Arbeitspapier

Does inattentiveness matter for DSGE modelling? An empirical investigation

The purpose of this paper is to investigate the empirical performance of the standard New Keynesian dynamic stochastic general equilibrium (DSGE) model in its usual form with full-information rational expectations and compare it with versions assuming inattentiveness- namely sticky information and imperfect information data revision. Using a Bayesian estimation approach on US quarterly data (both real-time and survey) from 1969 to 2015, we find that the model with sticky information fits best and is the only one that can generate the delayed responses observed in the data. The imperfect information data revision model is improved fits better when survey data is used in place of real-time data, suggesting that it contains extra information.

Sprache
Englisch

Erschienen in
Series: Cardiff Economics Working Papers ; No. E2021/35

Klassifikation
Wirtschaft
Bayesian Analysis: General
Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
Model Evaluation, Validation, and Selection
General Aggregative Models: General
General Aggregative Models: Keynes; Keynesian; Post-Keynesian
General Aggregative Models: Forecasting and Simulation: Models and Applications
Thema
Expectation formation
Inattentive expectation
New Keynesian
DSGE
Bayesian estimation

Ereignis
Geistige Schöpfung
(wer)
Chou, Jenyu
Easaw, Joshy Z.
Minford, Patrick
Ereignis
Veröffentlichung
(wer)
Cardiff University, Cardiff Business School
(wo)
Cardiff
(wann)
2021

Handle
Letzte Aktualisierung
10.03.2025, 11:44 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Chou, Jenyu
  • Easaw, Joshy Z.
  • Minford, Patrick
  • Cardiff University, Cardiff Business School

Entstanden

  • 2021

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