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Approximating and simulating the stochastic growth model: Parameterized expectations, neural networks, and the genetic algorithm

Citations

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Cited by:

  1. Richard Dennis, 2004. "Specifying and estimating New Keynesian models with instrument rules and optimal monetary policies," Working Paper Series 2004-17, Federal Reserve Bank of San Francisco.
  2. Julien Pascal, 2025. "Solving economic models with neural networks without backpropagation," BCL working papers 196, Central Bank of Luxembourg.
  3. Mahdi Ebrahimi Kahou & Jesús Fernández-Villaverde & Jesse Perla & Arnav Sood, 2021. "Exploiting Symmetry in High-Dimensional Dynamic Programming," CESifo Working Paper Series 9161, CESifo.
  4. Lepetyuk, Vadym & Maliar, Lilia & Maliar, Serguei, 2020. "When the U.S. catches a cold, Canada sneezes: A lower-bound tale told by deep learning," Journal of Economic Dynamics and Control, Elsevier, vol. 117(C).
  5. Jésus Fernández-Villaverde & Galo Nuño & Jesse Perla & Jesús Fernández-Villaverde, 2024. "Taming the Curse of Dimensionality: Quantitative Economics with Deep Learning," CESifo Working Paper Series 11448, CESifo.
  6. Marlon Azinovic & Luca Gaegauf & Simon Scheidegger, 2022. "Deep Equilibrium Nets," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 63(4), pages 1471-1525, November.
  7. Maliar, Lilia & Maliar, Serguei, 2022. "Deep learning classification: Modeling discrete labor choice," Journal of Economic Dynamics and Control, Elsevier, vol. 135(C).
  8. G.C. Lim & P.D. McNelis, 2002. "Central Bank Learning, Terms of Trade Shocks & Currency Risks: Should Only Inflation Matter for Monetary Policy?," Computing in Economics and Finance 2002 68, Society for Computational Economics.
  9. Lim, G. C. & McNelis, Paul D., 2004. "Learning and the monetary policy strategy of the European Central Bank," Journal of International Money and Finance, Elsevier, vol. 23(7-8), pages 997-1010.
  10. Javier J. Pérez, 2004. "A Log-Linear Homotopy Approach to Initialize the Parameterized Expectations Algorithm," Computational Economics, Springer;Society for Computational Economics, vol. 24(1), pages 59-75, August.
  11. Richard Dennis, 2006. "The frequency of price adjustment and New Keynesian business cycle dynamics," Working Paper Series 2006-22, Federal Reserve Bank of San Francisco.
  12. Hull, Isaiah, 2015. "Approximate dynamic programming with post-decision states as a solution method for dynamic economic models," Journal of Economic Dynamics and Control, Elsevier, vol. 55(C), pages 57-70.
  13. G.C. Lim & Paul D. McNelis, 2001. "Central Bank Learning, Terms of Trade Shocks & Currency Risk: Should Exchange Rate Volatility Matter for Monetary Policy?," Boston College Working Papers in Economics 509, Boston College Department of Economics.
  14. Vytautas Valaitis & Alessandro T. Villa, 2024. "A machine learning projection method for macro‐finance models," Quantitative Economics, Econometric Society, vol. 15(1), pages 145-173, January.
  15. Floortje Alkemade & Han Poutré & Hans Amman, 2009. "Robust Evolutionary Algorithm Design for Socio-Economic Simulation: A Correction," Computational Economics, Springer;Society for Computational Economics, vol. 33(1), pages 99-101, February.
  16. Lim, G.C. & McNelis, Paul D., 2007. "Inflation targeting, learning and Q volatility in small open economies," Journal of Economic Dynamics and Control, Elsevier, vol. 31(11), pages 3699-3722, November.
  17. JOSEPH Charles & DEWANDARU Janu & GUNADI Iman, 2010. "Playing Hard or Soft? : A Simulation of Indonesian Monetary Policy in Targeting Low Inflation Using a Dynamic General Equilibrium Model," EcoMod2003 330700074, EcoMod.
  18. Alexeeva, Tatyana A. & Kuznetsov, Nikolay V. & Mokaev, Timur N. & Zelinka, Ivan, 2025. "Chaotic dynamics in an overlapping generations model: Forecasting and regularization," Chaos, Solitons & Fractals, Elsevier, vol. 196(C).
  19. Shaw, Philip, 2014. "A nonparametric approach to solving a simple one-sector stochastic growth model," Economics Letters, Elsevier, vol. 125(3), pages 447-450.
  20. Pedro Afonso Fernandes, 2024. "Forecasting with Neuro-Dynamic Programming," Papers 2404.03737, arXiv.org.
  21. Heer, Burkhard & Maußner, Alfred, 2008. "Computation Of Business Cycle Models: A Comparison Of Numerical Methods," Macroeconomic Dynamics, Cambridge University Press, vol. 12(5), pages 641-663, November.
  22. S. Sirakaya & Stephen Turnovsky & M. Alemdar, 2006. "Feedback Approximation of the Stochastic Growth Model by Genetic Neural Networks," Computational Economics, Springer;Society for Computational Economics, vol. 27(2), pages 185-206, May.
  23. Adalbert Mayer, 2022. "An Agent-Based Macroeconomic Model with Endogenous Intertemporal Decision Rules," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 48(4), pages 548-579, October.
  24. G. Lim & Paul Mcnelis, 2006. "Central Bank Learning and Taylor Rules with Sticky Import Prices," Computational Economics, Springer;Society for Computational Economics, vol. 28(2), pages 155-175, September.
  25. Roumasset, James A. & Wada, Christopher A., 2012. "Ordering the extraction of renewable resources: The case of multiple aquifers," Resource and Energy Economics, Elsevier, vol. 34(1), pages 112-128.
  26. Lim, G.C. & McNelis, Paul D., 2007. "Central bank learning, terms of trade shocks and currency risk: Should only inflation matter for monetary policy?," Journal of International Money and Finance, Elsevier, vol. 26(6), pages 865-886, October.
  27. McAdam, Peter & McNelis, Paul, 2005. "Forecasting inflation with thick models and neural networks," Economic Modelling, Elsevier, vol. 22(5), pages 848-867, September.
  28. Aryan Eftekhari & Michel Juillard & Normann Rion & Simon Scheidegger, 2025. "Scalable Global Solution Techniques for High-Dimensional Models in Dynare," Papers 2503.11464, arXiv.org.
  29. Maliar, Lilia & Maliar, Serguei & Winant, Pablo, 2021. "Deep learning for solving dynamic economic models," Journal of Monetary Economics, Elsevier, vol. 122(C), pages 76-101.
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