Fat Tails and Spurious Estimation of Consumption-Based Asset Pricing Models
Alexis Akira Toda and
Kieran James Walsh
MPRA Paper from University Library of Munich, Germany
Abstract:
The standard generalized method of moments (GMM) estimation of Euler equations in heterogeneous-agent consumption-based asset pricing models is inconsistent under fat tails because the GMM criterion is asymptotically random. To illustrate this, we generate asset returns and consumption data from an incomplete-market dynamic general equilibrium model that is analytically solvable and exhibits power laws in consumption. Monte Carlo experiments suggest that the standard GMM estimation is inconsistent and susceptible to Type II errors (incorrect non-rejection of false models). Estimating an overidentified model by dividing agents into age cohorts appears to mitigate Type I and II errors.
Keywords: consumption-based CAPM; generalized method of moments; heterogeneous-agent model; power law (search for similar items in EconPapers)
JEL-codes: C58 D31 D52 D58 G12 (search for similar items in EconPapers)
Date: 2016-11-17
New Economics Papers: this item is included in nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://mpra.ub.uni-muenchen.de/78980/1/MPRA_paper_78980.pdf original version (application/pdf)
Related works:
Journal Article: Fat tails and spurious estimation of consumption‐based asset pricing models (2017) 
Working Paper: Fat tails and spurious estimation of consumption-based asset pricing models (2017) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:78980
Access Statistics for this paper
More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().