Net-Loss Reciprocation and the Context Dependency of Economic Choices

This paper proposes a novel explanation for the context dependency of individual choices in two-player games. Context dependency refers to the well-established phenomenon that a player, when choosing from a given opportunity set created by the other player’s strategy, chooses differently in different situations because of different alternatives to the other player’s strategy. The utility model used to explain this kind of context dependency incorporates a preference for net-loss reciprocation. Net-loss reciprocation means that a player’s willingness to impose a net loss (i.e., loss minus gain) on the other player increases in the net loss that he or she derives from the other player’s strategy. I show that net-loss reciprocation together with the method for calculating net losses developed in this paper explains the context dependencies in individual behaviour that have been documented in a number of experimental studies, whereas existing models of intention-based reciprocity fail to explain all the evidence

Nashbots: How Political Scientists have Underestimated Human Rationality, and How to Fix It

Political scientists use experiments to test the predictions of game-theoretic models. In a typical experiment, each subject makes choices that determine her own earnings and the earnings of other subjects, with payments corresponding to the utility payoffs of a theoretical game. But social preferences distort the correspondence between a subject’s cash earnings and her subjective utility, and since social preferences vary, anonymously matched subjects cannot know their opponents’ preferences between outcomes, turning many laboratory tasks into games of incomplete information. We reduce the distortion of social preferences by pitting subjects against algorithmic agents (“Nashbots”). Across 11 experimental tasks, subjects facing human opponents played rationally only 36% of the time, but those facing algorithmic agents did so 60% of the time. We conclude that experimentalists have underestimated the economic rationality of laboratory subjects by designing tasks that are poor analogies to the games they purport to test

Recommender systems and their ethical challenges

This article presents the first, systematic analysis of the ethical challenges posed by recommender systems through a literature review. The article identifies six areas of concern, and maps them onto a proposed taxonomy of different kinds of ethical impact. The analysis uncovers a gap in the literature: currently user-centred approaches do not consider the interests of a variety of other stakeholders—as opposed to just the receivers of a recommendation—in assessing the ethical impacts of a recommender system

Matching Code and Law: Achieving Algorithmic Fairness with Optimal Transport

Increasingly, discrimination by algorithms is perceived as a societal and legal problem. As a response, a number of criteria for implementing algorithmic fairness in machine learning have been developed in the literature. This paper proposes the Continuous Fairness Algorithm (CFA$\theta$) which enables a continuous interpolation between different fairness definitions. More specifically, we make three main contributions to the existing literature. First, our approach allows the decision maker to continuously vary between specific concepts of individual and group fairness. As a consequence, the algorithm enables the decision maker to adopt intermediate ``worldviews'' on the degree of discrimination encoded in algorithmic processes, adding nuance to the extreme cases of ``we're all equal'' (WAE) and ``what you see is what you get'' (WYSIWYG) proposed so far in the literature. Second, we use optimal transport theory, and specifically the concept of the barycenter, to maximize decision maker utility under the chosen fairness constraints. Third, the algorithm is able to handle cases of intersectionality, i.e., of multi-dimensional discrimination of certain groups on grounds of several criteria. We discuss three main examples (credit applications; college admissions; insurance contracts) and map out the legal and policy implications of our approach. The explicit formalization of the trade-off between individual and group fairness allows this post-processing approach to be tailored to different situational contexts in which one or the other fairness criterion may take precedence. Finally, we evaluate our model experimentally.Comment: Vastly extended new version, now including computational experiment

Cognition and framing in sequential bargaining for gains and losses

Noncooperative game-theoretic models of sequential bargaining give an underpinning to cooperative solution concepts derived from axioms, and have proved useful in applications (see Osborne and Rubinstein 1990). But experimental studies of sequential bargaining with discounting have generally found systematic deviations between the offers people make and perfect equilibrium offers derived from backward induction (e.g., Ochs and Roth 1989). We have extended this experimental literature in two ways. First, we used a novel software system to record the information subjects looked at while they bargained. Measuring patterns of information search helped us draw inferences about how people think, testing as directly as possible whether people use backward induction to compute offers. Second, we compared bargaining over gains that shrink over time (because of discounting) to equivalent bargaining over losses that expand over time. In the games we studied, two players bargain by making a finite number of alternating offers. A unique subgame-perfect equilibrium can be computed by backward induction. The induction begins in the last period and works forward. Our experiments use a three-round game with a pie of $5.00 and a 50-percent discount factor (so the pie shrinks to$2.50 and $1.25 in the second and third rounds). In the perfect equilibrium the first player offers the second player$1.25 and keeps $3.75

Intelligent tutoring agent for settlers of Catan

An Intelligent Tutoring Agent (ITA) for the board game Settlers of Catan (SoC) is introduced. It uses CLIPS knowledge bases, connected by JCLIPS to a JAVA implementation of SoC. It is founded on a new theoretical framework that describes the development of negotiation skills in children. Using this framework, the ITA helps children in developing negotiation skills through play, which makes it unique in its kind

Minimum wage setting and standards of fairness

We examine the setting of minimum wages, arguing that they can best be understood as a reflection of voters' notions of fairness. We arrive at this conclusion through an empirical investigation of the implications of three models, considered in the context of policy setting by sub-units in a federation: a competing interests group model; a constrained altruism model; and a fairness based model. In the latter model, voters are interested in banning what they view to be unfair transactions, with the notion of fairness based on comparisons to the "going" unskilled wage. We use data on minimum wages set in the ten Canadian provinces from 1969 to 2005 to carry out the investigation. A key implication of the models that is borne out in the data is that minimum wages should be set as a positive function of the location of the unskilled wage distribution. Together, the results indicate that minimum wages are set according to a "fairness" standard and that this may exacerbate movements in inequality.

Fairness and Direct Democracy

The median voter model (direct democracy) has wide applicability, but it is based on selfish voters i.e. voters who derive utility solely from 'own' payoff. The recent literature has pointed to fairness and concern for others as basic human motives that explain a range of economic phenomena. We examine the implications of introducing fair voters who have a preference for fairness as in Fehr and Schmidt (1999). Within a simple general equilibrium model, we demonstrate the existence of a Condorcet winner for fair voters using the single crossing property of voters’ preferences. In a fair voter model, unlike a selfish voter model, poverty can lead to increased redistribution. Mean preserving spreads of income increase equilibrium redistribution. Greater fairness leads to greater redistribution. The introduction of selfish voters in an economy where the median voter is fair can have a large impact on the redistributive outcome. An empirical exercise using OECD data illustrates the potential importance of fairness in explaining redistribution.Redistribution; other regarding preferences; single crossing property; income inequality; American Exceptionalism

Anomalies: Ultimatums, Dictators and Manners

Economics can be distinguished from other social sciences by the belief that most (all?) behavior can be explained by assuming that agents have stable, well-defined preferences and make rational choices consistent with those preferences in markets that (eventually) clear. An empirical result qualifies as an anomaly if it is difficult to "rationalize" or if implausible assumptions are necessary to explain it within the paradigm. This column will resume, after a long rest, the investigation of such anomalies

Social Preferences - Literature Survey

This paper surveys the theories of social preferences. Social preferences are based on that people not only care about their own well-being, but they have a certain concern with payoffs and/or actions of others. We classify two approaches: distributional and intention-based models, and later discuss models that combine both theories. In order to provide a better illustration of the discussed models, we derive predictions of these models for two classic experimental protocols: ultimatum game and public good game with punishment. These predictions are compared with the stylized facts of these two games.