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Article
Publication date: 5 May 2008

Joshua D. Woodard and Philip Garcia

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…

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Abstract

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.

Details

Agricultural Finance Review, vol. 68 no. 1
Type: Research Article
ISSN: 0002-1466

Keywords

Article
Publication date: 26 July 2013

Nicholas D. Paulson, Joshua D. Woodard and Bruce Babcock

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…

Abstract

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 Senate's bill would be expected to be preferred over the House's bill for corn and soybean producers, particularly those in the Midwest. Also, the RLC program in the House's Bill typically would be projected to pay much less than the Senate's 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.

Article
Publication date: 7 September 2015

Apurba Shee, Calum G. Turvey and Joshua Woodard

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…

Abstract

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.

Details

Agricultural Finance Review, vol. 75 no. 3
Type: Research Article
ISSN: 0002-1466

Keywords

Article
Publication date: 1 July 2014

Calum G. Turvey, Joshua Woodard and Edith Liu

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…

Abstract

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 Itô's 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.

Details

Agricultural Finance Review, vol. 74 no. 2
Type: Research Article
ISSN: 0002-1466

Keywords

Article
Publication date: 3 May 2016

Joshua Woodard

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)…

1784

Abstract

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.

Details

Agricultural Finance Review, vol. 76 no. 1
Type: Research Article
ISSN: 0002-1466

Keywords

Article
Publication date: 26 August 2014

Bruce J. Sherrick, Christopher A. Lanoue, Joshua Woodard, Gary D. Schnitkey and Nicholas D. Paulson

The purpose of this paper is to contribute to the empirical evidence about crop yield distributions that are often used in practical models evaluating crop yield risk and…

Abstract

Purpose

The purpose of this paper is to contribute to the empirical evidence about crop yield distributions that are often used in practical models evaluating crop yield risk and insurance. Additionally, a simulation approach is used to compare the performance of alternative specifications when the underlying form is not known, to identify implications for the choice of parameterization of yield distributions in modeling contexts.

Design/methodology/approach

Using a unique high-quality farm-level corn yield data set, commonly used parametric, semi-parametric, and non-parametric distributions are examined against widely used in-sample goodness-of-fit (GOF) measures. Then, a simulation framework is used to assess the out-of-sample characteristics by using known distributions to generate samples that are assessed in an insurance valuation context under alternative specifications of the yield distribution.

Findings

Bias and efficiency trade-offs are identified for both in- and out-of-sample contexts, including a simple insurance rating application. Use of GOF measures in small samples can lead to inappropriate selection of candidate distributions that perform poorly in straightforward economic applications. The β distribution consistently overstates rates even when fitted to data generated from a β distribution, while the Weibull consistently understates rates; though small sample features slightly favor Weibull. The TCMN and kernel density estimators are least biased in-sample, but can perform very badly out-of-sample due to overfitting issues. The TCMN performs reasonably well across sample sizes and initial conditions.

Practical implications

Economic applications should consider the consequence of bias vs efficiency in the selection of characterizations of yield risk. Parsimonious specifications often outperform more complex characterizations of yield distributions in small sample settings, and in cases where more demanding uses of extreme-event probabilities are required.

Originality/value

The study helps provide guidance on the selection of distributions used to characterize yield risk and provides an extensive empirical demonstration of yield risk measures across a high-quality set of actual farm experiences. The out-of-sample examination provides evidence of the impact of sample size, underlying variability, and region of the probability measure used on the performance of candidate distributions.

Details

Agricultural Finance Review, vol. 74 no. 3
Type: Research Article
ISSN: 0002-1466

Keywords

Content available

Abstract

Details

Agricultural Finance Review, vol. 76 no. 1
Type: Research Article
ISSN: 0002-1466

Content available
Article
Publication date: 5 May 2015

Assistant Professor Lysa Porth and Professor ßKen Seng Tan

15

Abstract

Details

Agricultural Finance Review, vol. 75 no. 1
Type: Research Article
ISSN: 0002-1466

Content available

Abstract

Details

Agricultural Finance Review, vol. 74 no. 2
Type: Research Article
ISSN: 0002-1466

Article
Publication date: 1 July 2014

Lysa Porth, Wenjun Zhu and Ken Seng Tan

The purpose of this paper is to address some of the fundamental issues surrounding crop insurance ratemaking, from the perspective of the reinsurer, through the…

Abstract

Purpose

The purpose of this paper is to address some of the fundamental issues surrounding crop insurance ratemaking, from the perspective of the reinsurer, through the development of a scientific pricing framework.

Design/methodology/approach

The generating process of the historical loss cost ratio's (LCR's) are reviewed, and the Erlang mixture distribution is proposed. A modified credibility approach is developed based on the Erlang mixture distribution and the liability weighted LCR, and information from the observed data of the individual region/province is integrated with the collective experience of the entire crop reinsurance program in Canada.

Findings

A comprehensive data set representing the entire crop insurance sector in Canada is used to show that the Erlang mixture distribution captures the tails of the data more accurately compared to conventional distributions. Further, the heterogeneous credibility premium based on the liability weighted LCR's is more conservative, and provides a more scientific approach to enhance the reinsurance pricing.

Research limitations/implications

Credibility models are in the early stages of application in the area of agriculture insurance, therefore, the credibility models presented in this paper could be verified with data from other geographical regions.

Practical implications

The credibility-based Erlang mixture model proposed in this paper should be useful for crop insurers and reinsurers to enhance their ratemaking frameworks.

Originality/value

This is the first paper to introduce the Erlang mixture model in the context of agricultural risk modeling. Two modified versions of the Bühlmann-Straub credibility model are also presented based on the liability weighted LCR to enhance the reinsurance pricing framework.

Details

Agricultural Finance Review, vol. 74 no. 2
Type: Research Article
ISSN: 0002-1466

Keywords

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