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on Information and Communication Technologies |
| By: | Andrea Galeotti; Sanjeev Goyal; Matthew O. Jackson; Fernando Vega-Redondo; Leeat Yariv |
| Abstract: | In a variety of contexts - ranging from public goods provision to information collection - a player's well-being depends on own action as well as on the actions taken by his or her neighbors. We provide a framework to analyze such strategic interactions when neighborhood structure, modeled in terms of an underlying network of connections, a¤ects payo¤s. We provide results characterizing how the network structure, an individual.s position within the network, the nature of games (strategic substitutes versus complements and positive versus negative externalities), and the level of information, shape individual behavior and payoffs. |
| Keywords: | Networks, Network Games, Graphical Games, Diffusion, Incomplete Information |
| JEL: | D85 C72 L14 Z13 |
| Date: | 2008 |
| URL: | http://d.repec.org/n?u=RePEc:eui:euiwps:eco2008/07&r=ict |
| By: | Michael Ostrovsky; Michael Schwarz |
| Abstract: | This paper explores information disclosure in matching markets, e.g., the informativeness of transcripts given out by universities. We show that the same, "benchmark," amount of information is disclosed in essentially all equilibria. We then demonstrate that if universities disclose the benchmark amount of information, students and employers will not find it profitable to contract early; if they disclose more, unraveling will occur. |
| JEL: | D82 D83 I2 J0 |
| Date: | 2008–01 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:13766&r=ict |
| By: | Peter Robinson |
| Abstract: | We consider a multivariate continuous time process, generated by a system of linear stochastic differential equations, driven by white noise and involving coefficients that possibly vary over time. The process is observable only at discrete, but not necessarily equally-spaced, time points (though equal spacing significantly simplifies matters). Such settings represent partial extensions of ones studied extensively by A.R. Bergstrom. A model for the observed time series is deduced. Initially we focus on a first-order model, but higher-order ones are discussed in case of equally-spaced observations. Some discussion of issues of statistical inference is included. |
| Keywords: | Stochastic differential equations, time-varying coefficients, discrete sampling, irregular sampling. |
| JEL: | C32 |
| Date: | 2007–06 |
| URL: | http://d.repec.org/n?u=RePEc:cep:stiecm:/2007/520&r=ict |