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Nonparametric spectrum estimation for spatial data

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  • Robinson, Peter M.

Abstract

Smoothed nonparametric kernel spectral density estimates are considered for stationary data observed on a d-dimensional lattice. The implications for edge effect bias of the choice of kernel and bandwidth are considered. Under some circumstances the bias can be dominated by the edge effect. We show that this problem can be mitigated by tapering. Some extensions and related issues are discussed.

Suggested Citation

  • Robinson, Peter M., 2006. "Nonparametric spectrum estimation for spatial data," LSE Research Online Documents on Economics 4543, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:4543
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    File URL: http://eprints.lse.ac.uk/4543/
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    References listed on IDEAS

    as
    1. 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.
    2. Andrews, Donald W K, 1991. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Econometrica, Econometric Society, vol. 59(3), pages 817-858, 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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