Lower Bounds on Approximation Errors to Numerical Solutions of Dynamic Economic Models.
We propose a novel methodology for evaluating the accuracy of numerical solutions to dynamic economic models. It consists in constructing a lower bound on the size of approximation errors. A small lower bound on errors is a necessary condition for accuracy: If a lower error bound is unacceptably lar...
| Publicado en: | Econometrica Vol. 85; no. 3; pp. 991 - 1013 |
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| Autores principales: | , , |
| Formato: | Artículo |
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Wiley-Blackwell
May2017
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=123458885&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 123458885 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00129682 ECN jtl: Econometrica issn: 00129682 maglogo: Y pubinfo: dt: May2017 vid: 85 iid: 3 pid: 480 pub: Wiley-Blackwell artinfo: ui: 123458885 10.3982/ECTA12791 ppf: 991 ppct: 22 formats: tig: atl: Lower Bounds on Approximation Errors to Numerical Solutions of Dynamic Economic Models. aug: au: Judd, Kenneth L. Maliar, Lilia Maliar, Serguei affil: Hoover Institution, Stanford University NBER Dept. of Economics, Stanford University Dept. of Economics, University of Alicante Dept. of Economics, Lucas Hall, Leavey School of Business, Santa Clara University su: Economic models Errors Equations Approximation theory Chebyshev systems sug: subj: Economic models Errors Equations Approximation theory Chebyshev systems keyword: accuracy approximate solution Approximation errors backward error analysis error bound Euler equation residuals forward error analysis lower error bound new Keynesian model numerical solution upper error bound accuracy approximate solution Approximation errors backward error analysis error bound Euler equation residuals forward error analysis lower error bound new Keynesian model numerical solution upper error bound ab: We propose a novel methodology for evaluating the accuracy of numerical solutions to dynamic economic models. It consists in constructing a lower bound on the size of approximation errors. A small lower bound on errors is a necessary condition for accuracy: If a lower error bound is unacceptably large, then the actual approximation errors are even larger, and hence, the approximation is inaccurate. Our lower-bound error analysis is complementary to the conventional upper-error (worst-case) bound analysis, which provides a sufficient condition for accuracy. As an illustration of our methodology, we assess approximation in the first- and second-order perturbation solutions for two stylized models: a neoclassical growth model and a new Keynesian model. The errors are small for the former model but unacceptably large for the latter model under some empirically relevant parameterizations. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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