IDEAS home Printed from https://ideas.repec.org/r/red/issued/v8y2005i2p360-391.html
   My bibliography  Save this item

Impacts of Priors on Convergence and Escapes from Nash Inflation

Citations

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


Cited by:

  1. Berardi, Michele & Galimberti, Jaqueson K., 2013. "A note on exact correspondences between adaptive learning algorithms and the Kalman filter," Economics Letters, Elsevier, pages 139-142.
  2. George W. Evans & William A. Branch, 2005. "Model Uncertainty and Endogenous Volatility," Computing in Economics and Finance 2005 33, Society for Computational Economics.
  3. Thomas Sargent & Noah Williams & Tao Zha, 2009. "The Conquest of South American Inflation," Journal of Political Economy, University of Chicago Press, vol. 117(2), pages 211-256, April.
  4. In-Koo Cho & Kenneth Kasa, 2017. "Gresham's Law of Model Averaging," American Economic Review, American Economic Association, pages 3589-3616.
  5. Glenn D. Rudebusch & Eric T. Swanson, 2012. "The Bond Premium in a DSGE Model with Long-Run Real and Nominal Risks," American Economic Journal: Macroeconomics, American Economic Association, pages 105-143.
  6. Thomas Sargent & Noah Williams & Tao Zha, 2006. "Shocks and Government Beliefs: The Rise and Fall of American Inflation," American Economic Review, American Economic Association, pages 1193-1224.
  7. Hans Dewachter & Marco Lyrio, 2008. "Learning, Macroeconomic Dynamics and the Term Structure of Interest Rates," NBER Chapters,in: Asset Prices and Monetary Policy, pages 191-245 National Bureau of Economic Research, Inc.
  8. Berardi, Michele & Galimberti, Jaqueson K., 2017. "Empirical calibration of adaptive learning," Journal of Economic Behavior & Organization, Elsevier, vol. 144(C), pages 219-237.
  9. Kaushik Mitra & Seppo Honkapohja, 2004. "Learning Stability in Economies with Heterogenous Agents," Royal Holloway, University of London: Discussion Papers in Economics 04/17, Department of Economics, Royal Holloway University of London, revised Jul 2004.
  10. KevinX.D. Huang & Zheng Liu & Tao Zha, 2009. "Learning, Adaptive Expectations and Technology Shocks," Economic Journal, Royal Economic Society, vol. 119(536), pages 377-405, March.
  11. Robert Tetlow & Peter von zur Muehlen, 2004. "Avoiding Nash Inflation: Bayesian and Robus Responses to Model Uncertainty," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 7(4), pages 869-899, October.
  12. In-Koo Cho & Kenneth Kasa, 2015. "Learning and Model Validation," Review of Economic Studies, Oxford University Press, vol. 82(1), pages 45-82.
  13. Luca Benati, 2005. "U.K. Monetary Regimes and Macroeconomic Stylised Facts," Computing in Economics and Finance 2005 107, Society for Computational Economics.
  14. Seppo Honkapohja & Kaushik Mitra, 2006. "Learning Stability in Economies with Heterogeneous Agents," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 9(2), pages 284-309, April.
  15. Slobodyan, Sergey & Wouters, Raf, 2012. "Learning in an estimated medium-scale DSGE model," Journal of Economic Dynamics and Control, Elsevier, pages 26-46.
  16. Lars E. O. Svensson, 2003. "Monetary policy and learning," Economic Review, Federal Reserve Bank of Atlanta, pages 11-16.
  17. George W. Evans & Seppo Honkapohja & Thomas Sargent & Noah Williams, 2012. "Bayesian Model Averaging, Learning and Model Selection," CDMA Working Paper Series 201203, Centre for Dynamic Macroeconomic Analysis.
  18. Carboni, Giacomo & Ellison, Martin, 2009. "The Great Inflation and the Greenbook," Journal of Monetary Economics, Elsevier, vol. 56(6), pages 831-841, September.
  19. Josef Hollmayr & Christian Matthes, 2013. "Learning about fiscal policy and the effects of policy uncertainty," Working Paper 13-15, Federal Reserve Bank of Richmond.
  20. Norman, Thomas W.L., 2015. "Learning, hypothesis testing, and rational-expectations equilibrium," Games and Economic Behavior, Elsevier, vol. 90(C), pages 93-105.
  21. Rondina, Francesca, 2012. "The role of model uncertainty and learning in the US postwar policy response to oil prices," Journal of Economic Dynamics and Control, Elsevier, vol. 36(7), pages 1009-1041.
  22. Kim, Young Se, 2009. "Exchange rates and fundamentals under adaptive learning," Journal of Economic Dynamics and Control, Elsevier, vol. 33(4), pages 843-863, April.
  23. Luca Benati, 2005. "U.K. Monetary Regimes and Macroeconomic Stylised Facts," Computing in Economics and Finance 2005 107, Society for Computational Economics.
  24. Bigio, Saki, 2010. "Learning under fear of floating," Journal of Economic Dynamics and Control, Elsevier, vol. 34(10), pages 1923-1950, October.
  25. Timothy Cogley & Thomas J. Sargent, 2005. "The conquest of US inflation: Learning and robustness to model uncertainty," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 8(2), pages 528-563, April.
  26. James M. Nason & Takashi Kano, 2004. "Business Cycle Implications of Habit Formation," Econometric Society 2004 Far Eastern Meetings 619, Econometric Society.
  27. Branch, William A., 2016. "Imperfect knowledge, liquidity and bubbles," Journal of Economic Dynamics and Control, Elsevier, vol. 62(C), pages 17-42.
  28. Pierpaolo Battigalli & Simone Cerreia-Vioglio & Fabio Maccheroni & Massimo Marinacci & Thomas Sargent, 2016. "A Framework for the Analysis of Self-Confi rming Policies," Working Papers 573, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
  29. Hollmayr, Josef & Matthes, Christian, 2015. "Learning about fiscal policy and the effects of policy uncertainty," Journal of Economic Dynamics and Control, Elsevier, vol. 59(C), pages 142-162.
  30. Jess Benhabib & Chetan Dave, 2014. "Learning, Large Deviations and Rare Events," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 17(3), pages 367-382, July.
  31. F. Canova & F. Ferroni & C. Matthes, 2015. "Approximating time varying structural models with time invariant structures," Working papers 578, Banque de France.
  32. Davide Delle Monache & Ivan Petrella, 2014. "Adaptive Models and Heavy Tails," Working Papers 720, Queen Mary University of London, School of Economics and Finance.
  33. Kolyuzhnov, Dmitri & Bogomolova, Anna & Slobodyan, Sergey, 2014. "Escape dynamics: A continuous-time approximation," Journal of Economic Dynamics and Control, Elsevier, pages 161-183.
  34. Magud, Nicolas E., 2008. "On asymmetric business cycles and the effectiveness of counter-cyclical fiscal policies," Journal of Macroeconomics, Elsevier, pages 885-905.
  35. Carboni, Giacomo & Ellison, Martin, 2007. "Learning and the Great Inflation," CEPR Discussion Papers 6250, C.E.P.R. Discussion Papers.
  36. Ellis W. Tallman, 2003. "Monetary policy and learning: Some implications for policy and research," Economic Review, Federal Reserve Bank of Atlanta, pages 1-9.
  37. Francesca Rondina, 2017. "Model Uncertainty and the Direction of Fit of the Postwar U.S. Phillips Curve(s)," Working Papers 1702E, University of Ottawa, Department of Economics.
  38. Matthes, Christian & Hollmayr, Josef, 2015. "Tales of Transition Paths: Policy Uncertainty and Random Walks," Working Paper 15-11, Federal Reserve Bank of Richmond.
  39. Bullard, James & Suda, Jacek, 2016. "The stability of macroeconomic systems with Bayesian learners," Journal of Economic Dynamics and Control, Elsevier, pages 1-16.
  40. William Branch & George W. Evans, 2007. "Model Uncertainty and Endogenous Volatility," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 10(2), pages 207-237, April.
  41. J. Huston McCulloch, 2005. "The Kalman Foundations of Adaptive Least Squares: Applications to Unemployment and Inflation," Computing in Economics and Finance 2005 239, Society for Computational Economics.
  42. Jacopo Piana & Daniele Bianchi, 2017. "Expected Spot Prices and the Dynamics of Commodity Risk Premia," 2017 Meeting Papers 1149, Society for Economic Dynamics.
  43. Giri, Rahul, 2012. "Local costs of distribution, international trade costs and micro evidence on the law of one price," Journal of International Economics, Elsevier, pages 82-100.
IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.