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Estimating Euler Equations with Noisy Data: Two Exact GMM Estimators

Sule Alan (), Orazio Attanasio () and Martin Browning

No 2005-10, CAM Working Papers from University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics

Abstract: In this paper we exploit the specific structure of the Euler equation and develop two alternative GMM estimators that deal explicitly with measurement error. The first estimator assumes that the measurement error is lognormally distributed. The second estimator drops the distributional assumption and solves out for the unknown, but constant, conditional mean. Our Monte Carlo results suggest that both proposed estimators perform much better than conventional alternatives based on the exact Euler equation or its log-linear approximation, especially with short panels.

Keywords: nonlinear models; measurement error; Euler equation (search for similar items in EconPapers)
JEL-codes: C13 E21 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-dev and nep-mac
Date: 2005-05
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http://www.econ.ku.dk/cam/wp0910/wp0406/2005-10.pdf/ (application/pdf)

Related works:
Journal Article: Estimating Euler equations with noisy data: two exact GMM estimators (2009) Downloads
Working Paper: Estimating Euler Equations with Noisy Data: Two Exact GMM Estimators (2006) Downloads
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