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We demonstrate that widely used measures of antigay sentiment and the size of the lesbian, gay, bisexual, and transgender (LGBT) population are misestimated, likely substantially. In a series of online experiments using a large and diverse but nonrepresentative sample, we compare estimates from the standard methodology of asking sensitive questions to measures from a “veiled” methodology that precludes inference about an individual but provides population estimates. The veiled method increased self-reports of antigay sentiment, particularly in the workplace: respondents were 67% more likely to disapprove of an openly gay manager when asked with a veil, and 71% more likely to say it should be legal to discriminate in hiring on the basis of sexual orientation. The veiled methodology also produces larger estimates of the fraction of the population that identifies as LGBT or has had a sexual experience with a member of the same sex. Self-reports of nonheterosexual identity rose by 65%, and same-sex sexual experiences by 59%. We conduct a “placebo test” and show that for nonsensitive placebo items, the veiled methodology produces effects that are small in magnitude and not significantly different from zero in seven out of eight items. Taken together, the results suggest antigay discrimination might be a more significant issue than formerly considered, as the nonheterosexual population and antigay workplace-related sentiment are both larger than previously measured. Data, as supplemental material, are available at http://dx.doi.org/10.1287/mnsc.2016.2503 . This paper was accepted by Uri Gneezy, behavioral economics .

The social sciences—including economics—have long called for transparency in research to counter threats to producing robust and replicable results. In this paper, we discuss the pros and cons of three of the more prominent proposed approaches: pre-analysis plans, hypothesis registries, and replications. They have been primarily discussed for experimental research, both in the field including randomized control trials and the laboratory, so we focus on these areas. A pre-analysis plan is a credibly fixed plan of how a researcher will collect and analyze data, which is submitted before a project begins. Though pre-analysis plans have been lauded in the popular press and across the social sciences, we will argue that enthusiasm for pre-analysis plans should be tempered for several reasons. Hypothesis registries are a database of all projects attempted; the goal of this promising mechanism is to alleviate the “file drawer problem,” which is that statistically significant results are more likely to be published, while other results are consigned to the researcher's “file drawer.” Finally, we evaluate the efficacy of replications. We argue that even with modest amounts of researcher bias—either replication attempts bent on proving or disproving the published work—or modest amounts of poor replication attempts—designs that are underpowered or orthogonal to the hypothesis—replications correct even the most inaccurate beliefs within three to five replications. We offer practical proposals for how to increase the incentives for researchers to carry out replications.

Can an organization avoid blame for an unpopular action when an adviser advises it to do it? We present experimental evidence suggesting this is the case—advice to be selfish substantially decreases punishment of being selfish. Further, this result is true despite advisers’ misaligned incentives, known to all: Through a relational contract incentive, advisers are motivated to tell the decision makers what they want to hear. Through incentivized elicitations, we find suggestive evidence that advice moves punishment by affecting beliefs of how necessary the selfish action was. In follow-up treatments, however, we show advice does not decrease punishment solely through a beliefs channel. Advice not only changes beliefs about what happened, but also the perceived morality of it. Finally, in treatments in which advisers are available, the data suggest selfish decision makers act more selfishly. This paper was accepted by Axel Ockenfels, behavioral economics.

We make a two-pronged proposal to (i) strengthen the incentives for replication work and (ii) better organize and draw attention to the replications that are conducted. First we propose that top journals publish short “replication reports.” These reports could summarize novel work replicating an existing high-impact paper, or they could highlight a replication result embedded in a wider-scope published paper. Second, we suggest incentivizing replications with the currency of our profession: citations. Enforcing a norm of citing replication work alongside the original would provide incentives for replications to both authors and journals.

This paper experimentally analyzes the schooling decisions of poor households in urban Brazil. We elicit parents' choices between monthly government transfers conditional on their adolescent child attending school and guaranteed, unconditional transfers of varying sizes. In the baseline treatment, an overwhelming majority of parents prefer conditional transfers to larger unconditional transfers. However, few parents prefer conditional payments if they are offered text message notifications whenever their child misses school. These findings suggest important intergenerational conflicts in these schooling decisions, a lack of parental control and observability of school attendance, and an additional rationale for conditional cash transfer programs-the monitoring they provide.

We assess the rate of replication for empirical papers in the 2010 American Economic Review. Across 70 empirical papers, we find that 29 percent have 1 or more citation that partially replicates the original result. While only a minority of papers has a published replication, a majority (60 percent) have either a replication, robustness test, or an extension. Surveying authors within the literature, we find substantial uncertainty over the number of extant replications.

This paper shows moral decision making is not well predicted by the overall fairness of an act but rather by the fairness of the consequences that follow directly. In laboratory experiments, thirdparty punishment for keeping money from a poorer player decreases when an intermediary actor is included in the transaction. This is true for completely passive intermediaries, even though intermediation decreases the payout of the poorest player and hurts equity, and because intermediation distances the transgressor from the outcome. A separate study shows rewards of charitable giving decrease when the saliency of an intermediary is increased.

Can an organization avoid blame for an unpopular action when an adviser advises it to do it? We present experimental evidence suggesting this is the case--advice to be selfish substantially decreases punishment of being selfish. Further, this result is true despite advisers' misaligned incentives, known to all: Through a relational contract incentive, advisers are motivated to tell the decision makers what they want to hear. Through incentivized elicitations, we find suggestive evidence that advice moves punishment by affecting beliefs of how necessary the selfish action was. In follow-up treatments, however, we show advice does not decrease punishment solely through a beliefs channel. Advice not only changes beliefs about what happened, but also the perceived morality of it. Finally, in treatments in which advisers are available, the data suggest selfish decision makers act more selfishly.

We show that the provision of social information influences a high-stakes decision and this influence persists over time. In a field experiment involving thousands of admits to Teach For America, those told about the previous year's matriculation rate are more likely to accept a teaching job, complete training, start, and return a second year. To show robustness, we develop a simple theory that identifies subgroups where we expect larger treatment effects and find our effect is larger in those subgroups. That social information can have a powerful, persistent effect on high-stakes behavior broadens its relevance for policy and theory.

We demonstrate that widely used measures of antigay sentiment and the size of the lesbian, gay, bisexual, and transgender (LGBT) population are misestimated, likely substantially. In a series of online experiments using a large and diverse but nonrepresentative sample, we compare estimates from the standard methodology of asking sensitive questions to measures from a \"veiled\" methodology that precludes inference about an individual but provides population estimates. The veiled method increased self-reports of antigay sentiment, particularly in the workplace: respondents were 67% more likely to disapprove of an openly gay manager when asked with a veil, and 71% more likely to say it should be legal to discriminate in hiring on the basis of sexual orientation. The veiled methodology also produces larger estimates of the fraction of the population that identifies as LGBT or has had a sexual experience with a member of the same sex. Self-reports of nonheterosexual identity rose by 65%, and same-sex sexual experiences by 59%. We conduct a \"placebo test\" and show that for nonsensitive placebo items, the veiled methodology produces effects that are small in magnitude and not significantly different from zero in seven out of eight items. Taken together, the results suggest antigay discrimination might be a more significant issue than formerly considered, as the nonheterosexual population and antigay workplace-related sentiment are both larger than previously measured.