Just as we learn from, influence, and are influenced by others, our social interactions drive economic growth in cities, regions, and nations--determining where households live, how children learn, ...and what cities and firms produce.From Neighborhoods to Nationssynthesizes the recent economics of social interactions for anyone seeking to understand the contributions of this important area. Integrating theory and empirics, Yannis Ioannides explores theoretical and empirical tools that economists use to investigate social interactions, and he shows how a familiarity with these tools is essential for interpreting findings. The book makes work in the economics of social interactions accessible to other social scientists, including sociologists, political scientists, and urban planning and policy researchers.
Focusing on individual and household location decisions in the presence of interactions, Ioannides shows how research on cities and neighborhoods can explain communities' composition and spatial form, as well as changes in productivity, industrial specialization, urban expansion, and national growth. The author examines how researchers address the challenge of separating personal, social, and cultural forces from economic ones. Ioannides provides a toolkit for the next generation of inquiry, and he argues that quantifying the impact of social interactions in specific contexts is essential for grasping their scope and use in informing policy.
Revealing how empirical work on social interactions enriches our understanding of cities as engines of innovation and economic growth,From Neighborhoods to Nationscarries ramifications throughout the social sciences and beyond.
Loneliness is a rising global problem just as digital communication platforms have afforded people greater opportunities to interact. This paradox suggests that increased opportunities for social ...interactions may be insufficient for relieving loneliness. Using daily diary methodology, we examined how features of social interactions—type and perceived quality—predicted daily loneliness. Over 14 consecutive days, 269 adult participants provided 2986 daily reports on their loneliness levels, the types of daily social interactions they had, and the quality of these social interactions. Results indicated that in-person interactions most strongly predicted reduced loneliness relative to other interaction types. Interactions characterized by positive qualities were associated with lower same-day loneliness. In turn, interactions characterized by negative qualities were associated with higher same-day loneliness. Across all subjective qualities, feeling closed off and distant from others during interactions was the strongest predictor of same-day loneliness. These findings highlight that time spent socializing is not a panacea for reducing loneliness, and increasing in-person interactions and reducing negative social experiences may best foster social connection.
