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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

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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 

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

REFERENCES

Abel, A. (1990) Asset prices under habit formation and catching up with the Joneses. American Economic Review Papers and Proceedings 80, 38–42.Google Scholar
Araujo, F. and Issler, J.V. (2011) A Stochastic Discount Factor Approach to Asset Pricing Using Panel Data Asymptotics. Working paper, Graduate School of Economics, Getulio Vargas Foundation, ensaios econômicos da EPGE 717.Google Scholar
Attanasio, O.P., Banks, J., and Tanner, S. (2002) Asset holding and consumption volatility. Journal of Political Economy 110 (4), 771–792.CrossRefGoogle Scholar
Campbell, J.Y. and Cochrane, J. (1999) Force of habit: A consumption-based explanation of aggregate stock market behavior. Journal of Political Economy 107 (2), 205–251.CrossRefGoogle Scholar
Campbell, J.Y. and Deaton, A. (1989) Why is consumption so smooth? Review of Economic Studies 56, 357–374.CrossRefGoogle Scholar
Campbell, J.Y. and Mankiw, N.G. (1989) Consumption, income and interest rates: Reinterpreting the time series evidence. In Blanchard, O.J. and Fischer, S. (eds.), NBER Macroeconomics Annual, pp. 185–214. Cambridge, MA: MIT Press.Google Scholar
Campbell, J.Y. and Mankiw, N.G. (1990) Permanent income, current income, and consumption. Journal of Business and Economic Statistics 8, 265–280.Google Scholar
Carroll, C.D. (2001) Death to the log-linearized consumption euler equation! (And very poor health to the second-order approximation). The B.E. Journal of Macroeconomics 1 (1), 1–38.Google Scholar
Cumby, R.E. and Huizinga, J. (1992) Testing the autocorrelation structure of disturbances in ordinary least squares and instrumental variables regressions. Econometrica 60 (1), 185–195.CrossRefGoogle Scholar
Driscoll, J.C. and Kraay, A.C. (1998). Consistent covariance matrix estimation with spatially dependent panel data. Review of Economics and Statistics 80 (4), 549–560.CrossRefGoogle Scholar
Epstein, L.G. and Zin, S.E. (1989) Substitution, risk aversion, and the temporal behavior of consumption and asset returns: A theoretical framework. Econometrica 57, 937–968.CrossRefGoogle Scholar
Epstein, L.G. and Zin, S.E. (1991) Substitution, risk aversion and the temporal behavior of consumption and asset returns: An empirical analysis. Journal of Political Economy 99, 263–286.CrossRefGoogle Scholar
Flavin, M.A. (1981) The adjustments of consumption to changing expectations about future income. Journal of Political Economy 89, 974–1009.CrossRefGoogle Scholar
Hall, R.E. (1978) Stochastic implications of the life cycle-permanent income hypothesis: Theory and evidence. Journal of Political Economy 86, 971–987.CrossRefGoogle Scholar
Hall, R.E. (1988) Intertemporal substitution in consumption. Journal of Political Economy 96, 339–357.CrossRefGoogle Scholar
Hansen, L.P., Heaton, J. and Yaron, A. (1996). Finite-sample properties of some alternative GMM estimators. Journal of Business and Economic Statistics 14 (3), 262–280.Google Scholar
Hansen, L.P. and Singleton, K.J. (1982) Generalized instrumental variables estimation of nonlinear rational expectations models. Econometrica 50, 1269–1286.CrossRefGoogle Scholar
Hansen, L.P. and Singleton, K.J. (1983) Stochastic consumption, risk aversion, and the temporal behavior of asset returns. Journal of Political Economy 91, 249–265.CrossRefGoogle Scholar
Hansen, L.P. and Singleton, K.J. (1984) Erratum of the article “ Generalized instrumental variables estimation of nonlinear rational expectations models.'' Econometrica 52 (1), 267–268.CrossRefGoogle Scholar
Mehra, R. and Prescott, E. (1985) The equity premium: A puzzle. Journal of Monetary Economics 15, 145–161.CrossRefGoogle Scholar
Mulligan, C. (2002) Capital, Interest, and Aggregate Intertemporal Substitution. NBER working paper 9373.CrossRefGoogle Scholar
Mulligan, C. and Threinen, L. (2010) The Marginal Products of Residential and Non-residential Capital through 2009. NBER working paper 15897.CrossRefGoogle Scholar
Pagan, A.R. and Hall, D. (1983) Diagnostic tests as residual analysis. Econometric Reviews 2 (2), 159–218.CrossRefGoogle Scholar
Pesaran, M.H. and Taylor, L.W. (1999) Diagnostics for IV regressions. Oxford Bulletin of Economics and Statistics 61 (2), 255–281.CrossRefGoogle Scholar
Vissing-Jørgensen, A. (2002) Limited asset market participation and the elasticity of intertemporal substitution. Journal of Political Economy 110, 825–853.CrossRefGoogle Scholar
Weber, C.E. (2002) Intertemporal non-separability and “rule of thumb” consumption. Journal of Monetary Economics 49, 293–308.CrossRefGoogle Scholar
Weil, P. (1989) The equity premium puzzle and the risk-free rate puzzle. Journal of Monetary Economics 24, 401–421.CrossRefGoogle Scholar