nep-soc New Economics Papers
on Social Norms and Social Capital
Issue of 2023‒01‒30
nine papers chosen by
Fabio Sabatini
Università degli Studi di Roma “La Sapienza”

  1. Religious Identity, Trust, Reciprocity, and Prosociality: Theory and Evidence By Sanjit Dhami; Mengxing Wei; Pavan Mamidi
  2. Response to Guinnane and Hoffman: Medieval Anti-Semitism, Weimar Social Capital, and the Rise of the Nazi Party: A Reconsideration By Nico Voigtländer; Hans-Joachim Voth
  3. Predicting trustworthiness across cultures: An experiment By Adam Zylbersztejn; Zakaria Babutsidze; Nobuyuki Hanaki
  4. Measuring an artificial intelligence agent's trust in humans using machine incentives By Tim Johnson; Nick Obradovich
  5. Confirmation Bias in Social Networks By Marcos Ross Fernandes
  6. The Dynamics of Networks and Homophily By Matthew O. Jackson; Stephen M. Nei; Erik Snowberg; Leeat Yariv
  7. Na?ve Learning in Social Networks with Fake News: Bots as a Singularity By Saeed Badri; Bernd Heidergott; Ines Lindner
  8. The Propagation of Unethical Behaviours: Cheating Responses to Tax Evasion By Andrea F.M. Martinangeli; Lisa Windsteiger
  9. Are profiles of social, cultural, and economic capital related to living well with dementia? Longitudinal findings from the IDEAL programme By Sabatini, Serena; Martyr, Anthony; Gamble, Laura D.; Jones, Ian R.; Collins, Rachel; Matthews, Fiona E.; Knapp, Martin; Thom, Jeanette M.; Henderson, Catherine; Victor, Christina; Pentecost, Claire; Clare, Linda

  1. By: Sanjit Dhami; Mengxing Wei; Pavan Mamidi
    Abstract: We use the trust and the dictator games to explore the effects of religious identity on trust, trustworthiness, prosociality, and conditional reciprocity within a beliefs-based model. We provide a novel and rigorous theoretical model to derive the relevant predictions, which are then tested in pre-registered lab-in-the-field experiments from villages in the Indian states of Bihar and Uttar Pradesh. We find strong evidence of religious identity effects in the beliefs, and the chosen actions, for Hindu and Muslim subjects. Priming has little effect on Hindu subjects but it enhances religious polarization in beliefs and actions among Muslim subjects. There is taste-based discrimination but no statistical discrimination. All our underlying assumptions on beliefs, and their dependence on priming and identity are confirmed by the data, identifying a precise beliefs-based mechanism for the effects of religious identity. More religious subjects expect greater prosociality/reciprocity and often are more prosocial/reciprocal.
    Keywords: religious identity, trust, trustworthiness, prosociality, priming, conditional reciprocity
    JEL: C91 D01 D84 D91
    Date: 2022
  2. By: Nico Voigtländer; Hans-Joachim Voth
    Abstract: Guinnane and Hoffman (subsequently GH) comment on two of our papers: Voigtländer and Voth: “Persecution Perpetuated” (2012, subsequently PP) and Satyanath, Voigtländer and Voth: Bowling for Fascism (2017, subsequently BF). They allege that our econometric results are fragile and depend on outliers in the state of Bavaria; that our results do not account for the role of institutional actors, and that we ‘misinterpret’ history. This brief response addresses these allegations and shows that i) GH’s empirical criticisms are targeted at small subsets of our results; ii) use ad hoc, restrictive specifications – standard procedures to address GH’s concerns about outliers actually confirm our results; iii) GH’s conceptual critique is misguided and based on a misrepresentation of Weimar history, especially when it comes to the case of Bavaria. In sum, the empirical findings in PP and BF stand as in our original publications.
    Date: 2022
  3. By: Adam Zylbersztejn (GATE Lyon Saint-Étienne - Groupe d'analyse et de théorie économique - ENS Lyon - École normale supérieure - Lyon - UL2 - Université Lumière - Lyon 2 - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon - UJM - Université Jean Monnet - Saint-Étienne - Université de Lyon - CNRS - Centre National de la Recherche Scientifique); Zakaria Babutsidze (GREDEG - Groupe de Recherche en Droit, Economie et Gestion - UNS - Université Nice Sophia Antipolis (1965 - 2019) - COMUE UCA - COMUE Université Côte d'Azur (2015-2019) - CNRS - Centre National de la Recherche Scientifique - UCA - Université Côte d'Azur, OFCE - Observatoire français des conjonctures économiques (Sciences Po) - Sciences Po - Sciences Po); Nobuyuki Hanaki (Osaka University [Osaka])
    Abstract: We contribute to the ongoing debate in the psychological literature on the role of thin slices of observable information in predicting others' social behavior, and its generalizability to cross-cultural interactions. We experimentally assess the degree to which subjects, drawn from culturally dierent populations (France and Japan), are able to predict strangers' trustworthiness based on a set of visual stimuli (mugshot pictures, neutral videos, loaded videos, all recorded in an additional French sample) under varying cultural distance to the target agent in the recording. Our main nding is that cultural distance is not detrimental for predicting trustworthiness in strangers, but that it may aect the perception of dierent components of communication in social interactions.
    Keywords: Trustworthiness, communication, hidden action game, cross-cultural comparison, laboratory experiment
    Date: 2021
  4. By: Tim Johnson; Nick Obradovich
    Abstract: Scientists and philosophers have debated whether humans can trust advanced artificial intelligence (AI) agents to respect humanity's best interests. Yet what about the reverse? Will advanced AI agents trust humans? Gauging an AI agent's trust in humans is challenging because--absent costs for dishonesty--such agents might respond falsely about their trust in humans. Here we present a method for incentivizing machine decisions without altering an AI agent's underlying algorithms or goal orientation. In two separate experiments, we then employ this method in hundreds of trust games between an AI agent (a Large Language Model (LLM) from OpenAI) and a human experimenter (author TJ). In our first experiment, we find that the AI agent decides to trust humans at higher rates when facing actual incentives than when making hypothetical decisions. Our second experiment replicates and extends these findings by automating game play and by homogenizing question wording. We again observe higher rates of trust when the AI agent faces real incentives. Across both experiments, the AI agent's trust decisions appear unrelated to the magnitude of stakes. Furthermore, to address the possibility that the AI agent's trust decisions reflect a preference for uncertainty, the experiments include two conditions that present the AI agent with a non-social decision task that provides the opportunity to choose a certain or uncertain option; in those conditions, the AI agent consistently chooses the certain option. Our experiments suggest that one of the most advanced AI language models to date alters its social behavior in response to incentives and displays behavior consistent with trust toward a human interlocutor when incentivized.
    Date: 2022–12
  5. By: Marcos Ross Fernandes
    Abstract: In this study, I propose a theoretical social learning model to investigate how confirmation bias affects opinions when agents exchange information over a social network. Hence, besides exchanging opinions with friends, agents observe a public sequence of potentially ambiguous signals and interpret it according to a rule that includes confirmation bias. First, this study shows that regardless of level of ambiguity both for people or networked society, only two types of opinions can be formed, and both are biased. However, one opinion type is less biased than the other depending on the state of the world. The size of both biases depends on the ambiguity level and relative magnitude of the state and confirmation biases. Hence, long-run learning is not attained even when people impartially interpret ambiguity. Finally, analytically confirming the probability of emergence of the less-biased consensus when people are connected and have different priors is difficult. Hence, I used simulations to analyze its determinants and found three main results: i) some network topologies are more conducive to consensus efficiency, ii) some degree of partisanship enhances consensus efficiency even under confirmation bias and iii) open-mindedness (i.e. when partisans agree to exchange opinions with opposing partisans) might inhibit efficiency in some cases.
    Keywords: Social Networks; Social Learning; Misinformation; Confirmation Bias
    JEL: C11 D83 D85
    Date: 2023–01–09
  6. By: Matthew O. Jackson; Stephen M. Nei; Erik Snowberg; Leeat Yariv
    Abstract: We examine friendships and study partnerships among university students over several years. At the aggregate level, connections increase over time, but homophily on gender and ethnicity is relatively constant across time, university residences, and different network layers. At the individual level, homophilous tendencies are persistent across time and network layers. Furthermore, we see assortativity in homophilous tendencies. There is weaker, albeit significant, homophily over malleable characteristics---risk preferences, altruism, study habits, and so on. We find little evidence of assimilation over those characteristics. We also document the nuanced impact of network connections on changes in Grade Point Average.
    JEL: D85 I21 J15 J16 Z13
    Date: 2022–12
  7. By: Saeed Badri (Vrije Universiteit Amsterdam); Bernd Heidergott (Vrije Universiteit Amsterdam); Ines Lindner (Vrije Universiteit Amsterdam)
    Abstract: We study the impact of bots on social learning in a social network setting. Regular agents receive independent noisy signals about the true value of a variable and then communicate in a network. They na¨?vely update beliefs by repeatedly taking weighted averages of neighbors’ opinions. Bots are agents in the network that spread fake news by disseminating biased information. Our main contributions are threefold. (1) We show that the consensus of the network is a mapping of the interaction rate between the agents and bots and is discontinuous at zero mass of bots. This implies that even a comparatively “infinitesimal” small number of bots still has a sizeable impact on the consensus and hence represents an obstruction to the “wisdom of crowds”. (2) We prove that the consensus gap induced by the marginal presence of bots depends neither on the agent network or bot layout nor on the assumed connection structure between agents and bots. (3) We show that before the ultimate (and bot-infected) consensus is reached, the network passes through a quasi-stationary phase which has the potential to mitigate the harmful impact of bots.
    Keywords: Fake news, Misinformation, Social networks, Social Media, Wisdom of Crowds
    JEL: D83 D85 Z13
    Date: 2022–12–22
  8. By: Andrea F.M. Martinangeli; Lisa Windsteiger
    Abstract: We explore cheating in a die roll task in response to information about tax evasion in a large-scale experiment on a representative sample of the Italian population. We thus generalise laboratory findings on conditional behaviours (cooperation, cheating) to uncover their real-world bearing in the context of tax compliance. Cheating is conditioned on information about tax evasion, as is the perceived tax compliance norm. We uncover asymmetries along the income gradient: Conditional cheating responses are driven by information about tax evasion on behalf of top income earners, while perceived tax compliance norms are driven by information about tax evasion among low income earners. Instrumental variable investigations of posterior beliefs about tax evasion strengthen these results, and reveal moreover that information about top income tax evasion erodes social trust, reinforces beliefs that wealth accumulation only occurs at others’ expense, and increases beliefs that a fundamental role of the State is that of ensuring an equitable distribution of income.
    Keywords: tax evasion, tax avoidance, conditional cooperation, cheating, survey experiment
    JEL: D01 D31 D63 H23 H26
    Date: 2022
  9. By: Sabatini, Serena; Martyr, Anthony; Gamble, Laura D.; Jones, Ian R.; Collins, Rachel; Matthews, Fiona E.; Knapp, Martin; Thom, Jeanette M.; Henderson, Catherine; Victor, Christina; Pentecost, Claire; Clare, Linda
    Abstract: Rationale: Research exploring social, cultural, and economic capital among people with dementia is scarce. Objective: We describe levels of social, cultural, and economic capital in people with dementia at baseline and levels of social and cultural capital 12 and 24 months later. We identify groups of people with dementia having different combinations of capital and explore whether the identified groups differ in personal characteristics at baseline and in quality of life (QoL), satisfaction with life (SwL), and well-being over time. Method: Baseline, 12-months, and 24-months data from 1537 people with dementia (age, mean = 76.4 years; SD = 8.5; Alzheimer's Disease = 55.4%) enrolled in the IDEAL cohort were analyzed. Social (interactions with friends, civic participation, social participation, neighborhood trust, social network), cultural (education, cultural participation) and economic (annual income) capital, QoL, SwL, well-being, and personal characteristics were assessed. Results: Compared to people their age, people with dementia reported slightly lower frequency of interactions with friends, social networks and social support, civic and cultural participation, education, and annual income. However, social engagement, cultural participation, and annual income are low among British older adults. Latent profile analysis identified four groups that, based on their levels of social, cultural, and economic capital were named socially and economically privileged (18.0% of participants); financially secure (21.0% of participants); low capital (36.9% of participants); and very low capital (24.1% of participants). Latent growth curve models showed that over time QoL, SwL, and well-being remained largely stable for all groups. Compared to the low capital group, the socially and economically privileged and financially secure groups had higher QoL and well-being whereas the group with very low capital had poorer QoL, SwL, and well-being. Conclusions: New policies and efforts from the government, philanthropic foundations, the voluntary and primary care sectors are needed to address social, cultural, and economic disadvantage among people with dementia.
    Keywords: assets; capital; dementia; latent profile analysis; longitudinal; quality of life; resources; satisfaction with life; well-being; ES/L001853/2; ES/L001853/2
    JEL: J1
    Date: 2023–01–01

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