01886cam a22002657 4500001000700000003000500007005001700012008004100029100001900070245016000089260006600249490004200315500001800357520075100375530006101126538007201187538003601259690010101295700001901396700002101415710004201436830007701478856003801555856002701593w16708NBER20140730102852.0140730s2011 mau||||fs|||| 000 0 eng d1 aJudd, Kenneth.10aOne-node Quadrature Beats Monte Carloh[electronic resource]:bA Generalized Stochastic Simulation Algorithm /cKenneth Judd, Lilia Maliar, Serguei Maliar. aCambridge, Mass.bNational Bureau of Economic Researchc2011.1 aNBER working paper seriesvno. w16708 aJanuary 2011.3 aIn conventional stochastic simulation algorithms, Monte Carlo integration and curve fitting are merged together and implemented by means of regression. We perform a decomposition of the solution error and show that regression does a good job in curve fitting but a poor job in integration, which leads to low accuracy of solutions. We propose a generalized notion of stochastic simulation approach in which integration and curve fitting are separated. We specifically allow for the use of deterministic (quadrature and monomial) integration methods which are more accurate than the conventional Monte Carlo method. We achieve accuracy of solutions that is orders of magnitude higher than that of the conventional stochastic simulation algorithms. aHardcopy version available to institutional subscribers. aSystem requirements: Adobe [Acrobat] Reader required for PDF files. aMode of access: World Wide Web. 7aC63 - Computational Techniques • Simulation Modeling2Journal of Economic Literature class.1 aMaliar, Lilia.1 aMaliar, Serguei.2 aNational Bureau of Economic Research. 0aWorking Paper Series (National Bureau of Economic Research)vno. w16708.4 uhttp://www.nber.org/papers/w16708 uurn:doi:10.3386/w16708