On the Finite Sample Properties of Pre-test Estimators of Spatial Models
Gianfranco Piras () and
No Working Paper 2013-07, Working Papers from Regional Research Institute, West Virginia University
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.
Keywords: cliff-ord; spatial; model; lagrange multiplier; monte carlo (search for similar items in EconPapers)
JEL-codes: C4 C5 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm, nep-geo, nep-ore and nep-ure
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Journal Article: On the finite sample properties of pre-test estimators of spatial models (2014)
Working Paper: On the Finite Sample Properties of Pre-Test Estimators of Spatial Models (2014)
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