Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/284031 
Erscheinungsjahr: 
2023
Schriftenreihe/Nr.: 
Staff Report No. 1071
Verlag: 
Federal Reserve Bank of New York, New York, NY
Zusammenfassung: 
We provide a toolkit for efficient online estimation of heterogeneous agent (HA) New Keynesian (NK) models based on Sequential Monte Carlo methods. We use this toolkit to compare the out-of-sample forecasting accuracy of a prominent HANK model, Bayer et al. (2022), to that of the representative agent (RA) NK model of Smets and Wouters (2007, SW). We find that HANK's accuracy for real activity variables is notably inferior to that of SW. The results for consumption in particular are disappointing since the main difference between RANK and HANK is the replacement of the RA Euler equation with the aggregation of individual households' consumption policy functions, which reflects inequality.
Schlagwörter: 
HANK
Bayesian inference
sequential Monte Carlo methods
JEL: 
C11
C32
D31
E32
E37
E52
Persistent Identifier der Erstveröffentlichung: 
Dokumentart: 
Working Paper

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