IDEAS home Printed from https://ideas.repec.org/r/wly/emetrp/v85y2017ip1575-1612.html
   My bibliography  Save this item

Using Adaptive Sparse Grids to Solve High‐Dimensional Dynamic Models

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Andreas Lanz & Gregor Reich & Ole Wilms, 2022. "Adaptive grids for the estimation of dynamic models," Quantitative Marketing and Economics (QME), Springer, vol. 20(2), pages 179-238, June.
  2. Werner, Maximilian, 2023. "Occasionally binding liquidity constraints and macroeconomic dynamics," Journal of Economic Dynamics and Control, Elsevier, vol. 150(C).
  3. Hui Chen & Antoine Didisheim & Simon Scheidegger, 2021. "Deep Structural Estimation:With an Application to Option Pricing," Cahiers de Recherches Economiques du Département d'économie 21.14, Université de Lausanne, Faculté des HEC, Département d’économie.
  4. Philipp Renner & Karl Schmedders, 2020. "Discrete‐time dynamic principal–agent models: Contraction mapping theorem and computational treatment," Quantitative Economics, Econometric Society, vol. 11(4), pages 1215-1251, November.
  5. Prateek Bansal & Vahid Keshavarzzadeh & Angelo Guevara & Shanjun Li & Ricardo A Daziano, 2022. "Designed quadrature to approximate integrals in maximum simulated likelihood estimation [Evaluating simulation-based approaches and multivariate quadrature on sparse grids in estimating multivariat," The Econometrics Journal, Royal Economic Society, vol. 25(2), pages 301-321.
  6. Duong Ngotran, 2016. "The E-Monetary Theory," 2016 Papers png175, Job Market Papers.
  7. Judd, Kenneth L. & Maliar, Lilia & Maliar, Serguei & Valero, Rafael, 2014. "Smolyak method for solving dynamic economic models: Lagrange interpolation, anisotropic grid and adaptive domain," Journal of Economic Dynamics and Control, Elsevier, vol. 44(C), pages 92-123.
  8. Cao, Dan & Evans, Martin & Lua, Wenlan, 2020. "Real Exchange Rate Dynamics Beyond Business Cycles," MPRA Paper 99054, University Library of Munich, Germany, revised 10 Mar 2020.
  9. Fernández-Villaverde, J. & Rubio-Ramírez, J.F. & Schorfheide, F., 2016. "Solution and Estimation Methods for DSGE Models," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 527-724, Elsevier.
  10. Yongyang Cai & Kenneth Judd & Jevgenijs Steinbuks, 2017. "A nonlinear certainty equivalent approximation method for dynamic stochastic problems," Quantitative Economics, Econometric Society, vol. 8(1), pages 117-147, March.
  11. Dan Cao & Wenlan Luo & Guangyu Nie, 2023. "Global GDSGE Models," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 51, pages 199-225, December.
  12. Ivan Rudik & Derek Lemoine & Maxwell Rosenthal, 2018. "General Bayesian Learning in Dynamic Stochastic Models: Estimating the Value of Science Policy," 2018 Meeting Papers 369, Society for Economic Dynamics.
  13. Kristensen, Dennis & Mogensen, Patrick K. & Moon, Jong Myun & Schjerning, Bertel, 2021. "Solving dynamic discrete choice models using smoothing and sieve methods," Journal of Econometrics, Elsevier, vol. 223(2), pages 328-360.
  14. Aryan Eftekhari & Simon Scheidegger, 2022. "High-Dimensional Dynamic Stochastic Model Representation," Papers 2202.06555, arXiv.org.
  15. Alexander W. Blocker & Laurence J. Kotlikoff & Stephen A. Ross & Sergio Villar Vallenas, 2019. "The True Cost of Social Security," Tax Policy and the Economy, University of Chicago Press, vol. 33(1), pages 131-163.
  16. Daniel Harenberg & Stefano Marelli & Bruno Sudret & Viktor Winschel, 2019. "Uncertainty quantification and global sensitivity analysis for economic models," Quantitative Economics, Econometric Society, vol. 10(1), pages 1-41, January.
  17. Victor Duarte & Diogo Duarte & Dejanir H. Silva, 2024. "Machine Learning for Continuous-Time Finance," CESifo Working Paper Series 10909, CESifo.
  18. Adrien Auclert & Bence Bardóczy & Matthew Rognlie & Ludwig Straub, 2021. "Using the Sequence‐Space Jacobian to Solve and Estimate Heterogeneous‐Agent Models," Econometrica, Econometric Society, vol. 89(5), pages 2375-2408, September.
  19. Ikefuji, Masako & Laeven, Roger J.A. & Magnus, Jan R. & Muris, Chris, 2020. "Expected utility and catastrophic risk in a stochastic economy–climate model," Journal of Econometrics, Elsevier, vol. 214(1), pages 110-129.
  20. Philipp Renner & Simon Scheidegger, 2017. "Machine learning for dynamic incentive problems," Working Papers 203620397, Lancaster University Management School, Economics Department.
  21. Peter Schober & Julian Valentin & Dirk Pflüger, 2022. "Solving High-Dimensional Dynamic Portfolio Choice Models with Hierarchical B-Splines on Sparse Grids," Computational Economics, Springer;Society for Computational Economics, vol. 59(1), pages 185-224, January.
  22. Julien Albertini & Stéphane Moyen, 2020. "A General and Efficient Method for Solving Regime-Switching DSGE Models," Working Papers 2035, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
  23. Sergei Seleznev, 2016. "Solving DSGE models with stochastic trends," Bank of Russia Working Paper Series wps15, Bank of Russia.
  24. Alexander Yu Morozov & Andrey A. Zhuravlev & Dmitry L. Reviznikov, 2021. "Sparse Grid Adaptive Interpolation in Problems of Modeling Dynamic Systems with Interval Parameters," Mathematics, MDPI, vol. 9(4), pages 1-17, February.
  25. Marlon Azinovic & Jan v{Z}emliv{c}ka, 2023. "Economics-Inspired Neural Networks with Stabilizing Homotopies," Papers 2303.14802, arXiv.org.
  26. Marc Bourreau & Yutec Sun, 2022. "Competition and Quality: Evidence from the Entry of Mobile Network Service," Working Papers 22-04, NET Institute.
  27. Miftakhova, Alena & Judd, Kenneth L. & Lontzek, Thomas S. & Schmedders, Karl, 2020. "Statistical approximation of high-dimensional climate models," Journal of Econometrics, Elsevier, vol. 214(1), pages 67-80.
  28. 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.
  29. Jasmina Hasanhodzic & Laurence J. Kotlikoff, 2017. "Valuing Government Obligations When Markets are Incomplete," NBER Working Papers 24092, National Bureau of Economic Research, Inc.
  30. Harrison, Richard & Waldron, Matt, 2021. "Optimal policy with occasionally binding constraints: piecewise linear solution methods," Bank of England working papers 911, Bank of England.
  31. Felix Kubler & Simon Scheidegger, 2018. "Self-justi ed equilibria: Existence and computation," 2018 Meeting Papers 694, Society for Economic Dynamics.
  32. Hui Chen & Antoine Didisheim & Simon Scheidegger, 2021. "Deep Structural Estimation: With an Application to Option Pricing," Papers 2102.09209, arXiv.org.
  33. Simon Scheidegger & Adrien Treccani, 2021. "Pricing American Options under High-Dimensional Models with Recursive Adaptive Sparse Expectations [Telling from Discrete Data Whether the Underlying Continuous-Time Model Is a Diffusion]," Journal of Financial Econometrics, Oxford University Press, vol. 19(2), pages 258-290.
  34. Yongyang Cai & Simon Scheidegger & Sevin Yeltekin & Philipp Renner & Kenneth Judd, 2017. "Optimal Dynamic Fiscal Policy with Endogenous Debt Limits," 2017 Meeting Papers 1543, Society for Economic Dynamics.
  35. Philipp Renner, 2020. "An augmented first-order approach for incentive problems," Working Papers 297498586, Lancaster University Management School, Economics Department.
  36. Miranda-Pinto, Jorge & Young, Eric R., 2019. "Comparing dynamic multisector models," Economics Letters, Elsevier, vol. 181(C), pages 28-32.
  37. Jasmina Hasanhodzic & Laurence J. Kotlikoff, 2019. "Valuing Government Obligations When Markets Are Incomplete," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 51(7), pages 1815-1855, October.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.