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Favoritism refers to the act of offering jobs, contracts and resources to members of one's own social group in preference to others who are outside the group. This paper examines the economic origins and the consequences of favoritism.
Geography and social links shape economic interactions. In industries, schools, and markets, the entire network determines outcomes. This paper analyzes a large class of games and obtains a striking result. Equilibria depend on a single network measure: the lowest eigenvalue. This paper is the first to uncover the importance of the lowest eigenvalue to economic and social outcomes. It captures how much the network amplifies agents' actions. The paper combines new tools—potential games, optimization, and spectral graph theory—to solve for all Nash and stable equilibria and applies the results to R&D, crime, and the econometrics of peer effects.
We study network games under strategic complementarities. Agents are embedded in a fixed network. They choose a positive, continuous action and interact with their network neighbors. Interactions are positive and actions are bounded from above. We first derive new sufficient conditions for uniqueness, covering all concave as well as some non-concave best responses. We then study the relationship between position and action and identify situations where a more central agent always plays a higher action in equilibrium. We finally analyze comparative statics. We show that a shock may not propagate throughout the entire network and uncover a general pattern of decreasing interdependence.
We provide the first empirical application of a new approach proposed by Lee (Journal of Econometrics 2007; 140(2), 333–374) to estimate peer effects in a linear-in-means model when individuals interact in groups. Assumingsufficient group size variation, this approach allows to control for correlated effects at the group level and to solve the simultaneity (reflection) problem. We clarify the intuition behind identification of peer effects in the model. We investigate peer effects in student achievement in French, Science, Mathematics and History in secondary schools in the Province of Québec (Canada). We estimate the model using conditional maximum likelihood and instrumental variables methods. We find some evidence of peer effects. The endogenous peer effect is large and significant in Mathematics but imprecisely estimated in the other subjects. Some contextual peer effects are also significant. In particular, for most subjects, the average age of peers has a negative effect on own test score. Using calibrated Monte Carlo simulations, we find that high dispersion in group sizes helps with potential issues of weak identification. Copyright © 2012 John Wiley & Sons, Ltd.
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We model network formation when heterogeneous nodes enter sequentially and form connections through both random meetings and network-based search, but with type-dependent biases. We show that there is “long-run integration”, whereby the composition of types in sufficiently old nodesʼ neighborhoods approaches the global type-distribution, provided that the network-based search is unbiased. However, younger nodesʼ connections still reflect the biased meetings process. We derive the type-based degree distributions and group-level homophily patterns when there are two types and location-based biases. Finally, we illustrate aspects of the model with an empirical application to data on citations in physics journals.
This paper studies the dynamics of fundamental research. We develop a simple model where researchers allocate their effort between improving existing fields and inventing new ones. A key assumption is that scientists derive utility from recognition from other scientists. We show that the economy can be either in a regime where new fields are constantly invented, and then converges to a steady state, or in a cyclical regime where periods of innovation alternate with periods of exploitation. Our analysis provides a rigorous foundation to the Kuhnian theory of scientific evolution. We show that scientists' care for reputation has a strong impact on research dynamics and tends to favor innovation. Especially, innovation fads may emerge. We also study welfare and find that the academic reputational reward system can help align scientists' short-term incentives with society's long-term interests.