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.

T he social sciences-including economics-have long called for transparency in research to counter threats to producing robust and replicable results (for example, McAleer, Pagan, and Volker 1985; Roth 1994). Recently, the push for transparency has focused on a few specific policies. In this paper, we discuss the pros and cons of three of the more prominent proposed approaches: pre-analysis plans, hypothesis registries, and replications. While these policies potentially extend to all different empirical and perhaps also theoretical approaches, 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. Pre-analysis plans have been lauded in the popular press (for example, Chambers 2014; Nyhan 2014) and across the social sciences (for example, Humphreys, de la Sierra, and van der Windt 2013;Monogan 2013;Miguel et al. 2014). We will argue for tempering such enthusiasm for pre-analysis plans for three reasons. First, recent empirical literature suggests the behavioral problems that pre-analysis plans attenuate are not a pervasive problem in experimental economics. Second, pre-analysis plans have quite limited value in cases where more than one hypothesis is tested, piloted, or surveyed, and also where null results may not be reported. However, in very costly one-of-a-kind field experiments, including heroic efforts as the Oregon

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This paper experimentally analyzes the schooling decisions of poor households with adolescent children in urban Brazil. Parents in our study were being paid large monthly transfers by the local government conditional upon their children attending school. We elicit parents' incentivized choices between such conditional monthly payments and guaranteed, unconditional monthly payments of varying relative sizes. In the baseline treatment, an overwhelming majority of parents prefer conditional transfers to larger unconditional transfers. However, parents reveal much weaker preferences for the conditionality if either (i) their child is not informed that the conditionality would be dropped or (ii) if parents are offered to receive free text-message notifications whenever their child misses school. These findings suggest important intergenerational conflicts in these schooling decisions and a lack of parental control and observability of school attendance. Further experimental treatments are consistent with parental preferences not just to keep the children in the classroom but also off the streets.JEL Classification: C92, D13, D19, D82, I21, J13, O12