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108
The Evolution of Social and Economic Networks
 Journal of Economic Theory
, 1999
"... : We examine the dynamic formation and stochastic evolution of networks connecting individuals. The payoff to an individual from an economic or social activity depends on the network of connections among individuals. Over time individuals form and sever links connecting themselves to other individua ..."
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Cited by 349 (20 self)
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: We examine the dynamic formation and stochastic evolution of networks connecting individuals. The payoff to an individual from an economic or social activity depends on the network of connections among individuals. Over time individuals form and sever links connecting themselves to other individuals based on the improvement that the resulting network offers them relative to the current network. We call such sequences of networks, improving paths,' and show that such sequences can include cycles and study conditions on underlying allocation rules that characterize cycles. Building on the concept of improving paths, we consider a stochastic evolutionary process where in addition to intended changes in the network there is a small probability of unintended changes or errors. Predictions can be made regarding the relative likelihood that the stochastic process will lead to any given network at some time, and the evolutionary process selects from among the statically stable networks and c...
A Survey of Models of Network Formation: Stability and Efficiency
, 2003
"... I survey the recent literature on the formation of networks. I provide definitions of network games, a number of examples of models from the literature, and discuss some of what is known about the (in)compatibility of overall societal welfare with individual incentives to form and sever links. ..."
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Cited by 196 (14 self)
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I survey the recent literature on the formation of networks. I provide definitions of network games, a number of examples of models from the literature, and discuss some of what is known about the (in)compatibility of overall societal welfare with individual incentives to form and sever links.
Discrete Choice with Social Interactions

, 2000
"... This paper provides an analysis of aggregate behavioral outcomes when individual utility exhibits social interaction effects. We study generalized logistic models of individual choice which incorporate terms reflecting the desire of individuals to conform to the behavior of others in an environment ..."
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Cited by 184 (10 self)
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This paper provides an analysis of aggregate behavioral outcomes when individual utility exhibits social interaction effects. We study generalized logistic models of individual choice which incorporate terms reflecting the desire of individuals to conform to the behavior of others in an environment of noncooperative decisionmaking. Laws of large numbers are generated in such environments. Multiplicity of
A generalized moments estimator for the autoregressive parameter in a spatial model
 International Economic Review
, 1999
"... This paper is concerned with the estimation of the autoregressive parameter in a widely considered spatial autocorrelation model. The typical estimator for this parameter considered in the literature is the (quasi) maximum likelihood estimator corresponding to a normal density. However, as discussed ..."
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Cited by 95 (12 self)
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This paper is concerned with the estimation of the autoregressive parameter in a widely considered spatial autocorrelation model. The typical estimator for this parameter considered in the literature is the (quasi) maximum likelihood estimator corresponding to a normal density. However, as discussed in the paper, the (quasi) maximum likelihood estimator may not be computationally feasible in many cases involving moderate or large sized samples. In this paper we suggest a generalized moments estimator that is computationally simple irrespective of the sample size. We provide results concerning the large and small sample properties of this estimator. 1 Introduction 1 There exists a large body of literature that considers autocorrelation of the disturbances across cross sectional units for panel data, i.e., data which are observed both across cross sectional units and over time. However, the estimation of models that permit for autocorrelation of the disturbances across
Measuring social interactions
, 1999
"... This paper presents on overview of the economics that lies behind social interaction models and briefly discusses the empirical approaches to social interactions. We present a simple model with local interactions, similar to Glaeser, Sacerdote and Scheinkman (1996) but using a continuous action spac ..."
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Cited by 80 (2 self)
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This paper presents on overview of the economics that lies behind social interaction models and briefly discusses the empirical approaches to social interactions. We present a simple model with local interactions, similar to Glaeser, Sacerdote and Scheinkman (1996) but using a continuous action space and starting with optimizing behavior. We then extend the model to include both global and local interactions. We suggest and use a methodology for using variation of intracity aggregates to identify the relative sizes of local and global interactions. We also present a model with endogenous location choice and use the predictions of that model to identify the sources of crosscity variance that are due to sorting and interaction. Finally, we present a brief discussion of using timeseries to estimate the social interactions in broad aggregates.
Agentbased computational models and generative social science
 Complexity
, 1999
"... This article argues that the agentbased computational model permits a distinctive approach to social science for which the term “generative ” is suitable. In defending this terminology, features distinguishing the approach from both “inductive ” and “deductive ” science are given. Then, the followi ..."
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Cited by 64 (0 self)
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This article argues that the agentbased computational model permits a distinctive approach to social science for which the term “generative ” is suitable. In defending this terminology, features distinguishing the approach from both “inductive ” and “deductive ” science are given. Then, the following specific contributions to social science are discussed: The agentbased computational model is a new tool for empirical research. It offers a natural environment for the study of connectionist phenomena in social science. Agentbased modeling provides a powerful way to address certain enduring—and especially interdisciplinary—questions. It allows one to subject certain core theories—such as neoclassical microeconomics—to important types of stress (e.g., the effect of evolving preferences). It permits one to study how rules of individual behavior give rise—or “map up”—to macroscopic regularities and organizations. In turn, one can employ laboratory behavioral research findings to select among competing agentbased (“bottom up”) models. The agentbased approach may well have the important effect of decoupling individual rationality from macroscopic equilibrium and of separating decision science from social science more generally. Agentbased modeling offers powerful new forms of hybrid theoreticalcomputational work; these are particularly relevant to the study of nonequilibrium systems. The agentbased approach invites the interpretation of society as a distributed computational device, and in turn the interpretation of social dynamics as a type of computation. This interpretation raises important foundational issues in social science—some related to intractability, and some to undecidability proper. Finally, since “emergence” figures prominently in this literature, I take up the connection between agentbased modeling and classical emergentism, criticizing the latter and arguing that the two are incompatible. � 1999 John Wiley &
Spatial Econometrics
 PALGRAVE HANDBOOK OF ECONOMETRICS: VOLUME 1, ECONOMETRIC THEORY
, 2001
"... Spatial econometric methods deal with the incorporation of spatial interaction and spatial structure into regression analysis. The field has seen a recent and rapid growth spurred both by theoretical concerns as well as by the need to be able to apply econometric models to emerging large geocoded da ..."
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Cited by 64 (5 self)
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Spatial econometric methods deal with the incorporation of spatial interaction and spatial structure into regression analysis. The field has seen a recent and rapid growth spurred both by theoretical concerns as well as by the need to be able to apply econometric models to emerging large geocoded data bases. The review presented in this chapter outlines the basic terminology and discusses in some detail the specification of spatial effects, estimation of spatial regression models, and specification tests for spatial effects.
Place of Work and Place of Residence: Informal Hiring Networks and Labor Market Outcomes
 JOURNAL OF POLITICAL ECONOMY
, 2004
"... We use a novel dataset and research design to empirically detect the effect of social interactions among neighbors on labor market outcomes. Specifically, using Census data that characterize residential and employment locations down to the city block, we examine whether individuals residing in the s ..."
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Cited by 56 (2 self)
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We use a novel dataset and research design to empirically detect the effect of social interactions among neighbors on labor market outcomes. Specifically, using Census data that characterize residential and employment locations down to the city block, we examine whether individuals residing in the same block are more likely to work together than individuals in nearby but not identical blocks. We find significant evidence of social interactions; the baseline probability of working together is 0.93 % at the block level compared to 0.51 % at the block group level (a collection of ten contiguous blocks). We also provide evidence as to which types of matches between individuals result in greater levels of referrals. These findings are robust to the introduction of detailed controls for sociodemographic characteristics and block group fixed effects, as well as across various specifications intended to address sorting and housing market rather than labor market referrals. Further, our estimated effects have a significant impact on a wide range of labor market outcomes more generally.
The economics of social networks
 PROCEEDINGS OF THE 9 TH WORLD CONGRESS OF THE ECONOMETRIC SOCIETY
, 2005
"... The science of social networks is a central field of sociological study, a major application of random graph theory, and an emerging area of study by economists, statistical physicists and computer scientists. While these literatures are (slowly) becoming aware of each other, and on occasion drawing ..."
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Cited by 53 (2 self)
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The science of social networks is a central field of sociological study, a major application of random graph theory, and an emerging area of study by economists, statistical physicists and computer scientists. While these literatures are (slowly) becoming aware of each other, and on occasion drawing from one another, they are still largely distinct in their methods, interests, and goals. Here, my aim is to provide some perspective on the research from these literatures, with a focus on the formal modeling of social networks and the two major types of models: those based on random graphs and those based on game theoretic reasoning. I highlight some of the strengths, weaknesses, and potential synergies between these two network modeling approaches.
On the asymptotic distribution of the Moran I test statistic with applications
 Journal of Econometrics104
"... By far, the most popular test for spatial correlation is the one based on Moran’s (1950) I test statistic. Despite this, the available results in the literature concerning the large sample distribution of this statistic are limited and have been derived under assumptions that do not cover many appli ..."
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Cited by 45 (6 self)
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By far, the most popular test for spatial correlation is the one based on Moran’s (1950) I test statistic. Despite this, the available results in the literature concerning the large sample distribution of this statistic are limited and have been derived under assumptions that do not cover many applications of interest. In this paper we first give a general result concerning the large sample distribution of Moran I type test statistics. We then apply this result to derive the large sample distribution of the Moran I test statistic for a variety of important models. In order to establish these results we also give a new central limit theorem for linearquadratic forms.