Social Segregation and the Dynamics of Group Inequality

We explore the dynamics of group inequality when segregation of social networks places the initially less affluent group at a disadvantage in acquiring human capital. Extending Loury (1977), we demonstrate that (i) group differences in economic success can persist across generations in the absence of either discrimination or group differences in ability, provided that social segregation is sufficiently great, (ii) there is threshold level of integration above which group inequality cannot be sustained, (iii) this threshold varies systematically but non-monotonically with the population share of the disadvantaged group, (iv) crossing the threshold induces convergence to a common high level of human capital if the less affluent population share is suf- ficiently small (and the opposite, otherwise), and (v) a race-neutral policy that reduces the cost of acquiring human capital can expand the range over which reducing segregation can be Pareto-improving. JEL Categories: D31, Z13, J71segregation, networks, group inequality, human capital

The cost of segregation in (social) networks

This paper investigates the welfare effect of income redistribution in the private provision of public goods on networks. We first show that the welfare effect of income redistribution is determined by Bonacich centrality. Then we develop an index based on the network structure of interactions, which, roughly speaking, measures the welfare effect of income redistribution confined to a component of contributors. The proposed index vanishes when applied to large components of contributors that display special segregated interactions, which suggests an “asymptotic neutrality” of redistributive policies. JEL classification C72; D31; H4

Identity and Social Distance in Friendship Formation

We analyze a network formation model where agents belong to different communities. Both individual benefits and costs depend on direct as well as indirect connections. Benefits of an indirect connection decrease with distance in the network while the cost of a link depends on the type of agents involved. Two individuals from the same community always face a low linking cost and the cost of forming a relationship for two individuals of different communities diminishes with the rate of exposure of each of them to the other community. We derive a number of results with regard to equilibrium networks. In particular, socialization among the same type of agents can be weak even if the within-type link cost is very low and oppositional identity patterns can arise for a wide range of parameters. Our model also suggests that policies aiming at reducing segregation are socially desirable only if they reduce the within-community cost differential by a sufficiently large amount.networks; identity; homophily; social norms

Social Segregation and the Dynamics of Group Inequality

We explore the dynamics of group inequality when segregation of social networks places the initially less affluent group at a disadvantage in acquiring human capital. Extending Loury (1977), we demonstrate that (i) group differences in economic success can persist across generations in the absence of either discrimination or group differences in ability, provided that social segregation is sufficiently great, (ii) there is threshold level of integration above which group inequality cannot be sustained, (iii) this threshold varies systematically but non-monotonically with the population share of the disadvantaged group, (iv) crossing the threshold induces convergence to a common high level of human capital if the less affluent population share is sufficiently small (and the opposite, otherwise), and (v) a race-neutral policy that reduces the cost of acquiring human capital can expand the range over which reducing segregation can be Pareto-improving

Measuring and mitigating behavioural segregation using Call Detail Records

The overwhelming amounts of data we generate in our daily routine and in social networks has been crucial for the understanding of various social and economic factors. The use of this data represents a low-cost alternative source of information in parallel to census data and surveys. Here, we advocate for such an approach to assess and alleviate the segregation of Syrian refugees in Turkey. Using a large dataset of mobile phone records provided by Turkey's largest mobile phone service operator, Türk Telekom, in the frame of the Data 4 Refugees project, we define, analyse and optimise inter-group integration as it relates to the communication patterns of two segregated populations: refugees living in Turkey and the local Turkish population. Our main hypothesis is that making these two communities more similar (in our case, in terms of behaviour) may increase the level of positive exposure between them, due to the well-known sociological principle of homophily. To achieve this, working from the records of call and SMS origins and destinations between and among both populations, we develop an extensible, statistically-solid, and reliable framework to measure the differences between the communication patterns of two groups. In order to show the applicability of our framework, we assess how house mixing strategies, in combination with public and private investment, may help to overcome segregation. We first identify the districts of the Istanbul province where refugees and local population communication patterns differ in order to then utilise our framework to improve the situation. Our results show potential in this regard, as we observe a significant reduction of segregation while limiting, in turn, the consequences in terms of rent increase

Small World Networks with Segregation Patterns and Brokers

Many social networks have the following properties: (i) a short average distance between any two individuals; (ii) a high clustering coefficient; (iii) segregation patterns; the presence of (iv) brokers and (v) hubs. (i) and (ii) define a small world network. This paper develops a strategic network formation model where agents have heterogeneous knowledge of the network: cognizant agents know the whole network, while ignorant ones are less knowledgeable. For a broad range of parameters, all pairwise Nash (PN) networks have properties (i)-(iv). There are some PN networks with one hub. Cognizant agents have higher betweenness centrality: they are the brokers who connect different parts of the network. Ignorant agents cause the emergence of segregation patterns. The results are robust to varying the number of cognizant agents and to increasing the knowledge level of ignorant ones. An application shows the relevance of the results to assessing the welfare impact of an increase in network knowledge due to, e.g., improved access to social networking tools.Network, Cognitive Network, Small World, Broker, Segregation

The Persistence of Segregation in Buffalo, New York

Debates about the causes of segregation continue to consider the role that own-race preferences have in understanding the persistence of racial residential segregation in American cities. In this paper, I offer an alternative to the own-race preference model. I argue that segregation of low-income Black households from Whites persists in Buffalo, New York, because the spatial rootedness of Blacks’ survival strategies leads households to choose housing in the central city, where their social networks and most Black households live. I illustrate this argument by exploring the multiple reasons for why a group of African American households, who were prompted to move through the settlement of a high-profile housing discrimination lawsuit, chose to relocate to neighborhoods in the central city in Buffalo. I adopt a context-sensitive perspective in making the argument and further argue that such approaches are ultimately useful in capturing the complex reasons that underlie the persistence of segregation

A statistical model for brain networks inferred from large-scale electrophysiological signals

Network science has been extensively developed to characterize structural properties of complex systems, including brain networks inferred from neuroimaging data. As a result of the inference process, networks estimated from experimentally obtained biological data, represent one instance of a larger number of realizations with similar intrinsic topology. A modeling approach is therefore needed to support statistical inference on the bottom-up local connectivity mechanisms influencing the formation of the estimated brain networks. We adopted a statistical model based on exponential random graphs (ERGM) to reproduce brain networks, or connectomes, estimated by spectral coherence between high-density electroencephalographic (EEG) signals. We validated this approach in a dataset of 108 healthy subjects during eyes-open (EO) and eyes-closed (EC) resting-state conditions. Results showed that the tendency to form triangles and stars, reflecting clustering and node centrality, better explained the global properties of the EEG connectomes as compared to other combinations of graph metrics. Synthetic networks generated by this model configuration replicated the characteristic differences found in brain networks, with EO eliciting significantly higher segregation in the alpha frequency band (8-13 Hz) as compared to EC. Furthermore, the fitted ERGM parameter values provided complementary information showing that clustering connections are significantly more represented from EC to EO in the alpha range, but also in the beta band (14-29 Hz), which is known to play a crucial role in cortical processing of visual input and externally oriented attention. These findings support the current view of the brain functional segregation and integration in terms of modules and hubs, and provide a statistical approach to extract new information on the (re)organizational mechanisms in healthy and diseased brains.Comment: Due to the limitation "The abstract field cannot be longer than 1,920 characters", the abstract appearing here is slightly shorter than that in the PDF fil

Barriers and Bridges: An Action Plan for Overcoming Obstacles and Unlocking Opportunities for African American Men in Pittsburgh

Among the region's residents, Pittsburgh's African American men have historically and disproportionately faced unprecedented barriers to economic opportunities. This study, supported by The Heinz Endowments, focuses on structural barriers that contribute to persistent racial disparities in the Pittsburgh region. Structural barriers are obstacles that collectively affect a group disproportionately and perpetuate or maintain stark disparities in outcomes. Structural barriers can be policies, practices, and other norms that favor an advantaged group while systematically disadvantaging a marginalized group. A community touched by racebased structural barriers can be identified by the racial and economic stratification of its residents; Pittsburgh, like many large cities in the United States, fits that description

Stochastic network formation and homophily

This is a chapter of the forthcoming Oxford Handbook on the Economics of Networks