Central bank research hub - Papers by Stephen Terry
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Research hub papers by author Stephen TerryenAlternative Methods of Solving State-Dependent Pricing Models
http://www.kc.frb.org/PUBLICAT/RESWKPAP/PDF/RWP08-10.pdf
Kansas City Fed Working Papers by Edward S. Knotek II and Stephen TerryAlternative Methods of Solving State-Dependent Pricing Models2009-01-01T12:00:00ZWe use simulation-based techniques to compare and contrast two methods for solving state-dependent pricing models: discretization, which solves and simulates the model on a grid; and collocation, which relies on Chebyshev polynomials. While both methods produce qualitatively similar results, statistically significant quantitative differences do arise. We present evidence favoring discretization over collocation in this context, given a lack of robustness in the latter.Alternative Methods of Solving State-Dependent Pricing ModelsAbstracthttp://www.kc.frb.org/PUBLICAT/RESWKPAP/Rwp08-10.htmFull texthttp://www.kc.frb.org/PUBLICAT/RESWKPAP/PDF/RWP08-10.pdfEdward S. Knotek IIStephen TerryEdward S. Knotek II and Stephen Terry2008-12Federal Reserve Bank of Kansas City Research Working PapersC63C68E31E37Markov-Chain Approximations of Vector Autoregressions: Application of General Multivariate-Normal Integration Techniques
http://www.kc.frb.org/Publicat/RESWKPAP/PDF/RWP08-02.pdf
Kansas City Fed Working Papers by Edward S. Knotek II and Stephen TerryMarkov-Chain Approximations of Vector Autoregressions: Application of General Multivariate-Normal Integration Techniques2008-11-01T12:00:00ZDiscrete Markov chains can be useful to approximate vector autoregressive processes for economists doing computational work. One such approximation method first presented by Tauchen (1986) operates under the general theoretical assumption of a transformed VAR with diagonal covariance structure for the process error term. We demonstrate one simple method of more conveniently treating this approximation problem in practice using readily available multivariate-normal integration techniques to allow for arbitrary positive-semidefinite covariance structures. Examples are provided using processes with non-diagonal and singular non-diagonal error covariances.Markov-Chain Approximations of Vector Autoregressions: Application of General Multivariate-Normal Integration TechniquesAbstracthttp://www.kc.frb.org/Publicat/RESWKPAP/rwp08-02.htmFull texthttp://www.kc.frb.org/Publicat/RESWKPAP/PDF/RWP08-02.pdfEdward S. Knotek IIStephen TerryEdward S. Knotek II and Stephen Terry2008-10Federal Reserve Bank of Kansas City Research Working PapersC32C63