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Deep learning for solving dynamic economic models

Citations

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Cited by:

  1. Pedro Afonso Fernandes, 2024. "Forecasting with Neuro-Dynamic Programming," Papers 2404.03737, arXiv.org.
  2. Sergio Ocampo & Baxter Robinson, 2024. "Computing Longitudinal Moments for Heterogeneous Agent Models," Computational Economics, Springer;Society for Computational Economics, vol. 64(3), pages 1891-1912, September.
  3. Ashwin, Julian & Beaudry, Paul & Ellison, Martin, 2025. "Neural network learning for nonlinear economies," Journal of Monetary Economics, Elsevier, vol. 149(C).
  4. Fernández-Villaverde, Jesús & Marbet, Joël & Nuño, Galo & Rachedi, Omar, 2025. "Inequality and the zero lower bound," Journal of Econometrics, Elsevier, vol. 249(PC).
  5. Xianhua Peng & Steven Kou & Lekang Zhang, 2024. "A Machine Learning Algorithm for Finite-Horizon Stochastic Control Problems in Economics," Papers 2411.08668, arXiv.org, revised Dec 2024.
  6. Douglas Kiarelly Godoy de Araujo, 2023. "gingado: a machine learning library focused on economics and finance," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Data science in central banking: applications and tools, volume 59, Bank for International Settlements.
  7. Zhouzhou Gu & Mathieu Lauri`ere & Sebastian Merkel & Jonathan Payne, 2024. "Global Solutions to Master Equations for Continuous Time Heterogeneous Agent Macroeconomic Models," Papers 2406.13726, arXiv.org.
  8. Kase, Hanno & Melosi, Leonardo & Rottner, Matthias, 2022. "Estimating Nonlinear Heterogeneous Agents Models with Neural Networks," CEPR Discussion Papers 17391, C.E.P.R. Discussion Papers.
  9. Jesús Fernández-Villaverde & Galo Nuño & Jesse Perla, 2024. "Taming the Curse of Dimensionality: Quantitative Economics with Deep Learning," NBER Working Papers 33117, National Bureau of Economic Research, Inc.
  10. Tahvonen, Olli & Suominen, Antti & Malo, Pekka & Viitasaari, Lauri & Parkatti, Vesa-Pekka, 2022. "Optimizing high-dimensional stochastic forestry via reinforcement learning," Journal of Economic Dynamics and Control, Elsevier, vol. 145(C).
  11. Aryan Eftekhari & Simon Scheidegger, 2022. "High-Dimensional Dynamic Stochastic Model Representation," Papers 2202.06555, arXiv.org.
  12. Emmet Hall-Hoffarth, 2023. "Non-linear approximations of DSGE models with neural-networks and hard-constraints," Papers 2310.13436, arXiv.org.
  13. Victor Duarte & Diogo Duarte & Dejanir H. Silva, 2024. "Machine Learning for Continuous-Time Finance," CESifo Working Paper Series 10909, CESifo.
  14. Mahdi Ebrahimi Kahou & Jesse Perla & Geoff Pleiss, 2024. "Solving Models of Economic Dynamics with Ridgeless Kernel Regressions," Papers 2406.01898, arXiv.org, revised Oct 2025.
  15. 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.
  16. Alexeeva, Tatyana & Diep, Quoc Bao & Kuznetsov, Nikolay & Zelinka, Ivan, 2023. "Forecasting and stabilizing chaotic regimes in two macroeconomic models via artificial intelligence technologies and control methods," Chaos, Solitons & Fractals, Elsevier, vol. 170(C).
  17. Ruxin Chen, 2025. "Deep Reinforcement Learning in a Search-Matching Model of Labor Market Fluctuations," Economies, MDPI, vol. 13(10), pages 1-16, October.
  18. Eftekhari, Aryan & Juillard, Michel & Rion, Normann & Scheidegger, Simon, 2025. "Scalable Global Solution Techniques for High-Dimensional Models in Dynare," Dynare Working Papers 86, CEPREMAP.
  19. Pascal, Julien, 2024. "Artificial neural networks to solve dynamic programming problems: A bias-corrected Monte Carlo operator," Journal of Economic Dynamics and Control, Elsevier, vol. 162(C).
  20. Pagnoncelli, Bernardo K. & Homem-de-Mello, Tito & Lagos, Guido & Castañeda, Pablo & García, Javier, 2024. "Solving constrained consumption–investment problems by decomposition algorithms," European Journal of Operational Research, Elsevier, vol. 319(1), pages 292-302.
  21. Marlon Azinovic & Jan v{Z}emliv{c}ka, 2023. "Economics-Inspired Neural Networks with Stabilizing Homotopies," Papers 2303.14802, arXiv.org.
  22. Maliar, Lilia & Maliar, Serguei, 2022. "Deep learning classification: Modeling discrete labor choice," Journal of Economic Dynamics and Control, Elsevier, vol. 135(C).
  23. Jiequn Han & Yucheng Yang & Weinan E, 2025. "DeepHAM: A Global Solution Method for Heterogeneous Agent Models with Aggregate Shocks," Swiss Finance Institute Research Paper Series 25-06, Swiss Finance Institute.
  24. Jiequn Han & Yucheng Yang & Weinan E, 2021. "DeepHAM: A Global Solution Method for Heterogeneous Agent Models with Aggregate Shocks," Papers 2112.14377, arXiv.org, revised Feb 2022.
  25. 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.
  26. Isaiah Hull & Or Sattath & Eleni Diamanti & Göran Wendin, 2024. "Quantum Algorithms," Contributions to Economics, in: Quantum Technology for Economists, chapter 0, pages 37-103, Springer.
  27. Skavysh, Vladimir & Priazhkina, Sofia & Guala, Diego & Bromley, Thomas R., 2023. "Quantum monte carlo for economics: Stress testing and macroeconomic deep learning," Journal of Economic Dynamics and Control, Elsevier, vol. 153(C).
  28. Elisei Leonov, 2023. "Neural Network-Based Numerical Analysis of the Impact of Pandemic Shocks in Three-Sector DSGE Model," Russian Journal of Money and Finance, Bank of Russia, vol. 82(4), pages 80-107, December.
  29. Thomas J. Sargent & John Stachurski, 2024. "Dynamic Programming: Finite States," Papers 2401.10473, arXiv.org.
  30. Marlon Azinovic-Yang & Jan v{Z}emliv{c}ka, 2025. "Deep Learning in the Sequence Space," Papers 2509.13623, arXiv.org.
  31. 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.
  32. Vladimir Skavysh & Sofia Priazhkina & Diego Guala & Thomas Bromley, 2022. "Quantum Monte Carlo for Economics: Stress Testing and Macroeconomic Deep Learning," Staff Working Papers 22-29, Bank of Canada.
  33. Ajit Desai, 2023. "Machine Learning for Economics Research: When What and How?," Papers 2304.00086, arXiv.org, revised Apr 2023.
  34. Vadim Grishchenko & Ivan Krylov, 2024. "New Approaches to Measuring, Analysing, and Forecasting Prices: A Review of the Bank of Russia, NES, and HSE University Workshop," Russian Journal of Money and Finance, Bank of Russia, vol. 83(2), pages 92-111, June.
  35. Montes-Galdón, Carlos & Ajevskis, Viktors & Brázdik, František & Garcia, Pablo & Gatt, William & Lima, Diana & Mavromatis, Kostas & Ortega, Eva & Papadopoulou, Niki & De Lorenzo, Ivan & Kolb, Benedikt, 2024. "Using structural models to understand macroeconomic tail risks," Occasional Paper Series 357, European Central Bank.
  36. Benjamin Fan & Edward Qiao & Anran Jiao & Zhouzhou Gu & Wenhao Li & Lu Lu, 2025. "Deep Learning for Solving and Estimating Dynamic Macro-finance Models," Computational Economics, Springer;Society for Computational Economics, vol. 65(6), pages 3885-3921, June.
  37. Ciccarelli, Matteo & Darracq Pariès, Matthieu & Priftis, Romanos & Angelini, Elena & Bańbura, Marta & Bokan, Nikola & Fagan, Gabriel & Gumiel, José Emilio & Kornprobst, Antoine & Lalik, Magdalena & Mo, 2024. "ECB macroeconometric models for forecasting and policy analysis," Occasional Paper Series 344, European Central Bank.
  38. Kshama Dwarakanath & Tucker Balch & Svitlana Vyetrenko, 2024. "ABIDES-Economist: Agent-Based Simulator of Economic Systems with Learning Agents," Papers 2402.09563, arXiv.org, revised Aug 2025.
  39. Benjamin Fan & Edward Qiao & Anran Jiao & Zhouzhou Gu & Wenhao Li & Lu Lu, 2023. "Deep Learning for Solving and Estimating Dynamic Macro-Finance Models," Papers 2305.09783, arXiv.org.
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