<> "The repository administrator has not yet configured an RDF license."^^ . <> . . . "Applications of Statistical Physics to the Social and Economic Sciences"^^ . "This thesis applies statistical physics concepts and methods to quantitatively analyze\r\nsocioeconomic systems. For each system we combine theoretical models and\r\nempirical data analysis in order to better understand the real-world system in relation\r\nto the complex interactions between the underlying human agents. This thesis is\r\nseparated into three parts: (i) response dynamics in financial markets, (ii) dynamics\r\nof career trajectories, and (iii) a stochastic opinion model with quenched disorder.\r\nIn Part I we quantify the response of U.S. markets to financial shocks, which\r\nperturb markets and trigger “herding behavior” among traders. We use concepts\r\nfrom earthquake physics to quantify the decay of volatility shocks after the “main\r\nshock.” We also find, surprisingly, that we can make quantitative statements even\r\nbefore the main shock. In order to analyze market behavior before as well as after\r\n“anticipated news” we use Federal Reserve interest-rate announcements, which are\r\nregular events that are also scheduled in advance.\r\nIn Part II we analyze the statistical physics of career longevity. We construct\r\na stochastic model for career progress which has two main ingredients: (a) random\r\nforward progress in the career and (b) random termination of the career. We incorporate\r\nthe rich-get-richer (Matthew) effect into ingredient (a), meaning that it is easier\r\nto move forward in the career the farther along one is in the career. We verify the\r\nmodel predictions analyzing data on 400,000 scientific careers and 20,000 professional\r\nsports careers. Our model highlights the importance of early career development,\r\nshowing that many careers are stunted by the relative disadvantage associated with\r\ninexperience.\r\nIn Part III we analyze a stochastic two-state spin model which represents a system\r\nof voters embedded on a network. We investigate the role in consensus formation of “zealots”, which are agents with time-independent opinion. Our main result is the\r\nunexpected finding that it is the number and not the density of zealots which determines\r\nthe steady-state opinion polarization. We compare our findings with results\r\nfor United States Presidential elections.\r\n"^^ . "2011" . . . . "Boston University, Graduate School of Arts and Sciences"^^ . . . "Department of Physics, Boston University, Graduate School of Arts and Sciences"^^ . . . . . . . . . "Alexander M."^^ . "Petersen"^^ . "Alexander M. Petersen"^^ . . . . . . "Applications of Statistical Physics to the Social and Economic Sciences (PDF)"^^ . . . . . . . . . . . "petersen_thesis_2011a.pdf"^^ . . . "Applications of Statistical Physics to the Social and Economic Sciences (Image (JPEG))"^^ . . . . . . "preview.jpg"^^ . . . "Applications of Statistical Physics to the Social and Economic Sciences (Indexer Terms)"^^ . . . . . . "indexcodes.txt"^^ . . "HTML Summary of #694 \n\nApplications of Statistical Physics to the Social and Economic Sciences\n\n" . "text/html" . . . "H Social Sciences (General)"@en . . . "HA Statistics"@en . . . "QC Physics"@en . .