Bounded Rationality

The observation of the actual behavior by economic decision makers in the lab and in the field justifies that bounded rationality has been a generally accepted assumption in many socio-economic models. The goal of this paper is to illustrate the difficulties involved in providing a correct definition of what a rational (or irrational) agent is. In this paper we describe two frameworks that employ different approaches for analyzing bounded rationality. The first is a spatial segregation set-up that encompasses two optimization methodologies: backward induction and forward induction. The main result is that, even under the same state of knowledge, rational and non-rational agents may match their actions. The second framework elaborates on the relationship between irrationality and informational restrictions. We use the beauty contest (Nagel, 1995) as a device to explain this relationship.Behavioral economics, bounded rationality, partial information

Outerfactor and the indirect journal impact

In this paper, we use research chains across the citation graph as the basis for journal impact analysis. While some existing measures take into account research chains that end in a given journal, we calculate the proportion of research chains that include a journal, obtaining a new index of journal impact, Outerfactor, that is directly related to Pagerank (Brin and Page, 1998), Eigenfactor (Bergstrom, 2007) and the Invariant Method (Pinsky and Narin, 1976). In this way, the Outerfactor score obtained by each journal is independent on its own citation pattern and its article share. To our knowledge, this is the fi�rst measure that satis�fes these invariance properties whilst accounting for both direct and indirect impact. Based on research chains that connect two journals, we also construct new measures for analyzing cross-impact. This cross-impact analysis results in a two-fold view of Outerfactor in terms of a journal�'s infl�uence (impact) on other journals, or a journal�'s contribution to all journals' �impact scores. Finally, we provide an illustration with 60 economics journals, showing how Outerfactor performs compared to other measures: apart from its cardinal invariance, Outerfactor behaves more robustly to ordinal manipulation than other eigenvector-based measures.citation analysis, impact factor, eigenfactor, eigenvector-based measures, manipulation

Who's Who in Crime Network. Wanted the Key Player

Criminals are embedded in a network of relationships. Social ties among criminals are modeled by means of a graph where criminals compete for a booty and benefit from local interactions with their neighbours. Each criminal decides in a non-cooperative way how much crime effort he will exert. We show that the Nash equilibrium crime effort of each individual is proportional to his equilibrium Bonacich-centrality in the network, thus establishing a bridge to the sociology literature on social networks. We then analyze a policy that consists of finding and getting rid of the key player, that is, the criminal who, once removed, leads to the maximum reduction in aggregate crime. We provide a geometric characterization of the key player identified with an optimal inter-centrality measure, which takes into account both a player's centrality and his contribution to the centrality of the others. We also provide a geometric characterization of the key group, which generalizes the key player for a group of criminals of a given size. We finally endogeneize the crime participation decision, resulting in a key player policy, which effectiveness depends on the outside opportunities available to criminals.Social Networks; Crime; Centrality Measures; Key Group; Policies

Random—walk—based segregation measures

We propose an intuitive way of how to measure segregation in social and spatial networks. Using random walks, we define the segregation index as the probability that an individual meets an individual from the same social group. The segregation index is a generalization of the isolation index and a homophily index introduced in Currarini et al. (2009), and it has a closed– form relation to PageRank that facilitates its computation. We also show that the Spectral Segregation Index proposed by Echenique and Fryer (2007) is not continuous with respect to the network structure. Finally, we apply the measure to Spanish census data and to citations data from Economics, and rationalize the index as the equilibrium outmode of a game

Bounded rationality

The observation of the actual behavior by economic decision makers in the lab and in the field justifies that bounded rationality has been a generally accepted assumption in many socio-economic models. The goal of this paper is to illustrate the difficulties involved in providing a correct definition of what a rational (or irrational) agent is. In this paper we describe two frameworks that employ different approaches for analyzing bounded rationality. The first is a spatial segregation set-up that encompasses two optimization methodologies: backward induction and forward induction. The main result is that, even under the same state of knowledge, rational and non-rational agents may match their actions. The second framework elaborates on the relationship between irrationality and informational restrictions. We use the beauty contest (Nagel, 1995) as a device to explain this relationship

Delinquent Networks

Delinquents are embedded in a network of relationships. Social ties among delinquents are modelled by means of a graph where delinquents compete for a booty and benefit from local interactions with their neighbors. Each delinquent decides in a non cooperative way how much delinquency effort he will exert. Using the network model developed by Ballester et al. (2006), we characterize the Nash equilibrium and derive an optimal enforcement policy, called the key-player policy, which targets the delinquent who, once removed, leads to the highest aggregate delinquency reduction. We then extend our characterization of optimal single player network removal for delinquency reduction, the key player, to optimal group removal, the key group. We also characterize and derive a policy that targets links rather than players. Finally, we endogenize the network connecting delinquents by allowing players to join the labor market instead of committing delinquent offenses. The key-player policy turns out to be much more complex since it depends on wages and on the structure of the network.Social networks, delinquency decision, key group, NP-hard problem, crime policies

Peer effects in public contributions: theory and experimental evidence

This paper analyzes the impact of social integration on cooperative behavior. We show that if the social network shows assortative mixing then conditional cooperation is an equilibrium strategy for altruistic subjects with a high degree of social integration.We provide experimental evidence on the relationship between individuals’ position in a social network and their contributions in a public good game.public good game, social networks, conditional cooperation.

Peer effects in public contributions: theory and experimental evidence

This paper analyzes the impact of social integration on cooperative behavior. We show that if the social network shows assortative mixing then conditional cooperation is an equilibrium strategy for altruistic subjects with a high degree of social integration.We provide experimental evidence on the relationship between individuals’ position in a social network and their contributions in a public good game.María Paz Espinosa acknowledges financial aid from MEC (SEJ2006-06309/ECON) and Gobierno Vasco, DEUI (IT-313-07); Pablo Brañas-Garza from DGCYT (SEJ2007-62081/ECON)

Outerfactor and the indirect journal impact

In this paper, we use research chains across the citation graph as the basis for journal impact analysis. While some existing measures take into account research chains that end in a given journal, we calculate the proportion of research chains that include a journal, obtaining a new index of journal impact, Outerfactor, that is directly related to Pagerank (Brin and Page, 1998), Eigenfactor (Bergstrom, 2007) and the Invariant Method (Pinsky and Narin, 1976). In this way, the Outerfactor score obtained by each journal is independent on its own citation pattern and its article share. To our knowledge, this is the fi�rst measure that satis�fes these invariance properties whilst accounting for both direct and indirect impact. Based on research chains that connect two journals, we also construct new measures for analyzing cross-impact. This cross-impact analysis results in a two-fold view of Outerfactor in terms of a journal�'s infl�uence (impact) on other journals, or a journal�'s contribution to all journals' �impact scores. Finally, we provide an illustration with 60 economics journals, showing how Outerfactor performs compared to other measures: apart from its cardinal invariance, Outerfactor behaves more robustly to ordinal manipulation than other eigenvector-based measures