000			02017mam a2200301 a 4500
001			2003499
003			BD-DhUL
005			20160508143828.0
008			970306s1997 nyua b 001 0 eng
010			_a 97012147
020			_a0387982337 (hc : alk. paper)
035			_a(OCoLC)ocm36549128
040			_aDLC _cDLC _dC#P _dOrLoB-B _dBD-DhUL
050	0	0	_aHB139 _b.D674 1997
082	0	0	_a330.015195 _221 _bDOB
100	1		_aDorfman, Jeffrey H.
245	1	0	_aBayesian economics through numerical methods : _ba guide to econometrics and decision-making with prior information / _cJeffrey H. Dorfman.
260			_aNew York : _bSpringer, _cc1997.
300			_avii, 110 p. : _bill. ; _c25 cm.
504			_aIncludes bibliographical references (p. 97-107) and index.
505	0	0	_gCh. 1. _tIntroduction -- _gCh. 2. _tA Quick Course in Bayesian Statistics and Decision Theory -- _gCh. 3. _tNew Advances in Numerical Bayesian Techniques -- _gCh. 4. _tImposing Economic Theory -- _gCh. 5. _tStudying Parameters of Interest -- _gCh. 6. _tUnit Root and Cointegration Tests -- _gCh. 7. _tModel Specification Uncertainty -- _gCh. 8. _tForecasting -- _gCh. 9. _tMore Realistic Models Through Numerical Methods -- _gCh. 10. _tDecision Theory Applications.
520			_aThe 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.
520	8		_aThe 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.
650		0	_aEconometrics.
650		0	_aBayesian statistical decision theory.
900			_aAUTH _bTOC
942			_2ddc _cBK
999			_c61840 _d61840