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Efficient Semiparametric Estimation of Expectations in Dynamic Nonlinear Systems

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  • Jeon, Byung M.

    (Rice U)

  • Brown, Bryan
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    Abstract

    Semiparametric estimation of the expectations of a general class of dynamic functions is considered. Such expectation functionals that are of interest for dynamic models are one- and multi-period ahead forecasting functions, distribution functions, and covariance matrices. The semiparametric efficiency bound for this problem is established and an estimator, which attains the bound is developed. The explicit form of the semiparmetric efficient expectation estimator is worked out for several explicit assumptions regarding the degree of dependence between the predetermined variables and the disturbances of the model. Under the assumption of independence, the one- and multi-period ahead residual-based predictors proposed by Brown and Mariano (1989) are shown to be semiparametric efficient. Under unconditional mean zero assumption, we propose an improved heteroskedastic autocorrelation consistent estimator.

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    File URL: http://www.ruf.rice.edu/~econ/papers/2001papers/09Jeon.pdf
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    Bibliographic Info

    Paper provided by Rice University, Department of Economics in its series Working Papers with number 2001-09.

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    Date of creation: Jan 2001
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    Handle: RePEc:ecl:riceco:2001-09

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    1. Back, Kerry & Brown, David P, 1993. "Implied Probabilities in GMM Estimators," Econometrica, Econometric Society, vol. 61(4), pages 971-75, July.
    2. Newey, W.K., 1989. "Uniform Convergence In Probability And Stochastic Equicontinuity," Papers 342, Princeton, Department of Economics - Econometric Research Program.
    3. White, Halbert & Domowitz, Ian, 1984. "Nonlinear Regression with Dependent Observations," Econometrica, Econometric Society, vol. 52(1), pages 143-61, January.
    4. Bryan W. Brown & Whitney K. Newey, 1998. "Efficient Semiparametric Estimation of Expectations," Econometrica, Econometric Society, vol. 66(2), pages 453-464, March.
    5. Brown, Bryan W & Maital, Shlomo, 1981. "What Do Economists Know? An Empirical Study of Experts' Expectations," Econometrica, Econometric Society, vol. 49(2), pages 491-504, March.
    6. Brown, Bryan W & Mariano, Roberto S, 1984. "Residual-Based Procedures for Prediction and Estimation in a Nonlinear Simultaneous System," Econometrica, Econometric Society, vol. 52(2), pages 321-43, March.
    7. Brown, Bryan W. & Mariano, Roberto S., 1989. "Predictors in Dynamic Nonlinear Models: Large-Sample Behavior," Econometric Theory, Cambridge University Press, vol. 5(03), pages 430-452, December.
    8. Andrews, Donald W K, 1987. "Consistency in Nonlinear Econometric Models: A Generic Uniform Law of Large Numbers [On Unification of the Asymptotic Theory of Nonlinear Econometric Models]," Econometrica, Econometric Society, vol. 55(6), pages 1465-71, November.
    9. Bryan W. Brown & Douglas J. Hodgson, 2007. "Semiparametric efficiency bounds in dynamic non-linear systems under elliptical symmetry," Econometrics Journal, Royal Economic Society, vol. 10(1), pages 35-48, 03.
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    Cited by:
    1. Park, B.U. & Sickles, R.C. & Simar, L., 2000. "Semiparametric Efficient Estimation of AR(1) Panel Data Models," Papers 0020, Catholique de Louvain - Institut de statistique.

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