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Using Samples of Unequal Length in Generalized Method of Moments Estimation

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  • Anthony W. Lynch
  • Jessica A. Wachter

Abstract

Many applications in financial economics use data series with different starting or ending dates. This paper describes estimation methods, based on the generalized method of moments (GMM), which make use of all available data for each moment condition. We introduce two asymptotically equivalent estimators that are consistent, asymptotically normal, and more efficient asymptotically than standard GMM. We apply these methods to estimating predictive regressions in international data and show that the use of the full sample affects point estimates and standard errors for both assets with data available for the full period and assets with data available for a subset of the period. Monte Carlo experiments demonstrate that reductions hold for small-sample standard errors as well as asymptotic ones.

Suggested Citation

  • Anthony W. Lynch & Jessica A. Wachter, 2008. "Using Samples of Unequal Length in Generalized Method of Moments Estimation," NBER Working Papers 14411, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:14411
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    1. Ghysels, Eric & Hall, Alastair, 1990. "A Test for Structural Stability of Euler Conditions Parameters Estimated via the Generalized Method of Moments Estimator," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 31(2), pages 355-364, May.
    2. Swamy, P. A. V. B. & Mehta, J. S., 1975. "On Bayesian estimation of seemingly unrelated regressions when some observations are missing," Journal of Econometrics, Elsevier, vol. 3(2), pages 157-169, May.
    3. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    4. Ghysels, Eric & Guay, Alain & Hall, Alastair, 1998. "Predictive tests for structural change with unknown breakpoint," Journal of Econometrics, Elsevier, vol. 82(2), pages 209-233, February.
    5. Duffie, Darrell & Singleton, Kenneth J, 1993. "Simulated Moments Estimation of Markov Models of Asset Prices," Econometrica, Econometric Society, vol. 61(4), pages 929-952, July.
    6. Campbell, J.Y. & Shiller, R.J., 1988. "Stock Prices, Earnings And Expected Dividends," Papers 334, Princeton, Department of Economics - Econometric Research Program.
    7. Pastor, Lubos & Stambaugh, Robert F., 2002. "Investing in equity mutual funds," Journal of Financial Economics, Elsevier, vol. 63(3), pages 351-380, March.
    8. Goetzmann, William N. & Jorion, Philippe, 1999. "Re-Emerging Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 34(1), pages 1-32, March.
    9. Michael W. Brandt, 1999. "Estimating Portfolio and Consumption Choice: A Conditional Euler Equations Approach," Journal of Finance, American Finance Association, vol. 54(5), pages 1609-1645, October.
    10. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2005. "There is a risk-return trade-off after all," Journal of Financial Economics, Elsevier, vol. 76(3), pages 509-548, June.
    11. Sowell, Fallaw, 1996. "Optimal Tests for Parameter Instability in the Generalized Method of Moments Framework," Econometrica, Econometric Society, vol. 64(5), pages 1085-1107, September.
    12. Conniffe, Denis, 1985. "Estimating regression equations with common explanatory variables but unequal numbers of observations," Journal of Econometrics, Elsevier, vol. 27(2), pages 179-196, February.
    13. Stambaugh, Robert F., 1997. "Analyzing investments whose histories differ in length," Journal of Financial Economics, Elsevier, vol. 45(3), pages 285-331, September.
    14. Andrew J. Patton, 2006. "Estimation of multivariate models for time series of possibly different lengths," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(2), pages 147-173, March.
    15. Pastor, Lubos & Stambaugh, Robert F., 2002. "Mutual fund performance and seemingly unrelated assets," Journal of Financial Economics, Elsevier, vol. 63(3), pages 315-349, March.
    16. Yacine Aït-Sahalia, 2005. "How Often to Sample a Continuous-Time Process in the Presence of Market Microstructure Noise," The Review of Financial Studies, Society for Financial Studies, vol. 18(2), pages 351-416.
    17. Stambaugh, Robert F., 1999. "Predictive regressions," Journal of Financial Economics, Elsevier, vol. 54(3), pages 375-421, December.
    18. Campbell, John Y & Shiller, Robert J, 1988. " Stock Prices, Earnings, and Expected Dividends," Journal of Finance, American Finance Association, vol. 43(3), pages 661-676, July.
    19. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
    20. Andrews, Donald W K & Ploberger, Werner, 1994. "Optimal Tests When a Nuisance Parameter Is Present Only under the Alternative," Econometrica, Econometric Society, vol. 62(6), pages 1383-1414, November.
    21. Nelson, Charles R & Kim, Myung J, 1993. "Predictable Stock Returns: The Role of Small Sample Bias," Journal of Finance, American Finance Association, vol. 48(2), pages 641-661, June.
    22. Fama, Eugene F. & French, Kenneth R., 1989. "Business conditions and expected returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 25(1), pages 23-49, November.
    23. Bandi, Federico M. & Russell, Jeffrey R., 2006. "Separating microstructure noise from volatility," Journal of Financial Economics, Elsevier, vol. 79(3), pages 655-692, March.
    24. Kjetil Storesletten & Chris I. Telmer & Amir Yaron, 2004. "Cyclical Dynamics in Idiosyncratic Labor Market Risk," Journal of Political Economy, University of Chicago Press, vol. 112(3), pages 695-717, June.
    25. Schmidt, Peter, 1977. "Estimation of seemingly unrelated regressions with unequal numbers of observations," Journal of Econometrics, Elsevier, vol. 5(3), pages 365-377, May.
    26. Hall, Alastair R., 2004. "Generalized Method of Moments," OUP Catalogue, Oxford University Press, number 9780198775201.
    27. Cavanagh, Christopher L. & Elliott, Graham & Stock, James H., 1995. "Inference in Models with Nearly Integrated Regressors," Econometric Theory, Cambridge University Press, vol. 11(5), pages 1131-1147, October.
    28. Donald W. K. Andrews & Ray C. Fair, 1988. "Inference in Nonlinear Econometric Models with Structural Change," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 55(4), pages 615-640.
    29. 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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    Cited by:

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    3. Martin M. Andreasen & Tom Engsted & Stig V. Møller & Magnus Sander, 2016. "Bond Market Asymmetries across Recessions and Expansions: New Evidence on Risk Premia," CREATES Research Papers 2016-26, Department of Economics and Business Economics, Aarhus University.
    4. Jonathan Fletcher & Patricia Ntozi-Obwale, 2009. "Exploring the Conditional Performance of U.K. Unit Trusts," Journal of Financial Services Research, Springer;Western Finance Association, vol. 36(1), pages 21-44, August.
    5. Yiying Cheng & Yaozhong Hu & Hongwei Long, 2020. "Generalized moment estimators for $$\alpha $$α-stable Ornstein–Uhlenbeck motions from discrete observations," Statistical Inference for Stochastic Processes, Springer, vol. 23(1), pages 53-81, April.
    6. Anthony W. Lynch & Oliver Randall, 2011. "Why Surplus Consumption in the Habit Model May be Less Persistent than You Think," NBER Working Papers 16950, National Bureau of Economic Research, Inc.
    7. Efstathios Avdis & Jessica A. Wachter, 2013. "Maximum likelihood estimation of the equity premium," NBER Working Papers 19684, National Bureau of Economic Research, Inc.
    8. Barras, Laurent & Malkhozov, Aytek, 2016. "Does variance risk have two prices? Evidence from the equity and option markets," Journal of Financial Economics, Elsevier, vol. 121(1), pages 79-92.
    9. Laurent Barras & Aytek Malkhozov, 2015. "Does variance risk have two prices? Evidence from the equity and option markets," BIS Working Papers 521, Bank for International Settlements.

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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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