NON AND SEMI-PARAMETRIC ESTIMATION IN MODELS WITH UNKNOWN SMOOTHNESS

Yulia Kotlyarova and Victoria Zinde-Walsh

Departmental Working Papers from McGill University, Department of Economics

Abstract: Many asymptotic results for kernel-based estimators were established under some smoothness assumption on density. For cases where smoothness assumptions that are used to derive unbiasedness or asymptotic rate may not hold we propose a combined estimator that could lead to the best available rate without knowledge of density smoothness. A Monte Carlo example confirms good performance of the combined estimator.

JEL-codes: C14 (search for similar items in EconPapers)
Pages: 10 pages
Date: 2006-09
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (19)

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Related works:
Journal Article: Non- and semi-parametric estimation in models with unknown smoothness (2006)
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Persistent link: https://EconPapers.repec.org/RePEc:mcl:mclwop:2006-15

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