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on Social Norms and Social Capital |
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Issue of 2025–09–22
ten papers chosen by Fabio Sabatini, Università degli Studi di Roma “La Sapienza” |
| By: | Francesco Slataper; Luis Menéndez; Daniel Montolio; Hannes Mueller |
| Abstract: | This article exploits data from a political conflict between language groups to show how political events can rapidly redefine how these groups interact on social media. Leveraging on a unique dataset of 26 million retweets by 120 000 Catalan- and Spanish- speaking Twitter users, we estimate individual exposure to tweets with a network-based model. We then compare two shocks in the same region and year: the Barcelona terror attack and the Catalan independence referendum of 2017. The referendum, and related police violence, triggered a sharp, symmetric jump in retweeting across language groups. The terror attack, by contrast, did not lead to a similar realignment. |
| Keywords: | echo-chambers, ethno-linguistic conflict, polarization, political conflict, retweet behavior, social media, social networks |
| JEL: | D74 C55 C45 |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:bge:wpaper:1505 |
| By: | Christian Ochsner; Lukas Schmid |
| Abstract: | We study the effects of the largest adverse health shock in modern medicine—the 1918 influenza pandemic—on subsequent shifts in health-related attitudes and behavior and future-oriented policies. Our analysis builds upon self-digitized, individuallevel death-register excerpts, vaccination records, and popular vote counts. We find that greater exposure to influenza leads to a decline in societal support for public health measures at the aggregate level, mainly triggered by deceased peers. However, individual-level data reveal increased vaccination rates in families who experienced influenza-related deaths. These differences did not exist before the pandemic. Our findings link to a U-shaped relationship between suffering from the pandemic and support for effective health policies. Places with predominantly indirectly-affected families drive the aggregate backlash. This challenges the idea that past health shocks improve life expectancy through societal learning. |
| Keywords: | Health behavior, Health attitudes, 1918 influenza pandemic, Mistrust |
| JEL: | I12 I18 H51 D72 N34 |
| Date: | 2025–06 |
| URL: | https://d.repec.org/n?u=RePEc:cer:papers:wp796 |
| By: | Maria De Paola; Roberto Nisticò; Vincenzo Scoppa |
| Abstract: | This paper examines the impact of co-workers’ fertility on individual fertility decisions. Using matched employer-employee data from Italian social security records (2016–2020), we estimate how fertility among co-workers of similar age and occupation affects the individual likelihood of having a child. We exploit variation introduced by the 2015 Jobs Act, which reduced fertility among workers hired under weaker employment protection. Focusing on workers hired before the reform and using the share of colleagues hired after the reform as an instrument for peer fertility, we find that a one-percentage-point increase in peer fertility raises individual fertility by 0.4 percentage points (a 10% increase). Heterogeneity analysis suggests that while social influence and social norms are key mechanisms, information sharing and career concerns, particularly among women, tend to moderate the response. Our findings highlight how changes in employment protection may have unintended fertility spillovers through workplace social interactions. |
| Keywords: | career concerns, EPL, fertility, social learning, social norms, workplace |
| JEL: | C3 J13 J65 J41 M51 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12131 |
| By: | Davis, John B. (Department of Economics Marquette University); (Department of Economics Marquette University) |
| Abstract: | Disadvantaged social groups in the US suffered disproportionately in the covid pandemic and Great Recession, worsening high levels of inequality associated with their post-1980 declining intergenerational income mobility. For black Americans this reflects the long history of racial discrimination beginning with slavery. Reparations paid to descendants of enslaved individuals to eliminate the black-white wealth gap is a step toward addressing this history. A further needed step is to build predominantly black communities human and social capital through public investments in community health care centers (CHCs) and historically black colleges and universities (HBCUs). There is considerable evidence that investments in early childhood education positively affect later school performance, income and earnings, higher education, crime, and other well-being outcomes. CHCs and HBCUs promote early childhood education. This paper argues compensation is due to both individuals and their communities, and reparations payments should be accompanied by public investments in those communities. |
| Keywords: | reparations, racial inequality, human capital, social capital, early childhood education, CHCs, HBCUs, restitutive justice, restorative justice |
| JEL: | D31 D63 I31 J15 Z13 |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:mrq:wpaper:2025-05 |
| By: | Naoki Akaeda |
| Abstract: | Although previous international comparative research has focused on social policy and social capital as crucial factors in promoting self-rated health, notable gaps remain. First, few studies have explored the interaction effect of these factors on self-rated health. Second, in terms of the proxies of social policy, earlier publications may mingle the levels and distribution of welfare provisions. To overcome these limitations, this study adopts three dimensions of welfare transfers as proxies of social policy to analyze the cross-level interaction effects of welfare transfers and social capital on self-rated health. For the analysis, this study utilizes data from the Luxembourg Income Study Database, the World Values Survey, and the European Values Study including multiple rounds. An international comparative analysis revealed that transfer share may strengthen the health impact of social trust, whereas low-income targeting may weaken the correlations between two types of civic participation, in particular, Olson-type and Putnam-type associations, and self-rated health. |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:lis:liswps:904 |
| By: | Tamara Schnell (Carl von Ossietzky Universität Oldenburg, Institute for Social Sciences, Working group “Organiza-tion and Innovation”, Oldenburg); Ricarda Schmidt-Scheele (Carl von Ossietzky Universität Oldenburg, Institute for Social Sciences, Working group “Organiza-tion and Innovation”, Oldenburg) |
| Abstract: | AI decision aids are increasingly adopted in public administration to support complex decisions tra-ditionally carried out by employees of public authorities. While prior research has emphasized deci-sion-makers’ trust in AI, less attention has been paid to stakeholders who are exposed to and af-fected by these emerging AI-supported decision-making processes and outcomes. In such con-texts, it is not only the AI itself – its process, performance, and purpose – that is assessed for trustworthiness, but also existing constellations of decision-makers and institutions that govern decision-making. We argue that trust in AI is socially embedded. Drawing on sociological theories of trust, we propose a framework that conceptualizes trust in AI decision aids as shaped by existing trust relations with decision-makers and institutions involved in decision-making – the ‘shadow of the past’. To explore this, we examine a case study of an AI-augmented geographic information system (AI-GIS) developed to support spatial planning for onshore wind energy in the course of sustainably energy transition dynamics in Germany. Based on 38 interviews with stakeholders from seven groups involved in spatial planning and wind energy development, we analyze initial (mis)trust in the AI-GIS. Using a combination of qualitative comparative analysis (QCA) and qualitative content analysis, we identify four distinct configurations that condition stakeholders’ (mis)trust. Each re-flects a unique interplay of interpersonal and institutional trust relations. The study offers a more nuanced understanding of trust in AI as a relational, context-dependent phenomenon, highlighting the relevance of institutions and existing trust relations for understanding and guiding AI adoption. It therefore directly contributes to the literature on sustainability transitions and their place-specific dynamics. AI systems are considered viable technical solutions for the transformation of energy, water, or food systems. Accordingly, trust in these AI systems needs to be understood as highly context-dependent: Trust is developed and experienced within specific institutional set-tings, regulatory cultures, and histories of technology adoption. Hence, our paper di-rects attention to who trusts what AI, where, and under what institutional arrangements and urges this to be a central question in the sustainability transitions literature. |
| Keywords: | Trust in AI, Social embeddedness of trust, Trust in institutions, Qualitative Comparative Analysis (QCA), Spatial planning, Onshore wind energy |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:aoe:wpaper:2502 |
| By: | David Jesuit; Thomas Greitens |
| Abstract: | This chapter considers the comparative impact of ineffective policies on declining trust in government and its impact on the policy process. It relies on the most recent module from the 2016 International Social Survey Program’s (ISSP) series on the “Role of Government, ” which was only recently made available to researchers. This survey measures individual satisfaction with several policy outcomes, as well as the fairness of bureaucratic processes and trust in government. Ineffective policy is operationalized using two approaches derived from these data, both of which are based on respondents’ evaluation of public policies in different countries. The first approach emphasizes perceptions of policy effectiveness in providing health care, maintaining adequate standards of living, and managing national security threats. The second approach emphasizes perceptions of negative policy outcomes requiring changes in spending levels across a variety of policy domains. Results from multilevel models suggest that when the public perceives policy ineffectiveness, their trust in government and perceptions of bureaucratic fairness decline. As a result, the ability of the public to use the policy process to transform ineffective policies erodes and public accountability over the policy process disappears, resulting in a downward spiral of bad policy outcomes and declining trust in public servants and institutions. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:lis:liswps:900 |
| By: | Sona Badalyan |
| Abstract: | This paper exploits a unique norm-shifting setting—a German pension reform that equalized retirement ages across genders—to examine how old-age employment propagates through workplace networks. The reform raised women’s earliest claiming age from 60 to 63 for cohorts born in 1952 onward. Using the universe of workgroups from social security records, I compare women whose peers were just above or below the reform cutoff. I find that women are more likely to remain employed at older ages when their peers do, with stronger effects in the regions of former West Germany, with its traditional gender norms. Gender-neutral pension reforms thus amplify their impact through peer influence, fostering regional convergence in late-career employment patterns. |
| Keywords: | aging, gender, peer effects, old age employment, social norms |
| JEL: | D85 H55 J14 J16 J22 J26 Z13 |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:cer:papers:wp800 |
| By: | Benjamin W. Cowan; Todd R. Jones |
| Abstract: | This paper examines how people adjust their time use when they experience an increase in time spent alone, which is a growing share of adults’ lives. We utilize the dramatic rise in remote work following the onset of the pandemic, which is associated with a large decline in time spent in the physical presence of non-household members during the workday, to observe the extent to which individuals substitute toward more in-person interactions in non-work settings. We first document that on days that individuals work from home, they spend 3.5 additional hours in activities spent entirely alone and over 5 fewer hours in activities that include any non-household members. We then use a difference-in-difference strategy to ask what happens to time allocations when workers are induced toward remote work by analyzing changes over time in how workers in teleworkable occupations—who experienced the lion’s share of the post-COVID increase in remote work—spend their time relative to workers in non-teleworkable occupations. Averaging over all days of the week, we see a relative increase in time spent in activities spent entirely alone by 32 minutes and a decrease in activities that include any non-household members by 38 minutes for workers in teleworkable jobs. Normalizing by the increase in average daily remote work time (46 minutes), these estimates are of a similar magnitude to what we observe in our descriptive analysis. When individuals are induced to work from home, they exhibit almost no substitution toward spending more time with others who are not in their household to make up for the loss of time with others at work. |
| Keywords: | work from home, social isolation, time use |
| JEL: | J22 J24 I31 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12117 |
| By: | Alexander Erlei |
| Abstract: | Generative AI is transforming the provision of expert services. This article uses a series of one-shot experiments to quantify the behavioral, welfare and distribution consequences of large language models (LLMs) on AI-AI, Human-Human, Human-AI and Human-AI-Human expert markets. Using a credence goods framework where experts have private information about the optimal service for consumers, we find that Human-Human markets generally achieve higher levels of efficiency than AI-AI and Human-AI markets through pro-social expert preferences and higher consumer trust. Notably, LLM experts still earn substantially higher surplus than human experts -- at the expense of consumer surplus - suggesting adverse incentives that may spur the harmful deployment of LLMs. Concurrently, a majority of human experts chooses to rely on LLM agents when given the opportunity in Human-AI-Human markets, especially if they have agency over the LLM's (social) objective function. Here, a large share of experts prioritizes efficiency-loving preferences over pure self-interest. Disclosing these preferences to consumers induces strong efficiency gains by marginalizing self-interested LLM experts and human experts. Consequently, Human-AI-Human markets outperform Human-Human markets under transparency rules. With obfuscation, however, efficiency gains disappear, and adverse expert incentives remain. Our results shed light on the potential opportunities and risks of disseminating LLMs in the context of expert services and raise several regulatory challenges. On the one hand, LLMs can negatively affect human trust in the presence of information asymmetries and partially crowd-out experts' other-regarding preferences through automation. On the other hand, LLMs allow experts to codify and communicate their objective function, which reduces information asymmetries and increases efficiency. |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2509.06069 |