Presents new models, methods, and techniques and considersimportant real-world applications in political science, sociology,economics, marketing, and financeEmphasizing interdisciplinary coverage, Bayesian Inferencein the Social Sciences builds upon the recent growth inBayesian methodology and examines an array of topics in modelformulation, estimation, and applications. The book presents recentand trending developments in a diverse, yet closely integrated, setof research topics within the social sciences and facilitates thetransmission of new ideas and methodology across disciplines whilemaintaining manageability, coherence, and a clear focus.Bayesian Inference in the Social Sciences featuresinnovative methodology and novel applications in addition to newtheoretical developments and modeling approaches, including theformulation and analysis of models with partial observability,sample selection, and incomplete data. Additional areas of inquiryinclude a Bayesian derivation of empirical likelihood and method ofmoment estimators, and the analysis of treatment effect models withendogeneity. The book emphasizes practical implementation, reviewsand extends estimation algorithms, and examines innovativeapplications in a multitude of fields. Time series techniques andalgorithms are discussed for stochastic volatility, dynamic factor,and time-varying parameter models. Additional featuresinclude:* Real-world applications and case studies that highlight assetpricing under fat-tailed distributions, price indifference modelingand market segmentation, analysis of dynamic networks, ethnicminorities and civil war, school choice effects, and businesscycles and macroeconomic performance* State-of-the-art computational tools and Markov chain MonteCarlo algorithms with related materials available via thebook's supplemental website* Interdisciplinary coverage from well-known internationalscholars and practitionersBayesian Inference in the Social Sciences is an ideal referencefor researchers in economics, political science, sociology, andbusiness as well as an excellent resource for academic, government,and regulation agencies. The book is also useful for graduate-levelcourses in applied econometrics, statistics, mathematical modelingand simulation, numerical methods, computational analysis, and thesocial sciences.