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Generalized method of trimmed moments

Cizek,Pavel
Abstract
High breakdown-point regression estimators protect against large errors and data contamination. We adapt and generalize the concept of trimming used by many of these robust estimators so that it can be employed in the context of the generalized method of moments. The proposed generalized method of trimmed moments (GMTM) offers a globally robust estimation approach (contrary to many existing locally robust estimators) applicable in models identified and estimated using moment conditions. We derive the consistency and asymptotic distribution of GMTM in a general setting, propose a robust test of overidentifying conditions, and demonstrate the application of GMTM in the instrumental variable regression. We also compare the finite-sample performance of GMTM and existing estimators by means of Monte Carlo simulation.
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Date
2016-04
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Tilburg University Research Output Collection
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Keywords
Asymptotic normality, Generalized method of moments, Instrumental variables regression, Robust estimation, Trimming
Citation
Cizek, P 2016, 'Generalized method of trimmed moments', Journal of Statistical Planning and Inference, vol. 171, pp. 63-78. https://doi.org/doi:10.1016/j.jspi.2015.11.004
URI
https://hdl.handle.net/20.500.14602/64778
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