Coupled Dynamics of Labor and Firms through Complex Networks

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dc.contributor.advisorAxtell, Robert L.
dc.contributor.authorGuerrero, Omar A.
dc.creatorGuerrero, Omar A.
dc.date2013-08
dc.date.accessioned2013-08-20T15:47:19Z
dc.date.available2018-09-01T06:35:21Z
dc.date.issued2013-08-20
dc.description.abstractThis dissertation bridges the gap between labor and firm dynamics through the study of complex networks in labor markets. With extensive use of large-scale employer-employee matched micro-data and agent-based modeling, we tap into the effects that networked structures (between individuals or between firms) exert in labor outcomes and employment dynamics. Some of the contributions of this work are: (i) the first characterization of a network of firms for an entire economy (connected through labor flows, i.e. labor flow networks); (ii) the study of the relationship between labor flow networks and employment dynamics; (iii) agent-based models that generate rich stylized facts about labor, firm, and social dynamics from microeconomic behavior; (iv) providing the microeconomic foundations of the formation process of labor flow networks by coupling job search models with models about the formation of complex networks. We show that the study of labor dynamics can be enriched by coupling firm dynamics. Using agent-based modeling is a natural way to deal with the heterogeneous experiences of workers and firms while maintaining a simple representation of the labor market. Despite their simplicity these models are grounded on empirical evidence obtained from large-scale micro-data and are capable of generating numerous stylized facts simultaneously. This approach has great potential for the design and evaluation of labor policies. Therefore, governments, regulators, and policy-makers would be greatly benefited from collecting large-scale labor micro-data, analyzing labor flow networks, and developing agent-based models of labor markets.
dc.description.noteThis work is embargoed by the author and will not be available until September 2018.
dc.identifier.urihttps://hdl.handle.net/1920/8377
dc.language.isoen_US
dc.rightsCopyright 2013 Omar A. Guerrero
dc.subjectLabor flows
dc.subjectLabor networks
dc.subjectAgent-based
dc.subjectComplex networks
dc.subjectFirm dynamics
dc.subjectLabor dynamics
dc.titleCoupled Dynamics of Labor and Firms through Complex Networks
dc.typeDissertation
thesis.degree.disciplineComputational Social Science
thesis.degree.grantorGeorge Mason University
thesis.degree.levelDoctoral
thesis.degree.namePhD in Computational Social Science

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