Impacts of Weather and Time Horizon Selection on Crop Insurance Ratemaking: A Conditional Distribution Approach

An important issue in the agricultural actuarial literature is the extent to which sample period selection affects the accuracy of insurance rating. A conditional Weibull distribution approach is developed which explicitly models the interaction of weather, technology, and other variables on probabilistic yield outcomes to address this issue. Results from an application with an extensive producer-level yield dataset representing commercial-scale Illinois firms suggest that the impact of weather heterogeneity on risk estimation across reasonable samples is likely not as great as is often claimed. The results also suggest that yield risk is decreasing significantly through time, and indicate the presence of trend acceleration. A rating analysis indicates that violations in the risk evolution assumptions of the rating approaches used in the Federal Crop Insurance Program—which implicitly assume increasing yield risk through time when yields trend—result in severely biased rates, with typical overstatements of 200% to 400% for Midwest corn.Conditional Weibull Distribution, Conditional Production Function, Catastrophic Risk Modeling, Sample Selection, Yield Risk, Crop Insurance, Ratemaking, Crop Production/Industries, Risk and Uncertainty,

Spatial Aggregation and Weather Risk Management

Previous studies identify limited potential efficacy of weather derivatives in hedging agricultural exposures. In contrast to earlier studies which investigate the problem at low levels of aggregation, we find using straight forward temperature contracts that better weather hedging opportunities exist at higher levels of spatial aggregation. Aggregating production exposures reduces idiosyncratic (i.e. localized or region specific) risk, leaving a greater proportion of the total risk in the form of systemic weather risk which can be effectively hedged using weather derivatives. The aggregation effect suggests that the potential for weather derivatives in agriculture may be greater than previously thought, particularly for aggregators of risk such as re/insurers.weather derivatives, spatial aggregation, corn, yield risk, crop insurance, hedging, Risk and Uncertainty,

A high-speed digital signal processor for atmospheric radar, part 7.3A

The Model SP-320 device is a monolithic realization of a complex general purpose signal processor, incorporating such features as a 32-bit ALU, a 16-bit x 16-bit combinatorial multiplier, and a 16-bit barrel shifter. The SP-320 is designed to operate as a slave processor to a host general purpose computer in applications such as coherent integration of a radar return signal in multiple ranges, or dedicated FFT processing. Presently available is an I/O module conforming to the Intel Multichannel interface standard; other I/O modules will be designed to meet specific user requirements. The main processor board includes input and output FIFO (First In First Out) memories, both with depths of 4096 W, to permit asynchronous operation between the source of data and the host computer. This design permits burst data rates in excess of 5 MW/s

The accuracy of dynamic attitude propagation

Propagating attitude by integrating Euler's equation for rigid body motion has long been suggested for the Earth Radiation Budget Satellite (ERBS) but until now has not been implemented. Because of limited Sun visibility, propagation is necessary for yaw determination. With the deterioration of the gyros, dynamic propagation has become more attractive. Angular rates are derived from integrating Euler's equation with a stepsize of 1 second, using torques computed from telemetered control system data. The environmental torque model was quite basic. It included gravity gradient and unshadowed aerodynamic torques. Knowledge of control torques is critical to the accuracy of dynamic modeling. Due to their coarseness and sparsity, control actuator telemetry were smoothed before integration. The dynamic model was incorporated into existing ERBS attitude determination software. Modeled rates were then used for attitude propagation in the standard ERBS fine-attitude algorithm. In spite of the simplicity of the approach, the dynamically propagated attitude matched the attitude propagated with good gyros well for roll and yaw but diverged up to 3 degrees for pitch because of the very low resolution in pitch momentum wheel telemetry. When control anomalies significantly perturb the nominal attitude, the effect of telemetry granularity is reduced and the dynamically propagated attitudes are accurate on all three axes

One Loop Corrected Mode Functions for SQED during Inflation

We solve the one loop effective scalar field equations for spatial plane waves in massless, minimally coupled scalar quantum electrodynamics on a locally de Sitter background. The computation is done in two different gauges: a non-de Sitter invariant analogue of Feynman gauge, and in the de Sitter invariant, Lorentz gauge. In each case our result is that the finite part of the conformal counterterm can be chosen so that the mode functions experience no significant one loop corrections at late times. This is in perfect agreement with a recent, all orders stochastic prediction.Comment: 26 pages, uses LaTeX 2 epsilon, no figures, version 2 has an updated reference lis

The Effect of Features on the Functional Form of the Scalar Power Spectrum

We study how the scalar power spectrum of single-scalar inflation depends functionally on models with features which have been proposed to explain anomalies in the data. We exploit a new formalism based on evolving the norm-squared of the scalar mode functions, rather than the mode functions themselves.Comment: 27 pages, 14 figures, uses LaTeX2e; version 2 contains an expanded section 4 which explains how to compute the phase of the mode function so that the propagator and non-Gaussianity can be derive

Graviton Loop Corrections to Vacuum Polarization in de Sitter in a General Covariant Gauge

We evaluate the one-graviton loop contribution to the vacuum polarization on de Sitter background in a 1-parameter family of exact, de Sitter invariant gauges. Our result is computed using dimensional regularization and fully renormalized with BPHZ counterterms, which must include a noninvariant owing to the time-ordered interactions. Because the graviton propagator engenders a physical breaking of de Sitter invariance two structure functions are needed to express the result. In addition to its relevance for the gauge issue this is the first time a covariant gauge graviton propagator has been used to compute a noncoincident loop. A number of identities are derived which should facilitate further graviton loop computations.Comment: 61 pages, 1 figure, 11 tables, version 2 (63 pages) revised for publication in CQ

Evaluating Yield Models for Crop Insurance Rating

Generated crop insurance rates depend critically on the distributional assumptions of the underlying crop yield loss model. Using farm level corn yield data from 1972-2008, we revisit the problem of examining in-sample goodness-of-fit measures across a set of flexible parametric, semi-parametric, and non-parametric distributions. Simulations are also conducted to investigate the out-of-sample efficiency properties of several competing distributions. The results indicate that more parameterized distributional forms fit the data better in-sample due to the fact that they have more parameters, but are generally less efficient out-of-sample–and in some cases more biased–than more parsimonious forms which also fit the data adequately, such as the Weibull. The results highlight the relative advantages of alternative distributions in terms of the bias-efficiency tradeoff in both in- and out-of-sample frameworks.Yield distributions, Crop Insurance, Weibull Distribution, Beta Distribution, Mixture Distribution, Out-of-Sample Efficiency, Goodness-of-Fit, Insurance Rating Efficiency, Farm Management, Financial Economics, Land Economics/Use,