Uhlig Toolkit

A Toolkit for Analysing Nonlinear Dynamic Stochastic Models Easily. Chapter 3 provides a toolkit for solving such nonlinear dynamic discrete-time stochastic models easily, building on log-linearizing the necessary equations characterizing the equilibrium and solving for the recursive equilibrium law of motion with the method of undetermined coefficients. This chapter comes with an extensive and well documented library of Matlab programs, which can be downloaded in a self-extracting zip-file. Read the readme.m file

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References in zbMATH (referenced in 8 articles )

Showing results 1 to 8 of 8.
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  1. Atıcı, Ferhan M.; Cheng, Gang; Lebedinsky, Alex: A nonlinear stochastic growth model on discrete time domains (2016)
  2. Meyer-Gohde, Alexander; Neuhoff, Daniel: Solving and estimating linearized DSGE models with VARMA shock processes and filtered data (2015)
  3. Algan, Yann; Challe, Edouard; Ragot, Xavier: Incomplete markets and the output-inflation tradeoff (2011)
  4. Blake, Andrew P.; Zampolli, Fabrizio: Optimal policy in Markov-switching rational expectations models (2011)
  5. Meyer-Gohde, Alexander: Linear rational-expectations models with lagged expectations: a synthetic method (2010)
  6. Lombardo, Giovanni; Sutherland, Alan: Computing second-order-accurate solutions for rational expectation models using linear solution methods (2007)
  7. Silos, Pedro: Assessing Markov chain approximations: a minimal econometric approach (2006)
  8. Dennis, Richard: Solving for optimal simple rules in rational expectations models (2004)