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Spatial correlation robust inference with Errors in Location or Distance

Author

Listed:
  • Timothy Conley

    (Institute for Fiscal Studies and University of Chicago)

  • Francesca Molinari

    (Institute for Fiscal Studies and Cornell University)

Abstract

This paper presents results from a Monte Carlo study concerning inference with spatially dependent data. It investigates the impact of location/distance measurement errors upon the accuracy of parametric and nonparametric estimators of asymptotic variances.

Suggested Citation

  • Timothy Conley & Francesca Molinari, 2005. "Spatial correlation robust inference with Errors in Location or Distance," CeMMAP working papers CWP10/05, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    • Handle: RePEc:ifs:cemmap:10/05
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    File URL: http://cemmap.ifs.org.uk/wps/cwp1005.pdf
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    References listed on IDEAS

    as
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