Arbeitspapier

Modeling model uncertainty

Recently there has been much interest in studying monetary policy under model uncertainty. We develop methods to analyze different sources of uncertainty in one coherent structure useful for policy decisions. We show how to estimate the size of the uncertainty based on time series data, and incorporate this uncertainty in policy optimization. We propose two different approaches to modeling model uncertainty. The first is model error modeling, which imposes additional structure on the errors of an estimated model, and builds a statistical description of the uncertainty around a model. The second is set membership identification, which uses a deterministic approach to find a set of models consistent with data and prior assumptions. The center of this set becomes a benchmark model, and the radius measures model uncertainty. Using both approaches, we compute the robust monetary policy under different model uncertainty specifications in a small model of the US economy.

Sprache
Englisch

Erschienen in
Series: ECB Working Paper ; No. 169

Klassifikation
Wirtschaft
Monetary Policy
Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
Criteria for Decision-Making under Risk and Uncertainty
Thema
estimation
Model uncertainty
monetary policy

Ereignis
Geistige Schöpfung
(wer)
Onatski, Alexei
Williams, Noah
Ereignis
Veröffentlichung
(wer)
European Central Bank (ECB)
(wo)
Frankfurt a. M.
(wann)
2002

Handle
Letzte Aktualisierung
10.03.2025, 11:41 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

  • Onatski, Alexei
  • Williams, Noah
  • European Central Bank (ECB)

Entstanden

  • 2002

Ähnliche Objekte (12)