A large body of recent research argues that social, or non-market, interactions can explain a wide range of puzzling phenomena from fashion cycles to stock market crashes. This paper attempts to connect the range of these papers with a general model and a broad empirical overview. We establish...

In many cases, aggregate data is used to make inferences about individual level behavior. If there are social interactions in which one person’s actions influence his neighbor’s incentives or information, then these inferences are inappropriate. The presence of positive social...

Aggregate data is often used to make inferences about individual level behavior. If there are social interactions in which one person's actions influence his neighbor's incentives or information, then these inferences are inappropriate. The presence of positive social interactions, or strategic...

In many cases, aggregate data is used to make inferences about individual level behavior. If there are social interactions in which one person's actions influence his neighbor's incentives or information, then these inferences are inappropriate. The presence of positive social interactions, or...

Using a sample of Harvard undergraduates, we analyze trust and social capital in two experiments. Trusting behavior and trustworthiness rise with social connection; differences in race and nationality reduce the level of trustworthiness. Certain individuals appear to be persistently more...

The high degree of variance of crime rates across space (and across time) is one of the oldest puzzles in the social sciences (see Quetelet (1835)). Our empirical work strongly suggests that this variance is not the result of observed or unobserved geographic attributes. This paper presents a...

We examine the relationship between urban characteristics in 1960 and urban growth (income and population) between 1960 and 1990. Our major findings are that income and population growth move together and both types of growth are (1) positively related to initial schooling, (2) negatively...