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An Empirical Network Formation Model With Incomplete Information
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Book Synopsis An Empirical Network Formation Model with Incomplete Information by : Wenyu Zhou
Download or read book An Empirical Network Formation Model with Incomplete Information written by Wenyu Zhou and published by . This book was released on 2019 with total page 42 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis studies a network formation model with incomplete information, which introduces the neighborhood effect into the analysis of network formation. We show that the model is identified under some mild conditions. To overcome the computational burden, we propose to use the nested pseudo-likelihood algorithm to estimate the parameters of interest. Finite sample performance of the NPL estimation method is investigated through several Monte Carlo experiments. We find that a positive neighborhood effect makes agents more likely to form links, which can increase the network density. Besides, we also discuss three potential research directions.
Book Synopsis Two-Step Estimation of Network-Formation Models with Incomplete Information by : Michael P. Leung
Download or read book Two-Step Estimation of Network-Formation Models with Incomplete Information written by Michael P. Leung and published by . This book was released on 2015 with total page 39 pages. Available in PDF, EPUB and Kindle. Book excerpt: We model network formation as a simultaneous game of incomplete information, allowing linking decisions to depend on the structure of the network as well as the attributes of agents. When the data is rationalized by a symmetric equilibrium, meaning observationally equivalent agents choose the same ex-ante strategies, the model can be estimated using a computationally simple two-step estimator. We derive its asymptotic properties under a sequence of models sending the number of agents to infinity, which enables inference with only a single network observation. Our procedure generalizes dyadic regression, allowing the latent index to be a function of endogenous regressors that depend on the network. We apply the estimator to study trust networks in rural Indian villages.
Book Synopsis An Empirical Model for Strategic Network Formation by :
Download or read book An Empirical Model for Strategic Network Formation written by and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis The Econometric Analysis of Network Data by : Bryan Graham
Download or read book The Econometric Analysis of Network Data written by Bryan Graham and published by Academic Press. This book was released on 2020-06-03 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Econometric Analysis of Network Data serves as an entry point for advanced students, researchers, and data scientists seeking to perform effective analyses of networks, especially inference problems. It introduces the key results and ideas in an accessible, yet rigorous way. While a multi-contributor reference, the work is tightly focused and disciplined, providing latitude for varied specialties in one authorial voice. Answers both 'why' and 'how' questions in network analysis, bridging the gap between practice and theory allowing for the easier entry of novices into complex technical literature and computation Fully describes multiple worked examples from the literature and beyond, allowing empirical researchers and data scientists to quickly access the 'state of the art' versioned for their domain environment, saving them time and money Disciplined structure provides latitude for multiple sources of expertise while retaining an integrated and pedagogically focused authorial voice, ensuring smooth transition and easy progression for readers Fully supported by companion site code repository 40+ diagrams of 'networks in the wild' help visually summarize key points
Book Synopsis An Empirical Model of Network Formation by : Bryan S. Graham
Download or read book An Empirical Model of Network Formation written by Bryan S. Graham and published by . This book was released on 2014 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt: I formalize a widely-used empirical model of network formation. The model allows for assortative matching on observables (homophily) as well as unobserved agent level heterogeneity in link surplus (degree heterogeneity). The joint distribution of observed and unobserved agent-level characteristics is left unrestricted. Inferences about homophily do not depend upon untestable assumptions about this distribution. The model is non-standard since the dimension of the heterogeneity parameter grows with the number of agents, and hence network size. Nevertheless, under certain conditions, a joint maximum likelihood (ML) procedure, which simultaneously estimates the common and agent-level parameters governing link formation, is consistent. Although the asymptotic sampling distribution of the common parameter is Normal, it (i) contains a bias term and (ii) its variance does not coincide with the inverse of Fisher's information matrix. Standard ML asymptotic inference procedures are invalid. Forming confidence intervals with a bias-corrected maximum likelihood estimate, and appropriate standard error estimates, results in correct coverage. I assess the value of these results for understanding finite sample behavior via a set of Monte Carlo experiments and through an empirical analysis of risk-sharing links in a rural Tanzanian village (cf., De Weerdt, 2004).
Book Synopsis The Econometric Analysis of Network Data by : Bryan Graham
Download or read book The Econometric Analysis of Network Data written by Bryan Graham and published by Academic Press. This book was released on 2020-05-15 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Econometric Analysis of Network Data serves as an entry point for advanced students, researchers, and data scientists seeking to perform effective analyses of networks, especially inference problems. It introduces the key results and ideas in an accessible, yet rigorous way. While a multi-contributor reference, the work is tightly focused and disciplined, providing latitude for varied specialties in one authorial voice. Answers both ‘why’ and ‘how’ questions in network analysis, bridging the gap between practice and theory allowing for the easier entry of novices into complex technical literature and computation Fully describes multiple worked examples from the literature and beyond, allowing empirical researchers and data scientists to quickly access the ‘state of the art’ versioned for their domain environment, saving them time and money Disciplined structure provides latitude for multiple sources of expertise while retaining an integrated and pedagogically focused authorial voice, ensuring smooth transition and easy progression for readers Fully supported by companion site code repository 40+ diagrams of ‘networks in the wild’ help visually summarize key points
Book Synopsis Challenges in Social Network Research by : Giancarlo Ragozini
Download or read book Challenges in Social Network Research written by Giancarlo Ragozini and published by Springer Nature. This book was released on 2019-12-06 with total page 245 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book includes both invited and contributed chapters dealing with advanced methods and theoretical development for the analysis of social networks and applications in numerous disciplines. Some authors explore new trends related to network measures, multilevel networks and clustering on networks, while other contributions deepen the relationship among statistical methods for data mining and social network analysis. Along with the new methodological developments, the book offers interesting applications to a wide set of fields, ranging from the organizational and economic studies, collaboration and innovation, to the less usual field of poetry. In addition, the case studies are related to local context, showing how the substantive reasoning is fundamental in social network analysis. The list of authors includes both top scholars in the field of social networks and promising young researchers. All chapters passed a double blind review process followed by the guest editors. This edited volume will appeal to students, researchers and professionals.
Book Synopsis Identification and Estimation of Network Formation Models by : Jun Sung Kim
Download or read book Identification and Estimation of Network Formation Models written by Jun Sung Kim and published by . This book was released on 2014 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: My thesis studies identification and estimation in network formation models. First, I study what can be learned from pairwise stable networks. Pairwise stability of a network gives strong identification power when I consider the probability that the observed network is pairwise stable. I propose a semiparametric maximum score estimator which is simple and computationally feasible. I apply the empirical model to social and economic networks in rural India, and find homophily patterns in village networks. Second, I propose a structural model of multigraph formation, where 1) individuals determine multiple types of links simultaneously; 2) all networks interact with each other; and 3) one or more networks are endogenous but not simultaneous. I extend the notion of pairwise stability to a multigraph, and show that the structural model is equivalent to a multinomial choice model. The presence of endogenous but not simultaneous networks is a source of an incomplete econometric model. Relying on partially identified econometric models, I characterize the sharp identification region of parameters by a finite set of moment inequalities. I apply the model to village networks and find that friendship affects risk sharing and favor exchange networks in the same direction. The last chapter studies an empirical model of network formation in the U.S. airline industry and investigates the size of network externalities. I assume that each airline builds a network that satisfies a weak notion of stability. That is, no airlines want to deviate from their current networks by a single route change. In this framework, I can use an entry game to investigate the airline industry and include network measures in the profit function to estimate network externalities. I find that when I control for the number of one-stop flights the effect of hub-size is larger than the case without considering one-stop flights.
Book Synopsis The Oxford Handbook of the Economics of Networks by : Yann Bramoullé
Download or read book The Oxford Handbook of the Economics of Networks written by Yann Bramoullé and published by Oxford University Press. This book was released on 2016-03-01 with total page 857 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Oxford Handbook of the Economics of Networks represents the frontier of research into how and why networks they form, how they influence behavior, how they help govern outcomes in an interactive world, and how they shape collective decision making, opinion formation, and diffusion dynamics. From a methodological perspective, the contributors to this volume devote attention to theory, field experiments, laboratory experiments, and econometrics. Theoretical work in network formation, games played on networks, repeated games, and the interaction between linking and behavior is synthesized. A number of chapters are devoted to studying social process mediated by networks. Topics here include opinion formation, diffusion of information and disease, and learning. There are also chapters devoted to financial contagion and systemic risk, motivated in part by the recent financial crises. Another section discusses communities, with applications including social trust, favor exchange, and social collateral; the importance of communities for migration patterns; and the role that networks and communities play in the labor market. A prominent role of networks, from an economic perspective, is that they mediate trade. Several chapters cover bilateral trade in networks, strategic intermediation, and the role of networks in international trade. Contributions discuss as well the role of networks for organizations. On the one hand, one chapter discusses the role of networks for the performance of organizations, while two other chapters discuss managing networks of consumers and pricing in the presence of network-based spillovers. Finally, the authors discuss the internet as a network with attention to the issue of net neutrality.
Book Synopsis Encyclopedia of the Sciences of Learning by : Norbert M. Seel
Download or read book Encyclopedia of the Sciences of Learning written by Norbert M. Seel and published by Springer Science & Business Media. This book was released on 2011-10-05 with total page 3643 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past century, educational psychologists and researchers have posited many theories to explain how individuals learn, i.e. how they acquire, organize and deploy knowledge and skills. The 20th century can be considered the century of psychology on learning and related fields of interest (such as motivation, cognition, metacognition etc.) and it is fascinating to see the various mainstreams of learning, remembered and forgotten over the 20th century and note that basic assumptions of early theories survived several paradigm shifts of psychology and epistemology. Beyond folk psychology and its naïve theories of learning, psychological learning theories can be grouped into some basic categories, such as behaviorist learning theories, connectionist learning theories, cognitive learning theories, constructivist learning theories, and social learning theories. Learning theories are not limited to psychology and related fields of interest but rather we can find the topic of learning in various disciplines, such as philosophy and epistemology, education, information science, biology, and – as a result of the emergence of computer technologies – especially also in the field of computer sciences and artificial intelligence. As a consequence, machine learning struck a chord in the 1980s and became an important field of the learning sciences in general. As the learning sciences became more specialized and complex, the various fields of interest were widely spread and separated from each other; as a consequence, even presently, there is no comprehensive overview of the sciences of learning or the central theoretical concepts and vocabulary on which researchers rely. The Encyclopedia of the Sciences of Learning provides an up-to-date, broad and authoritative coverage of the specific terms mostly used in the sciences of learning and its related fields, including relevant areas of instruction, pedagogy, cognitive sciences, and especially machine learning and knowledge engineering. This modern compendium will be an indispensable source of information for scientists, educators, engineers, and technical staff active in all fields of learning. More specifically, the Encyclopedia provides fast access to the most relevant theoretical terms provides up-to-date, broad and authoritative coverage of the most important theories within the various fields of the learning sciences and adjacent sciences and communication technologies; supplies clear and precise explanations of the theoretical terms, cross-references to related entries and up-to-date references to important research and publications. The Encyclopedia also contains biographical entries of individuals who have substantially contributed to the sciences of learning; the entries are written by a distinguished panel of researchers in the various fields of the learning sciences.
Book Synopsis Econometric Methods for Network Data by : Michael P. Leung
Download or read book Econometric Methods for Network Data written by Michael P. Leung and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation studies inference in network-formation models with game-theoretic foundations. These are discrete-choice models in which the binary outcome represents whether or not a pair of nodes forms a link. Strategic interactions result from "network externalities, " meaning that the surplus that a node pair enjoys from forming a link may depend on the existence of other links in the network. Estimation of strategic models faces two core difficulties. The first is that network externalities can generate link "autocorrelation, " since an ego's decision to form a link with an alter may depend on the alter's other link-formation decisions and vice versa. Moreover, we typically observe only a few networks in the data and often only a single network. Hence, it is nontrivial to obtain a central limit theorem in the strategic context. The development of a sampling theory for large networks remains an open problem and is a central theme of this dissertation. The second core difficulty is incompleteness due to multiple equilibria. For a fixed vector of node primitives there may be multiple networks consistent with the equilibrium restrictions imposed by the model. If the econometrician is unwilling to take a stance on the mechanism by which nodes coordinate on a particular equilibrium, then the model likelihood depends on an infinite-dimensional nuisance parameter, and the model may only be partially identified. The first chapter of this dissertation analyzes strategic models of network formation with incomplete information. We show that in a setting without unobserved heterogeneity, by conditioning on commonly known attributes, we can eliminate autocorrelation among links. Moreover, we show that equilibrium beliefs can be estimated directly from the data under the restriction that the observed equilibrium is symmetric. Then the structural parameters can be estimated using a simple two-step estimator that augments commonly used "dyadic regression" models with an additional nonparametric first step to account for network externalities. The second chapter studies models with complete information, allowing for unobserved heterogeneity. This chapter considers models that obey a weak "component externalities" restriction on network externalities. We derive conditions under which certain node-level functions of the network constitute alpha-mixing random fields, objects for which central limit theorems exist. In particular, homophily plays an important role in reducing autocorrelation. Our results enable the estimation of certain network moments that are useful for inference. The third chapter studies models with complete information under a stronger "local externalities" restriction on network externalities. Whereas a central limit theorem under component externalities requires a "subcritical" network comprised of a large number of small components, we show that a class of models obeying local externalities can generate sparse networks with giant components, properties consistent with real-world social networks. Further, we develop conditions under which certain network statistics, converge to their expectations as the size of the network goes to infinity. A key requirement is that nodes are homophilous with respect to a set of attributes and that the degree of homophily increases with the size of the network at a particular rate. That is, nodes are increasingly selective about their partners the larger the pool of available partners. The rate at which selectivity increases in part determines the "realism" of global properties of large networks and the possibility of a law of large numbers. We derive rates that are compatible with both objectives. We also develop moment inequalities for inference that are "sharp" in the sense that they fully exhaust the empirical implications of the equilibrium restrictions.
Download or read book Connections written by Sanjeev Goyal and published by Princeton University Press. This book was released on 2012-01-12 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: Networks pervade social and economic life, and they play a prominent role in explaining a huge variety of social and economic phenomena. Standard economic theory did not give much credit to the role of networks until the early 1990s, but since then the study of the theory of networks has blossomed. At the heart of this research is the idea that the pattern of connections between individual rational agents shapes their actions and determines their rewards. The importance of connections has in turn motivated the study of the very processes by which networks are formed. In Connections, Sanjeev Goyal puts contemporary thinking about networks and economic activity into context. He develops a general framework within which this body of research can be located. In the first part of the book he demonstrates that location in a network has significant effects on individual rewards and that, given this, it is natural that individuals will seek to form connections to move the network in their favor. This idea motivates the second part of the book, which develops a general theory of network formation founded on individual incentives. Goyal assesses the robustness of current research findings and identifies the substantive open questions. Written in a style that combines simple examples with formal models and complete mathematical proofs, Connections is a concise and self-contained treatment of the economic theory of networks, one that should become the natural source of reference for graduate students in economics and related disciplines.
Download or read book Handbook of Econometrics written by and published by Elsevier. This book was released on 2020-11-25 with total page 594 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Econometrics, Volume 7A, examines recent advances in foundational issues and "hot" topics within econometrics, such as inference for moment inequalities and estimation of high dimensional models. With its world-class editors and contributors, it succeeds in unifying leading studies of economic models, mathematical statistics and economic data. Our flourishing ability to address empirical problems in economics by using economic theory and statistical methods has driven the field of econometrics to unimaginable places. By designing methods of inference from data based on models of human choice behavior and social interactions, econometricians have created new subfields now sufficiently mature to require sophisticated literature summaries. Presents a broader and more comprehensive view of this expanding field than any other handbook Emphasizes the connection between econometrics and economics Highlights current topics for which no good summaries exist
Book Synopsis Handbook of Game Theory by : Petyon Young
Download or read book Handbook of Game Theory written by Petyon Young and published by Elsevier. This book was released on 2014-10-01 with total page 1025 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ability to understand and predict behavior in strategic situations, in which an individual’s success in making choices depends on the choices of others, has been the domain of game theory since the 1950s. Developing the theories at the heart of game theory has resulted in 8 Nobel Prizes and insights that researchers in many fields continue to develop. In Volume 4, top scholars synthesize and analyze mainstream scholarship on games and economic behavior, providing an updated account of developments in game theory since the 2002 publication of Volume 3, which only covers work through the mid 1990s. Focuses on innovation in games and economic behavior Presents coherent summaries of subjects in game theory Makes details about game theory accessible to scholars in fields outside economics
Book Synopsis A Semiparametric Network Formation Model with Unobserved Linear Heterogeneity by : Luis E. Candelaria
Download or read book A Semiparametric Network Formation Model with Unobserved Linear Heterogeneity written by Luis E. Candelaria and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis An Empirical Model of Dyadic Link Formation in a Network with Unobserved Heterogeneity by : Andreas Dzemski
Download or read book An Empirical Model of Dyadic Link Formation in a Network with Unobserved Heterogeneity written by Andreas Dzemski and published by . This book was released on 2017 with total page 76 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Computational Approaches to Studying the Co-evolution of Networks and Behavior in Social Dilemmas by : Rense Corten
Download or read book Computational Approaches to Studying the Co-evolution of Networks and Behavior in Social Dilemmas written by Rense Corten and published by John Wiley & Sons. This book was released on 2014-01-29 with total page 185 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Approaches to Studying the Co-evolution of Networks and Behaviour in Social Dilemmas shows students, researchers, and professionals how to use computation methods, rather than mathematical analysis, to answer research questions for an easier, more productive method of testing their models. Illustrations of general methodology are provided and explore how computer simulation is used to bridge the gap between formal theoretical models and empirical applications.
