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Estimating Euler Equations with Noisy Data: Two Exact GMM Estimators

Author

Listed:
  • 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.

Suggested Citation

  • Sule Alan & Orazio Attanasio & Martin Browning, 2005. "Estimating Euler Equations with Noisy Data: Two Exact GMM Estimators," CAM Working Papers 2005-10, University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics.
    • Handle: RePEc:kud:kuieca:2005_10
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    References listed on IDEAS

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    1. Shapiro, Matthew D., 1984. "The permanent income hypothesis and the real interest rate : Some evidence from panel data," Economics Letters, Elsevier, vol. 14(1), pages 93-100.
    2. Hall, Robert E, 1978. "Stochastic Implications of the Life Cycle-Permanent Income Hypothesis: Theory and Evidence," Journal of Political Economy, University of Chicago Press, vol. 86(6), pages 971-987, December.
    3. Jerry Hausman, 2001. "Mismeasured Variables in Econometric Analysis: Problems from the Right and Problems from the Left," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 57-67, Fall.
    4. Wansbeek, Tom, 2001. "GMM estimation in panel data models with measurement error," Journal of Econometrics, Elsevier, vol. 104(2), pages 259-268, September.
    5. Amemiya, Yasuo, 1985. "Instrumental variable estimator for the nonlinear errors-in-variables model," Journal of Econometrics, Elsevier, vol. 28(3), pages 273-289, June.
    6. Ventura, Eva, 1994. "A note on measurement error and Euler equations : An alternative to log-linear approximations," Economics Letters, Elsevier, vol. 45(3), pages 305-308.
    7. Deaton, Angus, 1985. "Panel data from time series of cross-sections," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 109-126.
    8. Sule Alan & Martin Browning, 2003. "Estimating Intertemporal Allocation Parameters using Simulated Residual Estimation," CAM Working Papers 2003-03, University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics.
    9. Joseph G. Altonji & Aloysius Siow, 1987. "Testing the Response of Consumption to Income Changes with (Noisy) Panel Data," The Quarterly Journal of Economics, Oxford University Press, vol. 102(2), pages 293-328.
    10. Attanasio, Orazio P & Browning, Martin, 1995. "Consumption over the Life Cycle and over the Business Cycle," American Economic Review, American Economic Association, vol. 85(5), pages 1118-1137, December.
    11. Stock, James H & Wright, Jonathan H & Yogo, Motohiro, 2002. "A Survey of Weak Instruments and Weak Identification in Generalized Method of Moments," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(4), pages 518-529, October.
    12. Orazio P. Attanasio & Hamish Low, 2004. "Estimating Euler Equations," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 7(2), pages 405-435, April.
    13. Hall, Robert E & Mishkin, Frederic S, 1982. "The Sensitivity of Consumption to Transitory Income: Estimates from Panel Data on Households," Econometrica, Econometric Society, vol. 50(2), pages 461-481, March.
    14. Martin Browning & Annamaria Lusardi, 1996. "Household Saving: Micro Theories and Micro Facts," Journal of Economic Literature, American Economic Association, vol. 34(4), pages 1797-1855, December.
    15. James H. Stock & Jonathan Wright, 2000. "GMM with Weak Identification," Econometrica, Econometric Society, vol. 68(5), pages 1055-1096, September.
    16. Hausman, J. A. & Newey, W. K. & Powell, J. L., 1995. "Nonlinear errors in variables Estimation of some Engel curves," Journal of Econometrics, Elsevier, vol. 65(1), pages 205-233, January.
    17. 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, vol. 50(3), pages 273-295, December.
    18. Hong, Han & Tamer, Elie, 2003. "A simple estimator for nonlinear error in variable models," Journal of Econometrics, Elsevier, vol. 117(1), pages 1-19, November.
    19. Runkle, David E., 1991. "Liquidity constraints and the permanent-income hypothesis : Evidence from panel data," Journal of Monetary Economics, Elsevier, vol. 27(1), pages 73-98, February.
    20. Browning, Martin & Deaton, Angus & Irish, Margaret, 1985. "A Profitable Approach to Labor Supply and Commodity Demands over the Life-Cycle," Econometrica, Econometric Society, vol. 53(3), pages 503-543, May.
    21. Karen E. Dynan, 2000. "Habit Formation in Consumer Preferences: Evidence from Panel Data," American Economic Review, American Economic Association, vol. 90(3), pages 391-406, June.
    22. Hansen, Lars Peter & Singleton, Kenneth J, 1982. "Generalized Instrumental Variables Estimation of Nonlinear Rational Expectations Models," Econometrica, Econometric Society, vol. 50(5), pages 1269-1286, September.
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    More about this item

    Keywords

    nonlinear models; measurement error; Euler equation;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth

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