Arbeitspapier

Estimating dynamic equilibrium economies: linear versus nonlinear likelihood

This paper compares two methods for undertaking likelihood-based inference in dynamic equilibrium economies: a sequential Monte Carlo filter proposed by Fernández-Villaverde and Rubio-Ramírez (2004) and the Kalman filter. The sequential Monte Carlo filter exploits the nonlinear structure of the economy and evaluates the likelihood function of the model by simulation methods. The Kalman filter estimates a linearization of the economy around the steady state. The authors report two main results. First, both for simulated and for real data, the sequential Monte Carlo filter delivers a substantially better fit of the model to the data as measured by the marginal likelihood. This is true even for a nearly linear case. Second, the differences in terms of point estimates, even if relatively small in absolute values, have important effects on the moments of the model. The authors conclude that the nonlinear filter is a superior procedure for taking models to the data.

Sprache
Englisch

Erschienen in
Series: Working Paper ; No. 2004-3

Klassifikation
Wirtschaft

Ereignis
Geistige Schöpfung
(wer)
Fernández-Villaverde, Jesús
Rubio-Ramírez, Juan Francisco
Ereignis
Veröffentlichung
(wer)
Federal Reserve Bank of Atlanta
(wo)
Atlanta, GA
(wann)
2004

Handle
Letzte Aktualisierung
20.09.2024, 08:23 MESZ

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

  • Fernández-Villaverde, Jesús
  • Rubio-Ramírez, Juan Francisco
  • Federal Reserve Bank of Atlanta

Entstanden

  • 2004

Ähnliche Objekte (12)