Estimating HANK for Central Banks

Acharya, Sushant; Chen, William; Del Negro, Marco; Dogra, Keshav; Gleich, Aidan; Goyal, Shlok; Lee, Donggyu; Matlin, Ethan; Sarfati, Reca; Sengupta, Sikata

doi:10.59576/sr.1071

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Estimating HANK for Central Banks

Abstract: 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.

Keywords: HANK model; Heterogeneous-agent New Keynesian (HANK) model; Bayesian inference; sequential Monte Carlo methods;

JEL Classification: C11; C32; D31; E32; E37; E52;

https://doi.org/10.59576/sr.1071