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on Network Economics |
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Issue of 2018‒03‒12
three papers chosen by Pedro CL Souza Pontifícia Universidade Católica do Rio de Janeiro |
| By: | Elliott, M.; Golub, B. |
| Abstract: | Suppose agents can exert costly effort that creates nonrival, heterogeneous benefits for each other. At each possible outcome, a weighted, directed network describing marginal externalities is defined. We show that Pareto efficient outcomes are those at which the largest eigenvalue of the network is 1. An important set of efficient solutions - Lindahl outcomes - are characterized by contributions being proportional to agents' eigenvector centralities in the network. The outcomes we focus on are motivated by negotiations. We apply the results to identify who is essential for Pareto improvements, how to efficiently subdivide negotiations, and whom to optimally add to a team. |
| Date: | 2018–02–07 |
| URL: | http://d.repec.org/n?u=RePEc:cam:camdae:1813&r=net |
| By: | Samuel Bazzi; Amalavoyal V. Chari; Shanthi Nataraj; Alexander D. Rothenberg |
| Abstract: | Despite the importance of agglomeration externalities in theoretical work, evidence for their nature, scale, and scope remains elusive, particularly in developing countries. Identification of productivity spillovers between firms is a challenging task, and estimation typically requires, at a minimum, panel data, which are often not available in developing country contexts. In this paper, we develop a novel identification strategy that uses information on the network structure of producer relationships to provide estimates of the size of productivity spillovers. Our strategy builds on that proposed by Bramoulle et al. (2009) for estimating peer effects, and is one of the first applications of this idea to the estimation of productivity spillovers. We improve upon the network structure identification strategy by using panel data and validate it with exchange-rate induced trade shocks that provide additional identifying variation. We apply this strategy to a long panel dataset of manufacturers in Indonesia to provide new estimates of the scale and size of productivity spillovers. Our results suggest positive productivity spillovers between manufacturers in Indonesia, but estimates of TFP spillovers are considerably smaller than similar estimates based on firm-level data from the U.S. and Europe, and they are only observed in a few industries. |
| Date: | 2017–03 |
| URL: | http://d.repec.org/n?u=RePEc:ran:wpaper:wr-1182&r=net |
| By: | Maia King (Queen Mary University of London (PhD candidate), University of Oxford); |
| Abstract: | Community enforcement is an important device for sustaining efficiency in some repeated games of cooperation. We investigate cooperation when information about players' reputations spreads to their future partners through links in a social network that connects them. We nd that information supports cooperation by increasing trust between players, and obtain the `radius of trust': an endogenous network listing the potentially cooperative relationships between pairs of players in a community. We identify two aspects of trust, which relate to the network structure in different ways. Where trust depends on the shadow of punishment, players are trusted if others can communicate about them. This is linked to 2-connectedness of the network and the length of cycles within it. Where trust relates to knowledge of a player's type, players are trusting if they are more likely to receive information through their network connections. Both aspects of trust are linked to new centrality measures that we construct from the probabilities of node-to-node information transmission in networks, for which we provide a novel and simple method of calculation. |
| Keywords: | Cooperation, community enforcement, information transmission, networks, im-perfect private monitoring, repeated games, reputation, trust |
| JEL: | C73 D83 D85 L14 Z13 |
| Date: | 2017–12–12 |
| URL: | http://d.repec.org/n?u=RePEc:qmw:qmwecw:842&r=net |