000			01676nam a22002057a 4500
999			_c3510 _d3510
005			20221217122749.0
008			221217b ||||| |||| 00| 0 eng d
020			_a9780691161082
082			_a339.5015 _bHER
100			_aHerbst, Edward P. _911006
245			_aBayesian estimation of DSGE models
260			_bPrinceton University Press _aNew Jersey _c2016
300			_axix, 275 p.
365			_aUSD _b49.50
520			_aDynamic stochastic general equilibrium (DSGE) models have become one of the workhorses of modern macroeconomics and are extensively used for academic research as well as forecasting and policy analysis at central banks. This book introduces readers to state-of-the-art computational techniques used in the Bayesian analysis of DSGE models. The book covers Markov chain Monte Carlo techniques for linearized DSGE models, novel sequential Monte Carlo methods that can be used for parameter inference, and the estimation of nonlinear DSGE models based on particle filter approximations of the likelihood function. The theoretical foundations of the algorithms are discussed in depth, and detailed empirical applications and numerical illustrations are provided. The book also gives invaluable advice on how to tailor these algorithms to specific applications and assess the accuracy and reliability of the computations. Bayesian Estimation of DSGE Models is essential reading for graduate students, academic researchers, and practitioners at policy institutions
650			_aEquilibrium (Economics) -- Mathematical models _911007
650			_aBayesian statistical decision theory _91505
700			_aSchorfheide, Frank _911008
942			_2ddc _cBK