Fairness Considerations Research Articles

Perceptions and Motivations for Uterus Transplant in Transgender Women

Uterus transplant has been demonstrated to be a viable fertility-restoring treatment for women categorized as female at birth with absolute uterine factor infertility. Recent advancements, as well as considerations of fairness and equality in reproductive care, have now led to the possibility of uterus transplant being undertaken in transgender women. To investigate the reproductive aspirations of transgender women and their perceptions of uterus transplant. This cross-sectional survey study used a 27-item electronic questionnaire to investigate the reproductive aspirations of 182 transgender women older than 16 years, including their perceptions of and motivations for uterus transplant, between May 1 and November 1, 2019. Perceptions of and motivations for uterus transplant, including perceived significance of the ability to gestate, menstruate, and have a physiologically functioning vagina. A total of 182 transgender women completed the questionnaire; most women (109 [60%]) were aged 20 to 29 years. Most did not have children prior to transitioning (167 [92%]) and expressed a desire to have children in the future (171 [94%]). In addition, most respondents agreed or strongly agreed that the ability to gestate and give birth to children (171 [94%]) and menstruate (161 [88%]) would enhance perceptions of their femininity. Similarly, high proportions strongly agreed or agreed that having a transplanted, functioning vagina would improve their sexual experience (163 [90%]), improve their quality of life (163 [90%]), and help them to feel like more of a woman (168 [92%]). Nearly all respondents (180 [99%]) believed that uterus transplant would lead to greater happiness in transgender women. More than three-quarters of the respondents (140 [77%]) strongly agreed or agreed that they would be more inclined to cryopreserve sperm if uterus transplant became a realistic option. This study provides insights into the reproductive aspirations of transgender women and reports on their multifaceted motivation to undergo uterus transplant. The survey responses suggest that transgender women would choose to have female physiologic experiences, such as menstruation and gestation, as well as potentially having a physiologically functioning transplanted vagina. If proven feasible and safe in this setting, uterus transplant may facilitate the achievement of reproductive aspirations, improve quality of life, and further alleviate dysphoric symptoms in transgender women.

Research of Dual-channel Supply Chain Decision with Consideration of Low-carbon and Fairness Concerns

With in-depth implementation of policies on energy conservation and emission reduction and rising of low-carbon production practice in enterprises, low-carbon supply chain has gradually become a research issue which causes extensive attentions from scholars. However, most existing researches focus on supply chain decision and coordination under the background of single channel or mere consideration of fairness concerns of retailers. Therefore, the fairness concerns of manufacturers were taken into account in the double-channel low-carbon supply chain. A double-channel low-carbon supply chain model was constructed to research the influence of manufacturers’ fairness concerns to the optimal decision-making of all parties in the supply chain and to the overall performance of supply chain. The research results suggested that: with improvement of manufacturers’ fairness concern coefficient, the decision-making of supply chain members demonstrated different changing strength; the manufacturers’ fairness concern caused harm to overall profit of supply chain.

On the Fairness of Time-Critical Influence Maximization in Social Networks

Influence maximization has found applications in a wide range of real-world problems, for instance, viral marketing of products in an online social network, and information propagation of valuable information such as job vacancy advertisements and health-related information. While existing algorithmic techniques usually aim at maximizing the total number of people influenced, the population often comprises several socially salient groups, e.g., based on gender or race. As a result, these techniques could lead to disparity across different groups in receiving important information. Furthermore, in many of these applications, the spread of influence is time-critical, i.e., it is only beneficial to be influenced before a time deadline. As we show in this paper, the time-criticality of the information could further exacerbate the disparity of influence across groups. This disparity, introduced by algorithms aimed at maximizing total influence, could have far-reaching consequences, impacting people's prosperity and putting minority groups at a big disadvantage. In this work, we propose a notion of group fairness in time-critical influence maximization. We introduce surrogate objective functions to solve the influence maximization problem under fairness considerations. By exploiting the submodularity structure of our objectives, we provide computationally efficient algorithms with guarantees that are effective in enforcing fairness during the propagation process. We demonstrate the effectiveness of our approach through synthetic and real-world experiments.

Why Do People Demand Rent Control?

We conduct a representative survey experiment in Germany to understand why people support inefficient policies. In particular, we measure beliefs about and preferences for rent control -- a policy that is widely regarded as harmful by experts. To tease out causal mechanisms, we provide randomly selected subsets of participants with empirical estimates about the effects of rent control on rent prices and housing supply and with information about the consensus among economists against rent control. We find that people update their beliefs and that this leads to lower demand for rent control. Left-wingers update their beliefs more strongly, which reduces the ideological gap in support for rent control by about one-third. Providing information about economists' rejection of this policy leads to the largest reduction in support. However, the main drivers of support for rent control are fairness considerations and profit motives. Our study also highlights the importance of trust in expert advice since treatment effects are consistently larger among those who indicate trust in expert advice. Finally, an obfuscated follow-up survey conducted three weeks later reveals that the effects, both on support for rent control and on beliefs, persist only for those who trust.

Financial Risk Management and Explainable Trustworthy Responsible AI

This perspective paper is based on several sessions by the members of the Round Table AI at FIRM , with input from a number of external and international speakers. Its particular focus lies on the management of the model risk of productive models in banks and other financial institutions. The models in view range from simple rules-based approaches to Artificial Intelligence (AI) or Machine learning (ML) models with a high level of sophistication. The typical applications of those models are related to predictions and decision making around the value chain of credit risk (including accounting side under IFRS9 or related national GAAP approaches), insurance risk or other financial risk types. We expect more models of higher complexity in the space of anti money laundering, fraud detection and transaction monitoring as well as a rise of AI/ML models as alternatives to current methods in solving some of the more intricate stochastic differential equations needed for the pricing and/or valuation of derivatives. The same type of model is also successful in areas unrelated to risk management, such as sales optimization, customer lifetime value considerations, robo-advisory and other fields of applications. The paper makes reference to recent related publications from central banks, financial supervisors and regulators as well as by other relevant sources and working groups. It aims to give practical advice for establishing a risk-based governance and test framework for the mentioned model types and also discusses the use of recent technologies, approaches and platforms to support the establishment of responsible, trustworthy, explainable, auditable and manageable AI/ML in production. In view of the recent EU publication on AI (see European Commission 2021), also referred to as the EU Artificial Intelligence Act (AIA), we also see a certain added value for this paper as an instigator of further thinking outside of the financial services sector, in particular where “High Risk” models according to the mentioned EU consultation are concerned. Our key takeaways are: 1. There need to be general principles, requirements and tests to control model risk and fitness-for-purpose for each model. Particularly because AI is not a fixed category, we are talking about a spectrum of mathematical models of varying complexity, of which gradually more and more complex ones are becoming feasible. With regards to this fact, the mentioned governance elements (principles, requirements, tests to control model risk etc.) should hinge upon models’ respective purposes, influence on human lives and business impact, rather than upon model design or complexity. To satisfy these requirements of course, special tests will be necessary for more complex or even dynamic models. This holds true especially for the implementation of those models and their utilization in a scaling enterprise production environment. 2. To this end, it will be necessary and useful to combine the expertise and approaches of classical risk management and governance with those of data science and AI knowledge. 3. Many aspects of AI governance, algorithmic auditing and risk management of AI systems can be addressed with technology and computing platforms. In fact, an entire industry is about to emerge in this area. Many of the necessary techniques essentially consist of the use of somewhat less complex and more transparent models in their own right, with associated cost for maintenance and operation, and with inherent (more indirect and smaller) risks to operate them. Hence, there will always be residual risk and consequentially a need for human oversight. The level of residual risk should be covered via OpRisk Management (IT risk, mal-decisioning risk, reputational risk) and by AI incident management or AI model insurance. 4. Explainability, interpretability and transparency of models, data and decision making will be key to even enable an appropriate possibility to manage remaining model risks (“Explaining Explainable AI”). All three need to be directed towards the internal stakeholders of financial institutions, but – depending on model purpose – also towards the outside world, particularly to clients/consumers and supervisors. Each stakeholder needs to be informed about the model aspects in a different and specific way. There are technologies and experts to support interfacing the different domains involved. 5. One particular aspect of the “Explainable AI” agenda is to enable the fairness of AI decision making or decision support from a societal perspective (linked to the ESG agenda). The associated fairness considerations, starting from the need to explicitly define a notion of fairness and enable its implementation and ongoing validation, are by no means exclusive to AI modelling techniques. They pertain to classical decision making to the same extent; however, due to their lack of innate transparency, the cost of fairness will be higher for AI models. This should be taken into account in the business decisions around the choice of model design.

Dynamic Pricing with Fairness Constraints

Following the increasing popularity of personalized pricing, there is a growing concern from customers and policy makers regarding fairness considerations. This paper studies the problem of dynamic pricing with unknown demand under two types of fairness constraints: price fairness and demand fairness. For price fairness, the retailer is required to (i) set similar prices for different customer groups (called group fairness) and (ii) ensure that the prices over time for each customer group are relatively stable (called time fairness). We propose an algorithm based on an infrequently-changed upper-confidence-bound (UCB) method, which is proved to yield a near-optimal regret performance. In particular, we show that imposing group fairness does not affect the demand learning problem, in contrast to imposing time fairness. On the flip side, we show that imposing time fairness does not impact the clairvoyant optimal revenue, in contrast to imposing group fairness. For demand fairness, the retailer is required to satisfy that the resulting demand from different customer groups is relatively similar (e.g., the retailer offers a lower price to students to increase their demand to a similar level as non-students). In this case, we design an algorithm adapted from a primal-dual learning framework and prove that our algorithm also achieves a near-optimal performance.

Money Versus Social Rank: An Empirical Investigation of Unfairness in Social Anxiety

Social anxiety (SA) is characterized by marked difficulties in forming and maintaining social relationships. Several theoretical perspectives suggest that individuals with social anxiety tend to prioritize social rank goals. As such, the socially anxious view the world in hierarchical rather than cooperative terms. One hundred and eleven participants were assigned to one of three subgroups based on SA severity and depressed mood. The resulting subgroups consisted of participants with elevated levels of SA, with and without depressed mood (n = 46 and n = 24, respectively) as well as non-anxious participants (n = 41). By using an asymmetrical Ultimatum Game (UG) in which participants’ identities were concealed, we sought to investigate how SA levels modulate behavioural responses to unfair treatment and to subsequent fairness considerations. Overall, SA was associated with higher rejection rates of unfair splits, which suggests that participants with elevated SA prioritize fairness over financial maximization. Our findings also show that SA was associated with a tendency toward costly punishment, that is, both SA subgroups engaged in more punitive actions in spite of financial loss. Taken together, our findings show that given the chance, individuals with elevated SA can resort to active punishment instead than acting submissively in asymmetric interactions, in partial disagreement with theoretical models of SA. We further advance that social rank threats are important drivers of punitive actions in SA. Empirical and practical implications, as well as interpretative caveats, are discussed.

Fairness-Aware Link Optimization for Space-Terrestrial Integrated Networks: A Reinforcement Learning Framework

The integration of space and air components considering satellites and unmanned aerial vehicles (UAVs) into terrestrial networks in a space-terrestrial integrated network (STIN) has been envisioned as a promising solution to enhancing the terrestrial networks in terms of fairness, performance, and network resilience. However, employing UAVs introduces some key challenges, among which backhaul connectivity, resource management, and efficient three-dimensional (3D) trajectory designs of UAVs are very crucial. In this paper, low-Earth orbit (LEO) satellites are employed to alleviate the backhaul connectivity issues with UAV networks, where we address the problem of jointly determining backhaul-aware 3D trajectories of UAVs, resource management, and associations between users, satellites and base stations (BSs) in an STIN while satisfying ground users' quality-of-experience requirements and provisioning fairness concerning users' data rates. The proposed approach maximizes a novel objective function with joint consideration for BS's load and fairness, which can be categorized as a non-deterministic polynomial time hard (NP-hard) problem. To tackle this issue, we leverage a reinforcement learning framework, in which our problem is modeled as a multi-armed bandit problem. Accordingly, BSs learn the environment and its dynamics and then make decisions under an upper confidence bound based method. Simulation results show that our proposed approach outperforms the benchmark methods in terms of fairness, throughput, and load.

Penal Substitutionism, Divine Justice, and the Existence of God

Professor William Lane Craig argues that a particular set of concerns about the Christian doctrine of penal substitution (namely, that Jesus of Nazareth was sacrificed for the sins of humanity) can be satisfied. This article provides rebuttals to said replies in an attempt to render plausible the claim that God exists to the extent that God is perfectly just, and that divine justice requires, among other things, that God never engage in the harming of innocents, consistent with any doctrine of retributivism worthy of the name. The doctrine of God, then, must remain consistent with unqualified negative retributivism. Any theism which might suggest otherwise violates such vital considerations of justice and fairness and must be rejected.

Coverage-Aware Recharging Scheduling Using Mobile Charger in Wireless Sensor Networks

Energy recharging in wireless rechargeable sensor networks (WRSNs) has acquired much attention in recent years. In literature, many recharging path construction algorithms have been proposed. Most of them considered that all sensors are equally important and designed algorithms to increase the number of recharged sensors or decrease the path length of the mobile charger. However, different sensors have different coverage contributions. Recharging the sensors with larger coverage contribution can achieve better surveillance quality. The proposed recharging scheduling algorithm is divided into three phases, including the Initialization, Recharging Scheduling and Path Construction Phases. In the second phase, this paper proposed two recharging scheduling algorithms, namely the Cost-Effective (CE) algorithm and Cost-Effective with Considerations of Coverage and Fairness ( C <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> F) algorithm. The proposed two algorithms construct paths for the mobile charger and select the recharging sensors based on the higher weight in terms of larger coverage contribution and smaller path cost. Performance results show that the CE and C <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> F algorithms yield better performance in terms of the fairness of recharging, recharging stability and coverage ratio, as compared with the existing studies.

A MINIMAL ROLE FOR MINIMUM TAXES

The 2017 Tax Cuts and Jobs Act eliminated the alternative minimum tax for corporations and sharply eviscerated the alternative minimum tax for individuals. Yet recently there has been a resurgence of interest in minimum taxes both for the international tax systems and in certain domestic contexts.&#x0D; This Article argues that there should be a role, but a very minimal one, for minimum taxes in our tax system. While reasonable arguments have been put forward for minimum taxes, on closer examination, many of these arguments are found wanting. This Article, however, does make a second-best case for one type of minimum tax, namely as a backstop for a potentially flawed or deficient tax. That is the “minimal role for a minimum tax.”&#x0D; To develop this argument, I explore three distinct theoretical rationales for minimum taxes that have been put forward. First, I discuss the distinction between unilateral and multilateral minimum taxes and the potential role that multilateral minimum taxes can play in alleviating concerns that arise from tax competition and the presence of tax havens. While unilateral minimum taxes may have a strong rationale, the rationale for multilateral minimum taxes is not compelling. Second, I show how considerations of fairness, public perception, and alternative views of the corporation create a demand for minimum taxes. This demand, however, can be satisfied in other ways. Finally, I discuss how the imperfect targeting of tax preferences and practical limitations in the design and effectiveness of the most common taxes can provide a potential, but limited, efficiency rationale for the use of minimum taxes. I lastly provide an example of the use of minimum taxes for reforming state corporate taxation.

Елементи адміністративно-правового статусу Державної виконавчої служби України

High-quality execution of court decisions and decisions of other bodies is one of the main priorities of the Ministry of Justice of Ukraine, as the state must not only ensure fair consideration of cases in courts and other bodies, but also guarantee fair, high-quality and fast execution of such decisions. This task is assigned to the bodies of the State Executive Service and private bailiffs.Reform of execution of court decisions in general and the bodies of the State Executive Service in particular is key one both for Ukraine and the Ministry of Justice of Ukraine. The steps already taken in the area of ​​judicial reform and are being implemented today are yielding positive results, but the reform should be continued. In future, it is necessary to ensure the protection of society by ensuring obligatory enforcement of court decisions by modernizing the service of state bailiffs and protecting private bailiffs for the execution of court decisions.Any state body must have a clear legal status in order to function effectively. The current legal status of the State Executive Service of Ukraine is determined by the Constitution of Ukraine, Laws of Ukraine “On Enforcement Proceedings” dated 02.06.2016 № 1404-VIII, “On bodies and persons carrying out enforcement decisions and decisions of other bodies” dated 02.06.2016 № 1403-VIII and other laws, as well as international treaties of Ukraine, the consent to the binding nature of which was given by the Verkhovna Rada of Ukraine and regulations adopted for their implementation.In this article, the elements of the administrative and legal status of the State Executive Service of Ukraine are considered through the prism of the components, in particular: goals, objectives, functions, competence and powers, principles of the State Executive Service of Ukraine. Key words: purpose, tasks, functions, competence, powers, interaction of the State Executive Service of Ukraine.

Prejudice in Administrative Proceedings

The paper addresses the issues of judicial discretion in the application of appropriate preliminary categories for the fair and impartial consideration and settlement of disputes. The author focuses on the peculiarities of applying the prejudice to express contradictions and truth-falsehood, establishment of erroneousness and truth of assessment. The administrative court is to assess a prejudicial relationship between judicial decisions concerning an established legal fact or composition, the consequences or claims arising from the same legal relationship in the original proceedings. Such prejudice applies to the following cases: 1) emergence, change or termination of the main legal relationship in the primary process, affecting the use of prejudicial categories in derivative legal relations in the subsequent process; 2) emergence of a legal relationship not generated by the primary relationship, which contains interdependent substantive legal regulations; 3) recognition of a claim for a conviction due to confirmed preliminary categories by a primary court decision, etc. Direction of assessing the circumstances of the case are dealt with in the paper to establish the facts by comparing the judge’s rules of law and conduct of the parties on the basis of operational rules of law, taking into account «legal issues» (in material/primary and procedural/secondary components). Under the influence of the nature of reasoning, such effective evaluation criteria are formulated as observance of the principles of confidence in law, justice, honesty and morality; standards of reasonableness, impartiality, good faith; political goals of ensuring the common good, security of the state, public interests. Within the procedural discretion when using the preliminary categories, the judge is to fully and impartially investigate the «question of fact» regarding the modelling of scenarios and empirical knowledge of the truth on the levels of probability, conviction, absolute certainty. This subject of evaluation is dependent on previous decisions in the direction of «definitive» interpretation in order to make an unambiguous decision. The author adduces examples of legal positions of the Supreme Court and courts of previous instances on applying preliminary categories in administrative proceedings. It has been identified that the possibility of preliminary categories non-application in case of motivated judge’s disagreement in the way of the «recall» within the subject of consideration of the factual circumstances of the case is to be provided. Deviation from prejudice might be justified if there is a need for a «live» transition of judicial practice to interpretation, filling gaps and open «legitimate» completion of the law. Relevant changes are to be implemented in a natural, gradual and coordinated manner. Procedure for overcoming the legal force of the preliminary ruling of a court decision has been proposed. The universality of a court decision is conditional. The standard legitimate way to reject prejudice is to review court decisions. Such decisions might be reviewed for compliance with the law and validity in their adoption. Confirmation of a judicial error «cancels» the preliminary nature of such a decision. Moreover, if the draft decision contradicts the preliminary categories given in another court decision that has entered into force, it is necessary to review unacceptable legal facts and compositions. For example, these could be procedural abuses, artificial distortion (creation or forgery) of evidence, etc. Key words: discretion, judicial discretionary power, prejudice, falsity, truth, contradiction.

Support for a Lower State Pension Age for Disadvantaged Older Workers

Due to policy reforms, early exit from the labor market has decreased substantially and people are participating in the labor market until much higher ages than before. As a result, there are increasingly many people that struggle to continue working until they can comfortably retire, for example due to chronic health conditions or having to provide informal care. A potential solution would be to grant earlier access to state pension benefits (such as Social Security) for disadvantaged older workers. While it is known that many people are supportive of such a policy, the question remains how much earlier access would be granted under which circumstances. Here, using a quasi-experimental vignette design (10,350 observations nested in 2,070 respondents), we study how much earlier Dutch people would like to grant access to disadvantaged older workers. Relevant characteristics of older workers that are judged are the age at which they started working, the level of physical strain in their job, whether they have chronic health conditions, and whether they provide informal care to a loved one. The result show that, on average, people would grant older workers with chronic muscoskeletal conditions or cardiovascular disease one year earlier access to the state pension than normal, while older workers that provide daily informal care would be granted 10 months earlier access. Cumulative disadvantage could lead to a maximum of three years earlier access to pension benefits. This study provides important insights into fairness considerations surrounding state pension provisions, and implications for practice will be discussed.

The nexus between perceptions of inequality and preferences for redistribution

This paper shows that perceptions of inequality are a key factor in the formation of preferences for redistribution and thereby in the determination of the equilibrium redistribution level. We build on the novel stylized facts provided by the survey experimental literature on perceptions of income inequality, highlighting that agents incorrectly estimate the shape of the income distribution because of limited information. Agents with income above the mean believe they are poorer than they actually are, and agents with income below the mean believe themselves to be richer. We revisit the standard framework on the political economy of redistribution and extend it in two ways. First, we introduce a more general two-sided inequality aversion. Second, we incorporate perceptions of income inequality, modeled by assuming that agents form expectations on the income level of the richest and the poorest in society. We show analytically that the equilibrium redistribution level is crucially determined by the interplay between the information treatment correcting the bias in perceptions of inequality and fairness considerations specified by the degree of inequality aversion. By doing this, we add (biased) perceptions of inequality to the list of potential factors explaining why, notwithstanding high inequality, an increase in the desire for redistribution has not been observed in many countries.

Responsibility Considerations and the Design of Health Care Policies: A Survey Study of the Norwegian Population.

The objective of this article is to explore people's attitudes toward responsibility in the allocation of public health care resources. Special attention is paid to conceptualizations of responsibility involving blame and sanctions. A representative sample of the Norwegian population was asked about various responsibility mechanisms that have been proposed in the theoretical literature on health care and personal responsibility, from denial of treatment to a tax on unhealthy consumer goods. Survey experiments were employed to study treatment effects, such as whether fairness considerations affect attitudes about responsibility. We find that, overall, a substantial minority of the respondents find it fair to let the health care system sanction people-in one way or another-for voluntary behaviors that increase the risk of becoming ill. Quite surprisingly, we find that people are more prone to report that they should themselves be held responsible for unhealthy lifestyles than others.

The System of Procedural Principles of Proceedings in Administrative Offenses Cases

The paper provides definitions of the principles and system of principles of proceedings in cases of administrative offenses. Based on the norms of the Constitution of the Russian Federation, the European Convention for the Protection of Human Rights and Fundamental Freedoms, the Code of Administrative Offenses of the Russian Federation and the practice of their application, the author substantiates the position that the principles of proceedings in cases of administrative offenses are, to varying degrees, enshrined in regulatory legal acts constituting legislation on administrative offenses, both directly and indirectly. The system of procedural principles of proceedings in cases of administrative offenses is revealed. The author includes the following principles in this system: open consideration; state language; direct examination of evidence; freedom to evaluate evidence; compulsory consideration of applications; freedom to appeal against procedural decisions; competition and equality of the parties; fair consideration of the case; ensuring the right to defense. The content of these principles having a pronounced procedural nature is formed through a systemic interpretation of the provisions of the Constitution of the Russian Federation, the European Convention on Human Rights, the Code of Administrative Offenses of the Russian Federation, the case law of the Constitutional Court of the Russian Federation and the European Court of Human Rights. The author concludes that, despite the existence of various ways of consolidating the procedural principles of proceedings in cases of administrative offenses, the greatest efficiency of their perception and application will be achieved only when the principles are reflected in a special chapter of the Code of Administrative Offenses of the Russian Federation.

Strict Liability and the Purpose of Punishment

The main argument of this article is that only a clear conception of the purpose of punishment can orient the debate about the positioning of the fault requirement and strict liability doctrine in criminal law. A categorization of the varieties of strict liability offenses, as well as an adequate model for normatively appraising the legitimacy of these deviations from the principle of culpability, should be based on a systematic analysis of criminal law’s role and function in society. As is argued, the original purpose of criminal law consists in the stabilization of norms by means of punishment. Taking up that finding, this work provides a detailed view of the distinct mechanism of placing blame, allowing for the presentation of a clear scheme for categorizing and appraising the variety of strict liability offenses. It is stated that offenses substantively deviating from the standard mechanism of placing blame can potentially result in over-punishment, which is dysfunctional and not justifiable. Properly placing blame is essential for the appropriate fulfillment of criminal law’s purpose in society. Therefore, the claim of the principle of culpability and critiques of strict liability doctrine find their basis not only in considerations of fairness, but also social necessity. By presenting a systematic categorization of strict liability offenses, this research offers a clear approach to a frequently discussed doctrine and establishes new arguments against its legitimacy.

Working Longer but Not Harder: The Effects of Incentivizing Inputs versus Outputs in a Heterogeneous Workforce

ABSTRACTTo address the empirical phenomenon that organizations often reward time on the job as an end in itself, we design an experiment in which participants solve anagram puzzles, manipulating whether a compensation pool generated from the output of paired workers is allocated based on the individual inputs of relative time spent or on the individual outputs of puzzles solved. Relative to an output-based allocation, we find that an input-based allocation leads participants to spend more time on the task. However, when paired participants have widely different abilities, an input-based allocation also leads to less effort intensity, defined as puzzles solved per unit of time spent. We attribute these findings to fairness considerations, an interpretation we corroborate in a second experiment with purely individual incentives that finds the same effort duration advantage of input-based pay, but no offsetting disadvantage in effort intensity.JEL Classifications: D91; J33; M40.

Sharing and cooperation in an experiment with heterogeneous groups

We investigate the impact of inequality on sharing and cooperation using a dictator game and a linear public good game where some participants work for their endowment (“workers”) while others do not (“non-workers”). Moreover, we differentiate between two types of inequality, namely in source and in level. In contrast to most studies, participants are fully informed about the endowment of the other players. The key finding of our paper is that both sharing and cooperation critically depend on the source of the endowment. In particular, workers are more likely to share with other workers than with non-workers and more inclined to contribute to the public good when grouped with other workers rather than when grouped with non-workers. Considering also the choices made by non-workers, we argue that the worker premium in sharing and cooperation is based on fairness considerations rather than an in-group bias. Adding inequality in the level of endowment reduces the importance of the source of endowment as driver of behavior. This also suggests that reducing one layer of inequality may not improve cooperative behavior in society significantly, implying that a big-push policy tackling many dimensions of inequality at the same time may be required.