures, other comments Typographical errors are corrected and new references are adde

HYTHIRM Radiance Modeling and Image Analyses in Support of STS-119, STS-125 and STS-128 Space Shuttle Hypersonic Re-entries

We provide the first geometrically accurate (i.e., 3-D) temperature maps of the entire windward surface of the Space Shuttle during hypersonic reentry. To accomplish this task we began with estimated surface temperatures derived from CFD models at integral high Mach numbers and used them, the Shuttle's surface properties and reasonable estimates of the sensor-to-target geometry to predict the emitted spectral radiance from the surface (in units of W sr-1 m-2 nm-1). These data were converted to sensor counts using properties of the sensor (e.g. aperture, spectral band, and various efficiencies), the expected background, and the atmosphere transmission to inform the optimal settings for the near-infrared and midwave IR cameras on the Cast Glance aircraft. Once these data were collected, calibrated, edited, registered and co-added we formed both 2-D maps of the scene in the above units and 3-D maps of the bottom surface in temperature that could be compared with not only the initial inputs but also thermocouple data from the Shuttle itself. The 3-D temperature mapping process was based on the initial radiance modeling process. Here temperatures were guessed for each node in a well-resolved 3-D framework, a radiance model was produced and compared to the processed imagery, and corrections to the temperature were estimated until the iterative process converged. This process did very well in characterizing the temperature structure of the large asymmetric boundary layer transition the covered much of the starboard bottom surface of STS-119 Discovery. Both internally estimated accuracies and differences with CFD models and thermocouple measurements are at most a few percent. The technique did less well characterizing the temperature structure of the turbulent wedge behind the trip due to limitations in understanding the true sensor resolution. (Note: Those less inclined to read the entire paper are encouraged to read an Executive Summary provided at the end.