There is widespread agreement that given currently available data, we cannot accurately estimate the parameters of intertemporal allocation using GMM on Euler equations, whether they be exact or approximate. Our reading of this literature and our own results is that this is a small sample (strictly, short panel) problem. The alternative seems to be to move to full structural modelling. In the current state of the art this is cumbersome, fragile and unable to deal with significant heterogeneity. We present a novel structural estimation procedure that is based on simulating expectation errors; we refer to it as Simulated Residual Estimation (SRE). We develop variants of the basic procedure that allow us to account for measurement error in consumption, the 'news' in interest rate realisations and for heterogeneity in discount factors. An investigation of the small sample properties of the SRE estimator indicates that it dominates GMM estimation of both exact and approximate Euler equations in the case when we have short panels and noisy consumption data. An empirical application to two panels drawn from the PSID are presented. The results are very encouraging. We find that we can estimate the parameters of intertemporal allocation much more precisely than with a conventional GMM on a log-linearised model. For example, we find that the 95% confidence interval for the EIS is [0.27, 0.70] for the more educated whereas the IGMM confidence intervals are [-0.38, 0.90] and [-3.78, 6.22] for the linearized and nonlinear models respectively. Moreover, the parameter estimates seem quite reasonable. For example, we find discount factors that are less than, but close to unity. We also find a higher discount factor for the more educated group. We find that the more educated have a higher CRRA which we interpret to indicate that the constant EIS assumption of the iso-elastic form is rejected. Finally, we present results for a model that allows for heterogeneity in the discount factor within education groups. We reject strongly the homogeneity assumption and find that discount rates vary significantly within groups.
Download Info
To download:
If you experience problems downloading a file, check if you have the
proper application to
view it first. Information about this may be contained
in the File-Format links below. In case of further problems read
the IDEAS help
page. Note that these files are not on the IDEAS
site. Please be patient as the files may be large.
Publisher Info
Paper provided by University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics in its series CAM Working Papers with number
2003-03.
For technical questions regarding this item, or to correct its listing, contact: (Henriette Aabo Hansen).
Related research
Keywords:
Other versions of this item:
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.
[Downloadable!] (restricted)
Other versions:
Pierre-Olivier Gourinchas & Jonathan A. Parker, 2002.
"Consumption Over the Life Cycle,"
Econometrica,
Econometric Society, vol. 70(1), pages 47-89, January.
[Downloadable!] (restricted)
Gallant, A. Ronald & Tauchen, George, 1996.
"Which Moments to Match?,"
Econometric Theory,
Cambridge University Press, vol. 12(04), pages 657-681, October.
[Downloadable!]
Gourieroux, C & Monfort, A & Renault, E, 1993.
"Indirect Inference,"
Journal of Applied Econometrics,
John Wiley & Sons, Ltd., vol. 8(S), pages S85-118, Suppl. De.
[Downloadable!] (restricted)
Other versions:
Gourieroux, C. & Monfort, A. & Renault, E., 1992.
"Indirect Inference,"
Papers
92.279, Toulouse - GREMAQ.
Cited by: (explanations, 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.)
Did you know? Citation analysis on IDEAS includes online papers that are freely accessible and whose text could be automatically analyzed, currently about 210000 papers.