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We formulate and carry out an analytical treatment of a single-period portfolio choice model featuring a reference point in wealth, S-shaped utility (value) functions with loss aversion, and probability weighting under Kahneman and Tversky's cumulative prospect theory (CPT). We introduce a new measure of loss aversion for large payoffs, called the large-loss aversion degree (LLAD), and show that it is a critical determinant of the well-posedness of the model. The sensitivity of the CPT value function with respect to the stock allocation is then investigated, which, as a by-product, demonstrates that this function is neither concave nor convex. We finally derive optimal solutions explicitly for the cases in which the reference point is the risk-free return and those in which it is not (while the utility function is piecewise linear), and we employ these results to investigate comparative statics of optimal risky exposures with respect to the reference point, the LLAD, and the curvature of the probability weighting. This paper was accepted by Wei Xiong, finance.

Drawing from prospect theory, we use an experimental study design to explore how and why reference points of managers of family and nonfamily firms differ. We contribute to research on the role of economic theories for family businesses by elaborating on decision-making mechanisms in the context of family firms. Furthermore, we investigate whether family and nonfamily managers within family firms vary in their investment decisions. Our study demonstrates the importance of price volatility as a determinant of reference points and shows how the same type of information can lead to different reference points based on whether the manager is from a family or nonfamily firm.Plain English SummaryFamily and Nonfamily Firm Managers View Investment Information Differently. It is not clear why. We show that family firm managers were less sensitive to volatility leading to more patient investments. #ManagerialChoices #Investments #FamilyFirms. To better understand why the investments of family and nonfamily firms tend to differ, we investigated how the family and nonfamily firm context shapes managers’ assessment of investment pricing information. Using an experimental study, we examined how family versus nonfamily managers react to a series of investment pricing information and whether they set a higher or lower benchmark for returns. Surprisingly, we found that the organizational context matters greatly: The type of company – family or nonfamily-owned – significantly influenced managers’ mental benchmark values for investments (reference points) and their risk perceptions. Our study also revealed that while family and nonfamily firm managers react similarly to investment purchase price, current price, and average price, their response to price volatility significantly varied. Managers from family firms were shown to be less sensitive to price volatility (i.e., great investment price fluctuations) than managers from nonfamily firms, thus suggesting that nonfamily firm managers are more likely to focus on short-term gains from investments. Understanding these dynamics offers important insight into why managers from family versus nonfamily firms approach investments differently – their benchmarks for investments vary. Recognizing managers’ diverse reactions to investment risk and price changes should therefore help firms to make more informed investment decisions and to offer more tailored training to their managers, thereby fostering more informed decisions and positive investment outcomes.

The paper discusses fish stock assessment methods, emphasising methods for assessing stocks in developing nations. We present the advantages and disadvantages of each method discussed. Approaches to fish stock assessment include single-species, multi-species, multi-gear and ecosystem approaches. We discuss the Gordon–Schaefer (GS) model, a single-species surplus production model, as an alternative method for assessing fishery stocks in developing nations, with Malawi as an example of a developing nation. Although the GS model is not a contemporary method, it is still suitable for the situation in Malawi. We review how the GS model has been applied globally, in general, and in Malawi, in particular. The review shows that most studies have concentrated on the calculation of maximum sustainable yield or maximum economic yield, leaving out open access yield and optimum sustainable yield which is the dynamic reference point. Using all reference points is crucial in making correct management decisions. Bifurcation analysis, calculation of annual sustainable production, and calculation of depletion are missing in most studies. Future research should focus on integrating the use of all four reference points, bifurcation analysis, and calculation of depletion as well as annual sustainable production.

Stock depletion level is an important concept in the assessment and management of exploited fish stocks because it is often used in conjunction with reference points to infer stock status. Both the depletion level and reference points can be highly dependent on the stock–recruitment relationship. Here, we show how depletion level is estimated in stock assessment models, what data inform the depletion level, and how the stock–recruitment relationship influences the depletion level. There are a variety of data that provide information on abundance. In addition, to estimate the depletion level, unexploited absolute abundance needs to be determined. This often means extrapolating the abundance back in time to the start of the fishery, accounting for the removals and the productivity. Uncertainty in the depletion level arises because the model can account for the same removals by either estimating low productivity (e.g., low natural mortality) and high carrying capacity or high productivity and a low carrying capacity, and by estimating different relationships between productivity and depletion level, which are strongly controlled by the stock–recruitment relationship. Therefore, estimates of depletion are particularly sensitive to uncertainty in the biological processes related to natural mortality and the stock–recruitment relationship and to growth when length composition data are used. In addition, depletion-based reference points are highly dependent on the stock–recruitment relationship and need to account for recruitment variability, particularly autocorrelation, trends, and regime shifts. Future research needs to focus on estimating natural mortality, the stock–recruitment relationship, asymptotic length, shape of the selectivity curve, or management strategies that are robust to uncertainty in these parameters. Tagging studies, including close-kin mark-recapture, can address some of these issues. However, the stock–recruitment relationship will remain uncertain.

Objective To support the movement in marine fisheries management toward ecosystem‐based fisheries management by exploring ecosystem‐level reference points (ELRPs) as an option for managing fisheries at the ecosystem level. An ELRP is an ecosystem harvest level or indicator with one or more associated benchmarks or thresholds (i.e., targets, limits) to identify, monitor, or maintain desirable ecosystem conditions and functions. Methods This paper explores the development and implementation of ELRPs in fisheries management to support ecosystem and fisheries sustainability, help identify when ecosystem changes that impact fisheries resources occur, and foster discussions of trade‐offs in management decisions. Result We organize existing and potential ELRPs into five categories (statistical analysis of nonlinear dynamics and tipping points, ecosystem productivity, ecosystem trophic information, biodiversity, and human dimensions), provide an overview of analytical methods that can estimate ELRP benchmarks, provide examples of where ELRP benchmarks are being used today, and evaluate pros and cons of the different ELRP categories. We also attempt to identify potential next steps for fisheries scientists and managers to further the science, development, and application of ELRPs. Conclusion Ecosystem‐level reference points can be used as a proactive accountability mechanism to achieve ecosystem objectives and maintain the ecosystem in a preferred operating space or as an early warning that ecosystem‐level changes (e.g., tipping points) could be imminent if current biological and ecological trends in the system continue. Impact statement Ecosystem‐level reference points (ELRPs) are a fundamental concept in ecosystem‐based fisheries management (EBFM) that are not currently being used to their full potential. Given the challenges associated with managing fisheries in a changing climate, this paper highlights ELRPs as a tool to advance the field of EBFM in the United States and globally.

Assessing the state of exploitation of a resource is key to its management. In the fishery of the blue shrimp, Penaeus stylirostris , off the central-eastern coast of the Gulf of Baja California, this assessment process is critical for two reasons: the data is limited because only catch and effort data are available, and the dynamic biomass model is not applicable to short-lived (annual) species. In this study, a procedure based on the Leslie model was used, and applied to the last 15 annual fishing seasons (2006 to 2021). Estimates of the monthly biomass per fishing season, the corresponding harvest rates ( HR y ), and indicators for the survival ratio, s y , representing the remaining stock at the end of the fishing season (essentially spawners), and the fishery’s recruitment rate, ρ y , at the beginning of the fishing season, were obtained. These last two quantities, s y and ρ y , were related to identify a limit biological reference point that reflects the replacement level for the shrimp stock, defined here as the limit for population renewal rate, PRR Lim . Initially, a Kobe diagram was constructed based on HR y and s y , which indicated a sustainable fishery status that requires management measures to limit fishing to keep it sustainable, which is currently being implemented. A Kobe diagram was also constructed based on ρ y , instead of s y , yielding the same results. Additionally, we used Kobe’s diagrams to show the contribution of the environment and an ecosystem-based reference point.

In Europe, implementation of sustainable fisheries management has been reinforced in the latest common fisheries policy, and presently marine fish stocks are mostly managed through assessment of their exploitation and ecological status compared to reference points such as Maximum Sustainable Yield (MSY). However, MSY and its associated fishing mortality rate FMSY are sensitive to both stock characteristics and environment conditions. In parallel, climate change impacts are increasingly affecting fish stocks directly and indirectly but might also change the exploitation reference points and the associated level of catch. Here we explored the variability of MSY reference points under climate change by using a multi-species model applied to the Eastern English Channel, a highly exploited semi-continental sea. The spatial individual-based OSMOSE explicitly represents the entire fish life cycle of 14 species interacting through size-based opportunistic predation. The model was first parameterized and run to fit the historical situation (2000-2009) and then used to assess the ecosystem state for the 2050-2059 period, using two contrasting climate change scenarios (RCP 4.5 and RCP 8.5). For each condition, a monospecific MSY estimation routine was performed by varying species fishing mortality independently and allowed estimation of reference points for each species. The FMSY estimated with OSMOSE were mostly in accordance with available values derived from stock assessment and used for fishing advice. Evolution of reference points with climate change was compared across species and highlighted that overexploited cold-water species are likely to have both MSY and FMSY declining with climate warming. Considering all species together, MSY under RCP scenarios was expected to be higher than historical MSY for half of them, with no clear link with species temperature preferences, exploitation status or trophic level, but in relation with expected change of species biomass under climate change. By contrast, for 80% of cases FMSY projections showed consistent decreasing pattern as climate conditions changed from historical to RCP scenarios in the Eastern English Channel. This result constitutes a risk for fisheries management, and anticipation of climate change impacts on fish community would require targeting a smaller fishing mortality than FMSY to ensure sustainable exploitation of marine stocks.

Fisheries bycatch threatens populations of marine megafauna such as marine mammals, turtles, seabirds, sharks and rays, but fisheries impacts on non-target populations are often difficult to assess due to factors such as data limitation, poorly defined management objectives and lack of quantitative bycatch reduction targets. Limit reference points can be used to address these issues and thereby facilitate adoption and implementation of mitigation efforts. Reference points based on catch data and life history analysis can identify sustainability limits for bycatch with respect to defined population goals even when data are quite limited. This can expedite assessments for large numbers of species and enable prioritization of management actions based on mitigation urgency and efficacy. This paper reviews limit reference point estimators for marine megafauna bycatch, with the aim of highlighting their utility in fisheries management and promoting best practices for use. Different estimators share a common basic structure that can be flexibly applied to different contexts depending on species life history and available data types. Information on demographic vital rates and abundance is required; of these, abundance is the most data-dependent and thus most limiting factor for application. There are different approaches for handling management risk stemming from uncertainty in reference point and bycatch estimates. Risk tolerance can be incorporated explicitly into the reference point estimator itself, or probability distributions may be used to describe uncertainties in bycatch and reference point estimates, and risk tolerance may guide how those are factored into the management process. Either approach requires simulation-based performance testing such as management strategy evaluation to ensure that management objectives can be achieved. Factoring potential sources of bias into such evaluations is critical. This paper reviews the technical, operational, and political challenges to widespread application of reference points for management of marine megafauna bycatch, while emphasizing the importance of developing assessment frameworks that can facilitate sustainable fishing practices.

We examine the effect of an irrelevant task that may become a reference point on subjects’ effort, feelings and perceptions. All subjects complete up to 25 tasks and are paid $0.10 per task solved correctly. However, some subjects have an easy task of finding one letter and others have a hard task of finding two letters. In the irrelevant-task treatment conditions subjects are told about the two types of tasks and are then assigned randomly to one. In addition, there are two control conditions, and in each control condition subjects are assigned to a specific task without the other task being possible or mentioned. Subjects in the irrelevant-task treatments express more positive (negative) feelings when assigned to the easy (hard) task. The control conditions that have no reference point of another task are in between the two irrelevant-task treatments in the feeling ratings. We hypothesized that for a given task, the subjects in the experimental conditions that have more positive feelings will also solve more tasks, but this hypothesis was not supported by the data. Finally, subjects who receive the easy task complete more tasks than the ones with the hard task.

This paper studies the grey target evaluation model of science and technology talents by drawing on the ‘dominant-implicit’ double reference point. Input and output perspectives are adopted and developed to establish a dominant reference point for the evaluation of science and technology talents, which takes into account the ‘Peer-Status quo’ and ‘Baseline-History’, as well as an implicit reference point, such as the ‘Expectation-Opportunity’ and ‘Goal-Preference’. The framework of the grey target evaluation model for science and technology talents is then constructed and given a dual reference (dominant–implicit). The spherical grey target on the maximum, minimum and arithmetic mean values of the target effect measure values of each reference point is established to determine the reference point weight under the input and output indicators. This research will contribute to the comprehensive effect measure value and the ranking of results that relate to science and technology talents and will demonstrate that its applied method is feasible.