E-stability and stability of adaptive learning in models with asymmetric information

Research output: Working paperWorking papers

Authors

The paper demonstrates how the E–stability principle introduced by Evans and Honkapohja [2001] can be applied to models with heterogeneous and private information in order to assess the stability of rational expectations equilibria under learning. The paper extends already known stability results for the Grossman and Stiglitz [1980] model to a more general case with many differentially informed agents and to the case where information is endogenously acquired by optimizing agents. In both cases it turns out that the rational expectations equilibrium of the model is inherently E-stable and thus locally stable under recursive least squares learning.
Original languageEnglish
Place of PublicationLüneburg
PublisherInstitut für Volkswirtschaftslehre der Universität Lüneburg
Number of pages24
Publication statusPublished - 2007

    Research areas

  • Economics - adaptive learning, eductive stability, rational expectations

Documents

Recently viewed

Publications

  1. A simple nonlinear PD control for faster and high-precision positioning of servomechanisms with actuator saturation
  2. Selecting and Adapting Methods for Analysis and Design in Value-Sensitive Digital Social Innovation Projects: Toward Design Principles
  3. Volume of Imbalance Container Prediction using Kalman Filter and Long Short-Term Memory
  4. Influence of Process Parameters and Die Design on the Microstructure and Texture Development of Direct Extruded Magnesium Flat Products
  5. The delay vector variance method and the recurrence quantification analysis of energy markets
  6. Simple saturated PID control for fast transient of motion systems
  7. Dynamic Lot Size Optimization with Reinforcement Learning
  8. Constraint breeds creativity
  9. Introducing parametric uncertainty into a nonlinear friction model
  10. Need Satisfaction and Optimal Functioning at Leisure and Work: A Longitudinal Validation Study of the DRAMMA Model
  11. Switching Dispatching Rules with Gaussian Processes
  12. A computational study of a model of single-crystal strain-gradient viscoplasticity with an interactive hardening relation
  13. A Wavelet Packet Algorithm for Online Detection of Pantograph Vibrations
  14. Comparison of different FEM codes approach for extrusion process analysis
  15. Active and semi-supervised data domain description
  16. Faulty Process Detection Using Machine Learning Techniques
  17. Contextual movement models based on normalizing flows
  18. Lyapunov Convergence Analysis for Asymptotic Tracking Using Forward and Backward Euler Approximation of Discrete Differential Equations
  19. A Lean Convolutional Neural Network for Vehicle Classification
  20. Analyzing User Journey Data In Digital Health: Predicting Dropout From A Digital CBT-I Intervention
  21. Recognition and approach responses toward threatening objects
  22. Effectiveness of a guided multicomponent internet and mobile gratitude training program - A pragmatic randomized controlled trial
  23. Formative Perspectives on the Relation Between CSR Communication and CSR Practices
  24. Global Finite-Time Stabilization of Planar Linear Systems With Actuator Saturation
  25. Sensitivity to complexity - an important prerequisite of problem solving mathematics teaching
  26. Towards a spatial understanding of identity play
  27. Supporting the Development and Implementation of a Digitalization Strategy in SMEs through a Lightweight Architecture-based Method
  28. Dispatching rule selection with Gaussian processes
  29. Web-scale extension of RDF knowledge bases from templated websites
  30. Interpreting Strings, Weaving Threads
  31. Constraints are the solution, not the problem