Diversifying systemic risk in agriculture

2016 ◽  
Vol 76 (4) ◽  
pp. 512-531 ◽  
Author(s):  
Xiaoguang Feng ◽  
Dermot Hayes
Keyword(s):  
Crop Yield ◽  
Systemic Risk ◽  
Crop Insurance ◽  
Tail Dependence ◽  
Model Potential ◽  
High Dimensional ◽  
Computationally Efficient ◽  
Content Type ◽  
Insurance Portfolio ◽  
Systemic Nature

Purpose Portfolio risk in crop insurance due to the systemic nature of crop yield losses has inhibited the development of private crop insurance markets. Government subsidy or reinsurance has therefore been used to support crop insurance programs. The purpose of this paper is to investigate the possibility of converting systemic crop yield risk into “poolable” risk. Specifically, this study examines whether it is possible to remove the co-movement as well as tail dependence of crop yield variables by enlarging the risk pool across different crops and countries. Design/methodology/approach Hierarchical Kendall copula (HKC) models are used to model potential non-linear correlations of the high-dimensional crop yield variables. A Bayesian estimation approach is applied to account for estimation risk in the copula parameters. A synthetic insurance portfolio is used to evaluate the systemic risk and diversification effect. Findings The results indicate that the systemic nature – both positive correlation and lower tail dependence – of crop yield risks can be eliminated by combining crop insurance policies across crops and countries. Originality/value The study applies the HKC in the context of agricultural risks. Compared to other advanced copulas, the HKC achieves both flexibility and parsimony. The flexibility of the HKC makes it appropriate to precisely represent various correlation structures of crop yield risks while the parsimony makes it computationally efficient in modeling high-dimensional correlation structure.

Evaluating effectiveness of rainfall index insurance

2018 ◽  
Vol 78 (5) ◽  
pp. 611-625 ◽  
Author(s):  
Rui Zhou ◽  
Johnny Siu-Hang Li ◽  
Jeffrey Pai
Keyword(s):  
Crop Yield ◽  
Variance Reduction ◽  
Index Insurance ◽  
Corn Yield ◽  
Basis Risk ◽  
Content Type ◽  
Optimal Insurance ◽  
Rainfall Index ◽  
Temperature And Precipitation ◽  
Insurance Portfolio

Purpose The purpose of this paper is to examine the reduction of crop yield uncertainty using rainfall index insurances. The insurance payouts are determined by a transparent rainfall index rather than actual crop yield of any producer, thereby circumventing problems of adverse selection and moral hazard. The authors consider insurances on rainfall indexes of various months and derive an optimal insurance portfolio that minimizes the income variance for a crop producer. Design/methodology/approach Various regression models are considered to relate crop yield to monthly mean temperature and monthly cumulative precipitation. A bootstrapping method is used to simulate weather indexes and corn yield in a future year with the correlation between precipitation and temperature incorporated. Based on the simulated scenarios, the optimal insurance portfolio that minimizes the income variance for a crop producer is obtained. In addition, the impact of correlation between temperature and precipitation, availability of temperature index insurance and geographical basis risk on the effectiveness of rainfall index insurance is examined. Findings The authors illustrate the approach with the corn yield in Illinois east crop reporting district and weather data of a city in the same district. The analysis shows that corn yield in this district is negatively influenced by excessive precipitation in May and drought in June–August. Rainfall index insurance portfolio can reduce the income variance by up to 51.84 percent. Failing to incorporate the correlation between temperature and precipitation decreases variance reduction by 11.6 percent. The presence of geographical basis risk decreases variance reduction by a striking 24.11 percent. Allowing for the purchase of both rainfall and temperature index insurances increases variance reduction by 13.67 percent. Originality/value By including precipitation shortfall into explanatory variables, the extended crop yield model explains more fluctuation in crop yield than existing models. The authors use a bootstrapping method instead of complex parametric models to simulate weather indexes and crop yield for a future year and assess the effectiveness of rainfall index insurance. The optimal insurance portfolio obtained provides insights on the practical development of rainfall insurance for corn producers, from the selection of triggering index to the demand of the insurance.

Gaussian process modeling of nonstationary crop yield distributions with applications to crop insurance

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Wenbin Wu ◽  
Ximing Wu ◽  
Yu Yvette Zhang ◽  
David Leatham
Keyword(s):  
Gaussian Process ◽  
Crop Yield ◽  
Bayesian Model Averaging ◽  
Crop Yields ◽  
Crop Insurance ◽  
Model Averaging ◽  
Insurance Premium ◽  
Insurance Companies ◽  
Content Type ◽  
Stage Estimation

PurposeThe purpose of this paper is to bring out the development of a flexible model for nonstationary crop yield distributions and its applications to decision-making in crop insurance.Design/methodology/approachThe authors design a nonparametric Bayesian approach based on Gaussian process regressions to model crop yields over time. Further flexibility is obtained via Bayesian model averaging that results in mixed Gaussian processes.FindingsSimulation results on crop insurance premium rates show that the proposed method compares favorably with conventional estimators, especially when the underlying distributions are nonstationary.Originality/valueUnlike conventional two-stage estimation, the proposed method models nonstationary crop yields in a single stage. The authors further adopt a decision theoretic framework in its empirical application and demonstrate that insurance companies can use the proposed method to effectively identify profitable policies under symmetric or asymmetric loss functions.

How important is the transitional yield (t-yield)? An analysis of reforms to organic crop insurance

2019 ◽  
Vol 79 (2) ◽  
pp. 234-254 ◽  
Author(s):  
Timothy A. Delbridge ◽  
Robert P. King
Keyword(s):  
Crop Yield ◽  
Crop Insurance ◽  
Yield Potential ◽  
Yield Data ◽  
Data Set ◽  
Content Type ◽  
Insurance Program ◽  
Before And After ◽  
Production History ◽  
The Impact

PurposeThe USDA’s Risk Management Agency (RMA) made several changes to the crop insurance products available to organic growers for the 2014 crop year. Most notably, a 5 percent premium surcharge was removed and organic-specific transitional yields (t-yields) were issued for the first time. The purpose of this paper is to use farm-level organic crop yield data to analyze the impact of these reforms on producer insurance outcomes and compare the insurance options for new organic growers.Design/methodology/approachThis study uses a unique panel data set of organic corn and soybean yields to analyze the impact of organic crop insurance reforms. Actual Production History values and premium rates are calculated for each farm and crop yield sequence. Producer loss ratios and subsidized premium wedges are compared for yield, revenue and area-risk products before and after the instituted reforms.FindingsResults indicate that RMA succeeded in improving the actuarial soundness of the organic insurance program, though further refinement of organic t-yields may be necessary to accurately reflect the yield potential of organic producers and avoid reductions in program participation.Originality/valueThis paper provides insight into the effectiveness of reforms intended to improve the actuarial soundness of organic crop insurance and demonstrates the effect that the reforms are likely to have on new and existing organic farms. Because this analysis uses data collected independently of RMA and includes farms that may or may not have purchased crop insurance, it avoids the self-selection problems that might affect analyses using crop insurance program data.

Building insurance through an NGO

2016 ◽  
Vol 76 (1) ◽  
pp. 119-139 ◽  
Author(s):  
Marie-Christine Bélanger
Keyword(s):  
Design Methodology ◽  
Smallholder Farmers ◽  
Crop Insurance ◽  
Specific Training ◽  
Close Collaboration ◽  
Agricultural Insurance ◽  
Content Type ◽  
Level Of Education ◽  
Challenges And Opportunities

Purpose – This paper is based on a crop insurance implementation currently undergoing in Haiti. The purpose of this paper is to present the development of a program tailored to rice production in the Artibonite Valley, the challenges and opportunities that are arising from the exercise as well as pitfalls and ways to avoid them. Design/methodology/approach – The Système de Financement et d’Assurances Agricoles en Haïti’s approach for the development of crop insurance is in accordance with 13 concepts considered essential in the implementation of agricultural insurance programs. The case study is presented through each of these 13 fundamental concepts. Findings – The paper provides an insight on challenges any organization will face when implementing crop insurance for smallholder farmers. It points out notably that close collaboration of executing agencies with local partners is essential from data collection through insurance development and delivery and that all participants should receive a specific training tailored to their level of education and understanding. Social implications – Haiti is one of the poorest countries on the planet. Smallholder farmers could benefit a lot from crop insurance. It could help them stabilize their income when facing crop losses due to natural hazards or uncontrollable natural events. Originality/value – This paper fulfills an identified need to share real case studies exposing challenges faced when implementing crop insurance for smallholder farmers.

The US crop insurance program and WTO disciplines

2016 ◽  
Vol 76 (1) ◽  
pp. 6-14 ◽  
Author(s):  
Joseph William Glauber
Keyword(s):  
Dispute Settlement ◽  
Crop Insurance ◽  
Developed Countries ◽  
Eligibility Criteria ◽  
Agricultural Insurance ◽  
Content Type ◽  
Insurance Program ◽  
The Us ◽  
Domestic Support ◽  
Green Box

Purpose – The purpose of this paper is to examine the US crop insurance programs in the context of domestic support disciplines under the World Trade Organization (WTO). Crop insurance has become an integral part of many domestic support programs, not just in developed countries, but in important emerging markets as well. An often-cited impetus for the growth in insurance program is the potential treatment of such programs as exempt from WTO reduction commitments. Design/methodology/approach – A detailed examination of the so-called “green box provisions” of the Uruguay Round Agreement on Agriculture is presented with particular emphasis on eligibility criteria for crop yield and revenue insurance programs. Findings – While WTO rules potentially shield green box policies from reduction, few developed countries have notified agricultural insurance policies under Annex 2. Moreover, crop insurance programs have been challenged in recent WTO dispute settlement cases and domestic countervailing duty investigations. Originality/value – The paper presents a unique perspective on a program which has become the largest single farm program in the USA.

Impact of regulatory announcements on systemic risk in the Indian telecom sector

2018 ◽  
Vol 13 (5) ◽  
pp. 1395-1416 ◽  
Author(s):  
Sushma Priyadarsini Yalla ◽  
Som Sekhar Bhattacharyya ◽  
Karuna Jain
Keyword(s):  
Risk Premium ◽  
Systemic Risk ◽  
Service Providers ◽  
Policy Makers ◽  
Content Type ◽  
Risk Premiums ◽  
Buffering Hypothesis ◽  
Research Findings ◽  
Telecom Sector ◽  
The Impact

Purpose Post 1991, given the advent of liberalization and economic reforms, the Indian telecom sector witnessed a remarkable growth in terms of subscriber base and reduced competitive tariff among the service providers. The purpose of this paper is to estimate the impact of regulatory announcements on systemic risk among the Indian telecom firms. Design/methodology/approach This study employed a two-step methodology to measure the impact of regulatory announcements on systemic risk. In the first step, CAPM along with the Kalman filter was used to estimate the daily β (systemic risk). In the second step, event study methodology was used to assess the impact of regulatory announcements on daily β derived from the first step. Findings The results of this study indicate that regulatory announcements did impact systemic risk among telecom firms. The study also found that regulatory announcements either increased or decreased systemic risk, depending upon the type of regulatory announcements. Further, this study estimated the market-perceived regulatory risk premiums for individual telecom firms. Research limitations/implications The regulatory risk premium was either positive or negative, depending upon the different types of regulatory announcements for the telecom sector firms. Thus, this study contributes to the theory of literature by testing the buffering hypothesis in the context of Indian telecom firms. Practical implications The study findings will be useful for investors and policy-makers to estimate the regulatory risk premium as and when there is an anticipated regulatory announcement in the Indian telecom sector. Originality/value This is one of the first research studies in exploring regulatory risk among the Indian telecom firms. The research findings indicate that regulatory risk does exist in the telecom firms of India.

scholarly journals Multiscale, thermomechanical topology optimization of self-supporting cellular structures for porous injection molds

2019 ◽  
Vol 25 (9) ◽  
pp. 1482-1492
Author(s):  
Tong Wu ◽  
Andres Tovar
Keyword(s):  
Topology Optimization ◽  
Mechanical Performance ◽  
Mechanical Load ◽  
Design Method ◽  
Three Dimensional ◽  
Optimization Method ◽  
Cellular Structures ◽  
Injection Mold ◽  
Computationally Efficient ◽  
Content Type

Purpose This paper aims to establish a multiscale topology optimization method for the optimal design of non-periodic, self-supporting cellular structures subjected to thermo-mechanical loads. The result is a hierarchically complex design that is thermally efficient, mechanically stable and suitable for additive manufacturing (AM). Design/methodology/approach The proposed method seeks to maximize thermo-mechanical performance at the macroscale in a conceptual design while obtaining maximum shear modulus for each unit cell at the mesoscale. Then, the macroscale performance is re-estimated, and the mesoscale design is updated until the macroscale performance is satisfied. Findings A two-dimensional Messerschmitt Bolkow Bolhm (MBB) beam withstanding thermo-mechanical load is presented to illustrate the proposed design method. Furthermore, the method is implemented to optimize a three-dimensional injection mold, which is successfully prototyped using 420 stainless steel infiltrated with bronze. Originality/value By developing a computationally efficient and manufacturing friendly inverse homogenization approach, the novel multiscale design could generate porous molds which can save up to 30 per cent material compared to their solid counterpart without decreasing thermo-mechanical performance. Practical implications This study is a useful tool for the designer in molding industries to reduce the cost of the injection mold and take full advantage of AM.

The effects of overconfident yield forecasting on cross-coverage level crop insurance demand

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Clayton P. Michaud
Keyword(s):  
Crop Insurance ◽  
Insurance Coverage ◽  
Coverage Level ◽  
Insurance Demand ◽  
Management Tools ◽  
Content Type ◽  
Revenue Insurance ◽  
Yield Risk ◽  
Yield Forecasting ◽  
Yield Insurance

PurposeThis paper examines the effect of overconfident yield forecasting (optimism bias) on crop insurance coverage level choices across both yield and revenue insurance.Design/methodology/approachThis study simulates a representative producer’s preferred coverage level for both yield and revenue insurance under three potential models of decision-making and four potential manifestations of overconfident yield forecasting. The study then uses this framework to examine how coverage level choices change as overconfidence increases (decreases).FindingsAs overconfidence increases, producers prefer lower levels of crop insurance coverage than they would otherwise prefer, with extreme overconfidence inducing farmers to buy no insurance at all. While overconfidence affects cross-coverage demand for revenue and yield insurance similarly, this effect is more pronounced for yield insurance. Cross-coverage level demand for revenue insurance is relatively stable across changes in the correlation between prices and yields.Practical implicationsThis research has important implications for crop insurance subsidy design and crop insurance demand modeling.Originality/valueThere is a growing body of literature suggesting that producers are overconfident with regard to their future yield risk and that this bias reduces their willingness to pay for risk management tools such as crop insurance. This is the first study to look at how such overconfidence affects cross-coverage level demand for crop insurance.

Systemic risk in ASEAN-6: a new empirical investigation

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Trung Hai Le
Keyword(s):  
Empirical Evidence ◽  
Systemic Risk ◽  
Business Models ◽  
Financial Integration ◽  
Global Financial Crisis ◽  
Macroprudential Policy ◽  
Content Type ◽  
Risk Dynamics ◽  
Asean Countries ◽  
Book Values

PurposeThe authors provide a comprehensive study on systemic risk of the banking sectors in the ASEAN-6 countries. In particular, they investigate the systemic risk dynamics and determinants of 49 listed banks in the region over the 2000–2018 period.Design/methodology/approachThe authors employ the market-based SRISK measure of Brownlees and Engle (2017) to investigate the systemic risk of the ASEAN-6's banking sectors.FindingsThe authors find that the regional systemic risk fluctuates significantly and currently at par or higher level than that of the recent global financial crisis. Systemic risk is generally associated with banks that have bigger size, more traditional business models, lower quality in their loan portfolios, less profitable and with lower market-to-book values. However, these relationships vary significantly between ASEAN countries.Research limitations/implicationsThe research focuses on the systemic risk of ASEAN-6 countries. Therefore, the research results may lack generalizability to other countries.Practical implicationsThe authors’ empirical evidence advocates the use of capital surcharges on the systemically important financial institutions. Although the region has been pushing to higher financial integration in recent years, the authors encourage the regional regulators to account for the idiosyncratic characteristics of their banking sectors in designing effective macroprudential policy to contain systemic risk.Originality/valueThis paper provides the first study on the systemic risk of the ASEAN-6 region. The empirical evidence on the drivers of systemic risk would be of interest to the regional regulators.

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