This paper proposes a theoretical insurance model to explain well-documented loss underreporting and to study how strategic underreporting affects insurance demand. We consider a utility-maximizing insured who purchases a deductible insurance contract and follows a barrier strategy to decide whether she should report a loss. The insurer adopts a bonus-malus system with two rate classes, and the insured will move to or stay in the more expensive class if she reports a loss. First, we fix the insurance contract (deductibles) and obtain the equilibrium reporting strategy in semi-closed form. A key result is that the equilibrium barriers in both rate classes are strictly greater than the corresponding deductibles, provided that the insured economically prefers the less expensive rate class, thereby offering a theoretical explanation to underreporting. Second, we study an optimal deductible insurance problem in which the insured strategically underreports losses to maximize her utility. We find that the equilibrium deductibles are strictly positive, suggesting that full insurance, often assumed in related literature, is not optimal. Moreover, in equilibrium, the insured underreports a positive amount of her loss. Finally, we examine how underreporting affects the insurer’s expected profit.

This study investigates the impacts of behavioral finance on stock market volatility. The primary aims are to explain the reasons behind changes in the S&P 500 price within the context of behavioral finance and to analyze investor behavior in response to these changes. To achieve this, the research employs time-series analysis over a 10-year period, focusing on the S&P 500, real interest rates, consumer confidence, market volatility and credit default swaps while considering the effects of behavioral biases. The findings reveal several significant correlations: rising real interest rates negatively affect stocks due to loss aversion and sentiment. Conversely, higher consumer confidence tends to positively influence the stock market, driven by herding behavior and optimism. Additionally, market volatility shows a negative correlation with the S&P 500, influenced by risk aversion, recency bias and herding behavior. Moreover, an increase in credit default swap rates leads to stock market declines, primarily influenced by risk perception, loss aversion and herding behavior.

This paper studies dynamic reinsurance contracting and competition problems under model ambiguity in a reinsurance market with one primary insurer and n reinsurers, who apply the variance premium principle and who are distinguished by their levels of ambiguity aversion. The insurer negotiates reinsurance policies with all reinsurers simultaneously, which leads to a reinsurance tree structure with full competition among the reinsurers. We model the reinsurance contracting problems between the insurer and reinsurers by Stackelberg differential games and the competition among the reinsurers by a non-cooperative Nash game. We derive equilibrium strategies in semi-closed form for all the companies, whose objective is to maximize their expected surpluses penalized by a squared-error divergence term that measures their ambiguity. We find that, in equilibrium, the insurer purchases a positive amount of proportional reinsurance from each reinsurer. We further show that the insurer always prefers the tree structure to the chain structure, in which the risk of the insurer is shared sequentially among all reinsurers.

Faced with risky yields and returns, risk-averse farmers require a premium to take risks. In this paper, we estimate individual farmers’ degrees of risk aversion to adjust for the risk premium in returns and to replace the farmers’ realized returns with their certainty equivalent returns in the production function. In that way, the effect of the inputs on returns will automatically be risk-adjusted, i.e., we obtain risk-adjusted marginal effects of inputs, which can be used in decision-making support of farmers’ input choices in production. Using farm-level data from organic basmati rice smallholders in India, we illustrate this method using nonparametric production functions. The results show that the input elasticities and returns-to-scale estimates change when the farmers’ degree of risk aversion is taken into consideration.

The goal of natural resource damage assessment (NRDA) is to compensate the public for losses to natural resources from past or ongoing hazardous releases, including losses that may persist into the future. Compensation is delivered in the form of restoration projects. Resolving NRDA liability requires balancing losses and restoration benefits over multiple decades and converting them into a present value for calculating appropriate damages. For the past two decades, NRDA practitioners have used a real discount rate of 3 % to convert losses and benefits to a present value equivalent. That rate was based, in part, on real historical yields on risk-free debt (e.g., the real rate of return on 3-month Treasury bills). Declining interest rates on risk-free debt in recent years has led to suggestions to reexamine the historical consensus discount rate. This paper reviews two alternative conceptual paradigms for selecting a discount rate in NRDA cases: the social rate of time preference and discount rates for tort cases. We summarize historical data for empirically implementing the two paradigms and discuss the ramifications of the different options. Based on our review, we suggest maintaining the 3 % consensus as a practical solution to a range of empirical candidates within the two conceptual paradigms.

Most decisions involving risk are not taken in isolation. In addition to the risk from that decision, other independent, so-called ‘background’ risks, are considered. Our research adds to the growing evidence that this background risk influences risk-taking. We report results from a repeated lab-in-the-field investment task with Senegalese fishers in the presence of background risk related to their fishing income and their health. Our measure of background risk is the monthly wind condition. Without controls, we find that fishers act on average intemperately. Adding controls, we find that the impact of background risk on risk-taking—measured as the investment in the investment task—depends on the boat size of the fishers. When dividing the sample according to wealth, we find temperate behavior for the relatively poorer group and intemperate behavior that depends on boat lengths for the relatively richer group. Our results show the interrelations between background risk and context factors.

We analyze how taxes affect the choice between a life-long annuity and a one-off lump sum payment, the so-called annuitization decision. Using administrative data from a large Swiss pension fund, we impute taxes for the lump sum and the life-long annuity option. We show that taxes can explain a significant part of the variation in annuity rates. Exploiting kinks in the tax schedule of the one-off lump sum, we further find evidence for tax optimization strategies. Our findings suggest that individuals react strongly to tax incentives when making retirement choices.

Cleaner cooking is an important policy objective in the bid to achieve sustainable development. Despite efforts to encourage cleaner cooking fuel use, biomass fuel is still widely used in many developing countries. This study investigates the role of behavioral factors, particularly risk aversion, in the choice of cooking fuels in Ghana. In addition, we investigate how the improvement of supply infrastructure and services mitigates the impact of risk preferences in fuel choices. By employing data from the recent round of the Ghana Living Standards Survey, we find that risk-averse households are less likely to choose liquified petroleum gas as their cooking fuel. However, the effect is mitigated for households located in districts with more supply infrastructure. Additional analyses reveal the influence of risk and time preferences in other household behavior.

We study the optimal investment strategy to minimize the probability of lifetime ruin under a general mortality hazard rate. We explore the error between the minimum probability of lifetime ruin and the achieved probability of lifetime ruin if one follows a simple investment strategy inspired by earlier work in this area. We also include numerical examples to illustrate the estimation. We show that the nearly optimal probability of lifetime ruin under the simplified investment strategy is quite close to the original minimum probability of lifetime ruin under reasonable parameter values.

We present two models that shed light on two issues in the political economy of populism: incumbents who refuse to give up office following a democratic election; and politicians gambling with major policy shifts when their consequences are uncertain. In the democratic transition of power, common knowledge about the veracity of the election process enables citizens to threaten incumbents with protests if they attempt to retain their seats in power. If doubt over electoral integrity prevails, office-seeking incumbents sometimes reject electoral rules. In considering policy gambles, politicians supply policy shifts in response to voters and elites vying for a greater share of economic output. When the mapping from policy to outcomes is uncertain, voters opt for policy gambles, even though these are detrimental to their ex ante welfare, to redress the division of output. These models underscore the importance of institutions that address the source of each coordination failure.

Farm diversification is mainly driven by risk mitigation effects and economic gains related to complementarities between production activities. By combining these two aspects, we investigate diversification economies in a sample of French mixed sheep farming systems and rank these systems using stochastic dominance criteria. Partially diversified systems (Sheep-Grass, Sheep-Crop, Sheep-Landless) and fully diversified systems (Sheep-Grass-Crop-Landless) were evaluated. We find a high degree of diversification diseconomies in the sheep farming systems considered. The results also indicate that the fully diversified system is driven by its risk-reducing effects (including downside risk exposure) and that Sheep-Crop is the dominant system in terms of risk-adjusted returns.

This paper investigates the benefits of incorporating diversification effects into the pricing process of insurance policies from two different business lines. The paper shows that, for the same risk reduction, insurers pricing policies jointly can have a competitive advantage over those pricing them separately. However, the choice of competitiveness constrains the underwriting flexibility of joint pricers. The paper goes a step further by modelling explicitly the relationship between premiums and the number of customers in each line. Using the total collected premiums as a criterion to compare the competing strategies, the paper provides conditions for the optimal pricing decision based on policyholders’ sensitivity to price discounts. The results are illustrated for a portfolio of annuities and assurances. Further, using non-life data from the Brazilian insurance market, an empirical exploration shows that most pairs satisfy the condition for being priced jointly, even when pairwise correlations are high.

This paper reflects on the notion of partial ambiguity. Using a framework decomposing ambiguity into distinct layers of analysis, among which are risk and model uncertainty, and allowing for different attitudes toward these layers, I show that partial ambiguity may prove less desirable than full ambiguity, even under ambiguity aversion. This observation poses difficulties for interpreting the notion of partial ambiguity in relation to the partial information available to determine the potential compositions of an ambiguous urn. Two Ellsberg-style thought experiments are described to challenge the meaning of partial ambiguity further, and an alternative interpretation, based on a more ambiguous relation, is discussed.

The present article describes the main insights deriving from the papers collected in this special issue which jointly provide a ‘room with a view’ on some of the most relevant issues in climate policy such as: the role of uncertainty, the distributional implications of climate change, the drivers and applications of decarbonizing innovation, the role of emissions trading and its interactions with companion policies. While looking at different issues and from different angles, all papers share a similar attention to policy aspects and implications, especially in developing countries. This is particularly important to evaluate whether and to what extent the climate policies adopted thus far in developed countries can be replicated in emerging economies.

In this paper, the optimal insurance design is studied from the perspective of an insured, who faces an insurable risk and a background risk. For the reduction of ex post moral hazard, alternative insurance contracts are asked to satisfy the principle of indemnity and the incentive-compatible condition. As in the literature, it is assumed that the insurer calculates the insurance premium solely on the basis of the expected indemnity. When the insured has a general mean-variance preference, an explicit form of optimal insurance is derived explicitly. It is found that the stochastic dependence between the background risk and the insurable risk plays a critical role in the insured’s risk transfer decision. In addition, the optimal insurance policy can often change significantly once the incentive-compatible constraint is removed.

Firm operators continually manage multiple sources of risk. In an application to cattle feedlot operations, our objective is to determine if producers view output price and animal health risks separately or jointly. We conduct a survey with a choice experiment placing operators in forward looking, decision-making scenarios, and capture information on past risk management approaches. Evidence regarding a relationship between animal health and output price risk mitigation is mixed and depends on the decision being made. Combined, these results provide new insight into how managers approach multiple risks when facing resource constraints.

Much of public policy-making has in recent decades been driven by the idea of evidence-based policy – policy rooted in the principles of social science and, more specifically, empirical validation based on social and behavioural science. This article argues that evidence-based policy, while helping to improve the design of policies aimed at changing individual behaviour, lacks a recognition that individual and group choices are embedded in social relationships and institutions. There is a risk of over-relying not only on probabilistic models that under-state our condition of ‘radical uncertainty’ but also on data and metrics that are disconnected from the everyday experience of workers and citizens whose needs and interests cannot always be measured or managed. Since uncertainty is a fundamental reality of both the economy and social life, policy-making needs robust conceptual narratives to make sense of numbers and provide a sound basis on which to make decisions allied to ethical judgements.

This paper presents my thinking and concerns about formation of COVID-19 policy. Policy formation must cope with substantial uncertainties about the nature of the disease, the dynamics of transmission, and behavioral responses. Data uncertainties limit our knowledge of the past trajectory and current state of the pandemic. Data and modeling uncertainties limit our ability to predict the impacts of alternative policies. I explain why current epidemiological and macroeconomic modeling cannot deliver realistically optimal policy. I describe my recent work quantifying basic data uncertainties that make policy analysis difficult. I discuss approaches for policy choice under uncertainty and suggest adaptive policy diversification.

Defined contribution (DC) pension plans have been gaining ground in the last 10–20 years as the preferred system for many countries and other agencies, both private and public. The central question for a DC plan is how to invest in order to reach the participant's retirement goals. Given the financial illiteracy of the general population, it is common to offer a default policy for members who do not actively make investment choices. Using data from the Chilean system, we discuss an investment model with fixed contribution rates and compare the results with the existing default policy under multiple objectives. Our results indicate that the Chilean default policy has good overall performance, but specific closed-loop policies have a higher probability of achieving desired retirement goals and can reduce the expected shortfall at retirement.

We study climate change policies using the novel pattern scaling approach of regional transient climate response in order to develop a regional economy–climate model under conditions of deep uncertainty. We associate welfare weights with regions and analyze cooperative outcomes derived by the social planner's solution at the regional scale. Recent literature indicates that damages are larger in low latitude (warmer) areas and are projected to become relatively even larger in low latitude areas than at temperate latitudes. Under deep uncertainty, robust control policies are more conservative regarding emissions and, when regional distributional weights are introduced, carbon taxes are lower in the relatively poorer region. Mild concerns for robustness are welfare improving for the poor region, while strong concerns have welfare cost for all regions. We show that increasing regional temperatures will increase resources devoted to learning, in order to reduce deep uncertainty.