This paper shows that standard methods for estimating log-linearized consumption Euler equations using micro data cannot successfully uncover structural parameters like the coefficient of relative risk aversion from a dataset of simulated consumers behaving exactly according to the standard model. Furthermore, consumption growth for the simulated consumers is very highly statistically related to predictable income growth -- and thus standard `excess sensitivity' tests would reject the hypothesis that consumers are behaving according to the model. Results are not much better for the second-order approximation to the Euler equation. The paper concludes that empirical estimation of consumption Euler equations should be abandoned, and discusses some alternative empirical strategies that are not subject to the problems of Euler equation estimation.
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References listed on IDEAS Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
Pierre-Olivier Gourinchas & Jonathan A. Parker, 1999.
"Consumption Over the Life Cycle,"
NBER Working Papers
7271, National Bureau of Economic Research, Inc.
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Pierre-Olivier Gourinchas & Jonathan A. Parker, 2002.
"Consumption Over the Life Cycle,"
Econometrica,
Econometric Society, vol. 70(1), pages 47-89, January.
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