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Reverse mode differentiation for DSGE models

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  • Alfred Duncan

Abstract

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Suggested Citation

  • Alfred Duncan, 2021. "Reverse mode differentiation for DSGE models," Studies in Economics 2108, School of Economics, University of Kent.
    • Handle: RePEc:ukc:ukcedp:2108
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    File URL: https://www.kent.ac.uk/economics/repec/2108.pdf
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    References listed on IDEAS

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    1. Peijie Wang, 2020. "The Monetary Models," Springer Texts in Business and Economics, in: The Economics of Foreign Exchange and Global Finance, edition 3, chapter 8, pages 173-216, Springer.
    2. Farkas, Mátyás & Tatar, Balint, 2020. "Bayesian estimation of DSGE models with Hamiltonian Monte Carlo," IMFS Working Paper Series 144, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
    3. Binder, Michael & Pesaran, M. Hashem, 1997. "Multivariate Linear Rational Expectations Models," Econometric Theory, Cambridge University Press, vol. 13(6), pages 877-888, December.
    4. Edward P. Herbst & Frank Schorfheide, 2016. "Bayesian Estimation of DSGE Models," Economics Books, Princeton University Press, edition 1, number 10612.
    5. Anderson, Gary & Moore, George, 1985. "A linear algebraic procedure for solving linear perfect foresight models," Economics Letters, Elsevier, vol. 17(3), pages 247-252.
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    Cited by:

    1. Alfred Duncan & Charles Nolan, 2024. "Prudential Fiscal Stimulus," Working Papers 2024_03, Business School - Economics, University of Glasgow.

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    Keywords

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    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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