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On the Finite Sample Properties of Pre-test Estimators of Spatial Models

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  • Gianfranco Piras

    ()
    (Regional Research Institute, West Virginia University)

  • Ingmar R. Prucha

    ()
    (Department of Economics, University of Maryland)

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    Abstract

    This paper explores the properties of pre-tst strategies in estimating a linear Cliff-Ord -type spatial model when the researcher is unsure about the nature of the spatial dependence. More specifically, the paper explores the finite sample properties of the pre-test estimators introduced in Florax et al. (2003), which are based on Lagrange Multiplier (LM) tests, within the context of a Monte Carlo study. The performance of those estimators is compared with that of the maximum likelihood (ML) estimator of the encompassing model. We find that, even in a very simple setting, the bias of the estimates generated by pre-testing strategies can be very large in some cases and the empirical size of tests can differ substantially from the nominal size. This is in contrast to the ML estimator.

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    File URL: http://rri.wvu.edu/wp-content/uploads/2013/10/Piras_Finite-Sample-Properties_2013-07.pdf
    File Function: First version, 1996
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    File URL: ftp://ftp.grandiose.edu/pub/econ/WorkingPapers/surrec9602R.pdf
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    Bibliographic Info

    Paper provided by Regional Research Institute, West Virginia University in its series Working Papers with number 201307.

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    Length: 22 pages
    Date of creation: Jul 2013
    Date of revision:
    Handle: RePEc:rri:wpaper:201307

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    Related research

    Keywords: cliff-ord; spatial; model; lagrange multiplier; monte carlo;

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    1. Badi H. Baltagi & Long Liu, 2008. "Testing for Random Effects and Spatial Lag Dependence in Panel Data Models," Center for Policy Research Working Papers 102, Center for Policy Research, Maxwell School, Syracuse University.
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