Estimating Euler Equations with Noisy Data: Two Exact GMM Estimators
AbstractIn 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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Bibliographic InfoPaper provided by University of Oxford, Department of Economics in its series Economics Series Working Papers with number 283.
Date of creation: 01 Oct 2006
Date of revision:
Nonlinear Models; Measurement Error; Euler Equation;
Other versions of this item:
- 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.
- 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
This paper has been announced in the following NEP Reports:
- NEP-ALL-2007-04-14 (All new papers)
- NEP-ECM-2007-04-14 (Econometrics)
- NEP-MAC-2007-04-14 (Macroeconomics)
- NEP-UPT-2007-04-14 (Utility Models & Prospect Theory)
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- Attanasio, O.P. & Browning, M., 1993.
"Consumption Over the Life Cycle and Over the Business Cycle,"
9314, Tilburg - Center for Economic Research.
- 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 1118-37, December.
- Orazio P. Attanasio & Martin Browning, 1993. "Consumption over the Life Cycle and over the Business Cycle," NBER Working Papers 4453, National Bureau of Economic Research, Inc.
- 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.
- Amemiya, Yasuo, 1985. "Instrumental variable estimator for the nonlinear errors-in-variables model," Journal of Econometrics, Elsevier, vol. 28(3), pages 273-289, June.
- 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.
- Altonji, Joseph G & Siow, Aloysius, 1987. "Testing the Response of Consumption to Income Changes with (Noisy) Panel Data," The Quarterly Journal of Economics, MIT Press, vol. 102(2), pages 293-328, May.
- Wansbeek, Tom, 2001. "GMM estimation in panel data models with measurement error," Journal of Econometrics, Elsevier, vol. 104(2), pages 259-268, September.
- Martin Browning & Annamaria Lusardi, 1996.
"Household Saving: Micro Theories and Micro Facts,"
96-01, University of Copenhagen. Department of Economics.
- Robert E. Hall & Frederic S. Mishkin, 1982.
"The Sensitivity of Consumption to Transitory Income: Estimates from Panel Data on Households,"
NBER Working Papers
0505, National Bureau of Economic Research, Inc.
- 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.
- Orazio P. Attanasio & Hamish Low, 2000.
"Estimating Euler Equations,"
NBER Technical Working Papers
0253, National Bureau of Economic Research, Inc.
- 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.
- James H. Stock & Jonathan Wright, 2000. "GMM with Weak Identification," Econometrica, Econometric Society, vol. 68(5), pages 1055-1096, September.
- 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.
- 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.
- Deaton, Angus, 1985. "Panel data from time series of cross-sections," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 109-126.
- J. A. Hausman & W. K. Newey & J. L. Powel, 1988.
"Nonlinear Errors in Variables: Estimation of Some Engel Curves,"
504, Massachusetts Institute of Technology (MIT), Department of Economics.
- 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.
- 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.
- 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.
- 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.
- 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.
- Antoine Bozio & Guy Laroque & Cormac O'Dea, 2013. "Heterogeneity in time preference in older households," IFS Working Papers W13/02, Institute for Fiscal Studies.
- Sule Alan & Kadir Atalay & Thomas F. Crossley, 2012. "Euler Equation Estimation on Micro Data," KoÃ§ University-TUSIAD Economic Research Forum Working Papers 1221, Koc University-TUSIAD Economic Research Forum.
- 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.
- Naeem Ahmed & Matthew Brzozowski & Thomas F. Crossley, 2005. "Measurement Errors in Recall Food Expenditure Data," Quantitative Studies in Economics and Population Research Reports 396, McMaster University.
- 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.
- Naeem Ahmed & Matthew Brzozowski & Thomas Crossley, 2006. "Measurement errors in recall food consumption data," IFS Working Papers W06/21, Institute for Fiscal Studies.
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