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Nonparametric Spectrum Estimation for SpatialData

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  • Peter M Robinson

Abstract

Smoothed nonparametric kernel spectral density estimates areconsidered for stationary data observed on a d-dimensional lattice.The implications for edge effect bias of the choice of kernel andbandwidth are considered. Under some circumstances the bias canbe dominated by the edge effect. We show that this problem can bemitigated by tapering. Some extensions and related issues arediscussed.MSC: 62M30, 62M15 C22

Suggested Citation

  • Peter M Robinson, 2006. "Nonparametric Spectrum Estimation for SpatialData," STICERD - Econometrics Paper Series 498, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    • Handle: RePEc:cep:stiecm:498
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    File URL: https://sticerd.lse.ac.uk/dps/em/EM498.pdf
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    References listed on IDEAS

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    1. Andrews, Donald W K, 1991. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Econometrica, Econometric Society, vol. 59(3), pages 817-858, May.
    2. Robinson, P.M. & Vidal Sanz, J., 2006. "Modified Whittle estimation of multilateral models on a lattice," Journal of Multivariate Analysis, Elsevier, vol. 97(5), pages 1090-1120, May.
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    More about this item

    Keywords

    nonparametric spectrum estimation; edge effect; tapering.;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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