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Estimating Euler Equations with Noisy Data: Two Exact GMM Estimators

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Author Info

  • Sule Alan

    (Department of Economics, York University, Toronto)

  • Orazio Attanasio

    (Department of Economics, University College London)

  • Martin Browning

    (Institute of Economics, University of Copenhagen)

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.

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File URL: http://www.econ.ku.dk/cam/wp0910/wp0406/2005-10.pdf/
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Bibliographic Info

Paper provided by University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics in its series CAM Working Papers with number 2005-10.

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Length: 13 pages
Date of creation: May 2005
Date of revision:
Handle: RePEc:kud:kuieca:2005_10

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Keywords: nonlinear models; measurement error; Euler equation;

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References

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  1. Attanasio, O.P. & Browning, M.J., 1993. "Consumption over the life cycle and over the business cycle," Discussion Paper, Tilburg University, Center for Economic Research 1993-14, Tilburg University, Center for Economic Research.
  2. Browning, Martin & Deaton, Angus & Irish, Margaret, 1985. "A Profitable Approach to Labor Supply and Commodity Demands over the Life-Cycle," Econometrica, Econometric Society, Econometric Society, vol. 53(3), pages 503-43, May.
  3. J. A. Hausman & W. K. Newey & J. L. Powel, 1988. "Nonlinear Errors in Variables: Estimation of Some Engel Curves," Working papers, Massachusetts Institute of Technology (MIT), Department of Economics 504, Massachusetts Institute of Technology (MIT), Department of Economics.
  4. Orazio P. Attanasio & Hamish Low, 2000. "Estimating Euler Equations," NBER Technical Working Papers 0253, National Bureau of Economic Research, Inc.
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  6. Hausman, Jerry A. & Newey, Whitney K. & Ichimura, Hidehiko & Powell, James L., 1991. "Identification and estimation of polynomial errors-in-variables models," Journal of Econometrics, Elsevier, Elsevier, vol. 50(3), pages 273-295, December.
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  14. Martin Browning & Annamaria Lusardi, 1996. "Household Saving: Micro Theories and Micro Facts," Journal of Economic Literature, American Economic Association, American Economic Association, vol. 34(4), pages 1797-1855, December.
  15. James H. Stock & Jonathan Wright, 2000. "GMM with Weak Identification," Econometrica, Econometric Society, Econometric Society, vol. 68(5), pages 1055-1096, September.
  16. Sule Alan & Martin Browning, 2003. "Estimating Intertemporal Allocation Parameters using Simulated Residual Estimation," CAM Working Papers, University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics 2003-03, University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics.
  17. Amemiya, Yasuo, 1985. "Instrumental variable estimator for the nonlinear errors-in-variables model," Journal of Econometrics, Elsevier, Elsevier, vol. 28(3), pages 273-289, June.
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Cited by:
  1. Sule Alan & Kadir Atalay & Thomas F. Crossley, 2012. "Euler Equation Estimation on Micro Data," Koç University-TUSIAD Economic Research Forum Working Papers, Koc University-TUSIAD Economic Research Forum 1221, Koc University-TUSIAD Economic Research Forum.
  2. Antoine Bozio & Guy Laroque & Cormac O'Dea, 2013. "Heterogeneity in time preference in older households," IFS Working Papers, Institute for Fiscal Studies W13/02, Institute for Fiscal Studies.
  3. Naeem Ahmed & Matthew Brzozowski & Thomas Crossley, 2006. "Measurement errors in recall food consumption data," IFS Working Papers, Institute for Fiscal Studies W06/21, Institute for Fiscal Studies.
  4. Irina Khvostova & Alexander Larin & Anna Novak, 2014. "Euler equation with habits and measurement errors: estimates on Russian micro data," HSE Working papers, National Research University Higher School of Economics WP BRP 52/EC/2014, National Research University Higher School of Economics.
  5. Sule Alan & Martin Browning, 2010. "Estimating Intertemporal Allocation Parameters using Synthetic Residual Estimation," Review of Economic Studies, Oxford University Press, vol. 77(4), pages 1231-1261.
  6. Larin, Alexander & Novak, Anna & Khvostova, Irina, 2013. "Consumption dynamics in Russia: Estimates on microdata," Applied Econometrics, Publishing House "SINERGIA PRESS", Publishing House "SINERGIA PRESS", vol. 32(4), pages 29-44.
  7. Olga Gorbachev, 2011. "Did Household Consumption Become More Volatile?," American Economic Review, American Economic Association, American Economic Association, vol. 101(5), pages 2248-70, August.
  8. Naeem Ahmed & Matthew Brzozowski & Thomas F. Crossley, 2005. "Measurement Errors in Recall Food Expenditure Data," Social and Economic Dimensions of an Aging Population Research Papers, McMaster University 133, McMaster University.
  9. Jørgensen, Thomas H., 2013. "Structural estimation of continuous choice models: Evaluating the EGM and MPEC," Economics Letters, Elsevier, Elsevier, vol. 119(3), pages 287-290.
  10. Christian Chiglino & Nicole Tabasso, 2014. "Risk Aversion in a Model of Endogenous Growth," School of Economics Discussion Papers, School of Economics, University of Surrey 0314, School of Economics, University of Surrey.
  11. Natalia, Khorunzhina & Wayne Roy, Gayle, 2011. "Heterogenous intertemporal elasticity of substitution and relative risk aversion: estimation of optimal consumption choice with habit formation and measurement errors," MPRA Paper 34329, University Library of Munich, Germany.

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