Arbeitspapier
A moment-matching method for approximating vector autoregressive processes by finite-state Markov chains
This paper proposes a moment-matching method for approximating vector autoregressions by finite-state Markov chains. The Markov chain is constructed by targeting the conditional moments of the underlying continuous process. The proposed method is more robust to the number of discrete values and tends to outperform the existing methods for approximating multivariate processes over a wide range of the parameter space, especially for highly persistent vector autoregressions with roots near the unit circle.
- Sprache
-
Englisch
- Erschienen in
-
Series: Working Paper ; No. 2013-5
- Klassifikation
-
Wirtschaft
Statistical Simulation Methods: General
Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
Mathematical Methods; Programming Models; Mathematical and Simulation Modeling: General
General Aggregative Models: Neoclassical
Business Fluctuations; Cycles
Fiscal Policy
- Thema
-
Markov chain
vector autoregressive processes
numerical methods
moment matching
non-linear stochastic dynamic models state space discretization
stochastic growth model
fiscal policy
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Gospodinov, Nikolay
Lkhagvasuren, Damba
- Ereignis
-
Veröffentlichung
- (wer)
-
Federal Reserve Bank of Atlanta
- (wo)
-
Atlanta, GA
- (wann)
-
2013
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:42 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.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Gospodinov, Nikolay
- Lkhagvasuren, Damba
- Federal Reserve Bank of Atlanta
Entstanden
- 2013
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