Coordination under threshold uncertainty in a public goods game

We explored experimentally how threshold uncertainty affects coordination success in a threshold public goods game. Whereas all groups succeeded in providing the public good when the exact value of the threshold was known, uncertainty was generally detrimental for the public good provision. The negative effect of threshold uncertainty was particularly severe when it took the form of ambiguity, i.e. when players were not only unaware of the value of the threshold but also of its probability distribution. Early signaling of willingness to contribute and share the burden equitably helped groups in coping with threshold uncertainty.public good, threshold uncertainty, ambiguity, experiment

Fewer but poorer: Benevolent partiality in prosocial preferences

A prosocial action typically provides a more sizable benefit when directed at those who have less as opposed to those who have more. However, not all prosocial acts have a direct bearing on socioeconomic disadvantage, nor does disadvantage necessarily imply a greater need for the prosocial outcome. Of interest here, welfare impact may depend on the number of beneficiaries but not on their socioeconomic status. Across four preregistered studies of life-saving decisions, we demonstrate that when allocating resources, many people are benevolently partial. That is, they choose to help the disadvantaged even when this transparently implies sacrificing lives. We suggest that people construct prosocial aid as an opportunity to correct morally aversive inequalities, thusmaking relativelymore disadvantaged recipients amore justifiable target of help. Benevolent partiality is reduced when people reflect beforehand on what aspects they will prioritize in their donation decision

Coordination under threshold uncertainty in a public goods game

We explored experimentally how threshold uncertainty affects coordination success in a threshold public goods game. Whereas all groups succeeded in providing the public good when the exact value of the threshold was known, uncertainty was generally detrimental for the public good provision. The negative effect of threshold uncertainty was particularly severe when it took the form of ambiguity, i.e. when players were not only unaware of the value of the threshold but also of its probability distribution. Early signaling of willingness to contribute and share the burden equitably helped groups in coping with threshold uncertainty. --Public good,threshold uncertainty,ambiguity,experiment

Income tax and the motivation to work

Does income tax influence the motivation to work? We propose that the degree of effort exertion in the presence of income tax depends on people’s attitudes toward two key components of taxation: redistribution and government intervention. For people favorable toward both, working while taxed is aligned with personal identity and may actually enhance motivation. All others, however, may find taxes demotivating. In two incentive‐compatible labor experiments, framing wages as subject to an income tax significantly increased productivity among people chronically favorable toward both redistribution and government intervention. For everyone else, taxes did not reliably influence productivity. An objectively equivalent intervention that did not redistribute a portion of participants’ wages (framed as a wage “match” rather than a “tax”) did not motivate anyone to work harder. Our findings suggest that the net effect of income tax on productivity partly depends on the distribution of attitudes toward redistribution and government intervention.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/146613/1/bdm2078_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146613/2/bdm2078.pd

A blind spot for attractiveness discrimination

Discrimination remains a key challenge for social equity. There is widespread agreement that discrimination is unfair and should be punished. A prerequisite for this is that instances of discrimination are detected. Yet, some types of discrimination may be less apparent than others. Across seven studies (N = 3,486, five preregistered), we find that attractiveness discrimination often goes undetected compared to more prototypical types of discrimination (i.e., gender and race discrimination). This blind spot does not emerge because people perceive attractiveness discrimination to be unproblematic or desirable. Rather, our findings suggest that people’s ability to detect discrimination is bounded. People only focus on a few salient dimensions, such as gender and race, when scrutinizing decision outcomes (e.g., hiring or sentencing decisions) for bias. Consistent with this account, two interventions that increased the salience of attractiveness increased the detection of attractiveness discrimination, but also decreased the detection of gender and race discrimination

Crowdsourced consumer data: how do we make sure it's good?

Crowdsourcing data through online marketplaces such as Amazon Mechanical Turk poses new challenges about how consumer research should be designed, conducted and analysed. Additionally, it raises questions about the validity of the participants and the information they provide. As protocols for crowdsourcing data are still being worked out, we have developed a few guidelines that will benefit those using such platforms for research purposes

Running experiments on Amazon Mechanical Turk

Although Mechanical Turk has recently become popular among social scientists as a source of experimental data, doubts may linger about the quality of data provided by subjects recruited from online labor markets. We address these potential concerns by presenting new demographic data about the Mechanical Turk subject population, reviewing the strengths of Mechanical Turk relative to other online and offline methods of recruiting subjects, and comparing the magnitude of effects obtained using Mechanical Turk and traditional subject pools. We further discuss some additional benefits such as the possibility of longitudinal, cross cultural and prescreening designs, and offer some advice on how to best manage a common subject pool

The intermediate alternative effect: Considering a small tradeoff increases subsequent willingness to make large tradeoffs

Prior research has consistently demonstrated that people are reluctant to trade a good they own for an alternative good, particularly when the alternative (or “target”) represents a substantial departure from the “endowment”. We demonstrate that the endowment effect can be reduced by first making participants consider trading their endowment for an intermediate alternative (which shares some characteristics of the endowment and some characteristics of the target). We find that this “intermediate alternative effect” operates primarily by shifting one’s reference point in the direction of the target alternative. Even when the intermediate alternative is not adopted, the extent to which one’s endowment is treated as a reference point is weakened, which can also facilitate subsequent trading.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141910/1/jcpy384.pd

Running experiments on Amazon Mechanical Turk

Although Mechanical Turk has recently become popular among social scientists as a source of experimental data, doubts may linger about the quality of data provided by subjects recruited from online labor markets. We address these potential concerns by presenting new demographic data about the Mechanical Turk subject population, reviewing the strengths of Mechanical Turk relative to other online and offline methods of recruiting subjects, and comparing the magnitude of effects obtained using Mechanical Turk and traditional subject pools. We further discuss some additional benefits such as the possibility of longitudinal, cross cultural and prescreening designs, and offer some advice on how to best manage a common subject pool