Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/190330
Authors: 
Kukacka, Jiri
Jang, Tae-Seok
Sacht, Stephen
Year of Publication: 
2018
Series/Report no.: 
Economics Working Paper 2018-11
Abstract: 
In this paper, we introduce the simulated maximum likelihood method for identifying behavioral heuristics of heterogeneous agents in the baseline three-equation New Keynesian model. The method is extended to multivariate macroeconomic optimization problems, and the estimation pro-cedure is applied to empirical data sets. This approach considerably relaxes restrictive theoretical assumptions and enables a novel estimation of the intensity of choice parameter in discrete choice. In Monte Carlo simulations, we analyze the properties and behavior of the estimation method, which provides important information on the behavioral parameters of the New Keynesian model. However, the curse of dimensionality arises via a consistent downward bias for idiosyncratic shocks. Our empirical results show that the forward-looking version of both the behavioral and the rational model specifications exhibits good performance. We identify potential sources of misspecification for the hybrid version. A novel feature of our analysis is that we pin down the switching parameter for the intensity of choice for the Euro Area and US economy.
Subjects: 
Behavioral Heuristics
Intensity of Choice
Monte Carlo Simulations
New-Keynesian Model
Simulated Maximum Likelihood
JEL: 
C53
D83
E12
E32
Document Type: 
Working Paper
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