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,

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,

Actuarial Impacts of Loss Cost Ratio Ratemaking in U.S. Crop Insurance Programs

This study examines the actuarial implications of the loss cost ratio (LCR) ratemaking methodology employed by the Risk Management Agency as a component of base rates for U.S. crop insurance programs, and identifies specific conditions required for the LCR methodology to result in unbiased rates when liabilities trend. Specifically, constant relative yield risk resulting in growing absolute variance through time and other restrictive requirements are required for the LCR to result in unbiased rates. These requirements are tested against a large farm-level data set for Illinois corn. Our findings indicate that the conditions required for appropriate use of the LCR methodology are violated for this high premium volume market, resulting in large implied rate biases. The process does not correct itself through time with the addition of longer rating periods as sometimes claimed. A simple correction function is suggested and demonstrated.actuarially fair, crop insurance, insurance rating, loss cost ratio, risk growth, Risk Management Agency, yield trends, Crop Production/Industries, Risk and Uncertainty,

Portfolio Diversification with Commodity Futures: Properties of Levered Futures

This study extends previous work on the impact of commodity futures on portfolio performance by explicitly incorporating levered futures into the portfolio optimization problem. Using data on nine individual commodity futures and one aggregate index from 1994-2003, we find that collateralized and levered futures strategies perform similarly in an ex-post context. Significant differences between the approaches emerge however when constraints on investment behavior exist. Further, levered futures do not result in a prohibitive number of margin calls. The investment performances of the collateralized and the levered strategies vary little across different rebalancing intervals, and frequent portfolio rebalancing does not necessarily result in superior performance.Marketing,

The Causality of Foreign Direct Investment and Its Effects on Economic Growth: Re-estimated by a Directed Graph Approach

This paper uses the directed acyclic graph approach to analyze the causal patterns among foreign direct investment and other economic, social, and political variables, including GDP per capita as a proxy for economic growth. We find that economic growth causes FDI inflows for developing countries, while FDI induces economic growth for developed countries. Also, stock market is found to be an intermediary that amplifies the influence on FDI from many causal variables of FDI.FDI, economic growth, DAG, Financial Economics,

Effect of Agricultural Activity on River Water Quality: A Case Study for the Lower Colorado River Basin

This case study investigates the effect of a change in cropping pattern involving expanded acres of crops for biofuel feedstock, on the discharge of nutrients to rivers. Annual data from 1968-2008 on stream flow, cropped acres, and precipitation for Wharton County, Texas are used. A positive impact of increased corn acreage over this period on river discharge is identified.Biofuels, Stream Flow, Discharge, Production Economics, Resource /Energy Economics and Policy,

Seawater Desalination for Municipal Water Production

This paper examines the optimal allocation of several inputs in the context of seawater desalination by reverse osmosis (RO) as a source of municipal (or commercial or industrial) water. A cost-minimization model is developed, a production function is estimated, and sensitivity analyses are conducted using the optimization model to investigate the effect of environmental conditions and economic factors on the optimal input portfolio and the cost of operating a modeled seawater desalination facility. The objectives of this paper are to better understand the effect on the seawater desalination facility’s costs and input portfolio from changes in water quality, membrane lifespan, daily operations schedule, and energy prices. Findings include that lower total facility costs are associated with warm-weather water quality parameters, longer membrane life, and mid-range daily operations schedule (14.265 hours/day). Under most conditions, an interruptible power supply regime reduces facility costs. Exceptions include when the interruptible power supply regime implies significant reductions in operating hours and the associated reduction in energy price is very small.water, production, seawater desalination, Resource /Energy Economics and Policy,

Government Insurance Program Design, Incentive Effects, and Technology Adoption: The Case of Skip-Row Crop Insurance

Can the availability of poorly-designed government insurance alter technology adoption decisions? A theoretical model of technology adoption and insurance incentive effects for a high- and low-risk technology is developed and explored empirically using a unique dataset of skip-row agronomic trial data. A multivariate nonparametric resampling technique is developed, which augments the trial data with a larger dataset of conventional yields to improve estimation efficiency. Skip-row adoption is found to increase mean yields and reduce risk in areas prone to drought. RMA insurance rules have incentive-distorting impacts which disincentivize skip-row adoption

A spatial econometric approach to designing and rating scalable index insurance in the presence of missing data

Index-Based Livestock Insurance has emerged as a promising market-based solution for insuring livestock against drought-related mortality. The objective of this work is to develop an explicit spatial econometric framework to estimate insurable indexes that can be integrated within a general insurance pricing framework. We explore the problem of estimating spatial panel models when there are missing dependent variable observations and cross-sectional dependence, and implement an estimable procedure which employs an iterative method. We also develop an out-of-sample efficient cross-validation mixing method to optimise the degree of index aggregation in the context of spatial index models