{"product_id":"9781118771211","title":"Bayesian Inference in the Social Sciences","description":"\u003ch1\u003eBayesian Inference in the Social Sciences\u003c\/h1\u003e\u003ch3\u003eIvan Jeliazkov | Xin-She Yang\u003c\/h3\u003e\u003cdiv\u003e\u003cb\u003eMathematics \/ Probability \u0026amp; Statistics \/ Bayesian Analysis\u003c\/b\u003e\u003c\/div\u003e\u003cbr\u003e\u003cdiv\u003e\n\u003cp\u003e\u003cb\u003ePresents new models, methods, and techniques and considers important real-world applications in political science, sociology, economics, marketing, and finance\u003c\/b\u003e\u003cb\u003e\u003cbr\u003e \u003cbr\u003e \u003c\/b\u003eEmphasizing interdisciplinary coverage, \u003ci\u003eBayesian Inference in the Social Sciences\u003c\/i\u003e builds upon the recent growth in Bayesian methodology and examines an array of topics in model formulation, estimation, and applications. The book presents recent and trending developments in a diverse, yet closely integrated, set of research topics within the social sciences and facilitates the transmission of new ideas and methodology across disciplines while maintaining manageability, coherence, and a clear focus.\u003cbr\u003e \u003cbr\u003e \u003ci\u003eBayesian Inference in the Social Sciences\u003c\/i\u003e features innovative methodology and novel applications in addition to new theoretical developments and modeling approaches, including the formulation and analysis of models with partial observability, sample selection, and incomplete data. Additional areas of inquiry include a Bayesian derivation of empirical likelihood and method of moment estimators, and the analysis of treatment effect models with endogeneity. The book emphasizes practical implementation, reviews and extends estimation algorithms, and examines innovative applications in a multitude of fields. Time series techniques and algorithms are discussed for stochastic volatility, dynamic factor, and time-varying parameter models. Additional features include:\u003cbr\u003e \u003cbr\u003e \u003c\/p\u003e \u003cul\u003e \u003cli\u003eReal-world applications and case studies that highlight asset pricing under fat-tailed distributions, price indifference modeling and market segmentation, analysis of dynamic networks, ethnic minorities and civil war, school choice effects, and business cycles and macroeconomic performance\u003c\/li\u003e \u003cli\u003eState-of-the-art computational tools and Markov chain Monte Carlo algorithms with related materials available via the book’s supplemental website\u003c\/li\u003e \u003cli\u003eInterdisciplinary coverage from well-known international scholars and practitioners\u003c\/li\u003e \u003c\/ul\u003e \u003ci\u003e\u003cbr\u003e Bayesian Inference in the Social Sciences\u003c\/i\u003e is an ideal reference for researchers in economics, political science, sociology, and business as well as an excellent resource for academic, government, and regulation agencies. The book is also useful for graduate-level courses in applied econometrics, statistics, mathematical modeling and simulation, numerical methods, computational analysis, and the social sciences.\u003c\/div\u003e\u003cdiv\u003e  \u003cp\u003e\u003cb\u003eIVAN JELIAZKOV, PhD,\u003c\/b\u003e is Associate Professor of Economics and Statistics at the University of California, Irvine. Dr. Jeliazkov's research interests include Bayesian econometrics and discrete data analysis, model comparison, and simulation-based inference. In addition to developing new methods and estimation techniques, his work features applications in a variety of disciplines, including micro- and macroeconomics, marketing, political science, transportation, and environmental engineering.  \u003c\/p\u003e\n\u003cp\u003e\u003cb\u003eXIN-SHE YANG, PhD,\u003c\/b\u003e is Reader in Modeling and Optimization at Middlesex University, United Kingdom, as well as Adjunct Professor at Reykjavik University, Iceland. He is the author of \u003ci\u003eMathematical Modeling with Multidisciplinary Applications\u003c\/i\u003e and \u003ci\u003eEngineering Optimization: An Introduction with Metaheuristic Applications\u003c\/i\u003e, both of which are published by Wiley. \u003c\/p\u003e\n\u003c\/div\u003e\u003cbr\u003e\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd\u003ePublication Date: \u003c\/td\u003e\n\u003ctd\u003e29 September 2014\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePublisher: \u003c\/td\u003e\n\u003ctd\u003eWiley\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eImprint: \u003c\/td\u003e\n\u003ctd\u003eWiley\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eISBN-13: \u003c\/td\u003e\n\u003ctd\u003e9781118771211\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eFormat: \u003c\/td\u003e\n\u003ctd\u003eHardback\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePage Count: \u003c\/td\u003e\n\u003ctd\u003e352\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eWeight (oz): \u003c\/td\u003e\n\u003ctd\u003e21.12\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/table\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":44377726189708,"sku":"9781118771211","price":134.06,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0710\/9545\/1788\/files\/9781118771211.jpg?v=1780281767","url":"https:\/\/fh90cf-fv.myshopify.com\/products\/9781118771211","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}