Coefficient Of Absolute Risk Aversion Research Articles

Risk Preference Types, Limited Consideration, and Welfare

We provide sufficient conditions for semi-nonparametric point identification of a mixture model of decision making under risk, when agents make choices in multiple lines of insurance coverage (contexts) by purchasing a bundle. As a first departure from the related literature, the model allows for two preference types. In the first one, agents behave according to standard expected utility theory with CARA Bernoulli utility function, with an agent-specific coefficient of absolute risk aversion whose distribution is left completely unspecified. In the other, agents behave according to the dual theory of choice under risk combined with a one-parameter family distortion function, where the parameter is agent-specific and is drawn from a distribution that is left completely unspecified. Within each preference type, the model allows for unobserved heterogeneity in consideration sets, where the latter form at the bundle level—a second departure from the related literature. Our point identification result rests on observing sufficient variation in covariates across contexts, without requiring any independent variation across alternatives within a single context. We estimate the model on data on households’ deductible choices in two lines of property insurance, and use the results to assess the welfare implications of a hypothetical market intervention where the two lines of insurance are combined into a single one. We study the role of limited consideration in mediating the welfare effects of such intervention.

Competitive search with two-sided risk aversion

Search theory is widely used in economics to study markets where trading frictions are prevalent. However, all existing theoretical models assume that either buyers or sellers (or both) are risk neutral, and the case where both parties are risk averse remains unexplored. This paper is a first step to fill this gap. I analyze a static competitive search model where risk-averse agents with different wealth seek to exchange an indivisible good. The housing market is an important application since a home typically represents a large part of a person’s wealth. I prove that a competitive search equilibrium is constrained efficient, and derive a generalized Hosios condition that relates the gains of the two parties in each transaction. Under risk aversion, wealthier buyers are more concerned with increasing their trading probability than with getting the best price. The opposite is true for sellers when the coefficient of absolute risk aversion is non-increasing. This results in positive sorting in equilibrium, that is, wealthier (poorer) buyers and sellers trading with each other at higher (lower) prices. This sorting mechanism offers a novel explanation for why the separation between rich and poor neighborhoods can be persistent.

Risk aversion in share auctions: Estimating import rents from TRQs in Switzerland

This paper analyzes risk aversion in discriminatory share auctions. I generalize the k‐step share auction model of Kastl (2011, 2012) and establish that marginal profits are set‐identified for any given coefficient of constant absolute risk aversion. I also derive necessary conditions for best‐response behavior, which allows determining risk preferences from bidding data. Further, I show how the bidders' optimality conditions allow computing bounds on the marginal profits that are tighter than those currently available. I use my results to estimate import rents from Swiss tariff‐rate quotas on high‐quality beef. Rents are overestimated when ignoring risk aversion, and rent extraction is underestimated. Small bidders (small, privately owned butcheries) are more risk averse than large bidders (general retailers). Best response violations are few and uniform across bidder sizes.

Fractional stochastic dominance in rank-dependent utility and cumulative prospect theory

Two notions of fractional stochastic dominance (SD) were recently proposed by Müller et al. (2017) and Huang et al. (2020) based on mean-reducing spreads and the coefficient of absolute risk aversion, respectively. We formulate a general class of fractional SD generated by a convex transform, which includes those built from absolute or relative risk aversion as special cases, and this serves as a convenient technical tool for construction of new notions of fractional SD. We obtain equivalent conditions for a preference modeled by rank-dependent utility or cumulative prospect theory to be consistent with each notion of fractional SD. Furthermore, we provide an empirical estimator for the parameters in fractional SD relationships, and we illustrate this with a financial data analysis.

Farmers' Decision to Adoption of Modern Irrigation Systems Under Risk Condition: Application of Stochastic Efficiency With Respect to a Function Approach

To effectively tackle the issue of increasing irrigation water scarcity, farmers need to convert to modern irrigation systems with lower water use while achieving higher yields and profitability. Unlike the government support to cover a proportion of irrigation modernizing costs by public subsidies in Iran, the adoption rate is low. This is due to farmers' uncertainty about the trade-off between benefits from yield improvement and the added production costs. The historical gross margin of barley, wheat, forage corn, and tomato under surface, drip, permanent sprinkler, and semi-permanent sprinkler irrigation systems was generated using simulation and survey-based data for yield and published data for costs and prices over a 5-year period (2009–2015). The stochastic dominance (SD) and stochastic efficiency with respect to a function (SERF) approaches were used to evaluate the risk efficiency of various irrigation systems for main crops in the Bakhtegan Basin. Estimating certainty equivalent (CE), we ranked irrigation alternatives at different absolute risk-aversion coefficient (ra) levels. The findings show that drip irrigation systems for forage corn and tomato have higher CE values at all levels of absolute risk-aversion coefficient; however, the preferred system for barley and wheat varies with ra. Moreover, estimated risk premiums revealed that risk-neutral farmers would pay to move from surface systems to more efficient systems, whereas risk-averse farmers need to be paid to have the tendency to change their irrigation system. The important policy implication of these results is that risk premiums can consider justifying subsidy allocation in a manner that induces farmers to more risk-efficient irrigation systems.

Broiler Farming Risk and Stress Management Strategies

The broiler farming sector in tropical area suffer from high temperature and humidity stress and reduced daily bird growth rate. Small scale broiler farms at Sultanate of Oman has been performing poorly due to many constrains, including poor poultry farming practices, climate condition variability, feed grain price increase. The import of frozen poultry with cheap price and feed cost increased after Ukraine conflict and global food security issue significantly affect broiler cost of production and farming economic sustainability. Poultry feeding cost increased by 36% compared to last year due to corn and soybean grain price increased and exposed farmers to high risk and income uncertainties and jeopardize food security sustainability. The study applied Monte Carlo Simulation approach to assess risk management strategies and economic sustainability of three production level, products mix alternative under deferent market constrains. The broiler products mix and marketing constrains were examined considering different risk preference and ARAC of decisions makers. The stress analysis performed to test economic performance of alternative production strategies and identify factors affect broiler farming continuity and resilience. The overall results showed that broiler marketing risk and sale revenue volatilities is a highly uncertain and dynamically integrated complex system. Sale incentive policy need to be addressed and controlled through appropriate risk assessment and mitigation strategies and optimization production operation and control cost increase through vulnerability assessment. The net profit (baseline) scenarios with right production level and products mix following profitable market channels is more risk-efficient and sustainable compared to products mix with over supply production and without fast marketing access support channels. The study performed stochastic efficiency with respect to a function (SERF) and calculate Certain equivalent (CE) figure to rank alternative stress management strategies under stress situation. Stress management analysis showed that demand for parts and fresh products with sale revenue decline are risk averse and has highest CE figures followed by (cost frozen) products at all ARAC. The risk premium and willingness to pay analysis showed that (cost parts) products has highest risk premium figures followed by (cost fresh) and (demand frozen) products compared to baseline. The risk of cost increase needs to be monitored and controlled to avoid inside organization risk vulnerability. Risk premium (RP) needed to change from (cost fresh) to (cost frozen) products is RO 67,553 for risk neutral absolute risk aversion coefficient (ARAC). The study showed risk premium (RP) need to be paid to motivate a change from (demand frozen) alternative to (demand fresh) products activities is RO 24,928 and to change from (demand frozen) to (demand parts) is RO 64,379 for risk neutral absolute risk aversion coefficient (ARAC). Marketing incentive programs and regulating market are needed to understand broiler business risk and avoid significant loss due to sale delay and improve risk mitigation programs and imposed anti-dumping and countervailing duties on broiler products import. The risk of feed cost increase needs to be monitored and subsidized by Government to mitigate broiler farming risk and maintain business sustainability.

Measuring The Myopic Loss Aversion Premium: An Experimental Approach

ABSTRACT This paper proposes new methods to assess the myopic loss aversion premium (the expected return-differential) based on an experimental design by eliciting both willingness-to-pay and allocation percentage figures and also by inferring and comparing absolute risk aversion coefficients. Our results indicate a high level of loss aversion and support the existence of the myopic loss aversion bias.

A Game Model for Medical Service Pricing Based on the Diagnosis Related Groups.

Background: Currently there are various issues that exist in the medical institutions in China as a result of the price-setting in DRGs, which include the fact that medical institutions tend to choose patients and that the payment standard for complex cases cannot reasonably compensate the cost.Objective: The main objective is to prevent adverse selection problems in the operations of a diagnosis-related groups (DRGs) system with the game pricing model for scientific and reasonable pricing.Methods: The study proposes an improved bargaining game model over three stages, with the government and patients forming an alliance. The first stage assumes the alliance is the price maker in the Stackelberg game to maximize social welfare. Medical institutions are a price taker and decide the level of quality of medical service to maximize their revenue. A Stackelberg equilibrium solution is obtained. The second stage assumes medical institutions dominate the Stackelberg game and set an optimal service quality for maximizing their revenues. The alliance as the price taker decides the price to maximize the social welfare. Another Stackelberg equilibrium solution is achieved. The final stage establishes a Rubinstein bargaining game model to combine the Stackelberg equilibrium solutions in the first and second stage. A new equilibrium between the alliance and medical institutions is established.Results: The results show that if the price elasticity of demand increases, the ratio of cost compensation on medical institutions will increase, and the equilibrium price will increase. The equilibrium price is associated with the coefficient of patients' quality preference. The absolute risk aversion coefficient of patients affects government compensation and total social welfare.Conclusion: In a DRGs system, considering the demand elasticity and the quality preference of patients, medical service pricing can prevent an adverse selection problem. In the future, we plan to generalize these models to DRGs pricing systems with the effects of competition of medical institutions. In addition, we suggest considering the differential compensation for general hospitals and community hospitals in a DRGs system, in order to promote the goal of hierarchical diagnosis and treatment.

Multi-criteria group decision-making framework for offshore wind farm site selection based on the intuitionistic linguistic aggregation operators

Offshore wind farms have been rapidly proposed owing to the promotion of sustainable development policies. Site selection contributes to the success of offshore wind farm projects and is a complex multi-criteria group decision-making problem. This paper proposes a multi-criteria group decision-making method based on the intuitionistic linguistic aggregation operators and applies it to the site selection decision-making process of offshore wind farm. To begin with, the intuitionistic linguistic numbers are introduced to deal with the uncertainty and fuzziness in decision-making. An optimization weighting model that comprehensively considers subjective and objective factors is then established, which can effectively reflect the correlations among the criteria. Furthermore, in view of the limited rational behavior of the decision-makers, an extended intuitionistic linguistic aggregation operator is defined, according to which the criteria values can be aggregated into a numerical value for comparison. Finally, a case study in China is conducted to verify the rationality and effectiveness of this method. The research results show that the offshore wind farm located in Laizhou, Dongying is the optimal site, and the ranking results of the alternatives are sensitive to the absolute risk aversion coefficient.

Financial hedging in energy market by cross-learning machines

The recent price volatility in the energy market highlights the importance of financial hedging and the need of its incorporation into an investor’s set of portfolio strategies. Realizing the rapid advancement of artificial intelligence, our study empirically examines the use of machine learning models for hedging price risk associated with the holding of energy-based financial product. From a technical perspective, kernel regression and support vector machine are trained to estimate the time-varying optimal hedge ratio given the observed price movement and other factors. The estimated hedge ratio is then employed to guide the price hedging strategy of the crude oil contracts traded in the commodity exchanges. The two machine approaches’ hedging effectiveness against price risk is also compared with those of the un-hedged portfolio as well as a well-studied econometric time series approach. Our results indicate that the two forms of learning machines substantially outperform time series model and no-hedging over the out-of-sample period but neither machine dominates another across all testing scenarios. Given these mixed results between kernel regression and support vector machine, we propose and develop a kernel-supervised support vector machine to take advantage of the complementary nature of the two machine learning approaches and enhance the supervised learning process through hierarchical/sequential infusion of information. Cross-learning empirical testing shows that the proposed cross-learning machine is more effective in hedging than individual kernel regression and support vector machine. Furthermore, our study evaluates the impact of incorporating the coefficient of absolute risk aversion and the transaction costs to machine learning models. In general, cross-learning machine outperforms others in all tested scenarios.

Determining Risk Aversion in Share Auctions

This paper analyzes risk aversion in discriminatory share auctions. I generalize the k-step share auction model of Kastl (2011, 2012) and establish that marginal profits are set identified for any given coefficient of constant absolute risk aversion. I also derive necessary conditions for best-response behavior, which allows to fit risk preferences to the data. More, I show how the bidders' optimality conditions allow to compute bounds on the marginal profits that are tighter than those currently available. I use my results to estimate import rents from Swiss tariff-rate quotas on high-quality beef. Rents are overestimated and rent extraction is underestimated when ignoring risk aversion. Small bidders (small, privately owned butcheries) are more risk averse than large bidders (general retailers). For the fitted risk preferences, best response violations are few and uniform across bidder size.

A Compromise-Typed Variable Weight Decision Method for Hybrid Multiattribute Decision Making

The purpose of this paper is to develop a compromise-typed variable weight decision method for solving hybrid multiattribute decision making problems with multiple types of attribute values. The compromise-typed variable weight functions are defined and constructed by utility functions. Moreover, the variable weight synthesis and the orness measures based on the coefficients of absolute risk aversion are analyzed in variable weight decision making. The comprehensive values of alternatives based on the compromise-typed variable weight decision method are calculated. The decision-making results are determined according to the comprehensive values. Finally, an example and a detailed comparison analysis are presented to show the applicability and validity of the proposed method.

Effect of Social Security System on Consumption through Income and Uncertainty: Evidence from China

In our paper, we test how the social security system affects citizens’ consumption behavior through narrowing the income gap between residents with different social status and decreasing the uncertainty of income and cost. In the theoretical part, we firstly extend the model of Keynes to test the income distribution hypothesis; then, we use the coefficient of absolute risk aversion (CARA) model and a two-period model to test the uncertainty hypothesis. Empirically, (1) we use China’s data (2003–2012) to test the theoretical results, and find that the social security system has a positive effect on consumption by reducing the income gap; (2) according to a 10-year panel data (2003–2012), we find that reducing income uncertainty can increase consumption. Besides, medical insurance and endowment insurance have a positive impact on consumption by reducing citizens’ cost uncertainty, but to different extents.

Markov perfect equilibria in OLG models with risk sensitive agents

In this paper, we present an overlapping generation model (OLG for short) of resource extraction with a random production function and an altruism having both paternalistic and non-paternalistic features. All generations are risk-sensitive with a constant coefficient of absolute risk aversion. The preferences are represented by a possibly dynamic inconsistent dynamic recursive utility function with non-cooperating generations. Under general conditions on the aggregator and transition probability, we examine the existence and the uniqueness of a recursive utility function and the existence of a stationary mixed Markov Perfect Nash Equilibria.

Risk lovers, mixed risk loving and the preference to combine good with good

This paper examines the concept of 'risk loving' (that is risk seeking, intemperance, edginess, etc.), which can be characterised by preferences over simple lotteries. This paper analyses the notion of preferring to combine good with good, and bad with bad, as opposed to combining good with bad as usual. The significance of such preferences has implications on utility functions and are analysed in the paper. This paper extends Eeckhoudt and Schlesinger (2006) results to risk lovers, the results from Crainich et al. (2013) are also generalised to higher orders. We also generalise to higher orders the concept of bivariate risk seeking, introduced by Richard (1975) and called correlation loving by Epstein and Tanny (1980). In the expected utility framework, risk loving of order (N, M) coincides with the non-negativity of the (N, M)th partial derivative of the utility function. In dealing with mixed risk loving utility functions, we give several useful properties, for example, mixed risk loving is consistent with the mixture of positive exponential utilities and with non-increasing coefficients of absolute risk aversion at any order.

Upper Bounds on Risk Aversion Under Mean-Variance Utility

Based on a simple prior, this note derives upper bounds for the coefficient of absolute & relative risk aversion if utility can be written as depending linearly on the mean and variance of income.

Risk and risk management strategies of smallholder onion farmers in Sokoto state, Nigeria

The study examines risk and its management strategies among smallholder onion farmers in Sokoto State. Data were collected with the use of structured questionnaire designed to pull together information on the socioeconomic characteristics of the farmers in the area such as age, level of education, experience, family size, membership of farmer association, extension contact, risk preference of the farmers etc. Data was also collected on risk sources and risk management strategies. The primary data used were obtained from structured questionnaire administered to 120 randomly selected farmers. The analytical techniques that were used in the analysis of data were descriptive statistical tools such as means and percentages, Equally Likely Certainty Equivalent with a Purely Hypothetical Risky prospect (ELCEPH) technique and the 5-point Likert scale. The result showed that majority of the farmers are risk averse having a positive Arrow-Pratt absolute risk aversion coefficient.

Estimation of CARA Preferences and Positive Mathematical Programming

The purpose of this paper is to combine the estimation of output price risk and positive mathematical programming (PMP). It reconciles the risk programming presented by Freund with a consistent estimate of the constant absolute risk aversion (CARA) coefficient. It extends the PMP approach to calibration of realized production outputs and observed input prices. The results of this specification include 1) uniqueness of the calibrating solution, 2) elimination of the tautological calibration constraints typical of the original PMP procedure, 3) equivalence between a phase I calibrating solution and a solution obtained by combining phase I and phase II of the traditional PMP procedure. In this extended PMP framework, the cost function specification involves output quantities and input prices—contrary to the myopic cost function of the traditional PMP approach. This extension allows for a phase III calibrating model that replaces the usual linear technology with relations corresponding to Shephard lemma (in the primal constraints) and the marginal cost function (in the dual constraints). An empirical example with a sample of farms producing four crops illustrates the novel procedure.

Prudence and the convexity of compensation contracts

In a standard principal–agent model, we derive a new condition that relates the structure of the optimal contract to the agent’s risk preferences: The optimal contract is more convex than the likelihood ratio of the performance measure if and only if the coefficient of absolute prudence is larger than twice the coefficient of absolute risk aversion. With CRRA utility, this condition is satisfied if and only if relative risk aversion is less than one.

Incorporating risk in a positive mathematical programming framework: a dual approach

In this study we develop a new methodological proposal to incorporate risk into a farm-level positive mathematical programming (PMP) model. We estimate simultaneously the farm nonlinear cost function and a farmer-specific coefficient of absolute risk aversion as well as the resource shadow prices. The model is applied to a sample of representative arable crop farms from the Emilia-Romagna region in Italy. The estimation results confirm the calibration ability of the model and reveal the values of the individual risk aversion coefficients. We use the model to simulate different scenarios of crop price volatility, in order to explore the potential risk management role of an agri-environmental scheme.