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Tanya Rosenblat

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University of Michigan · Information

Active 2002–2025

h-index20
Citations2.8k
Papers568 last 5y
Funding$267k
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Research topics

  • Psychology
  • Economics
  • Social psychology
  • Microeconomics
  • Business

Selected publications

  • Promoting caste equality in the labor market: The role of self-confidence

    PLoS ONE · 2025-07-31 · 1 citations

    articleOpen accessSenior authorCorresponding

    We study how people perceive the self-confidence of individuals from different castes in India. In an experimental Indian labor market where employers and workers belong to different castes, employers evaluate worker resumes to predict the future productivity of workers who perform a real effort task. The baseline group uses resumes that reveal a productivity signal i.e.- performance in a practice task and caste information, while the treatment group receives an additional measure of worker self-confidence. We find that employers in both groups exhibit a discriminatory wage differential against lower caste workers. However, employers in the treatment group weigh lower caste workers' self-confidence more heavily than that of higher caste workers. This differential effect of confidence compensates for the lower evaluation and hence wage given to lower caste workers due to discrimination. From a policy perspective, these findings highlight the importance of non-cognitive skill training, such as training sessions for employment interviews where applicants can signal their self-confidence through interaction with employers.

  • Correcting Misperceptions about Support for Social Distancing to Combat COVID-19

    Economic Development and Cultural Change · 2023-08-02 · 2 citations

    articleOpen access

    the perceived benefits from social distancing. We estimate impacts on social distancing, measured using a combination of self-reports and reports of others. While experts surveyed in advance expected the treatment to increase social distancing, we find that its average effect is close to zero and significantly lower than expert predictions. However, the treatment's effect is heterogeneous, as predicted by theory: it decreases social distancing where current COVID-19 cases are low (where free-riding dominates), but increases it where cases are high (where the perceived-infectiousness effect dominates). These findings highlight that correcting misperceptions may have heterogeneous effects depending on disease prevalence.

  • Hiring Effective Health Promoters

    AEA Randomized Controlled Trials · 2023-07-05

    dataset
  • Hiring Effective Health Promoters

    AEA Randomized Controlled Trials · 2023-07-05

    dataset
  • Teaching and incentives: Substitutes or complements?

    Harvard Dataverse · 2023-07-12

    datasetOpen access

    Replication data, code, and codebooks for "Teaching and incentives: Substitutes or complements" from the project "Accelerating Changes in Norms about Social Distancing to Combat COVID-19". Paper Abstract: Interventions to promote learning are often categorized into supply- and demand-side approaches. In a randomized experiment to promote learning about COVID-19 among Mozambican adults, we study the interaction between a supply and a demand intervention, respectively: teaching via targeted feedback, and providing financial incentives to learners. In theory, teaching and learner-incentives may be substitutes (crowding out one another) or complements (enhancing one another). Experts surveyed in advance predicted a high degree of substitutability between the two treatments. In contrast, we find substantially more complementarity than experts predicted. Combining teaching and incentive treatments raises COVID-19 knowledge test scores by 0.5 standard deviations, though the standalone teaching treatment is the most cost-effective. The complementarity between teaching and incentives persists in the longer run, over nine months post-treatment.

  • Multiple social identities cloud norm perception: responses to COVID-19 among university aged Republicans and Democrats

    Frontiers in Behavioral Economics · 2023-10-03 · 2 citations

    articleOpen access

    Introduction Most work on social identity, defined as one's sense of self derived from membership to social groups, focuses on a single identity and its behavioral consequences. But a central insight of social identity theory is that people belong to multiple social groups, derive self-esteem from multiple identities and care to conform to the norms for those identities. However, very little work has turned its attention to understanding when and how multiple social identities interact. We motivate hypotheses with a framework that extends a social identity model to include multiple identities. Methods Using a longitudinal sample ( N > 600) of university students located primarily in Texas and throughout the US, we use university social identity, and the associated university norms, to characterize COVID related social distancing norms between April and October of 2020 and then unpack how another identity, the student's political identity, impacts perception of those norms. Results Despite incentives to do otherwise, we find that beliefs about university norms differ depending on the respondent's political identity. We interpret this as a spillover effect of attitudes from one identity to another. Discussion We relate our results back to a model of social identity, to the literature on spillovers where such psychological spillovers are hard to empirically identify, and to methods for future work on identity and spillovers.

  • Hiring Effective Health Promoters

    AEA Randomized Controlled Trials · 2023-07-05

    dataset
  • Hiring Effective Health Promoters

    AEA Randomized Controlled Trials · 2023-07-05

    dataset
  • Replication Package for: Correcting Misperceptions about Support for Social Distancing to Combat COVID-19

    Harvard Dataverse · 2023-07-18

    datasetOpen access

    Replication data, code, and codebooks for "Correcting Misperceptions about Support for Social Distancing to Combat COVID-19" from the project "Accelerating Changes in Norms about Social Distancing to Combat COVID-19". Paper Abstract: Can informing people of high community support for social distancing encourage them to do moreof it? We randomly assigned a treatment correcting individuals’ underestimates of community support for social distancing. In theory, informing people that more neighbors support social distancing than expected encourages free-riding and lowers the perceived benefits from social distancing. At the same time, the treatment induces people to revise their beliefs about the infectiousness of COVID-19 upwards; this perceived infectiousness effect as well as the norm adherence effect increase the perceived benefits from social distancing. We estimate impacts on social distancing, measured using a combination of self-reports and reports of others. While experts surveyed in advance expected the treatment to increase social distancing, we find that its average effect is close to zero and significantly lower than expert predictions. However, the treatment’s effect is heterogeneous, as predicted by theory: it decreases social distancing where current COVID-19 cases are low (where free-riding dominates), but increases it where cases are high (where the perceived-infectiousness effect dominates). These findings highlight that correcting misperceptions may have heterogeneous effects depending on disease prevalence.

  • Experimental Methods for Measuring Social Networks without Censoring

    Journal of Experimental Political Science · 2023-09-18

    articleOpen accessSenior authorCorresponding

    Abstract We elicit social networks among students in an Italian high school either by measuring the complete network in an incentive-compatible way or by using a truncated elicitation of at most five links. We find that truncation undercounts weak links by up to 90% but only moderately undercounts the time spent with strong friends. We use simulations to demonstrate that the measurement error induced by censoring might be particularly significant when studying phenomena such as social learning which are often thought to operate along weak ties. We then discuss how a modified network elicitation protocol might be able to reduce measurement error.

Recent grants

Frequent coauthors

  • Markus Möbius

    61 shared
  • Dean Yang

    22 shared
  • James E. Allen

    University of Michigan–Ann Arbor

    15 shared
  • James Riddell

    14 shared
  • Arlete Mahumane

    14 shared
  • Hang Yu

    14 shared
  • Stephen Leider

    10 shared
  • Quoc-Anh Do

    9 shared

Labs

  • Tanya RosenblatPI

Education

  • PhD, Economics

    Massachusetts Institute of Technology

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