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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. Pedro Afonso Fernandes, 2024. "Forecasting with Neuro-Dynamic Programming," Papers 2404.03737, arXiv.org.
  2. 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.
  3. 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.
  4. 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.
  5. Richard Dennis, 2006. "The Frequency of Price Adjustment Viewed Through the Lens of Aggregate Data," Working Paper Series 2006-22, Federal Reserve Bank of San Francisco.
  6. 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.
  7. 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).
  8. Fernández-Villaverde, Jesús & Ebrahimi Kahou, Mahdi & Perla, Jesse & Sood, Arnav, 2021. "Exploiting Symmetry in High-Dimensional Dynamic Programming," CEPR Discussion Papers 16285, Centre for Economic Policy Research.
  9. Marlon Azinovic-Yang & Jan Zemlicka, 2025. "Deep Learning in the Sequence Space," CERGE-EI Working Papers wp802, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
  10. 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).
  11. Richard Dennis, 2008. "The Frequency of Price Adjustment and New Keynesian Business Cycle Dynamics," CAMA Working Papers 2008-19, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  12. Eftekhari, Aryan & Juillard, Michel & Rion, Normann & Scheidegger, Simon, 2026. "Scalable global solution techniques for high-dimensional models in Dynare," Journal of Economic Dynamics and Control, Elsevier, vol. 182(C).
  13. 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.
  14. Shaw, Philip, 2014. "A nonparametric approach to solving a simple one-sector stochastic growth model," Economics Letters, Elsevier, vol. 125(3), pages 447-450.
  15. Marlon Azinovic-Yang & Jan v{Z}emliv{c}ka, 2025. "Deep Learning in the Sequence Space," Papers 2509.13623, arXiv.org, revised Mar 2026.
  16. 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.
  17. Fernández-Villaverde, Jesús & Nuño, Galo & Perla, Jesse, 2024. "Taming the Curse of Dimensionality: Quantitative Economics with Deep Learning," CEPR Discussion Papers 19636, Centre for Economic Policy Research.
  18. 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.
  19. 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.
  20. Julien Pascal, 2025. "Solving economic models with neural networks without backpropagation," BCL working papers 196, Central Bank of Luxembourg.
  21. Richard Dennis, 2005. "Specifying and Estimating New Keynesian Models with Instrument Rules and Optimal Monetary Policies," Working Paper Series 2004-17, Federal Reserve Bank of San Francisco.
  22. 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.
  23. 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.
  24. McAdam, Peter & McNelis, Paul, 2005. "Forecasting inflation with thick models and neural networks," Economic Modelling, Elsevier, vol. 22(5), pages 848-867, September.
  25. 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.
  26. 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.
  27. 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.
  28. 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.
  29. Maliar, Lilia & Maliar, Serguei, 2022. "Deep learning classification: Modeling discrete labor choice," Journal of Economic Dynamics and Control, Elsevier, vol. 135(C).
  30. 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.
  31. 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.
  32. 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.
  33. Nicolas Langren'e & Xiaolin Luo & Pavel V. Shevchenko & Ruiyi Zhang, 2026. "Deep Least Squares Monte Carlo methods for the valuation of variable annuities with guarantees," Papers 2605.27182, arXiv.org.
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