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Estimating Euler Equations with Noisy Data: Two Exact GMM Estimators

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  • Martin Browning
  • Sule Alan

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. The empirical application of the proposed estimators yields plausible estimates of the coefficient of relative risk aversion and discount rate.

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File URL: http://www.economics.ox.ac.uk/materials/working_papers/paper283.pdf
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Bibliographic Info

Paper provided by University of Oxford, Department of Economics in its series Economics Series Working Papers with number 283.

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Date of creation: 01 Oct 2006
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Handle: RePEc:oxf:wpaper:283

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Keywords: Nonlinear Models; Measurement Error; Euler Equation;

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  1. 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.
  2. Wansbeek, Tom, 2001. "GMM estimation in panel data models with measurement error," Journal of Econometrics, Elsevier, vol. 104(2), pages 259-268, September.
  3. 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 461-81, March.
  4. 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 503-43, May.
  5. 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.
  6. Hansen, Lars Peter & Singleton, Kenneth J, 1982. "Generalized Instrumental Variables Estimation of Nonlinear Rational Expectations Models," Econometrica, Econometric Society, vol. 50(5), pages 1269-86, September.
  7. Martin Browning & Annamaria Lusardi, 1995. "Household Saving: Micro Theories and Micro Facts," Department of Economics Working Papers 1995-02, McMaster University.
  8. Attanasio, O.P. & Browning, M., 1993. "Consumption Over the Life Cycle and Over the Business Cycle," Papers 9314, Tilburg - Center for Economic Research.
  9. 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.
  10. Joseph G. Altonji & Aloysius Siow, 1986. "Testing the Response of Consumption to Income Changes with (Noisy) PanelData," NBER Working Papers 2012, National Bureau of Economic Research, Inc.
  11. 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.
  12. 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.
  13. Orazio P. Attanasio & Hamish Low, 2000. "Estimating Euler Equations," NBER Technical Working Papers 0253, National Bureau of Economic Research, Inc.
  14. James H. Stock & Jonathan Wright, 2000. "GMM with Weak Identification," Econometrica, Econometric Society, vol. 68(5), pages 1055-1096, September.
  15. Deaton, Angus, 1985. "Panel data from time series of cross-sections," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 109-126.
  16. 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 518-29, October.
  17. 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.
  18. Amemiya, Yasuo, 1985. "Instrumental variable estimator for the nonlinear errors-in-variables model," Journal of Econometrics, Elsevier, vol. 28(3), pages 273-289, June.
  19. 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.
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Citations

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Cited by:
  1. Olga gorbachev, 2007. "Did Household Consumption Become More Volatile?," ESE Discussion Papers 161, Edinburgh School of Economics, University of Edinburgh.
  2. 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 133, McMaster University.
  3. Naeem Ahmed & Matthew Brzozowski & Thomas Crossley, 2006. "Measurement errors in recall food consumption data," IFS Working Papers W06/21, Institute for Fiscal Studies.
  4. 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.
  5. Christian Chiglino & Nicole Tabasso, 2014. "Risk Aversion in a Model of Endogenous Growth," School of Economics Discussion Papers 0314, School of Economics, University of Surrey.
  6. Irina Khvostova & Alexander Larin & Anna Novak, 2014. "Euler equation with habits and measurement errors: estimates on Russian micro data," HSE Working papers WP BRP 52/EC/2014, National Research University Higher School of Economics.
  7. 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.
  8. Larin, Alexander & Novak, Anna & Khvostova, Irina, 2013. "Consumption dynamics in Russia: Estimates on microdata," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 32(4), pages 29-44.
  9. Antoine Bozio & Guy Laroque & Cormac O'Dea, 2013. "Heterogeneity in time preference in older households," IFS Working Papers W13/02, Institute for Fiscal Studies.
  10. Sule Alan & Kadir Atalay & Thomas F. Crossley, 2012. "Euler Equation Estimation on Micro Data," Koç University-TUSIAD Economic Research Forum Working Papers 1221, Koc University-TUSIAD Economic Research Forum.
  11. Jørgensen, Thomas H., 2013. "Structural estimation of continuous choice models: Evaluating the EGM and MPEC," Economics Letters, Elsevier, vol. 119(3), pages 287-290.

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