Agricultural Financial Risks Resulting from Extreme Events

Decision‐makers in the agricultural sector operate in a volatile and risky environment. The statistical assessment of agricultural commodity prices is necessary to deduce the stylised facts of agricultural markets and guide the action of market participants. This article examines the kurtosis values of 60 agricultural commodities and presents evidence that the distributions of their returns are fat‐tailed. We use power‐law distributions to model the tail returns and the possible time‐varying extreme event risks in commodity markets. Our results suggest that the usefulness of the value at risk and expected shortfall as risk management tools is questionable.     

Collateral‐free lending with risk‐contingent credit for agricultural development: indemnifying loans against pulse crop price risk in India

This article addresses the problem of collateral‐free lending in the context of agricultural development. We investigate a viable alternative to traditional credit products through the development of risk‐contingent credit for operating loans and farm mortgages and apply the concept to agricultural loans for pulse crops in India. Risk‐contingent credit mitigates business and financial risk by reducing debt obligations depending on the embedded commodity options whose payoffs are linked with commodity price fluctuations. We analyze daily commodity spot prices for pulse crops in India and show how risk‐contingent structured financial instruments can be priced in practice.     

欧盟碳交易市场收益率厚尾特征与极端风险度量研究

选取欧盟碳金融市场收益率数据作为研究对象,基于极值理论通过对数据建立区组极大值模型(BMM)和超阈值模型(POT)来拟合收益率数据的尾部。结果表明:正态分布不能很好地描述欧盟碳金融市场收益率数据特征,而基于极值理论地的BMM和POT模型可以较好地拟合数据尾部;基于正态性假定下计算的风险度量指标,在高置信水平下会低估尾部数据的风险水平;基于极值理论的模型可以更好地拟合碳金融市场收益率数据,由此得到的风险度量指标可以更好地帮助风险管理者们监控和应对风险。     

Integrated Management of Land Use Systems under Systemic Risks and Security Targets: A Stochastic Global Biosphere Management Model

Interdependencies among land use systems resemble a complex network connected through demand–supply relationships. Disruption of this network may catalyse systemic risks affecting food, energy, water and environmental security (FEWES) worldwide. We describe the conceptual development, expansion and practical application of a stochastic version of the Global Biosphere Management Model (GLOBIOM), used to assess competition for land use between agriculture, bioenergy and forestry at regional and global scales. In the stochastic version of the model, systemic risks of various kinds are explicitly covered and can be analysed and mitigated in all their interactions. While traditional deterministic scenario analysis produces sets of scenario‐dependent outcomes, stochastic GLOBIOM explicitly derives robust outcomes that leave the systems better‐off, independently of which scenario applies. Stochastic GLOBIOM is formulated as a stochastic optimisation model that is critical for evaluating portfolios of robust interdependent decisions: ex‐ante strategic decisions (production allocation, storage capacities) and ex‐post adaptive (demand, trading, storage control) decisions. As an example, the model is applied to the question of optimal storage facilities, as buffers for production shortfalls, to meet regional and global FEWES requirements when extreme events occur. Expected shortfalls and storage capacities have a close relationship with Value‐at‐Risk (VaR) and Conditional Value‐at‐Risk (CVaR) risk measures. A Value of Stochastic Solutions is calculated to illustrate the benefits of the stochastic over the deterministic model approach.     

Welfare‐at‐Risk and Extreme Dependency of Regional Wheat Yields: Implications of a Stochastic CGE Model

Stochastic computable general equilibrium (CGE) models have ignored regional correlations in agricultural yields, assuming random shocks to be independent between regions. This could lead to misinterpretation of simulation outputs which ignore extreme positive or negative harvests at the global scale. We develop a multi‐regional CGE model which allows for five types of interregional correlation between wheat yields to analyse the vulnerability of countries against fluctuating international markets, focusing on Value at Risk (VaR) and extreme dependency. We find that global welfare risks could be underestimated by up to 33% if significant interregional correlations in yield shocks are not taken into account. Egypt, Kazakhstan, Ukraine, the former Soviet Union and Northern Africa are particularly vulnerable to global volatilities in terms of economic welfare.     

Modeling regime‐dependent agricultural commodity price volatilities

In stark contrast to financial markets, relatively little attention has been given to modeling agricultural commodity price volatility. In recent years, numerous methodologies with various strengths have been proposed for modeling price volatility in financial markets. We propose using a mixture of normals with unique GARCH processes in each component for modeling agricultural commodity prices. While a normal mixture model is quite flexible and allows for time varying skewness and kurtosis, its biggest strength is that each component can be viewed as a different market regime and thus estimated parameters are more readily interpreted. We apply the proposed model to ten different agricultural commodity weekly cash prices. Both in‐sample fit and out‐of‐sample forecasting tests confirm that the two‐state NM‐GARCH approach performs better than the traditional normal GARCH model. A significant and state‐dependent inverse leverage effect is detected only for pork in the regime where the price is expected to drop, indicating the volatility in this regime tends to increase more following a realized price rise than a realized price drop.     

Derivatives for Development? Small‐Farmer Vulnerability and the Financialization of Climate Risk Management

While agricultural production has always been a risky endeavour, it has become even more so in the current context of climatic change and increasing market uncertainty. Meanwhile, the rollback of state protections has rendered small‐scale farmers, especially marginalized peasant producers in the Global South, particularly vulnerable to these contemporary stressors. This essay critically evaluates the contemporary roll‐out of financial derivatives that purportedly aim to mitigate smallholder vulnerability. It gives particular attention to a novel type of derivative known as index‐based agricultural insurance (IBAI) that plays an increasingly prominent role in initiatives to ‘climate proof’ agriculture. The creation of IBAI markets has required significant work, including (1) technical interventions to debundle environmental risk from agricultural production and rebundle it in novel ways that support private financial capital and agricultural input suppliers, (2) extensive state support in the creation of risk markets, and (3) the construction of an accommodating ‘insurance culture’ among small‐scale producers. In addition to mitigating weather‐based risk, a primary objective of IBAI is to spur agricultural modernization. In promoting this agenda, IBAI initiatives may have the paradoxical effect of exposing smallholders to new risks while expanding their overall vulnerability to environmental and economic stressors.     

Can flexible agricultural microfinance loans limit the repayment risk of low diversified farmers?

Using a unique data set from a commercial microfinance institution in Madagascar, this article investigates the credit risk of microfinance loans with flexible repayment schedules for crop farmers. Flexible repayment schedules allow a redistribution of principal payments during periods with low agricultural returns to periods when agricultural returns are high through predefined grace periods. We apply propensity score matching to investigate how different numbers of grace periods reflecting different levels of production diversification affect the credit risk of crop farmers. In this attempt, three delinquency categories reflecting various levels of credit risk are assessed. Moreover, we consider the specifics of the regions where loans were disbursed. Our results reveal that loans with predefined grace periods show significantly higher delinquencies. This effect is significant over all three delinquency categories for loans disbursed to low diversified crop farmers. For the more diversified farmers, this effect is only significant for the lowest delinquency category. Hence, predefined grace periods might bridge periods with low agricultural returns but come at the cost of higher credit risk for the lender. The magnitude of these effects is, however, small.     

Market interdependence and volatility transmission among major crops

This article provides a comprehensive analysis of the dynamics of volatility across major agricultural commodities in the United States. Volatility interactions across markets may lower the effectiveness of diversification strategies to mitigate price risks and should be taken into account when analyzing the pricing behavior of different agricultural commodities. We follow a multivariate GARCH approach to evaluate the time evolution of conditional correlations and volatility transmission across corn, wheat, and soybeans price returns on a daily, weekly, and monthly basis. The period of analysis is from 1998 to 2012. The estimation results indicate a lack of lead‐lag relationships between corn, wheat, and soybeans price returns at the mean level. We find, however, important volatility spillovers across commodities, particularly at the weekly and monthly level. Wheat and corn seem to play a major role in terms of volatility transmission. Despite the supposed higher financial market integration of agricultural commodities, we do not observe that agricultural markets have become more interdependent in recent years.     

Publicly-funded UK agricultural R&D and 'social' total factor productivity

Most studies concerned with measuring the rate of return to publicly‐funded agricultural R&D investment have found high returns, suggesting under‐investment, and calls for increased expenditure have been common. However, the evaluation of returns tends to measure the effect of research expenditure against growth in total factor productivity (TFP), based on market inputs and outputs. When compared against growing public unease over the environmental effects of pursuing agricultural productivity growth, TFP indices become a misleading measure of growth. This paper integrates some non‐market components into the TFP index. The costs of two specific externalities of agricultural production, namely fertiliser and pesticide pollution, are integrated in a TFP index constructed for the period 1948–1995. This adjusted, or ‘social’, TFP index is measured against UK public R&D expenditures. The rates of return to agricultural R&D are reduced by using the ‘social’ as opposed to the traditional TFP index. Whilst both remain at justifiable levels, previous studies appear to have over‐estimated the effect of agricultural R&D expenditures. Furthermore, with changes in policy towards more socially acceptable but non‐productivity enhancing outcomes, such as animal welfare, rural diversification and organic farming, the future framework for analysing returns to agricultural R&D should not be so dependent on productivity growth as an indicator of research effectiveness.     

Are we risking too much? Perspectives on risk in farm modeling

Risk and uncertainty have been extensively studied by agricultural economists. In this paper we question (a) the predominant use of static frameworks to formally analyse risk; (b) the predominant focus on risk aversion as the motivation for considering risk and (c) the notion that explicitly probabilistic models are likely to be helpful to farmers in their decision making. We pose the question: for a risk‐averse farmer, what is the extra value of a recommendation derived from a model that represents risk aversion, compared to a model based on risk neutrality? The conclusion reached is that for the types of the decision problems most commonly modelled by agricultural economists, the extra value of representing risk aversion is commonly very little.     

Estimating multiproduct and product‐specific scale economies for agricultural cooperatives

This article estimates multiproduct and product‐specific scale economies, scope economies, and cost efficiency with single and annual cost frontiers using a nonparametric approach. Multiproduct scale and scope economies are found that suggests increasing scale and product diversification can reduce cost for agricultural cooperatives. Many agricultural cooperatives experience economies of scale indicating that variable returns to scale as opposed to constant returns to scale is the appropriate technology for modeling agricultural cooperatives. Product‐specific scale economies for all outputs are close to one indicating that individual outputs are operating close to constant returns to scale. Annual frontier estimates show that cooperatives have become less cost efficient over time, but scale and scope economies remain relatively consistent across years. Further, results show that economic measures obtained from the single frontier are statistically different from those measures calculated from annual frontiers, suggesting that the cost frontier has shifted over time. The trade‐off between cost efficiency and multiproduct scale economies indicates that smaller cooperatives can reduce a higher percentage of cost by increasing the scale of operations rather than just becoming cost efficient. Because larger incentives exist for small cooperatives to increase scale, mergers will likely continue until economies of scale are exhausted in the industry.     

Urban Sprawl and Farmland Prices

A theoretical model of farmland valuation is developed to explicitly account for three effects of urban sprawl: conversion of farmland to urban uses, effect on agricultural returns, and speculative effect as represented by farmland conversion risk. This model is estimated using county-level data in the continental United States. Evidence is found for all three effects of urban sprawl on farmland values. Counties more accessible to major urban centers have higher net agricultural returns. Subsidiary evidence supports that the latter effect may be attributed to survival of (or conversion to) high-valued agriculture around urban centers.     

Measuring Price Risk on UK Arable Farms

Price risk is estimated for a representative UK arable farm using value‐at‐risk (VaR). To determine the distribution of commodity returns, two multivariate generalised autoregressive conditional heteroscedasticity (GARCH) models, with t‐distributed and normally distributed errors, and a RiskMetrics^TM model are estimated. Returns show excess kurtosis and that the GARCH model with t‐distributed errors fits best. Estimates of VaR differ between models: both GARCH models perform well but the RiskMetrics^TM model underestimates expected losses. UK arable farms face substantial price risk.     

Effect of off‐farm income on smallholder commercialization: panel evidence from rural households in Ethiopia

This article investigates how off‐farm income affects crop output market participation decisions and marketed surplus of smallholder farmers in Ethiopia. A double‐hurdle model is estimated using three waves of panel data from the Ethiopian Rural Household Survey. Unobserved heterogeneity is controlled for using a correlated random effect procedure and potential endogeneity of explanatory variables using a control function approach. The results show that off‐farm income has no significant influence on household crop output market participation. However, conditional on market participation, additional off‐farm earnings negatively affect the marketed surplus. This indicates that farmers use off‐farm earnings for consumption rather than for investment in agricultural production. Policy measures that promote rural investment may help increase returns to labor for land‐poor households participating in off‐farm work in the process of agricultural commercialization.     

Risk communication,women’s participation and flood mitigation in Vietnam: An experimental study

Flood risk management has become important more than ever, because an escalating threat of unpredictable and extreme weather is affecting flood-prone communities. People-centred risk communication has been proposed as an effective strategy that can stimulate people to protect themselves against flood risks. However, little research with a sound theoretical underpinning has been done to examine the effectiveness of such a strategy in developing countries. We use a field experiment to analyse how risk communication can influence households’ intentions to implement mitigation measures. Our results show that communicating about the risk of floods and how to cope with floods significantly increased both threat and coping appraisals, and thereby motivated households to take more non-structural measures. While formal risk communication had certain direct effects on mitigation intention, informal risk communication percolated through psychological variables. Risk communication should focus on coping capacities for financial measures and address the problems of wishful thinking and disaster subculture of flood-prone households. Furthermore, women’s participation in risk communication did not change the intentions to take mitigation measures of the male household heads in the Vietnamese Mekong Delta.     

议企业财务风险的识别与防范

财务风险指企业财务活动中因有各种不确定因素影响 ,使企业财务收益与预期收益发生偏离 ,从而使企业蒙受经济损失的机会和可能。随着市场竞争的日趋激烈 ,财务风险对企业生存发展的影响也愈大 ,财务风险管理已经成了企业日常管理中一个非常重要的课题 ,本文就财务风险的识别、成因及防范处理等方面做了论述。     

Estimating the social welfare effects of New Zealand apple imports

International trade of agricultural products not only generates wealth but is also responsible for the introduction of invasive pests beyond their natural range. Comprehensive bioeconomic modelling frameworks are increasingly needed to assist in the resolution of import access disputes. However, frameworks that combine welfare analysis attributable to trade and invasive species spread management are lacking. This study provides a demonstration of how a comprehensive economic framework, which takes into account both the gains from trade and the costs of invasive species outbreaks, can inform decision‐makers when making quarantine decisions. We develop a partial equilibrium trade model considering international trade and combine it with a stratified dispersal model for the spread and management of potential outbreaks of an invasive species. An empirical estimation is made of the economic welfare consequences for Australia of allowing quarantine‐restricted trade in New Zealand apples to take place. The results suggest the returns to Australian society from importing New Zealand apples are likely to be negative. The price differential between the landed product with SPS measures in place and the autarkic price is insufficient to outweigh the increase in expected damage resulting from increased fire blight risk. As a consequence, this empirical analysis does not support the opening up of this trade.     

Crop insurance policies and purchases in France

While many crop insurance systems have been reformed around the world, few academic researches have addressed the determinants of the decision on crop insurance at the farm's micro level. In this article, both the financial and the agricultural literature lead to the identification of many rationales for the crop insurance decision. Using data from the period 2003–2006 on a representative survey of French farms (FADN‐RICA), we investigate the different factors that incite farmers to insure against crop risk. We emphasize that the highest risk farms are more likely to have insurance and this decision is positively related to the past amount of claims. Insurance is subscribed by larger farms because insurance appears too expensive for smaller farms, which are indeed naturally less diversified. Interestingly, financial variables (such as capital structure or return on investment) do not significantly determine the insurance decision.     

Credit Risk Models and Agricultural Lending

Credit risk models are developed and used to estimate capital requirements for agricultural lenders under the New Basel Capital Accord. The study uses credit value-at-risk methods to calculate probability of default, loss given default, and expected and unexpected losses. Two applied models, CreditMetrics and Moody's KMV , are estimated using farm financial data. The results show that the necessary capital for agricultural lenders under the New Basel Accord varies substantially depending on the riskiness and granularity of the portfolio.