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TESTING CONSUMPTION OPTIMALITY USING AGGREGATE DATA

Published online by Cambridge University Press:  18 January 2016

Fábio Augusto Reis Gomes  and
João Victor Issler
Fábio Augusto Reis Gomes
Affiliation:
University of São Paulo—Ribeirão Preto
João Victor Issler*
Affiliation:
Graduate School of Economics—EPGE, Getulio Vargas Foundation
*
Address correspondence to: João Victor Issler, Graduate School of Economics—EPGE, Getulio Vargas Foundation, Praia de Botafogo 190 s. 1100, Rio de Janeiro, RJ 22250-900, Brazil; e-mail: jissler@fgv.br.
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Abstract

This paper tests the optimality of consumption decisions at the aggregate level, taking into account popular deviations from the canonical constant-relative-risk-aversion (CRRA) utility function model—rule of thumb and habit. First, we provide extensive empirical evidence of the inappropriateness of linearization and testing strategies using Euler equations for consumption—a drawback for standard rule-of-thumb tests. Second, we propose a novel approach to testing for consumption optimality in this context: nonlinear estimation coupled with return aggregation, where rule-of-thumb behavior and habit are special cases of an all-encompassing model. We estimated 48 Euler equations using GMM. At the 5% level, we only rejected optimality twice out of 48 times. Moreover, out of 24 regressions, we found the rule-of-thumb parameter to be statistically significant only twice. Hence, lack of optimality in consumption decisions represent the exception, not the rule. Finally, we found the habit parameter to be statistically significant on four occasions out of 24.

Keywords

Consumption OptimalityIntertemporal SubstitutionRisk AversionAggregate ReturnHabitRule-of-Thumb BehaviorRepresentative-Consumer Model

Information

Type
Articles
Information
Macroeconomic Dynamics , Volume 21 , Special Issue 5: Recent Topics in Computational Macroeconomics , July 2017 , pp. 1119 - 1140
Copyright
Copyright © Cambridge University Press 2016 

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Footnotes

We are especially grateful to two anonymous referees, Caio Almeida, Marco Bonomo, Luis Braido, Carlos E. Costa, Russell Davidson, Pedro C. Ferreira, Karolina Goraus, Fredj Jawadi (Editor), Anwar Khyat, and Naércio A. Menezes Filho for their comments and suggestions on earlier versions of this paper. We also benefited from comments given by the participants of ISCEF conferences in Paris, 2014, where this paper was presented. The usual disclaimer applies. Fabio Augusto Reis Gomes and João Victor Issler gratefully acknowledge support given by CNPq-Brazil. Issler also acknowledges the support given by CAPES, Pronex, FAPERJ, and INCT. We gratefully acknowledge research assistance given by Rafael Burjack, Marcia Waleria Machado, and Marcia Marcos.

References

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