a guide to econometrics and decision-making with prior information Dorfman, Jeffrey H. creator text bibliography nyu New York Springer c1997 1997 monographic eng

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vii, 110 p. : ill. ; 25 cm. The aim of this book is to provide researchers in economics, finance, and statistics with an up-to-date introduction to the application of Bayesian techniques to empirical studies. It covers the full range of the new numerical techniques that have been developed over the last thirty years, notably: Monte Carlo sampling, antithetic replication, importance sampling, and Gibbs sampling. The result is a book that presents a roadmap of applied economic questions that can now be addressed empirically with Bayesian methods. Consequently, many researchers will find this a readily readable survey of this growing research topic. Ch. 1. Introduction -- Ch. 2. A Quick Course in Bayesian Statistics and Decision Theory -- Ch. 3. New Advances in Numerical Bayesian Techniques -- Ch. 4. Imposing Economic Theory -- Ch. 5. Studying Parameters of Interest -- Ch. 6. Unit Root and Cointegration Tests -- Ch. 7. Model Specification Uncertainty -- Ch. 8. Forecasting -- Ch. 9. More Realistic Models Through Numerical Methods -- Ch. 10. Decision Theory Applications. Jeffrey H. Dorfman. Includes bibliographical references (p. 97-107) and index. Econometrics Bayesian statistical decision theory HB139 .D674 1997 330.015195 DOB 0387982337 (hc : alk. paper) 97012147 DLC 970306 20160508143828.0 2003499