Authors: Ruben L. Bach, Christoph Kern, Ashley Amaya, Florian Keusch, Frauke Kreuter, Jan Hecht, and Jonathan Heinemann

A major concern arising from ubiquitous tracking of individuals' online activity is that algorithms may be trained to predict personal sensitive information, even for users who do not wish to reveal such information. Although previous research has shown that digital trace data can accurately predict sociodemographic characteristics, little is known about the potentials of such data to predict sensitive outcomes. Against this background, we investigate in this article whether we can accurately predict voting behaviour, which is considered personal sensitive information in Germany and subject to strict privacy regulations. Using records of web browsing and mobile device usage of about 2,000 online users eligible to vote in the 2017 German federal election combined with survey data from the same individuals, we find that online activities do not predict (self-reported) voting well in this population. These findings add to the debate about users' limited control over (inaccurate) personal information flows.

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Authors: Alvin E. Rotha, and Stephanie W. Wang

We study popular attitudes in Germany, Spain, the Philippines, and the United States toward three controversial markets—prostitution, surrogacy, and global kidney exchange (GKE). Of those markets, only prostitution is banned in the United States and the Philippines, and only prostitution is allowed in Germany and Spain. Unlike prostitution, majorities support legalization of surrogacy and GKE in all four countries. So, there is not a simple relation between public support for markets, or bans, and their legal and regulatory status. Because both markets and bans on markets require social support to work well, this sheds light on the prospects for effective regulation of controversial markets.

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Authors: Zachary D. Liscow and Abigail D. Pershing

Basic economic theory prescribes that redistribution typically take the form of cash rather than in-kind goods and services, since cash lets the recipient choose how to use the resources, thereby maximizing benefits to the recipient. Notwithstanding this benefit, among the trillions of dollars of annual transfers in the United States, redistribution is mostly—and increasingly—in-kind. We help explain why with novel survey experiments to better-understand Americans' preferences regarding the structure of government redistribution. Our survey experiment offers a large, demographically representative sample of respondents a hypothetical choice between a cash transfer and a transfer that can only be spent on a bundle of 'necessities.' We make three main points. First, survey respondents overwhelmingly preferred in-kind over cash transfers to the poor. The most important reason for this choice is paternalism: the belief that the poor will not spend cash on the right things. The preference for in-kind was common to a majority of virtually all segments of the general population, though not to a sample of elites. Second, stated preferences suggest that respondents are willing to redistribute considerably more in-kind than in cash. We also surveyed the poor, who preferred receiving cash, but not as strongly as the general population preferred redistributing in-kind. The modesty of this preference among the poor in part comes from a sizable minority that preferred in-kind redistribution, which many anticipated functioning as a self-control mechanism. Third, a randomized treatment explaining the value of choice significantly increased the preference for cash over in-kind, but it did not change the overall preference for in-kind.

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Authors: Jon Roozenbeek, Claudia R. Schneider, Sarah Dryhurst, John Kerr, Alexandra L. J. Freeman, Gabriel Recchia, Anne Marthe van der Bles and Sander van der Linden

Misinformation about COVID-19 is a major threat to public health. Using five national samples from the UK (n= 1050 and n= 1150), Ireland (n = 700), the USA (n = 700), Spain (n= 700) and Mexico (n= 700), we examine predictors of belief in the most common statements about the virus that contain misinformation. We also investigate the prevalence of belief in COVID-19 misinformation across different countries and the role of belief in such misinformation in predicting relevant health behaviours. We find that while public belief in misinformation about COVID-19 is not particularly common, a substantial proportion views this type of misinformation as highly reliable in each country surveyed. In addition, a small group of participants find common factual information about the virus highly unreliable. We also find that increased susceptibility to misinformation negatively affects people's self-reported compliance with public health guidance about COVID-19, as well as people's willingness to get vaccinated against the virus and to recommend the vaccine to vulnerable friends and family. Across all countries surveyed, we find that higher trust in scientists and having higher numeracy skills were associated with lower susceptibility to coronavirus-related misinformation. Taken together, these results demonstrate a clear link between susceptibility to misinformation and both vaccine hesitancy and a reduced likelihood to comply with health guidance measures, and suggest that interventions which aim to improve critical thinking and trust in science may be a promising avenue for future research.

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Authors: Alberto Alesina, Stefanie Stantcheva and Edoardo Teso

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Using new cross-country survey and experimental data, we investigate how beliefs about intergenerational mobility affect preferences for redistribution in France, Italy, Sweden, the United Kingdom, and the United States. Americans are more optimistic than Europeans about social mobility. Our randomized treatment shows pessimistic information about mobility and increases support for redistribution, mostly for 'equality of opportunity' policies. We find strong political polarization. Left-wing respondents are more pessimistic about mobility: their preferences for redistribution are correlated with their mobility perceptions; and they support more redistribution after seeing pessimistic information. None of this is true for right-wing respondents, possibly because they see the government as a 'problem' and not as the 'solution'.

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Authors: Alberto Alesina, Armando Miano and Stefanie Stantcheva

We design and conduct large-scale surveys and experiments in six countries to investigate how natives perceive immigrants and how these perceptions influence their preferences for redistribution. We find strikingly large misperceptions about the number and characteristics of immigrants: in all countries, respondents greatly overestimate the total number of immigrants, think immigrants are culturally and religiously more distant from them, and are economically weaker -- less educated, more unemployed, and more reliant on and favored by government transfers -- than is the case. Given the very negative baseline views that respondents have of immigrants, simply making them think about immigration before asking questions about redistribution, in a randomized manner, makes them support less redistribution, including actual donations to charities. Information about the true shares and origins of immigrants is ineffective, and mainly acts as a prime that makes people think about immigrants and reduces their support for redistribution. An anecdote about a 'hard working' immigrant is somewhat more effective, suggesting that when it comes to immigration, salience and narratives shape people's views more deeply than hard facts.

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Authors: Christina Leuker, Ralph Hertwig, Ksenija Gumenik, Lukas Maximilian Eggeling, Shahar Hechtlinger, Anastasia Kozyreva, Larissa Samaan and Nadine Fleischhut

On January 27, 2020, the first case of infection with the novel coronavirus was officially confirmed in Germany. Shortly thereafter, the government set up a crisis team, and the Heinsberg district reported an increasing number of infections. At the beginning of March, it became clear that the coronavirus was also spreading in Germany. Far-reaching restrictions on public and private life followed: major events were canceled, school closures announced, social contact restrictions came into force. The threat was new, global, and difficult to estimate at the beginning of March. The coronavirus dominated the media as much as private conversations in Germany. The population was exposed to an unprecedented flood of information, including misinformation and uncertainty: from daily statistics on infections, symptoms, risks, and behavioral recommendations, to personal reports, global comparisons, and measures designed to stop the virus or slow its spread. It is unclear how the population dealt with this flood of information and how information behavior changed with the decline in infection numbers and the easing of measures at the beginning of June. At the beginning of June, the population had to expect that risks would vary regionally and that measures would be adapted to the current infection situation. At the same time, the economic and social consequences of the restrictions caused by the pandemic must be dealt with. In the following report, we focus on four key questions: (1) How do people say they are getting information about the coronavirus at the beginning of the easing phase at the beginning of June, and how has behavior changed compared to the beginning of March? (2) What topics, for what reasons, and from what sources do people get information? (3) How do people deal with misinformation? (4) How do people perceive risks related to the coronavirus, and how well are they informed? Even if some population groups are at greater risk from infection (e.g. older people or people with pre-existing conditions), it is important that all citizens are sufficiently informed about risks and measures to control the spread of the coronavirus and protect at-risk groups. To answer these questions, Respondi conducted a representative online survey with N = 1107 on behalf of the Max Planck Institute for Human Development between June 3 and 6, 2020. The current population distribution was taken into account in terms of age (18–69 years), gender and federal state using quota samples.


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Authors: Jörg Drechsler, Emma Fössing, Lukas Olbrich & Stefan Zins 

Befragungen, die auf Basis von Zufallsstichproben erhoben werden, werden aufgrund hoher Kosten und niedriger Rücklaufquoten zunehmend unattraktiver. Gleichzeitig werden nicht‑zufallsbasierte Befragungen, die mutmaßlich kostengünstiger sind und eine schnellere Datenerhebung ermöglichen, immer beliebter. Im Projekt “Nonprobability Sample Inference” (NOSI) wird untersucht, inwieweit letzere eine praktikable Alternative zu Zufallsstichproben in der Arbeitsmarktforschung darstellen können. Zu diesem Zweck wird eine Zufallsstichprobe mit vier nicht‑zufallsbasierten Befragungen verschiedener Anbieter verglichen.

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