Joshua D. Woodard

Basis risk and weather hedging effectiveness

Basis risk – the risk that payoffs of a hedging instrument do not correspond to the underlying exposures – is cited as a primary concern for implementing weather data, we investigate several dimensions of weather basis risk in the U.S. corn market. Results suggest that while geographic basis risk can be significant, it should not preclude the use of geographic cross‐hedging, particularly with temperature as opposed to precipitation derivatives. Risk reduction is appreciable and the degree to which geographic basis risk impedes effective hedging diminishes as spatial aggregation in the risk exposure and hedging instrument increases.

A Spatial Econometric Analysis of Loss Experience in the U.S. Crop Insurance Program

Patterns in loss‐ratio experience in the U.S. corn insurance market are investigated with a spatial econometric model. The results demonstrate systematic geographically related misratings and provide estimates of the impacts of several observable factors on the magnitude of misrating in the program. The model is used to estimate actuarial cross‐subsidizations across the primary corn‐producing states and counties. The impacts of the primary factors are substantial, resulting in net premium transfers of approximately 26 percent of total premiums annually. The misratings likely have important insurance demand, welfare, and land‐use implications.

Estimation of Mixture Models using Cross-Validation Optimization: Implications for Crop Yield Distribution Modeling

A critical issue in identifying an appropriate characterization of crop yield distributions is that the best-fitting distribution in an in-sample framework is not necessarily the best choice out-of-sample. This study provides a methodology for estimating flexible and efficient mixture models using cross-validation that alleviates many of these associated model selection issues. The method is illustrated in an application to the rating of group risk insurance products. Results indicate that nonparametric models often fit best in-sample but are inefficient and consistently overstate true rates, and vice versa for parametric models. The proposed model provides unbiased rates and also has desirable efficiency properties. Copyright 2011, Oxford University Press.

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. Copyright 2012, Oxford University Press.

Big data and Ag-Analytics

Purpose - – The purpose of this paper is to provide a brief and necessarily partial overview of the design, motivation, and use of the Ag-Analytics platform (ag-analytics.org), focussing on integration and warehousing of publicly available research data for broad communities of researchers, including those in the area of agricultural finance. Design/methodology/approach - – The paper walks the reader through an overview of the layout and utilization of the Ag-Analytics platform, including a few example applications of some of the tools and web API’s. Findings - – Much of the data researchers routinely use in agricultural and environmental finance and related fields are often – strictly speaking – publicly available; however the form in which they are distributed leads to great inefficiencies in data sourcing and processing which can be greatly improved. The goal of the Ag-Analytics open data/open source platform is to help researchers centralize and share in such efforts. Development of systems for disseminating, documenting, and automating the processing of such data can lead to more transparency in research, better routes for validation, and a more robust research community. Practical implications - – Some of the tools and methods are discussed, as well as practical issues in data sourcing and automation for research. A few high level introductory examples and applications are illustrated. Originality/value - – Development and adoption of such systems and data resources remains seriously lacking in social science research, particularly in the economics, natural resource, environmental, and agricultural finance spheres. This brief provides an overview of one such system which should be of value to researchers in this field and many others.

Modelling “shallow loss” crop revenue programs: Issues and implications for the 2013 Farm Bill

Purpose - The purpose of this paper is to investigate changes proposed in 2012 to commodity programs for the new Farm Bill. Both the Senate and House Agriculture Committee versions of the new Farm Bill eliminate current commodity programs including direct payments, create new revenue-based commodity program options designed to cover “shallow” revenue losses, and also introduce supplemental crop insurance coverage for shallow revenue losses. Design/methodology/approach - This paper documents the payment functions for the new revenue programs proposed in both the Senate and House Ag Committee Farm Bills, and also estimates expected payments for each using a model based on historical county yield data, farmer-level risk rates from RMA, and commodity price levels from the March 2012 CBO baseline projections. Findings - The authors find significant variation in expected per acre payment across programs, crops, and regions. In general, the Senates bill would be expected to be preferred over the Houses bill for corn and soybean producers, particularly those in the Midwest. Also, the RLC program in the Houses Bill typically would be projected to pay much less than the Senates SCO or ARC programs for most producers in the Midwest. Originality/value - This study develops an extensive nationwide model of county and farm yield and price risks for the five major US crops and employs the model to evaluate expected payment rates and the distribution of payments under the House and Senate Farm Bill proposals. These analyses are important for program evaluation and should be of great interest to producers and policymakers.

Efficiency Impacts of Utilizing Soil Data in the Pricing of the Federal Crop Insurance Program

Abstract Since the Agricultural Act of 2014, the federal crop insurance program (FCIP) has been the cornerstone agricultural policy in the United States, and is the largest such program globally, with about

Financial engineering for the farm problem

100 billion in coverage annually. Given its scale and scope, the FCIP has the potential to have pervasive impacts on incentives and policy functioning if not designed and priced properly. Surprisingly, soil data are not considered by the government when establishing insurance guarantees or rates. Using soil data that could easily and feasibly be scaled nationally, we find that the pricing differentials caused by the governments failure to handle soil information leads to large errors in rating.

A field study for assessing risk-contingent credit for Kenyan pastoralists and dairy farmers

Purpose - – The purpose of this paper is to provide a general discussion of how techniques from financial engineering can be used to investigate the economic costs of farm programs and to aid in the design of new financial products to implement margin protection for dairy farmers. Specifically the paper investigates the Milk Income Loss Contract (MILC) and the Dairy Margin Protection (DMP) program. In addition the paper introduces the concept of the Milk to Corn Price ratio to protect margins. Design/methodology/approach - – The paper introduces and reviews the tools of financial engineering. These include the stochastic calculus and Itos Lemma. The empirical tool is Monte Carlo simulations. The approach is part pedagogy and part practice. Findings - – In this paper the authors illustrate how financial engineering can be used to price complex price stabilization formula in the USA and to illustrate its use in the design of new products. Practical implications - – In this paper the authors illustrate how financial engineering can be used to price complex price stabilization formula in the USA and to illustrate its use in the design of new products. Social implications - – Farm programs designed to protect dairy farmers margins are designed in a seemingly ad hoc fashion. Assessments of programs such as MILC or DMP are conducted on an ex-post basis using historical data. The financial engineering approach presented in this paper provides the means to add significant depth to the assessment of such programs which can be used in conjunction with Monte Carlo simulation to identify alternative model structures before they are written into law. Originality/value - – This paper builds upon an existing literature. Its originality is in the application of financial engineering techniques to farm dairy policy.

Crop yield distributions: fit, efficiency, and performance

Purpose - – The purpose of this paper is to assess the feasibility of risk-contingent credit (RCC) by presenting an experimental and participatory game designed to explain the concept of RCC to Kenyan pastoralists and dairy farmers. The paper investigates the uptake potential of RCC through qualitative assessment of field experiments and focus groups. Design/methodology/approach - – The paper presents a method of community engagement through a participatory game played in a series of Focus Group Discussions (FGDs). The paper also presents theoretical justification of RCC in credit market structure. Findings - – The game effectively explains the concept and mechanism of RCC by reflecting local situation and production potential. Participatory exercises within focus group discussions indicate that there exists a strong interest and support for RCC. Research limitations/implications - – The methodology described in this paper can be used in extension programs for promoting innovative rural microcredit in developing countries but should be modified according to the local production and associated weather and market risks. Originality/value - – Micro-insurance and credit program delivery can be improved by the innovative approach of community engagement for explaining financial products.